update version

revert update

.gitignore

@@ -0,0 +1,3 @@
+node_modules/
+package.json
+package-lock.json

AI_prompt.txt

@@ -1,15 +0,0 @@
-Consider the following scenarios:
-Scenario 1: The "Command & Control" Loop (Low Latency)Focus: Small payloads, Core NATS, bi-directional JSON.The Action: A user on a JavaScript dashboard clicks a "Start Simulation" button. This sends a JSON configuration (parameters like step_size and iterations) to Julia.The Flow: * JS (Sender): Recognizes the message is small ($< 10KB$). Packages it as a direct transport JSON envelope.Julia (Receiver): Listens on the NATS subject, decodes the JSON, and immediately acknowledges receipt with a "Running" status.Project Requirement Met: Fast, low-overhead communication for control signals without involving the fileserver.
-Scenario 2: The "Deep Dive" Analysis (High Bandwidth)Focus: Large Arrow tables, Claim-Check pattern, Julia to JS.The Action: Julia finishes a heavy computation and produces a 500MB DataFrame with 10 million rows. It needs to send this to the JS frontend for visualization (e.g., using Perspective.js or D3).The Flow:Julia (Sender): Converts the DataFrame to an Arrow IPC stream. It sees the size is $> 1MB$, so it uploads the bytes to the HTTP fileserver. It then publishes a NATS message with transport: "link" and the URL.JS (Receiver): Receives the URL, fetches the data via fetch(), and uses tableFromIPC() to load the data into memory with zero-copy.Project Requirement Met: Handling massive datasets that exceed NATS message limits while maintaining data integrity across languages.
-Scenario 3: Live Audio/Signal Processing (Multimedia & Metadata)Focus: Raw binary, bi-directional streaming, NATS Headers.The Action: The JS client captures a 2-second "chunk" of microphone audio. It needs Julia to perform a Fast Fourier Transform (FFT) or AI transcription.The Flow:JS (Sender): Sends the raw binary WAV/PCM data. It uses NATS Headers to store the metadata ($fs = 44.1kHz$, $channels = 1$) to keep the payload purely binary.Julia (Receiver): Processes the audio and sends back a JSON result (the transcription) and an Arrow Table (the frequency spectrum data).Project Requirement Met: Bi-directional flow involving mixed media (Audio) and technical results (Arrow).
-Scenario 4: The "Catch-Up" (Persistence & JetStream)Focus: NATS JetStream, late-joining consumers, state sync.The Action: Julia is constantly publishing "System Health" updates. The JS dashboard is closed for 10 minutes. When the user re-opens the dashboard, they need to see the last 10 minutes of history.The Flow:NATS (Server): Uses a JetStream with a Limits retention policy.JS (Consumer): Connects and requests a "Replay" from the last 10 minutes. It receives a mix of direct (small updates) and link (historical snapshots) messages.Project Requirement Met: Temporal decoupling—consumers can receive data that was sent while they were offline.
-
-Role: Principal Systems Architect & Lead Software Engineer.Objective: Implement a high-performance, bi-directional data bridge between a Julia service and a JavaScript (Node.js) service using NATS (Core & JetStream).⚠️ STRICT ARCHITECTURAL CONSTRAINTS (Non-Negotiable)Transport Strategy (Claim-Check Pattern):Direct Path: If payload is < 1MB, send data directly via NATS inside the message envelope (Base64 encoded).Link Path: If payload is > 1MB, upload to a shared HTTP fileserver/store. The NATS message must only contain the metadata and the download URL.Tabular Data Format: * MUST use Apache Arrow IPC Stream for all tables/DataFrames. No CSV or standard JSON-serialization of tables allowed.System Symmetry: * Both services must function as Producers AND Consumers.Modular Elegance: * Implementation must be abstracted into a SmartSend function and a SmartReceive handler. The developer calling these functions should not need to care if the data is going via NATS direct or HTTP link.Technical Stack & Use CasesJulia: NATS.jl, Arrow.jl, JSON3.jl, HTTP.jl.Node.js: nats.js, apache-arrow.Scenarios to Support: * Large Data: Sending a 500MB Arrow table from Julia $\rightarrow$ JS.Media: Sending a 5MB WAV file from JS $\rightarrow$ Julia.Signals: Sending small JSON control commands ($< 10KB$) directly via NATS.Implementation Requirements1. Unified JSON Envelope:Define a schema containing: correlation_id (UUID), type (table/binary/json), transport (direct/link), payload (if direct), and url (if link).2. The Julia Module:Implement SmartSend(subject, data, type): Handles Arrow serialization to an IOBuffer, checks size, and manages HTTP uploads for large blobs.Implement SmartReceive(msg): Parses envelope, handles the HTTP fetch with Exponential Backoff (to avoid race conditions), and restores the DataFrame.Include a basic HTTP.listen server to serve as the temporary storage.3. The JavaScript Module:Implement a symmetric SmartSend using nats.js and apache-arrow.Implement a JetStream Pull Consumer for SmartReceive to ensure backpressure and memory safety.4. Performance & Reliability:Demonstrate "Zero-Copy" reading of the Arrow IPC stream on the JS side.Log the correlation_id at every stage for distributed tracing.
-
-
-
-
-
-
-
-Create a walkthrough for Julia service-A service sending a mix-content chat message to Julia service-B. the chat message must includes 

DO_NOT_READ_AI_prompt.txt

@@ -0,0 +1,154 @@
+Consider the following scenarios:
+Scenario 1: The "Command & Control" Loop (Low Latency)Focus: Small payloads, Core NATS, bi-directional JSON.The Action: A user on a JavaScript dashboard clicks a "Start Simulation" button. This sends a JSON configuration (parameters like step_size and iterations) to Julia.The Flow: * JS (Sender): Recognizes the message is small ($< 10KB$). Packages it as a direct transport JSON envelope.Julia (Receiver): Listens on the NATS subject, decodes the JSON, and immediately acknowledges receipt with a "Running" status.Project Requirement Met: Fast, low-overhead communication for control signals without involving the fileserver.
+Scenario 2: The "Deep Dive" Analysis (High Bandwidth)Focus: Large Arrow tables, Claim-Check pattern, Julia to JS.The Action: Julia finishes a heavy computation and produces a 500MB DataFrame with 10 million rows. It needs to send this to the JS frontend for visualization (e.g., using Perspective.js or D3).The Flow:Julia (Sender): Converts the DataFrame to an Arrow IPC stream. It sees the size is $> 1MB$, so it uploads the bytes to the HTTP fileserver. It then publishes a NATS message with transport: "link" and the URL.JS (Receiver): Receives the URL, fetches the data via fetch(), and uses tableFromIPC() to load the data into memory with zero-copy.Project Requirement Met: Handling massive datasets that exceed NATS message limits while maintaining data integrity across languages.
+Scenario 3: Live Audio/Signal Processing (Multimedia & Metadata)Focus: Raw binary, bi-directional streaming, NATS Headers.The Action: The JS client captures a 2-second "chunk" of microphone audio. It needs Julia to perform a Fast Fourier Transform (FFT) or AI transcription.The Flow:JS (Sender): Sends the raw binary WAV/PCM data. It uses NATS Headers to store the metadata ($fs = 44.1kHz$, $channels = 1$) to keep the payload purely binary.Julia (Receiver): Processes the audio and sends back a JSON result (the transcription) and an Arrow Table (the frequency spectrum data).Project Requirement Met: Bi-directional flow involving mixed media (Audio) and technical results (Arrow).
+Scenario 4: The "Catch-Up" (Persistence & JetStream)Focus: NATS JetStream, late-joining consumers, state sync.The Action: Julia is constantly publishing "System Health" updates. The JS dashboard is closed for 10 minutes. When the user re-opens the dashboard, they need to see the last 10 minutes of history.The Flow:NATS (Server): Uses a JetStream with a Limits retention policy.JS (Consumer): Connects and requests a "Replay" from the last 10 minutes. It receives a mix of direct (small updates) and link (historical snapshots) messages.Project Requirement Met: Temporal decoupling—consumers can receive data that was sent while they were offline.
+
+Role: Principal Systems Architect & Lead Software Engineer.Objective: Implement a high-performance, bi-directional data bridge between a Julia service and a JavaScript (Node.js) service using NATS (Core & JetStream).⚠️ STRICT ARCHITECTURAL CONSTRAINTS (Non-Negotiable)Transport Strategy (Claim-Check Pattern):Direct Path: If payload is < 1MB, send data directly via NATS inside the message envelope (Base64 encoded).Link Path: If payload is > 1MB, upload to a shared HTTP fileserver/store. The NATS message must only contain the metadata and the download URL.Tabular Data Format: * MUST use Apache Arrow IPC Stream for all tables/DataFrames. No CSV or standard JSON-serialization of tables allowed.System Symmetry: * Both services must function as Producers AND Consumers.Modular Elegance: * Implementation must be abstracted into a SmartSend function and a SmartReceive handler. The developer calling these functions should not need to care if the data is going via NATS direct or HTTP link.Technical Stack & Use CasesJulia: NATS.jl, Arrow.jl, JSON3.jl, HTTP.jl.Node.js: nats.js, apache-arrow.Scenarios to Support: * Large Data: Sending a 500MB Arrow table from Julia $\rightarrow$ JS.Media: Sending a 5MB WAV file from JS $\rightarrow$ Julia.Signals: Sending small JSON control commands ($< 10KB$) directly via NATS.Implementation Requirements1. Unified JSON Envelope:Define a schema containing: correlation_id (UUID), type (table/binary/json), transport (direct/link), payload (if direct), and url (if link).2. The Julia Module:Implement SmartSend(subject, data, type): Handles Arrow serialization to an IOBuffer, checks size, and manages HTTP uploads for large blobs.Implement SmartReceive(msg): Parses envelope, handles the HTTP fetch with Exponential Backoff (to avoid race conditions), and restores the DataFrame.Include a basic HTTP.listen server to serve as the temporary storage.3. The JavaScript Module:Implement a symmetric SmartSend using nats.js and apache-arrow.Implement a JetStream Pull Consumer for SmartReceive to ensure backpressure and memory safety.4. Performance & Reliability:Demonstrate "Zero-Copy" reading of the Arrow IPC stream on the JS side.Log the correlation_id at every stage for distributed tracing.
+
+
+
+
+
+
+
+Create a walkthrough for Julia service-A service sending a mix-content chat message to Julia service-B. the chat message must includes 
+
+
+
+
+
+I updated the following:
+- NATSBridge.jl. Essentially I add NATS_connection keyword and new publish_message function to support the keyword. 
+Use them and ONLY them as ground truth.
+Then update the following files accordingly:
+- architecture.md
+- implementation.md
+
+All API should be semantically consistent and naming should be consistent across the board.
+
+
+
+
+
+
+
+
+
+Task: Update NATSBridge.js to reflect recent changes in NATSBridge.jl and docs
+Context: NATSBridge.jl and docs has been updated.
+Requirements:
+Source of Truth: Treat the updated NATSBridge.jl and docs as the definitive source.
+API Consistency: Ensure the Main Package API (e.g., smartsend(), publish_message()) uses consistent naming across all three supported languages.
+Ecosystem Variance: Low-level native functions (e.g., NATS.connect(), JSON.read()) should follow the conventions of the specific language ecosystem and do not require cross-language consistency.
+
+
+
+
+
+
+
+I'm expanding this Julia package (NATSBridge) into a cross-platform project by adding a JavaScript and Python/MicroPython implementation. To ensure accuracy, the Julia src directory will serve as the ground truth, as the documentation may be outdated.
+
+My goal is to maintain interface parity at the high-level API for a consistent user experience, while ensuring the low-level implementation adheres strictly to the idiomatic conventions of each respective language (e.g., multiple dispatch in Julia vs. asynchronous, prototype, or class-based patterns in JS and Python/MicroPython)
+
+Now, help me do the following:
+1) check architecture.md for any mistake.
+
+
+
+
+Help me expands this Julia package (NATSBridge) into a cross-platform project by adding a JavaScript and Python/MicroPython implementation. To ensure accuracy,  NATSBridge.jl will serve as the ground truth, as the documentation may be outdated.
+
+My goal is to maintain interface parity at the high-level API for a consistent user experience, while ensuring the low-level implementation adheres strictly to the idiomatic conventions of each respective language (e.g., multiple dispatch in Julia vs. asynchronous, prototype, or class-based patterns in JS and Python/MicroPython)
+
+Now do the following:
+1) check docs to see if there is any mistake.
+
+
+
+
+
+I'm expanding this Julia package (NATSBridge) into a cross-platform project by adding 
+a JavaScript, Python and MicroPython implementation. 
+The following will serve as the ground truth:
+- test_julia_mix_payloads_sender.jl
+- NATSBridge.jl
+- test_julia_mix_payloads_receiver.jl
+- architecture.md
+
+My goal is to maintain interface parity at the high-level API for a consistent user experience, 
+while ensuring the low-level implementation adheres strictly to the idiomatic conventions of each 
+respective language (e.g., multiple dispatch in Julia vs. asynchronous, prototype, or class-based 
+patterns in JS, Python and MicroPython)
+
+Now, help me do the following:
+1) Check whether natsbridge.js needs update or it already up to date.
+
+
+
+
+
+
+
+# ---------------------------------------------- 100 --------------------------------------------- #
+
+Got it — let’s rebuild your table in my own teaching style, keeping it crisp, intuitive, and easy for students to grasp. I’ll emphasize **purpose, audience, format, example, and KPI** in a way that flows like a story of how projects move from idea → contract → design → code → review → operations.
+
+---
+
+### SDD + GitOps Documentation Framework
+
+| Document        | Purpose (Rationale) | Primary Audience | Format / Content | Example (SaaS Context) | Measurement (KPI) |
+|-----------------|---------------------|-----------------|------------------|------------------------|-------------------|
+| **Requirements** | Capture the **business intent** — why we’re building this and what success looks like. Defines boundaries and user‑visible outcomes. | Stakeholders, Product Owners, Lead Developers | User stories, PRDs, acceptance criteria, non‑functional constraints. | “System must process tabular data from Julia to SvelteKit UI with <200ms latency for 5‑member teams.” | 95% of requests complete <200ms (synthetic monitoring). |
+| **Specification** | The **technical contract** — precise rules for inputs, outputs, and data shape. Ensures consistency across dev and test. | Developers, QA Engineers, CI/CD pipelines | OpenAPI, Protobuf, AsyncAPI. Endpoint definitions, schemas, error codes. | `contract.yaml` defining a NATS subject that accepts Arrow streams with snake_case headers. | 100% of messages validated against spec (CI block rate). |
+| **Architecture** | The **blueprint** — how components fit together, interact, and scale. Guides system structure and trade‑offs. | Architects, Senior Developers, DevOps | C4 diagrams, Mermaid.js, component/network/storage models. | Diagram showing 6‑node cluster routing traffic via Caddy → Node.js API → Julia pods. | 100% of major decisions logged with trade‑off analysis. |
+| **Walkthrough** | The **story of flow** — shows how pieces connect end‑to‑end and why steps are sequenced. Builds intuition for new devs. | New Developers, Team Members | TOUR.md, Loom videos, sequence diagrams. Step‑by‑step traces with rationale. | “UI sends JSON → Node.js wraps Claim‑Check → Julia pulls Arrow data (prevents NATS overflow).” | New developers ship feature in <2 days (PR timeline). |
+| **Implementation** | The **real code** — business logic, helpers, tests, configs. Where design becomes executable. | Developers, Code Reviewers | Source code, README.md, unit tests, setup scripts. | Julia function for matrix calculation + SvelteKit component rendering table. | >80% unit test coverage, <5% drift from spec. |
+| **Validation** | The **enforcer** — ensures implementation matches the spec. Blocks drift and human error. | Automation servers, QA, Lead Developers | CI jobs, contract tests, linting, integration checks. | CI job rejects PR with camelCase field not allowed by YAML spec. | <1% of PRs bypass validation gates. |
+| **Runbook** | The **operational manual** — how the system lives in production, scales, and recovers. Guides on‑call engineers. | DevOps, SREs, On‑call Developers | K8s manifests, Helm charts, Markdown guides. Deployment, scaling, backup/restore, troubleshooting. | GitOps manifest ensuring 6 Julia replicas restart if memory >80%. | MTTR <15 minutes for P1 incidents. |
+
+
+
+
+
+
+
+
+# ---------------------------------------------- 100 --------------------------------------------- #
+
+SDD + GitOps Documentation Stack
+Document,"Purpose (The ""Rationale"")",Primary Audience,Format / Content,Example (SaaS Context),"Measurement (KPI)"
+Requirements,"Defines the ""Why"" and the Business Boundary. It sets the constraints and success criteria so the team knows when a feature is ""done"" from a user's perspective.","Stakeholders, Product Owners, Lead Developers","Format: User Stories, PRDs. Content: Functional goals, non-functional requirements (latency, scale), and explicit ""out-of-scope"" items.","""The system must process high-volume tabular data from Julia to the SvelteKit UI with <200ms latency for 5-member teams."",""Pass/Fail: 95% of requests complete <200ms (measured via synthetic monitoring)""
+The Spec,"The Technical Contract. It serves as the single source of truth that defines the shape of data. In SDD, this file drives code generation and automated testing.","Developers, QA Engineers, CI/CD Pipelines","Format: OpenAPI (YAML), Protobuf, AsyncAPI. Content: Endpoint definitions, strict data types, error codes, and request/response schemas.",A contract.yaml defining a NATS subject that accepts an Apache Arrow stream with specific snake_case headers.",""Schema Validation Rate: 100% of messages validated against spec (CI block rate)""
+Architecture,"The Structural Blueprint. It explains how the ""pieces"" are arranged in the cluster. It defines the relationships between services, databases, and external providers.","System Architects, Senior Developers, DevOps","Format: C4 Model Diagrams, Mermaid.js. Content: Component diagrams, network flow, storage strategy, and technology stack definitions.",A diagram showing how the 6-node cluster routes traffic through Caddy to the Node.js API and offloads heavy math to Julia pods.",""Architecture Decision Log: 100% of major decisions documented with trade-off analysis""
+Walkthrough,"The Intuition & Flow. It connects multiple APIs/services into a cohesive end-to-end story. It explains the ""steps"" and the ""rationale"" behind the sequence of operations.","New Developers, Current Team Members","Format: TOUR.md, Loom videos, Sequence Diagrams. Content: Step-by-step trace of a feature, explanation of state changes, and the ""why"" behind complex logic.","""End-to-End Trace:"" 1. UI sends JSON to Node.js. 2. Node.js wraps it in a Claim-Check. 3. Julia pulls the Arrow data. Rationale: This prevents NATS memory overflow.",""Onboarding Velocity: New developers deploy feature in <2 days (tracked via PR timeline)""
+Implementation,"The Functional Reality. This is the actual execution of the logic. In SDD, parts of this are auto-generated to ensure it never drifts from the Spec.","Developers, Code Reviewers","Format: Source Code (Git), README.md. Content: Business logic, internal helper functions, unit tests, and local setup instructions.",The Julia function that performs the matrix calculation and the SvelteKit component that renders the resulting table.",""Code Coverage: >80% unit test coverage, <5% test drift from spec""
+Validation,"The Enforcement Layer. It ensures that the ""Reality"" (Code) actually matches the ""Contract"" (Spec). It prevents human error from breaking the system.","Automation Servers, QA, Lead Developers","Format: GitHub Actions, Dredd, Prism. Content: Contract tests, linting rules, and integration tests that check API compliance.",A CI job that blocks a Pull Request because a developer added a camelCase field that isn't allowed in the shared YAML spec.",""Block Rate: <1% of PRs reach production without validation (CI gate pass rate)""
+Runbook,"The Operational Life-Support. It defines how the system lives in production and how to fix it. In GitOps, the ""State"" is declared here.","DevOps, SREs, On-call Developers","Format: K8s Manifests, Helm Charts, Markdown. Content: Deployment steps, scaling triggers, backup/restore commands, and troubleshooting guides.",A GitOps manifest in Flux that ensures 6 replicas of the Julia service are always running and restarts them if memory hits 80%.",""MTTR: <15 minutes for P1 incidents (tracked via incident management system)""
+
+Do you understand the provided text? Don't fucking change the table content. I want you to add "Measurement (KPI)" column. it is only example of course. This table will be used for consult and teaching.
+
+
+# ---------------------------------------------- 100 --------------------------------------------- #
+
+Can you write the table and explain this approach and each doc in details then save to docs/SDD_FRAMEWORK.md so I can consult it later.
+Don't forget to add How to use this approach effectively.
+
+
+# ---------------------------------------------- 100 --------------------------------------------- #
+
+Since I develop src folder before I adopt SDD_FRAMEWORK.md approach, can you check src folder and my current doc files then write docs/requirements.md  according to SDD framework? Treat src as ground truth.
+
+# ---------------------------------------------- 100 --------------------------------------------- #
+
+
+
+
+
+
+
+
+
+

Project.toml

@@ -1,6 +1,6 @@
 name = "NATSBridge"
 uuid = "f2724d33-f338-4a57-b9f8-1be882570d10"
-version = "0.4.1"
+version = "0.5.5"
 authors = ["narawat <narawat@gmail.com>"]
 
 [deps]

README.md

@@ -0,0 +1,672 @@
+# NATSBridge - Cross-Platform Bi-Directional Data Bridge
+
+A high-performance, bi-directional data bridge for **Julia, JavaScript, Python, and MicroPython** applications using NATS (Core & JetStream), implementing the Claim-Check pattern for large payloads.
+
+[![License: MIT](https://img.shields.io/badge/License-MIT-blue.svg)](https://opensource.org/licenses/MIT)
+[![NATS](https://img.shields.io/badge/NATS-Enabled-green.svg)](https://nats.io)
+
+---
+
+## Table of Contents
+
+- [Overview](#overview)
+- [Cross-Platform Support](#cross-platform-support)
+- [Features](#features)
+- [Quick Start](#quick-start)
+- [API Reference](#api-reference)
+- [Payload Types](#payload-types)
+- [Cross-Platform Examples](#cross-platform-examples)
+- [Testing](#testing)
+- [Documentation](#documentation)
+- [License](#license)
+
+---
+
+## Overview
+
+NATSBridge enables seamless communication across multiple platforms through NATS, with intelligent transport selection based on payload size:
+
+| Transport | Payload Size | Method |
+|-----------|--------------|--------|
+| **Direct** | < 1MB | Sent directly via NATS (Base64 encoded) |
+| **Link** | >= 1MB | Uploaded to HTTP file server, URL sent via NATS |
+
+### Use Cases
+
+- **Chat Applications**: Text, images, audio, video in a single message
+- **File Transfer**: Efficient transfer of large files using claim-check pattern
+- **IoT/Embedded**: Sensor data, telemetry, and analytics pipelines (MicroPython)
+- **Cross-Platform Communication**: Interoperability between Julia, JavaScript, Python, and MicroPython systems
+
+---
+
+## Cross-Platform Support
+
+| Platform | Implementation | Features |
+|----------|----------------|----------|
+| **Julia** | [`src/NATSBridge.jl`](src/NATSBridge.jl) | Full feature set, Arrow IPC, multiple dispatch |
+| **JavaScript** | [`src/natsbridge.js`](src/natsbridge.js) | Node.js, async/await |
+| **JavaScript (Browser)** | [`src/natsbridge_csr.js`](src/natsbridge_csr.js) | Browser, WebSocket NATS, async/await |
+| **Python** | [`src/natsbridge.py`](src/natsbridge.py) | Desktop Python, asyncio, type hints |
+| **MicroPython** | [`src/natsbridge_mpy.py`](src/natsbridge_mpy.py) | Memory-constrained, synchronous API |
+
+### Platform Comparison
+
+| Feature | Julia | JavaScript | JavaScript (Browser) | Python | MicroPython |
+|---------|-------|------------|----------------------|--------|-------------|
+| Multiple Dispatch | ✅ Native | ❌ | ❌ | ❌ | ❌ |
+| Async/Await | ❌ | ✅ Native | ✅ Native | ✅ Native | ⚠️ (uasyncio) |
+| Type Safety | ✅ Strong | ⚠️ (TypeScript) | ⚠️ (TypeScript) | ✅ (Type hints) | ❌ |
+| Arrow IPC | ✅ Native | ✅ | ✅ | ✅ | ❌ |
+| Direct Transport | ✅ | ✅ | ✅ | ✅ | ✅ |
+| Link Transport | ✅ | ✅ | ✅ | ✅ | ⚠️ (Limited) |
+| Handler Functions | ✅ | ✅ | ✅ | ✅ | ✅ |
+| Cross-Platform API | ✅ | ✅ | ✅ | ✅ | ✅ |
+| WebSocket NATS | ❌ | ❌ | ✅ | ❌ | ❌ |
+
+---
+
+## Features
+
+- ✅ **Cross-platform messaging** for Julia, JavaScript, Python, and MicroPython applications
+- ✅ **Bi-directional messaging** with request-reply patterns
+- ✅ **Multi-payload support** - send multiple payloads with different types in one message
+- ✅ **Automatic transport selection** - direct vs link based on payload size
+- ✅ **Claim-Check pattern** for payloads > 1MB
+- ✅ **Apache Arrow IPC** support for tabular data (zero-copy reading)
+- ✅ **Exponential backoff** for reliable file server downloads
+- ✅ **Correlation ID tracking** for message tracing
+- ✅ **Reply-to support** for request-response patterns
+- ✅ **Handler function abstraction** - pluggable file server implementations (Plik, AWS S3, custom)
+
+---
+
+## Quick Start
+
+### Step 1: Start NATS Server
+
+```bash
+docker run -p 4222:4222 nats:latest
+```
+
+### Step 2: Start HTTP File Server (Optional)
+
+```bash
+# Create a directory for file uploads
+mkdir -p /tmp/fileserver
+
+# Start HTTP file server
+python3 -m http.server 8080 --directory /tmp/fileserver
+```
+
+### Step 3: Send Your First Message
+
+#### Julia
+
+```julia
+using NATSBridge
+
+data = [("message", "Hello World", "text")]
+env, env_json_str = smartsend("/chat/room1", data, broker_url="nats://localhost:4222")
+println("Message sent!")
+```
+
+#### JavaScript
+
+```javascript
+const NATSBridge = require('./src/natsbridge.js');
+
+const data = [["message", "Hello World", "text"]];
+const [env, env_json_str] = await NATSBridge.smartsend(
+    "/chat/room1",
+    data,
+    { broker_url: "nats://localhost:4222" }
+);
+console.log("Message sent!");
+```
+
+#### Python
+
+```python
+from natsbridge import smartsend
+
+data = [("message", "Hello World", "text")]
+env, env_json_str = await smartsend(
+    "/chat/room1",
+    data,
+    broker_url="nats://localhost:4222"
+)
+print("Message sent!")
+```
+
+---
+
+## API Reference
+
+### Unified API Standard
+
+All platforms use the same input/output format for payloads:
+
+**Input format for smartsend:**
+```
+[(dataname1, data1, type1), (dataname2, data2, type2), ...]
+```
+
+**Output format for smartreceive:**
+```
+{
+  "correlation_id": "...",
+  "msg_id": "...",
+  "timestamp": "...",
+  "send_to": "...",
+  "msg_purpose": "...",
+  "sender_name": "...",
+  "sender_id": "...",
+  "receiver_name": "...",
+  "receiver_id": "...",
+  "reply_to": "...",
+  "reply_to_msg_id": "...",
+  "broker_url": "...",
+  "metadata": {...},
+  "payloads": [(dataname1, data1, type1), (dataname2, data2, type2), ...]
+}
+```
+
+### smartsend
+
+Sends data either directly via NATS or via a fileserver URL, depending on payload size.
+
+#### Julia
+
+```julia
+using NATSBridge
+
+env, env_json_str = NATSBridge.smartsend(
+    subject::String,
+    data::AbstractArray{Tuple{String, Any, String}};
+    broker_url::String = "nats://localhost:4222",
+    fileserver_url = "http://localhost:8080",
+    fileserver_upload_handler::Function = plik_oneshot_upload,
+    size_threshold::Int = 1_000_000,
+    correlation_id::String = string(uuid4()),
+    msg_purpose::String = "chat",
+    sender_name::String = "NATSBridge",
+    receiver_name::String = "",
+    receiver_id::String = "",
+    reply_to::String = "",
+    reply_to_msg_id::String = "",
+    is_publish::Bool = true,
+    NATS_connection::Union{NATS.Connection, Nothing} = nothing,
+    msg_id::String = string(uuid4()),
+    sender_id::String = string(uuid4())
+)
+# Returns: ::Tuple{msg_envelope_v1, String}
+```
+
+#### JavaScript
+
+```javascript
+const NATSBridge = require('natsbridge');
+
+const [env, env_json_str] = await NATSBridge.smartsend(
+    subject,
+    data,  // Array of [dataname, data, type] tuples
+    {
+        broker_url: 'nats://localhost:4222',
+        fileserver_url: 'http://localhost:8080',
+        fileserver_upload_handler: NATSBridge.plikOneshotUpload,
+        size_threshold: 1_000_000,
+        correlation_id: uuidv4(),
+        msg_purpose: 'chat',
+        sender_name: 'NATSBridge',
+        receiver_name: '',
+        receiver_id: '',
+        reply_to: '',
+        reply_to_msg_id: '',
+        is_publish: true,
+        nats_connection: null,
+        msg_id: uuidv4(),
+        sender_id: uuidv4()
+    }
+);
+// Returns: Promise<[env, env_json_str]>
+```
+
+#### Python
+
+```python
+from natsbridge import NATSBridge
+
+env, env_json_str = await NATSBridge.smartsend(
+    subject: str,
+    data: List[Tuple[str, Any, str]],
+    broker_url: str = "nats://localhost:4222",
+    fileserver_url: str = "http://localhost:8080",
+    fileserver_upload_handler: Callable = plik_oneshot_upload,
+    size_threshold: int = 1_000_000,
+    correlation_id: str = None,
+    msg_purpose: str = "chat",
+    sender_name: str = "NATSBridge",
+    receiver_name: str = "",
+    receiver_id: str = "",
+    reply_to: str = "",
+    reply_to_msg_id: str = "",
+    is_publish: bool = True,
+    nats_connection: Any = None,
+    msg_id: str = None,
+    sender_id: str = None
+)
+# Returns: Tuple[Dict, str]
+```
+
+#### MicroPython
+
+```python
+from natsbridge import NATSBridge
+
+# Limited to direct transport (< 100KB threshold)
+env, env_json_str = NATSBridge.smartsend(
+    subject,
+    data,  # List of (dataname, data, type) tuples
+    broker_url="nats://localhost:4222",
+    size_threshold=100000  # Lower threshold for memory constraints
+)
+# Returns: Tuple[Dict, str]
+```
+
+### smartreceive
+
+Receives and processes messages from NATS, handling both direct and link transport.
+
+#### Julia
+
+```julia
+using NATSBridge
+
+env = NATSBridge.smartreceive(
+    msg::NATS.Msg;
+    fileserver_download_handler::Function = _fetch_with_backoff,
+    max_retries::Int = 5,
+    base_delay::Int = 100,
+    max_delay::Int = 5000
+)
+# Returns: ::JSON.Object{String, Any}
+```
+
+#### JavaScript
+
+```javascript
+const env = await NATSBridge.smartreceive(
+    msg,
+    {
+        fileserver_download_handler: NATSBridge.fetchWithBackoff,
+        max_retries: 5,
+        base_delay: 100,
+        max_delay: 5000
+    }
+);
+// Returns: Promise<env_object>
+```
+
+#### Python
+
+```python
+env = await NATSBridge.smartreceive(
+    msg,
+    fileserver_download_handler=fetch_with_backoff,
+    max_retries=5,
+    base_delay=100,
+    max_delay=5000
+)
+# Returns: Dict with "payloads" key
+```
+
+#### MicroPython
+
+```python
+env = NATSBridge.smartreceive(
+    msg,
+    fileserver_download_handler=_sync_fileserver_download,
+    max_retries=3,
+    base_delay=100,
+    max_delay=1000
+)
+# Returns: Dict with "payloads" key
+```
+
+---
+
+## Payload Types
+
+| Type | Julia | JavaScript | Python | MicroPython | Description |
+|------|-------|------------|--------|-------------|-------------|
+| `text` | `String` | `string` | `str` | `str` | Plain text strings |
+| `dictionary` | `Dict`, `NamedTuple` | `Object`, `Array` | `dict`, `list` | `dict` | JSON-serializable dictionaries |
+| `arrowtable` | `DataFrame`, `Arrow.Table` | `Array<Object>` | `pandas.DataFrame` | ❌ | Tabular data (Arrow IPC) |
+| `jsontable` | `Vector{NamedTuple}` | `Array<Object>` | `list[dict]` | ❌ | Tabular data (JSON) |
+| `image` | `Vector{UInt8}` | `Uint8Array`, `Buffer` | `bytes` | `bytearray` | Image data (PNG, JPG) |
+| `audio` | `Vector{UInt8}` | `Uint8Array`, `Buffer` | `bytes` | `bytearray` | Audio data (WAV, MP3) |
+| `video` | `Vector{UInt8}` | `Uint8Array`, `Buffer` | `bytes` | `bytearray` | Video data (MP4, AVI) |
+| `binary` | `Vector{UInt8}`, `IOBuffer` | `Uint8Array`, `Buffer` | `bytes`, `bytearray` | `bytearray` | Generic binary data |
+
+---
+
+## Cross-Platform Examples
+
+### Example 1: Chat with Mixed Content
+
+Send text, image, and large file in one message.
+
+#### Julia
+
+```julia
+using NATSBridge
+
+data = [
+    ("message_text", "Hello!", "text"),
+    ("user_avatar", image_data, "image"),
+    ("large_document", large_file_data, "binary")
+]
+
+env, env_json_str = NATSBridge.smartsend("/chat/room1", data; fileserver_url="http://localhost:8080")
+```
+
+#### JavaScript
+
+```javascript
+const NATSBridge = require('natsbridge');
+
+const data = [
+    ["message_text", "Hello!", "text"],
+    ["user_avatar", imageData, "image"],
+    ["large_document", largeFileData, "binary"]
+];
+
+const [env, env_json_str] = await NATSBridge.smartsend(
+    "/chat/room1",
+    data,
+    { fileserver_url: 'http://localhost:8080' }
+);
+```
+
+#### Python
+
+```python
+from natsbridge import NATSBridge
+
+data = [
+    ("message_text", "Hello!", "text"),
+    ("user_avatar", image_data, "image"),
+    ("large_document", large_file_data, "binary")
+]
+
+env, env_json_str = await NATSBridge.smartsend(
+    "/chat/room1",
+    data,
+    fileserver_url="http://localhost:8080"
+)
+```
+
+### Example 2: Dictionary Exchange
+
+Send configuration data between platforms.
+
+#### Julia
+
+```julia
+using NATSBridge
+
+config = Dict(
+    "wifi_ssid" => "MyNetwork",
+    "wifi_password" => "password123",
+    "update_interval" => 60
+)
+
+data = [("config", config, "dictionary")]
+env, env_json_str = NATSBridge.smartsend("/device/config", data)
+```
+
+#### JavaScript
+
+```javascript
+const NATSBridge = require('natsbridge');
+
+const config = {
+    wifi_ssid: "MyNetwork",
+    wifi_password: "password123",
+    update_interval: 60
+};
+
+const [env, env_json_str] = await NATSBridge.smartsend(
+    "/device/config",
+    [["config", config, "dictionary"]]
+);
+```
+
+#### Python
+
+```python
+from natsbridge import NATSBridge
+
+config = {
+    "wifi_ssid": "MyNetwork",
+    "wifi_password": "password123",
+    "update_interval": 60
+}
+
+data = [("config", config, "dictionary")]
+env, env_json_str = await NATSBridge.smartsend("/device/config", data)
+```
+
+### Example 3: Table Data (Arrow IPC)
+
+Send tabular data using Apache Arrow IPC format.
+
+#### Julia
+
+```julia
+using NATSBridge
+using DataFrames
+
+df = DataFrame(
+    id = [1, 2, 3],
+    name = ["Alice", "Bob", "Charlie"],
+    score = [95, 88, 92]
+)
+
+data = [("students", df, "arrowtable")]
+env, env_json_str = NATSBridge.smartsend("/data/analysis", data)
+```
+
+#### JavaScript
+
+```javascript
+const NATSBridge = require('natsbridge');
+
+const df = [
+    { id: 1, name: "Alice", score: 95 },
+    { id: 2, name: "Bob", score: 88 },
+    { id: 3, name: "Charlie", score: 92 }
+];
+
+const [env, env_json_str] = await NATSBridge.smartsend(
+    "/data/analysis",
+    [["students", df, "arrowtable"]]
+);
+```
+
+#### Python
+
+```python
+from natsbridge import NATSBridge
+import pandas as pd
+
+df = pd.DataFrame({
+    "id": [1, 2, 3],
+    "name": ["Alice", "Bob", "Charlie"],
+    "score": [95, 88, 92]
+})
+
+data = [("students", df, "arrowtable")]
+env, env_json_str = await NATSBridge.smartsend("/data/analysis", data)
+```
+
+### Example 4: Request-Response Pattern
+
+Bi-directional communication with reply-to support.
+
+#### Julia
+
+```julia
+using NATSBridge
+
+# Requester
+env, env_json_str = NATSBridge.smartsend(
+    "/device/command",
+    [("command", Dict("action" => "read_sensor"), "dictionary")];
+    broker_url="nats://localhost:4222",
+    reply_to="/device/response"
+)
+```
+
+#### JavaScript
+
+```javascript
+const NATSBridge = require('natsbridge');
+
+// Requester
+const [env, env_json_str] = await NATSBridge.smartsend(
+    "/device/command",
+    [["command", { action: "read_sensor" }, "dictionary"]],
+    { broker_url: 'nats://localhost:4222', reply_to: '/device/response' }
+);
+```
+
+#### Python
+
+```python
+from natsbridge import NATSBridge
+
+# Requester
+env, env_json_str = await NATSBridge.smartsend(
+    "/device/command",
+    [("command", {"action": "read_sensor"}, "dictionary")],
+    broker_url="nats://localhost:4222",
+    reply_to="/device/response"
+)
+```
+
+---
+
+## Testing
+
+### Test File Organization
+
+| Platform | Sender Tests | Receiver Tests |
+|----------|--------------|----------------|
+| **Julia** | `test/test_julia_*_sender.jl` | `test/test_julia_*_receiver.jl` |
+| **JavaScript** | `test/test_js_*_sender.js` | `test/test_js_*_receiver.js` |
+| **Python** | `test/test_py_*_sender.py` | `test/test_py_*_receiver.py` |
+
+### Run Tests
+
+#### Julia
+
+```bash
+# Text message exchange
+julia test/test_julia_text_sender.jl
+julia test/test_julia_text_receiver.jl
+
+# Dictionary exchange
+julia test/test_julia_dict_sender.jl
+julia test/test_julia_dict_receiver.jl
+
+# File transfer
+julia test/test_julia_file_sender.jl
+julia test/test_julia_file_receiver.jl
+
+# Mixed payload types
+julia test/test_julia_mix_payloads_sender.jl
+julia test/test_julia_mix_payloads_receiver.jl
+
+# Table exchange
+julia test/test_julia_table_sender.jl
+julia test/test_julia_table_receiver.jl
+```
+
+#### JavaScript (Node.js)
+
+```bash
+# Text message exchange
+node test/test_js_text_sender.js
+node test/test_js_text_receiver.js
+
+# Dictionary exchange
+node test/test_js_dictionary_sender.js
+node test/test_js_dictionary_receiver.js
+
+# Binary transfer
+node test/test_js_binary_sender.js
+node test/test_js_binary_receiver.js
+
+# Table exchange
+node test/test_js_table_sender.js
+node test/test_js_table_receiver.js
+```
+
+#### Python
+
+```bash
+# Text message exchange
+python3 test/test_py_text_sender.py
+python3 test/test_py_text_receiver.py
+
+# Dictionary exchange
+python3 test/test_py_dictionary_sender.py
+python3 test/test_py_dictionary_receiver.py
+
+# Binary transfer
+python3 test/test_py_binary_sender.py
+python3 test/test_py_binary_receiver.py
+
+# Table exchange
+python3 test/test_py_table_sender.py
+python3 test/test_py_table_receiver.py
+```
+
+---
+
+## Documentation
+
+For detailed architecture and implementation information, see:
+
+- [Architecture Documentation](docs/architecture_updated.md) - Cross-platform architecture, API parity, platform-specific patterns
+- [Implementation Guide](docs/implementation_updated.md) - Detailed implementation for each platform, handler functions, testing
+- [Tutorial](docs/tutorial_updated.md) - Step-by-step getting started guide
+- [Walkthrough](docs/walkthrough_updated.md) - Real-world application building guides
+
+---
+
+## License
+
+MIT License
+
+Copyright (c) 2026 NATSBridge Contributors
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

docs/SDD_FRAMEWORK.md

@@ -0,0 +1,402 @@
+# SDD + GitOps Documentation Framework
+
+This document defines the documentation framework for the NATSBridge project. It establishes a structured approach to creating, maintaining, and evolving technical documentation in alignment with GitOps principles—ensuring that documentation is versioned, auditable, and continuously validated alongside the codebase.
+
+---
+
+## The SDD Framework: Seven Pillars of Documentation
+
+| Document | Purpose (Rationale) | Primary Audience | Format / Content | Example (SaaS Context) | Measurement (KPI) |
+|----------|---------------------|-----------------|------------------|------------------------|-------------------|
+| **Requirements** | Capture the **business intent** — why we're building this and what success looks like. Defines boundaries and user-visible outcomes. | Stakeholders, Product Owners, Lead Developers | User stories, PRDs, acceptance criteria, non-functional constraints. | "System must process tabular data from Julia to SvelteKit UI with <200ms latency for 5-member teams." | 95% of requests complete <200ms (synthetic monitoring). |
+| **Specification** | The **technical contract** — precise rules for inputs, outputs, and data shape. Ensures consistency across dev and test. | Developers, QA Engineers, CI/CD pipelines | OpenAPI, Protobuf, AsyncAPI. Endpoint definitions, schemas, error codes. | `contract.yaml` defining a NATS subject that accepts Arrow streams with snake_case headers. | 100% of messages validated against spec (CI block rate). |
+| **Architecture** | The **blueprint** — how components fit together, interact, and scale. Guides system structure and trade-offs. | Architects, Senior Developers, DevOps | C4 diagrams, Mermaid.js, component/network/storage models. | Diagram showing 6-node cluster routing traffic via Caddy → Node.js API → Julia pods. | 100% of major decisions logged with trade-off analysis. |
+| **Walkthrough** | The **story of flow** — shows how pieces connect end-to-end and why steps are sequenced. Builds intuition for new devs. | New Developers, Team Members | TOUR.md, Loom videos, sequence diagrams. Step-by-step traces with rationale. | "UI sends JSON → Node.js wraps Claim-Check → Julia pulls Arrow data (prevents NATS overflow)." | New developers ship feature in <2 days (PR timeline). |
+| **Implementation** | The **real code** — business logic, helpers, tests, configs. Where design becomes executable. | Developers, Code Reviewers | Source code, README.md, unit tests, setup scripts. | Julia function for matrix calculation + SvelteKit component rendering table. | >80% unit test coverage, <5% drift from spec. |
+| **Validation** | The **enforcer** — ensures implementation matches the spec. Blocks drift and human error. | Automation servers, QA, Lead Developers | CI jobs, contract tests, linting, integration checks. | CI job rejects PR with camelCase field not allowed by YAML spec. | <1% of PRs bypass validation gates. |
+| **Runbook** | The **operational manual** — how the system lives in production, scales, and recovers. Guides on-call engineers. | DevOps, SREs, On-call Developers | K8s manifests, Helm charts, Markdown guides. Deployment, scaling, backup/restore, troubleshooting. | GitOps manifest ensuring 6 Julia replicas restart if memory >80%. | MTTR <15 minutes for P1 incidents. |
+
+---
+
+## Detailed Document Descriptions
+
+### 1. Requirements
+
+**Purpose**: Capture the *business intent* — why we're building this and what success looks like. Defines boundaries and user-visible outcomes.
+
+**Why It Matters**:
+- Aligns engineering efforts with business goals
+- Provides a north star for feature development
+- Establishes acceptance criteria before implementation begins
+- Creates a contract between product and engineering
+
+**Content Guidelines**:
+- User stories with clear acceptance criteria (As a X, I want Y so that Z)
+- Product Requirements Documents (PRDs) with success metrics
+- Non-functional requirements (performance, security, scalability)
+- Boundary definitions (what's in scope vs. out of scope)
+
+**Best Practices**:
+- Link each requirement to a measurable KPI
+- Keep requirements testable and verifiable
+- Maintain backward compatibility with existing requirements
+- Review and update requirements as business context changes
+
+---
+
+### 2. Specification
+
+**Purpose**: The *technical contract* — precise rules for inputs, outputs, and data shape. Ensures consistency across dev and test.
+
+**Why It Matters**:
+- Prevents implementation drift between components
+- Enables contract testing in CI/CD pipelines
+- Provides a single source of truth for data structures
+- Facilitates integration between teams
+
+**Content Guidelines**:
+- API endpoint definitions (methods, paths, parameters)
+- Request/response schemas (JSON, XML, Protobuf, AsyncAPI)
+- Error codes and their meanings
+- Data validation rules and constraints
+- Rate limiting and quota definitions
+
+**Best Practices**:
+- Use formal specification languages (OpenAPI 3.0+, AsyncAPI)
+- Version specifications alongside code
+- Generate client SDKs from specifications
+- Block CI on specification violations
+- Document edge cases and error scenarios
+
+---
+
+### 3. Architecture
+
+**Purpose**: The *blueprint* — how components fit together, interact, and scale. Guides system structure and trade-offs.
+
+**Why It Matters**:
+- Provides a mental model for system design
+- Guides technical decision-making and trade-off analysis
+- Facilitates onboarding of new architects and senior developers
+- Documents scaling and performance considerations
+
+**Content Guidelines**:
+- C4 diagrams (Context, Container, Component levels)
+- Mermaid.js flowcharts for sequence diagrams
+- Component interaction diagrams
+- Network topology and data flow
+- Storage and caching strategies
+- Scaling and resilience patterns
+
+**Best Practices**:
+- Use diagrams that are easy to update (Mermaid.js over static images)
+- Document trade-off decisions with Rationale Documents
+- Include scaling considerations for each component
+- Document failure modes and recovery strategies
+- Keep architecture diagrams versioned with code
+
+---
+
+### 4. Walkthrough
+
+**Purpose**: The *story of flow* — shows how pieces connect end-to-end and why steps are sequenced. Builds intuition for new devs.
+
+**Why It Matters**:
+- Reduces onboarding time for new developers
+- Provides context that code comments alone cannot convey
+- Explains the "why" behind architectural decisions
+- Helps identify gaps in the system design
+
+**Content Guidelines**:
+- Step-by-step flow descriptions with rationale
+- Sequence diagrams showing request/response patterns
+- "Tour of the codebase" guides
+- Video walkthroughs (Loom, internal recordings)
+- Debugging and tracing examples
+
+**Best Practices**:
+- Walk through real user journeys, not just technical flows
+- Include "what could go wrong" scenarios
+- Link walkthroughs to relevant code locations
+- Keep walkthroughs updated with architecture changes
+- Make walkthroughs interactive where possible
+
+---
+
+### 5. Implementation
+
+**Purpose**: The *real code* — business logic, helpers, tests, configs. Where design becomes executable.
+
+**Why It Matters**:
+- This is the actual artifact that runs in production
+- Code is the ultimate source of truth (when it matches spec)
+- Tests validate correctness and prevent regressions
+- Configuration files define runtime behavior
+
+**Content Guidelines**:
+- Business logic implementation
+- Helper functions and utilities
+- Unit and integration tests
+- Configuration files (YAML, JSON, environment)
+- Setup and development scripts
+- Code organization and module structure
+
+**Best Practices**:
+- Follow consistent code style and conventions
+- Write tests before or alongside implementation (TDD/BDD)
+- Document complex logic with inline comments
+- Keep configuration externalized and versioned
+- Use type annotations where applicable
+
+---
+
+### 6. Validation
+
+**Purpose**: The *enforcer* — ensures implementation matches the spec. Blocks drift and human error.
+
+**Why It Matters**:
+- Prevents breaking changes from reaching production
+- Catches specification violations early in the CI pipeline
+- Maintains data integrity and API consistency
+- Reduces manual QA effort through automation
+
+**Content Guidelines**:
+- CI/CD pipeline configurations
+- Contract testing scripts
+- Linting rules and configurations
+- Integration test suites
+- Schema validation jobs
+- Security scanning and audit jobs
+
+**Best Practices**:
+- Fail CI on specification violations
+- Run validation jobs on every commit and PR
+- Use automated code review tools
+- Maintain validation job health dashboard
+- Document validation failure remediation steps
+
+---
+
+### 7. Runbook
+
+**Purpose**: The *operational manual* — how the system lives in production, scales, and recovers. Guides on-call engineers.
+
+**Why It Matters**:
+- Reduces Mean Time To Recovery (MTTR) for incidents
+- Provides step-by-step guidance for common issues
+- Documents scaling and deployment procedures
+- Ensures operational knowledge is not siloed
+
+**Content Guidelines**:
+- Deployment procedures (manual and automated)
+- Scaling instructions (horizontal/vertical)
+- Backup and restore procedures
+- Troubleshooting guides for common issues
+- Runbook entries for specific error codes
+- Contact information and escalation paths
+
+**Best Practices**:
+- Write runbooks for every P1/P2 incident
+- Include exact commands and configuration snippets
+- Test runbooks periodically (chaos engineering)
+- Link runbook entries to relevant documentation
+- Keep runbooks updated when system changes
+
+---
+
+## How to Use This Approach Effectively
+
+### 1. Start with Requirements
+
+Before writing any code or documentation, establish clear requirements. Ask:
+- What business problem are we solving?
+- How will we measure success?
+- What are the non-negotiable constraints?
+
+**Action**: Create a `docs/requirements/` directory and start with `PRD.md` and `KPIs.md`.
+
+### 2. Define the Specification First
+
+Once requirements are stable, define the technical specification. This becomes the contract for implementation.
+
+**Action**: Create `docs/specification/` with `contract.yaml` (or appropriate format) and `error-codes.md`.
+
+### 3. Design the Architecture
+
+With requirements and specification in place, design the architecture. Document trade-off decisions explicitly.
+
+**Action**: Create `docs/architecture/` with Mermaid diagrams and `trade-offs.md`.
+
+### 4. Create Walkthroughs Early
+
+As soon as the architecture is defined, create walkthroughs. This helps identify gaps and provides onboarding material.
+
+**Action**: Create `docs/walkthrough/` with `TOUR.md` and sequence diagrams.
+
+### 5. Implement with Validation in Mind
+
+Write implementation code that adheres to the specification. Build validation into the CI pipeline from day one.
+
+**Action**: Ensure test files are co-located with implementation and run on every commit.
+
+### 6. Automate Validation
+
+Build automated validation that runs in CI/CD. This ensures spec compliance and prevents drift.
+
+**Action**: Configure CI jobs to validate against specification and block PRs on violations.
+
+### 7. Document Operations from Day One
+
+Create runbook entries as soon as deployment procedures are established. Update them when incidents occur.
+
+**Action**: Create `docs/runbook/` with entries for deployment, scaling, and common issues.
+
+---
+
+## GitOps Integration
+
+This documentation framework aligns with GitOps principles:
+
+| GitOps Principle | Documentation Alignment |
+|-----------------|------------------------|
+| **Versioned** | All documentation lives in git, with history and audit trail |
+| ** declarative** | Specifications and architecture are declarative contracts |
+| **Automated** | Validation jobs automate spec compliance checks |
+| **Self-Service** | Walkthroughs and runbooks enable self-service onboarding and operations |
+| **Observability** | KPIs and metrics are defined for each documentation artifact |
+
+**Git Structure**:
+```
+docs/
+├── requirements/       # PRDs, user stories, KPIs
+├── specification/      # OpenAPI, Protobuf, AsyncAPI specs
+├── architecture/       # C4 diagrams, Mermaid, trade-off docs
+├── walkthrough/        # TOUR.md, sequence diagrams
+├── implementation/     # Source code (in src/)
+├── validation/         # CI configs, test suites
+└── runbook/            # Deployment, scaling, troubleshooting
+```
+
+---
+
+## Metrics and Continuous Improvement
+
+Each documentation artifact has associated KPIs. Track these to ensure quality:
+
+| Document | KPI | Target |
+|----------|-----|--------|
+| Requirements | Requirement coverage | 100% of features have associated requirements |
+| Specification | Spec compliance rate | 100% of messages validate against spec |
+| Architecture | Decision documentation | 100% of major decisions logged with trade-offs |
+| Walkthrough | New dev time-to-first-PR | <2 days from onboarding to first contribution |
+| Implementation | Test coverage | >80% unit test coverage |
+| Validation | Bypass rate | <1% of PRs bypass validation gates |
+| Runbook | MTTR | <15 minutes for P1 incidents |
+
+**Review Cadence**:
+- Weekly: Review KPI dashboards and documentation gaps
+- Monthly: Update documentation based on incident learnings
+- Quarterly: Full framework review and improvement
+
+---
+
+## Template Examples
+
+### Requirements Template
+```markdown
+# PRD: Feature Name
+
+## Business Goal
+[What problem are we solving?]
+
+## Success Metrics
+- [Metric 1]: Target [value]
+- [Metric 2]: Target [value]
+
+## User Stories
+- As a [role], I want [feature] so that [benefit]
+  - Acceptance Criteria: [details]
+
+## Non-Functional Requirements
+- Performance: [details]
+- Security: [details]
+- Scalability: [details]
+
+## Out of Scope
+- [What's explicitly excluded]
+```
+
+### Specification Template
+```yaml
+# contract.yaml
+openapi: 3.0.0
+info:
+  title: NATSBridge API
+  version: 1.0.0
+paths:
+  /api/v1/endpoint:
+    post:
+      requestBody:
+        content:
+          application/json:
+            schema:
+              $ref: '#/components/schemas/Request'
+      responses:
+        '200':
+          description: Success
+          content:
+            application/json:
+              schema:
+                $ref: '#/components/schemas/Response'
+```
+
+### Architecture Template
+```mermaid
+%%{init: {'theme': 'base', 'themeVariables': {'primaryColor': '#3b82f6'}}}%%
+flowchart TD
+    A[Client] --> B[Caddy]
+    B --> C[Node.js API]
+    C --> D[Julia Worker]
+    D --> E[NATS Cluster]
+    E --> F[Storage]
+    
+    style A fill:#f9f9f9,stroke:#333
+    style E fill:#e0e7ff,stroke:#3b82f6
+```
+
+### Runbook Template
+```markdown
+# Runbook: Service Restart
+
+**Severity**: P2
+**Estimated Time**: 5 minutes
+
+## Symptoms
+- Service is unresponsive
+- Health checks are failing
+
+## Steps
+1. SSH to the host
+2. Run: `kubectl rollout restart deployment/natsbridge`
+3. Monitor: `kubectl get pods -l app=natsbridge -w`
+
+## Rollback
+- Run: `kubectl rollout undo deployment/natsbridge`
+
+## Post-Incident
+- [ ] Review logs for root cause
+- [ ] Update runbook if needed
+```
+
+---
+
+## Conclusion
+
+This SDD + GitOps Documentation Framework ensures that documentation is:
+- **Structured**: Seven distinct artifacts with clear purposes
+- **Automated**: Validation and CI/CD integration
+- **Versioned**: All documentation in git with history
+- **Measurable**: KPIs for quality and effectiveness
+- **Actionable**: Practical templates and examples
+
+Use this framework as a living document—update it as your team's needs evolve.

docs/implementation.md

@@ -1,599 +0,0 @@
-# Implementation Guide: Bi-Directional Data Bridge
-
-## Overview
-
-This document describes the implementation of the high-performance, bi-directional data bridge between Julia and JavaScript services using NATS (Core & JetStream), implementing the Claim-Check pattern for large payloads.
-
-### Multi-Payload Support
-
-The implementation uses a **standardized list-of-tuples format** for all payload operations. **Even when sending a single payload, the user must wrap it in a list.**
-
-**API Standard:**
-```julia
-# Input format for smartsend (always a list of tuples with type info)
-[(dataname1, data1, type1), (dataname2, data2, type2), ...]
-
-# Output format for smartreceive (always returns a list of tuples with type info)
-[(dataname1, data1, type1), (dataname2, data2, type2), ...]
-```
-
-Where `type` can be: `"text"`, `"dictionary"`, `"table"`, `"image"`, `"audio"`, `"video"`, `"binary"`
-
-**Examples:**
-```julia
-# Single payload - still wrapped in a list (type is required as third element)
-smartsend("/test", [(dataname1, data1, "text")], ...)
-
-# Multiple payloads in one message (each payload has its own type)
-smartsend("/test", [(dataname1, data1, "dictionary"), (dataname2, data2, "table")], ...)
-
-# Receive always returns a list with type info
-payloads = smartreceive(msg, ...)
-# payloads = [(dataname1, data1, "text"), (dataname2, data2, "table"), ...]
-```
-
-## Architecture
-
-The implementation follows the Claim-Check pattern:
-
-```
-┌─────────────────────────────────────────────────────────────────────────┐
-│                         SmartSend Function                              │
-└─────────────────────────────────────────────────────────────────────────┘
-                             │
-                             ▼
-┌─────────────────────────────────────────────────────────────────────────┐
-│  Is payload size < 1MB?                                                 │
-└─────────────────────────────────────────────────────────────────────────┘
-                             │
-           ┌─────────────────┴─────────────────┐
-           ▼                                   ▼
-     ┌─────────────────┐                 ┌─────────────────┐
-     │  Direct Path    │                 │  Link Path      │
-     │  (< 1MB)        │                 │  (> 1MB)        │
-     │                 │                 │                 │
-     │ • Serialize to  │                 │ • Serialize to  │
-     │   IOBuffer      │                 │   IOBuffer      │
-     │ • Base64 encode │                 │ • Upload to     │
-     │ • Publish to    │                 │   HTTP Server   │
-     │   NATS          │                 │ • Publish to    │
-     │                 │                 │   NATS with URL │
-     └─────────────────┘                 └─────────────────┘
-```
-
-## Files
-
-### Julia Module: [`src/julia_bridge.jl`](../src/julia_bridge.jl)
-
-The Julia implementation provides:
-
-- **[`MessageEnvelope`](../src/julia_bridge.jl)**: Struct for the unified JSON envelope
-- **[`SmartSend()`](../src/julia_bridge.jl)**: Handles transport selection based on payload size
-- **[`SmartReceive()`](../src/julia_bridge.jl)**: Handles both direct and link transport
-
-### JavaScript Module: [`src/NATSBridge.js`](../src/NATSBridge.js)
-
-The JavaScript implementation provides:
-
-- **`MessageEnvelope` class**: For the unified JSON envelope
-- **`MessagePayload` class**: For individual payload representation
-- **[`smartsend()`](../src/NATSBridge.js)**: Handles transport selection based on payload size
-- **[`smartreceive()`](../src/NATSBridge.js)**: Handles both direct and link transport
-
-## Installation
-
-### Julia Dependencies
-
-```julia
-using Pkg
-Pkg.add("NATS")
-Pkg.add("Arrow")
-Pkg.add("JSON3")
-Pkg.add("HTTP")
-Pkg.add("UUIDs")
-Pkg.add("Dates")
-```
-
-### JavaScript Dependencies
-
-```bash
-npm install nats.js apache-arrow uuid base64-url
-```
-
-## Usage Tutorial
-
-### Step 1: Start NATS Server
-
-```bash
-docker run -p 4222:4222 nats:latest
-```
-
-### Step 2: Start HTTP File Server (optional)
-
-```bash
-# Create a directory for file uploads
-mkdir -p /tmp/fileserver
-
-# Use any HTTP server that supports POST for file uploads
-# Example: Python's built-in server
-python3 -m http.server 8080 --directory /tmp/fileserver
-```
-
-### Step 3: Run Test Scenarios
-
-```bash
-# Scenario 1: Command & Control (JavaScript sender)
-node test/scenario1_command_control.js
-
-# Scenario 2: Large Arrow Table (JavaScript sender)
-node test/scenario2_large_table.js
-
-# Scenario 3: Julia-to-Julia communication
-# Run both Julia and JavaScript versions
-julia test/scenario3_julia_to_julia.jl
-node test/scenario3_julia_to_julia.js
-```
-
-## Usage
-
-### Scenario 0: Basic Multi-Payload Example
-
-#### Julia (Sender)
-```julia
-using NATSBridge
-
-# Send multiple payloads in one message (type is required per payload)
-smartsend(
-    "/test",
-    [("dataname1", data1, "dictionary"), ("dataname2", data2, "table")],
-    nats_url="nats://localhost:4222",
-    fileserver_url="http://localhost:8080",
-    metadata=Dict("custom_key" => "custom_value")
-)
-
-# Even single payload must be wrapped in a list with type
-smartsend("/test", [("single_data", mydata, "dictionary")])
-```
-
-#### Julia (Receiver)
-```julia
-using NATSBridge
-
-# Receive returns a list of payloads with type info
-payloads = smartreceive(msg, "http://localhost:8080")
-# payloads = [(dataname1, data1, "dictionary"), (dataname2, data2, "table"), ...]
-```
-
-### Scenario 1: Command & Control (Small JSON)
-
-#### JavaScript (Sender)
-```javascript
-const { smartsend } = require('./src/NATSBridge');
-
-// Single payload wrapped in a list
-const config = [{
-    dataname: "config",
-    data: { step_size: 0.01, iterations: 1000 },
-    type: "dictionary"
-}];
-
-await smartsend("control", config, {
-    correlationId: "unique-id"
-});
-
-// Multiple payloads
-const configs = [
-    {
-        dataname: "config1",
-        data: { step_size: 0.01 },
-        type: "dictionary"
-    },
-    {
-        dataname: "config2", 
-        data: { iterations: 1000 },
-        type: "dictionary"
-    }
-];
-
-await smartsend("control", configs);
-```
-
-#### Julia (Receiver)
-```julia
-using NATS
-using JSON3
-
-# Subscribe to control subject
-subscribe(nats, "control") do msg
-    env = MessageEnvelope(String(msg.data))
-    config = JSON3.read(env.payload)
-    
-    # Execute simulation with parameters
-    step_size = config.step_size
-    iterations = config.iterations
-    
-    # Send acknowledgment
-    response = Dict("status" => "Running", "correlation_id" => env.correlation_id)
-    publish(nats, "control_response", JSON3.stringify(response))
-end
-```
-
-### JavaScript (Receiver)
-```javascript
-const { smartreceive } = require('./src/NATSBridge');
-
-// Subscribe to messages
-const nc = await connect({ servers: ['nats://localhost:4222'] });
-const sub = nc.subscribe("control");
-
-for await (const msg of sub) {
-    const result = await smartreceive(msg);
-    
-    // Process the result
-    for (const { dataname, data, type } of result) {
-        console.log(`Received ${dataname} of type ${type}`);
-        console.log(`Data: ${JSON.stringify(data)}`);
-    }
-}
-```
-
-### Scenario 2: Deep Dive Analysis (Large Arrow Table)
-
-#### Julia (Sender)
-```julia
-using Arrow
-using DataFrames
-
-# Create large DataFrame
-df = DataFrame(
-    id = 1:10_000_000,
-    value = rand(10_000_000),
-    category = rand(["A", "B", "C"], 10_000_000)
-)
-
-# Send via SmartSend - wrapped in a list (type is part of each tuple)
-await SmartSend("analysis_results", [("table_data", df, "table")]);
-```
-
-#### JavaScript (Receiver)
-```javascript
-const { smartreceive } = require('./src/NATSBridge');
-
-const result = await smartreceive(msg);
-
-// Use table data for visualization with Perspective.js or D3
-// Note: Tables are sent as arrays of objects in JavaScript
-const table = result;
-```
-
-### Scenario 3: Live Binary Processing
-
-#### JavaScript (Sender)
-```javascript
-const { smartsend } = require('./src/NATSBridge');
-
-// Binary data wrapped in a list
-const binaryData = [{
-    dataname: "audio_chunk",
-    data: binaryBuffer,  // ArrayBuffer or Uint8Array
-    type: "binary"
-}];
-
-await smartsend("binary_input", binaryData, {
-    metadata: {
-        sample_rate: 44100,
-        channels: 1
-    }
-});
-```
-
-#### Julia (Receiver)
-```julia
-using WAV
-using DSP
-
-# Receive binary data
-function process_binary(data)
-    # Perform FFT or AI transcription
-    spectrum = fft(data)
-    
-    # Send results back (JSON + Arrow table)
-    results = Dict("transcription" => "sample text", "spectrum" => spectrum)
-    await SmartSend("binary_output", results, "json")
-end
-```
-
-### JavaScript (Receiver)
-```javascript
-const { smartreceive } = require('./src/NATSBridge');
-
-// Receive binary data
-function process_binary(msg) {
-    const result = await smartreceive(msg);
-    
-    // Process the binary data
-    for (const { dataname, data, type } of result) {
-        if (type === "binary") {
-            // data is an ArrayBuffer or Uint8Array
-            console.log(`Received binary data: ${dataname}, size: ${data.length}`);
-            // Perform FFT or AI transcription here
-        }
-    }
-}
-```
-
-### Scenario 4: Catch-Up (JetStream)
-
-#### Julia (Producer)
-```julia
-using NATSBridge
-
-function publish_health_status(nats_url)
-    # Send status wrapped in a list (type is part of each tuple)
-    status = Dict("cpu" => rand(), "memory" => rand())
-    smartsend("health", [("status", status, "dictionary")], nats_url=nats_url)
-    sleep(5)  # Every 5 seconds
-end
-```
-
-#### JavaScript (Consumer)
-```javascript
-const { connect } = require('nats');
-const { smartreceive } = require('./src/NATSBridge');
-
-const nc = await connect({ servers: ['nats://localhost:4222'] });
-const js = nc.jetstream();
-
-// Request replay from last 10 minutes
-const consumer = await js.pullSubscribe("health", { 
-    durable_name: "catchup",
-    max_batch: 100,
-    max_ack_wait: 30000
-});
-
-// Process historical and real-time messages
-for await (const msg of consumer) {
-    const result = await smartreceive(msg);
-    // result contains the list of payloads
-    // Each payload has: dataname, data, type
-    msg.ack();
-}
-```
-
-### Scenario 5: Selection (Low Bandwidth)
-
-**Focus:** Small Arrow tables, Julia to JavaScript. The Action: Julia wants to send a small DataFrame to show on a JavaScript dashboard for the user to choose.
-
-**Julia (Sender):**
-```julia
-using NATSBridge
-using DataFrames
-
-# Create small DataFrame (e.g., 50KB - 500KB)
-options_df = DataFrame(
-    id = 1:10,
-    name = ["Option A", "Option B", "Option C", "Option D", "Option E",
-            "Option F", "Option G", "Option H", "Option I", "Option J"],
-    description = ["Description A", "Description B", "Description C", "Description D", "Description E",
-                   "Description F", "Description G", "Description H", "Description I", "Description J"]
-)
-
-# Convert to Arrow IPC stream
-# Check payload size (< 1MB threshold)
-# Publish directly to NATS with Base64-encoded payload
-# Include metadata for dashboard selection context
-smartsend(
-    "dashboard.selection",
-    [("options_table", options_df, "table")],
-    nats_url="nats://localhost:4222",
-    metadata=Dict("context" => "user_selection")
-)
-```
-
-**JavaScript (Receiver):**
-```javascript
-const { smartreceive, smartsend } = require('./src/NATSBridge');
-
-// Receive NATS message with direct transport
-const result = await smartreceive(msg);
-
-// Decode Base64 payload (for direct transport)
-// For tables, data is an array of objects
-const table = result;  // Array of objects
-
-// User makes selection
-const selection = uiComponent.getSelectedOption();
-
-// Send selection back to Julia
-await smartsend("dashboard.response", [
-    { dataname: "selected_option", data: selection, type: "dictionary" }
-]);
-```
-
-**Use Case:** Julia server generates a list of available options (e.g., file selections, configuration presets) as a small DataFrame and sends to JavaScript dashboard for user selection. The selection is then sent back to Julia for processing.
-
-### Scenario 6: Chat System
-
-**Focus:** Every conversational message is composed of any number and any combination of components, spanning the full spectrum from small to large. This includes text, images, audio, video, tables, and files—specifically accommodating everything from brief snippets to high-resolution images, large audio files, extensive tables, and massive documents. Support for claim-check delivery and full bi-directional messaging.
-
-**Multi-Payload Support:** The system supports mixed-payload messages where a single message can contain multiple payloads with different transport strategies. The `smartreceive` function iterates through all payloads in the envelope and processes each according to its transport type.
-
-**Julia (Sender/Receiver):**
-```julia
-using NATSBridge
-using DataFrames
-
-# Build chat message with mixed payloads:
-# - Text: direct transport (Base64)
-# - Small images: direct transport (Base64)
-# - Large images: link transport (HTTP URL)
-# - Audio/video: link transport (HTTP URL)
-# - Tables: direct or link depending on size
-# - Files: link transport (HTTP URL)
-# 
-# Each payload uses appropriate transport strategy:
-# - Size < 1MB → direct (NATS + Base64)
-# - Size >= 1MB → link (HTTP upload + NATS URL)
-# 
-# Include claim-check metadata for delivery tracking
-# Support bidirectional messaging with replyTo fields
-
-# Example: Chat with text, small image, and large file
-chat_message = [
-    ("message_text", "Hello, this is a test message!", "text"),
-    ("user_avatar", image_bytes, "image"),  # Small image, direct transport
-    ("large_document", large_file_bytes, "binary")  # Large file, link transport
-]
-
-smartsend(
-    "chat.room123",
-    chat_message,
-    nats_url="nats://localhost:4222",
-    msg_purpose="chat",
-    reply_to="chat.room123.responses"
-)
-```
-
-**JavaScript (Sender/Receiver):**
-```javascript
-const { smartsend, smartreceive } = require('./src/NATSBridge');
-
-// Build chat message with mixed content:
-// - User input text: direct transport
-// - Selected image: check size, use appropriate transport
-// - Audio recording: link transport for large files
-// - File attachment: link transport
-// 
-// Parse received message:
-// - Direct payloads: decode Base64
-// - Link payloads: fetch from HTTP with exponential backoff
-// - Deserialize all payloads appropriately
-// 
-// Render mixed content in chat interface
-// Support bidirectional reply with claim-check delivery confirmation
-
-// Example: Send chat with mixed content
-const message = [
-    {
-        dataname: "text",
-        data: "Hello from JavaScript!",
-        type: "text"
-    },
-    {
-        dataname: "image",
-        data: selectedImageBuffer,  // Small image (ArrayBuffer or Uint8Array)
-        type: "image"
-    },
-    {
-        dataname: "audio",
-        data: audioUrl,  // Large audio, link transport
-        type: "audio"
-    }
-];
-
-await smartsend("chat.room123", message);
-```
-
-**Use Case:** Full-featured chat system supporting rich media. User can send text, small images directly, or upload large files that get uploaded to HTTP server and referenced via URLs. Claim-check pattern ensures reliable delivery tracking for all message components.
-
-**Implementation Note:** The `smartreceive` function iterates through all payloads in the envelope and processes each according to its transport type. See the standard API format in Section 1: `msgEnvelope_v1` supports `AbstractArray{msgPayload_v1}` for multiple payloads.
-
-## Configuration
-
-### Environment Variables
-
-| Variable | Default | Description |
-|----------|---------|-------------|
-| `NATS_URL` | `nats://localhost:4222` | NATS server URL |
-| `FILESERVER_URL` | `http://localhost:8080` | HTTP file server URL (base URL without `/upload` suffix) |
-| `SIZE_THRESHOLD` | `1_000_000` | Size threshold in bytes (1MB) |
-
-### Message Envelope Schema
-
-```json
-{
-  "correlationId": "uuid-v4-string",
-  "msgId": "uuid-v4-string",
-  "timestamp": "2024-01-15T10:30:00Z",
-  
-  "sendTo": "topic/subject",
-  "msgPurpose": "ACK | NACK | updateStatus | shutdown | chat",
-  "senderName": "agent-wine-web-frontend",
-  "senderId": "uuid4",
-  "receiverName": "agent-backend",
-  "receiverId": "uuid4",
-  "replyTo": "topic",
-  "replyToMsgId": "uuid4",
-  "BrokerURL": "nats://localhost:4222",
-  
-  "metadata": {
-    "content_type": "application/octet-stream",
-    "content_length": 123456
-  },
-  
-  "payloads": [
-    {
-      "id": "uuid4",
-      "dataname": "login_image",
-      "type": "image",
-      "transport": "direct",
-      "encoding": "base64",
-      "size": 15433,
-      "data": "base64-encoded-string",
-      "metadata": {
-        "checksum": "sha256_hash"
-      }
-    }
-  ]
-}
-```
-
-## Performance Considerations
-
-### Zero-Copy Reading
-- Use Arrow's memory-mapped file reading
-- Avoid unnecessary data copying during deserialization
-- Use Apache Arrow's native IPC reader
-
-### Exponential Backoff
-- Maximum retry count: 5
-- Base delay: 100ms, max delay: 5000ms
-- Implemented in both Julia and JavaScript implementations
-
-### Correlation ID Logging
-- Log correlation_id at every stage
-- Include: send, receive, serialize, deserialize
-- Use structured logging format
-
-## Testing
-
-Run the test scripts:
-
-```bash
-# Scenario 1: Command & Control (JavaScript sender)
-node test/scenario1_command_control.js
-
-# Scenario 2: Large Arrow Table (JavaScript sender)
-node test/scenario2_large_table.js
-```
-
-## Troubleshooting
-
-### Common Issues
-
-1. **NATS Connection Failed**
-   - Ensure NATS server is running
-   - Check NATS_URL configuration
-
-2. **HTTP Upload Failed**
-   - Ensure file server is running
-   - Check FILESERVER_URL configuration
-   - Verify upload permissions
-
-3. **Arrow IPC Deserialization Error**
-   - Ensure data is properly serialized to Arrow format
-   - Check Arrow version compatibility
-
-## License
-
-MIT

docs/requirements.md

@@ -0,0 +1,420 @@
+# Requirements Document: NATSBridge
+
+**Version**: 1.0.0  
+**Date**: 2026-03-13  
+**Status**: Active  
+**Ground Truth**: [`src/NATSBridge.jl`](../src/NATSBridge.jl)
+
+---
+
+## Executive Summary
+
+NATSBridge is a cross-platform, bi-directional data bridge that enables seamless communication between **Julia**, **JavaScript**, **Python**, and **MicroPython** applications using NATS as the message bus. The system implements the **Claim-Check pattern** for efficient handling of large payloads (>0.5MB) by uploading them to an HTTP file server instead of sending raw binary data over NATS.
+
+---
+
+## Business Goals
+
+### Primary Objectives
+
+1. **Cross-Platform Interoperability**: Enable seamless data exchange between Julia, JavaScript (for both Server-Side rendering and Client-Side rendering webapp), Python, and MicroPython applications without platform-specific barriers.
+
+2. **Efficient Large Payload Handling**: Implement intelligent transport selection based on payload size:
+   - **Direct Transport**: Small payloads (<0.5MB) sent directly via NATS
+   - **Link Transport**: Large payloads (≥0.5MB) uploaded to HTTP file server, URL sent via NATS
+
+3. **Unified API Across Platforms**: Provide consistent `smartsend()` and `smartreceive()` functions across all supported platforms while maintaining idiomatic implementations.
+
+4. **Developer Productivity**: Reduce onboarding time and simplify integration through comprehensive documentation and test examples.
+
+### Success Metrics
+
+| Metric | Target | Measurement Method |
+|--------|--------|-------------------|
+| 95% of messages complete within 200ms | 95% | Synthetic monitoring |
+| <2 days from onboarding to first PR | 2 days | PR timeline tracking |
+| 100% of messages validate against spec | 100% | CI block rate |
+| >80% unit test coverage | 80% | Test coverage tools |
+| <1% of PRs bypass validation gates | 1% | CI gate analysis |
+| MTTR <15 minutes for P1 incidents | 15 minutes | Incident tracking |
+
+---
+
+## User Stories
+
+### Core Functionality
+
+| Story | Priority | Acceptance Criteria |
+|-------|----------|---------------------|
+| **As a Julia developer**, I want to send text messages to JavaScript applications that lives on a server and also on a browser  | P1 | Text messages are serialized, encoded, and received correctly across platforms |
+| **As a Python developer**, I want to send tabular data to Julia applications | P1 | DataFrame exchange works with both Arrow IPC and JSON formats |
+| **As a JavaScript developer**, I want to send large files (>0.5MB) from JavaScript applications that lives on a server and also on a browser to other applications | P1 | Large files are automatically uploaded to file server and URLs are sent via NATS |
+| **As a MicroPython developer**, I want to send sensor data with minimal memory usage | P1 | Direct transport works for payloads <100KB on memory-constrained devices |
+
+### Multi-Payload Support
+
+| Story | Priority | Acceptance Criteria |
+|-------|----------|---------------------|
+| **As a developer**, I want to send mixed-content messages (text + image + file) | P1 | NATSBridge accepts list of (dataname, data, type) tuples and handles each payload appropriately |
+| **As a developer**, I want to receive multi-payload messages | P1 | NATSBridge returns payloads as list of tuples with correct types preserved |
+
+### File Server Integration
+
+| Story | Priority | Acceptance Criteria |
+|-------|----------|---------------------|
+| **As a developer**, I want to use Plik as the file server | P2 | Plik one-shot upload mode is supported with upload ID and token handling |
+| **As a developer**, I want to use custom HTTP file servers | P2 | Handler function abstraction allows plugging in AWS S3 or custom implementations |
+
+### Reliability Features
+
+| Story | Priority | Acceptance Criteria |
+|-------|----------|---------------------|
+| **As a developer**, I want automatic retry on file server download failures | P1 | Exponential backoff with configurable retries (default: 5, base_delay: 100ms, max_delay: 5000ms) |
+| **As a developer**, I want message tracing across distributed systems | P1 | Correlation ID is propagated through all message processing steps |
+
+---
+
+## Non-Functional Requirements
+
+### Performance Requirements
+
+| Requirement | Specification | Test Method |
+|-------------|---------------|-------------|
+| Message serialization overhead | <50ms for 10KB payload | Benchmark tests |
+| Message deserialization overhead | <50ms for 10KB payload | Benchmark tests |
+| NATS connection establishment | <100ms | Connection pool benchmarks |
+| File upload latency | <1s for 0.5MB file | Integration tests |
+| File download latency | <1s for 0.5MB file | Integration tests |
+
+### Scalability Requirements
+
+| Requirement | Specification |
+|-------------|---------------|
+| Concurrent connections | Support 100+ simultaneous NATS connections |
+| Message throughput | Handle 1000+ messages/second per instance |
+| File server scalability | Support horizontal scaling of file server backend |
+
+### Reliability Requirements
+
+| Requirement | Specification |
+|-------------|---------------|
+| Message delivery | At-least-once delivery semantics via NATS |
+| File server availability | Graceful degradation when file server is unavailable |
+| Connection recovery | Auto-reconnect on NATS connection failure |
+
+### Security Requirements
+
+| Requirement | Specification |
+|-------------|---------------|
+| Payload integrity | SHA-256 checksum support via metadata |
+| Transport security | TLS support for NATS connections |
+| File server security | Authentication token for file uploads |
+
+### Compatibility Requirements
+
+| Platform | Minimum Version | Notes |
+|----------|-----------------|-------|
+| Julia | 1.7+ | Arrow.jl required for arrowtable support |
+| Node.js | 16+ | nats.js required |
+| Python | 3.8+ | pyarrow required for arrowtable support |
+| MicroPython | 1.19+ | Limited to direct transport |
+
+---
+
+## Out of Scope
+
+### Phase 1 (Current Implementation)
+
+| Feature | Reason |
+|---------|--------|
+| NATS JetStream support | Core NATS sufficient for current use cases |
+| Message compression | Compression adds complexity without clear benefit |
+| Message encryption | Payload encryption is application-layer concern |
+| Persistent message queues | NATS request-reply pattern sufficient |
+| Advanced routing rules | Simple NATS subject matching sufficient |
+
+### Future Considerations
+
+| Feature | Future Phase |
+|---------|--------------|
+| JetStream streams and consumers | Phase 2 |
+| Message TTL and dead-letter queues | Phase 3 |
+| Message tracing with OpenTelemetry | Phase 3 |
+| Rate limiting and quota management | Phase 4 |
+
+---
+
+## Boundary Definitions
+
+### What NATSBridge Handles
+
+| Function | Description |
+|----------|-------------|
+| Message serialization | Converts data types to binary format |
+| Message encoding | Base64, JSON, Arrow IPC encoding |
+| Transport selection | Direct vs link based on size threshold |
+| NATS publishing | Publishes messages to NATS subjects |
+| NATS subscription | Receives and processes NATS messages |
+| File server upload | Uploads large payloads to HTTP server |
+| File server download | Downloads payloads from HTTP server with retry |
+| Correlation ID generation | Creates and propagates UUIDs |
+| Data deserialization | Converts binary format back to native types |
+
+### What NATSBridge Does NOT Handle
+
+| Function | Handled By |
+|----------|------------|
+| NATS server management | External NATS deployment |
+| File server management | External HTTP server deployment |
+| Application business logic | Application code using NATSBridge |
+| Message encryption | Application layer |
+| Message compression | Application layer |
+| Authentication/Authorization | NATS server configuration |
+
+---
+
+## Payload Type Requirements
+
+### Supported Payload Types
+
+| Type | Julia | JavaScript | Python | MicroPython | Description |
+|------|-------|------------|--------|-------------|-------------|
+| `text` | `String` | `string` | `str` | `str` | Plain text strings |
+| `dictionary` | `Dict`, `NamedTuple` | `Object`, `Array` | `dict`, `list` | `dict` | JSON-serializable data |
+| `arrowtable` | `DataFrame`, `Arrow.Table` | `Array<Object>` | `pandas.DataFrame` | ❌ | Tabular data (Arrow IPC) |
+| `jsontable` | `Vector{NamedTuple}` | `Array<Object>` | `list[dict]` | ⚠️ | Tabular data (JSON) |
+| `image` | `Vector{UInt8}` | `Uint8Array`, `Buffer` | `bytes` | `bytearray` | Image binary data |
+| `audio` | `Vector{UInt8}` | `Uint8Array`, `Buffer` | `bytes` | `bytearray` | Audio binary data |
+| `video` | `Vector{UInt8}` | `Uint8Array`, `Buffer` | `bytes` | `bytearray` | Video binary data |
+| `binary` | `Vector{UInt8}`, `IOBuffer` | `Uint8Array`, `Buffer` | `bytes`, `bytearray` | `bytearray` | Generic binary data |
+
+### Encoding Requirements
+
+| Payload Type | Encoding Method | Notes |
+|--------------|-----------------|-------|
+| `text` | UTF-8 → Base64 | Text must be String type |
+| `dictionary` | JSON → Base64 | JSON.jl for Julia |
+| `arrowtable` | Arrow IPC → Base64 | Requires Arrow.jl/pyarrow |
+| `jsontable` | JSON → Base64 | Human-readable format |
+| `image`/`audio`/`video`/`binary` | Direct → Base64 | Binary data preserved |
+
+---
+
+## Size Threshold Requirements
+
+### Direct Transport Threshold
+
+| Platform | Threshold | Notes |
+|----------|-----------|-------|
+| Desktop (Julia/JS/Python) | 0.5MB | Default size threshold |
+| MicroPython | 100KB | Lower threshold for memory constraints |
+
+### Maximum Payload Size
+
+| Platform | Maximum | Notes |
+|----------|---------|-------|
+| Desktop | Unlimited | Limited by NATS server configuration |
+| MicroPython | 50KB | Hard limit due to 256KB-1MB memory |
+
+---
+
+## Message Envelope Requirements
+
+### Required Fields
+
+| Field | Type | Purpose |
+|-------|------|---------|
+| `correlation_id` | String (UUID) | Track message flow across systems |
+| `msg_id` | String (UUID) | Unique message identifier |
+| `timestamp` | String (ISO 8601) | Message publication timestamp |
+| `send_to` | String | NATS subject to publish to |
+| `msg_purpose` | String | ACK, NACK, updateStatus, shutdown, chat |
+| `sender_name` | String | Sender application name |
+| `sender_id` | String (UUID) | Sender unique identifier |
+| `receiver_name` | String | Receiver application name (empty = broadcast) |
+| `receiver_id` | String (UUID) | Receiver unique identifier (empty = broadcast) |
+| `reply_to` | String | Topic for reply messages |
+| `reply_to_msg_id` | String | Message ID being replied to |
+| `broker_url` | String | NATS server URL |
+| `metadata` | Dict | Message-level metadata |
+| `payloads` | Array | List of payload objects |
+
+### Payload Fields
+
+| Field | Type | Purpose |
+|-------|------|---------|
+| `id` | String (UUID) | Unique payload identifier |
+| `dataname` | String | Name of the payload |
+| `payload_type` | String | Type: text, dictionary, arrowtable, etc. |
+| `transport` | String | direct or link |
+| `encoding` | String | none, json, base64, arrow-ipc |
+| `size` | Integer | Payload size in bytes |
+| `data` | Any | Base64 string or URL |
+| `metadata` | Dict | Payload-level metadata |
+
+---
+
+## Error Handling Requirements
+
+### Error Codes
+
+| Error | Condition | Response |
+|-------|-----------|----------|
+| `Unknown payload_type` | Unsupported type | Throw error |
+| `Failed to upload` | File server error | Throw error |
+| `Failed to fetch` | File server unavailable | Retry with exponential backoff |
+| `Unknown transport` | Invalid transport type | Throw error |
+| `NATS connection failed` | NATS unavailable | Throw error |
+
+### Exception Handling
+
+| Scenario | Handler |
+|----------|---------|
+| File server unavailable | Retry up to 5 times with exponential backoff |
+| NATS publish failure | Connection auto-reconnect |
+| Deserialization error | Log correlation ID and throw error |
+| Memory overflow (MicroPython) | Reject payloads >50KB |
+
+---
+
+## Testing Requirements
+
+### Unit Tests
+
+| Test Category | Coverage | Files |
+|---------------|----------|-------|
+| Serialization | All payload types | `test/test_*_sender.*` |
+| Deserialization | All payload types | `test/test_*_receiver.*` |
+| Transport selection | Direct vs link | `test/test_*_mix_payloads.*` |
+| File server upload | Plik integration | Platform-specific |
+| File server download | Exponential backoff | Platform-specific |
+
+### Integration Tests
+
+| Test Scenario | Success Criteria |
+|-------------|-----------------|
+| Cross-platform text message | Julia ↔ JavaScript ↔ Python |
+| Cross-platform tabular data | Arrow IPC round-trip |
+| Large file transfer | File server upload/download |
+| Multi-payload mixed content | All payload types in one message |
+
+---
+
+## API Contract
+
+### smartsend Signature
+
+```julia
+function smartsend(
+    subject::String,
+    data::AbstractArray{Tuple{String, Any, String}};
+    broker_url::String = "nats://localhost:4222",
+    fileserver_url::String = "http://localhost:8080",
+    fileserver_upload_handler::Function = plik_oneshot_upload,
+    size_threshold::Int = 1_000_000,
+    correlation_id::String = string(uuid4()),
+    msg_purpose::String = "chat",
+    sender_name::String = "NATSBridge",
+    receiver_name::String = "",
+    receiver_id::String = "",
+    reply_to::String = "",
+    reply_to_msg_id::String = "",
+    is_publish::Bool = true,
+    NATS_connection::Union{NATS.Connection, Nothing} = nothing,
+    msg_id::String = string(uuid4()),
+    sender_id::String = string(uuid4())
+)::Tuple{msg_envelope_v1, String}
+```
+
+### smartreceive Signature
+
+```julia
+function smartreceive(
+    msg::NATS.Msg;
+    fileserver_download_handler::Function = _fetch_with_backoff,
+    max_retries::Int = 5,
+    base_delay::Int = 100,
+    max_delay::Int = 5000
+)::JSON.Object{String, Any}
+```
+
+---
+
+## Dependencies
+
+### Required Dependencies
+
+| Platform | Package | Version |
+|----------|---------|---------|
+| Julia | NATS.jl | Latest stable |
+| Julia | JSON.jl | Latest stable |
+| Julia | Arrow.jl | Latest stable |
+| Julia | HTTP.jl | Latest stable |
+| Julia | UUIDs.jl | Latest stable |
+| Node.js | nats | Latest stable |
+| Node.js | node-fetch | Latest stable |
+| Python | nats-py | Latest stable |
+| Python | aiohttp | Latest stable |
+| Python | pyarrow | Latest stable |
+
+### Optional Dependencies
+
+| Platform | Package | Use Case |
+|----------|---------|----------|
+| Julia | DataFrames.jl | DataFrame support for arrowtable |
+| Python | pandas | DataFrame support for arrowtable |
+
+---
+
+## Deployment Requirements
+
+### Minimum Infrastructure
+
+| Component | Minimum | Notes |
+|-----------|---------|-------|
+| NATS Server | 1 instance | Single node for development |
+| File Server | 1 instance | HTTP server for large payloads |
+| Client Memory | 50MB | Desktop platforms |
+| Client Memory | 256KB | MicroPython devices |
+
+### Environment Variables
+
+| Variable | Default | Description |
+|----------|---------|-------------|
+| `NATS_URL` | `nats://localhost:4222` | NATS server URL |
+| `FILESERVER_URL` | `http://localhost:8080` | HTTP file server URL |
+| `SIZE_THRESHOLD` | `1000000` | Size threshold in bytes |
+
+---
+
+## Versioning
+
+### Current Version
+
+- **Major**: 1 (Breaking changes require major version bump)
+- **Minor**: 0 (Feature additions)
+- **Patch**: 0 (Bug fixes)
+
+### Version Compatibility
+
+| Version | Supported Platforms |
+|---------|---------------------|
+| v1.0.x | Julia 1.7+, Node.js 16+, Python 3.8+, MicroPython 1.19+ |
+
+---
+
+## Change Log
+
+| Date | Version | Changes |
+|------|---------|---------|
+| 2026-03-13 | 1.0.0 | Initial requirements document |
+
+---
+
+## References
+
+- [`src/NATSBridge.jl`](../src/NATSBridge.jl) - Ground truth implementation
+- [`README.md`](../README.md) - Project overview
+- [`docs/architecture.md`](./architecture.md) - Architecture documentation
+- [`docs/implementation.md`](./implementation.md) - Implementation details
+- [`docs/walkthrough.md`](./walkthrough.md) - Usage examples

docs/tutorial.md

@@ -0,0 +1,741 @@
+# Cross-Platform NATSBridge Tutorial
+
+A step-by-step guide to get started with NATSBridge across **Julia**, **JavaScript**, and **Python/MicroPython**.
+
+## Table of Contents
+
+1. [Overview](#overview)
+2. [Prerequisites](#prerequisites)
+3. [Installation](#installation)
+4. [Quick Start](#quick-start)
+5. [Basic Examples](#basic-examples)
+6. [Advanced Usage](#advanced-usage)
+
+---
+
+## Overview
+
+NATSBridge enables seamless communication across platforms through NATS, with automatic transport selection based on payload size:
+
+- **Direct Transport**: Payloads < 1MB are sent directly via NATS (Base64 encoded)
+- **Link Transport**: Payloads >= 1MB are uploaded to an HTTP file server and referenced via URL
+
+### Cross-Platform API Parity
+
+All three platforms use the same high-level API:
+
+```
+# Input format
+smartsend(subject, [(dataname, data, type), ...], options)
+
+# Output format
+(env, env_json_str) = smartsend(...)
+env = smartreceive(msg, options)
+```
+
+**Important Platform Differences:**
+
+1. **Encoding field:** Julia and JavaScript preserve the original serialization format in the encoding field (`"base64"`, `"json"`, or `"arrow-ipc"`), while Python and MicroPython always use `"base64"` for all direct transport payloads.
+
+2. **Async vs Sync:** JavaScript and Python desktop use async/await, while MicroPython uses synchronous API.
+
+### Supported Payload Types
+
+| Type | Julia | JavaScript | Python | MicroPython |
+|------|-------|------------|--------|-------------|
+| `text` | `String` | `string` | `str` | `str` |
+| `dictionary` | `Dict` | `Object` | `dict` | `dict` |
+| `arrowtable` | `DataFrame` | `Array<Object>` | `pandas.DataFrame` | ❌ |
+| `jsontable` | `Vector{NamedTuple}` | `Array<Object>` | `list[dict]` | ❌ |
+| `table` | ❌ | ❌ | `pandas.DataFrame` | ❌ |
+| `image` | `Vector{UInt8}` | `Uint8Array` | `bytes` | `bytearray` |
+| `audio` | `Vector{UInt8}` | `Uint8Array` | `bytes` | `bytearray` |
+| `video` | `Vector{UInt8}` | `Uint8Array` | `bytes` | `bytearray` |
+| `binary` | `Vector{UInt8}` | `Uint8Array` | `bytes` | `bytearray` |
+
+**Note on MicroPython:** MicroPython does not support table types (`arrowtable`, `jsontable`, or `table`) due to memory constraints. Use `dictionary` or `binary` instead.
+
+---
+
+## Prerequisites
+
+Before you begin, ensure you have:
+
+1. **NATS Server** running (or accessible)
+2. **HTTP File Server** (optional, for large payloads > 1MB)
+3. **Platform-specific packages** installed
+
+---
+
+## Installation
+
+### Julia
+
+```julia
+using Pkg
+Pkg.add("NATS")
+Pkg.add("Arrow")
+Pkg.add("JSON3")
+Pkg.add("HTTP")
+Pkg.add("UUIDs")
+Pkg.add("Dates")
+```
+
+### JavaScript (Node.js)
+
+```bash
+npm install nats uuid apache-arrow node-fetch
+```
+
+### JavaScript (Browser)
+
+```html
+<script src="https://unpkg.com/nats-js/dist/bundle/nats.min.js"></script>
+<script src="https://unpkg.com/apache-arrow/arrow.min.js"></script>
+```
+
+### Python (Desktop)
+
+```bash
+pip install nats-py aiohttp pyarrow pandas
+```
+
+### MicroPython
+
+Uses built-in modules: `network`, `socket`, `time`, `json`, `base64`
+
+---
+
+## Quick Start
+
+### Step 1: Start NATS Server
+
+```bash
+docker run -p 4222:4222 nats:latest
+```
+
+### Step 2: Start HTTP File Server (Optional)
+
+```bash
+mkdir -p /tmp/fileserver
+python3 -m http.server 8080 --directory /tmp/fileserver
+```
+
+### Step 3: Send Your First Message
+
+#### Julia
+
+```julia
+using NATSBridge
+
+# Send a text message
+data = [("message", "Hello World", "text")]
+env, env_json_str = smartsend("/chat/room1", data, broker_url="nats://localhost:4222")
+# env: msg_envelope_v1 struct with all metadata and payloads
+# env_json_str: JSON string representation of the envelope for publishing
+println("Message sent!")
+
+# Or use is_publish=false to get envelope and JSON without publishing
+env, env_json_str = smartsend("/chat/room1", data, broker_url="nats://localhost:4222", is_publish=false)
+# env: msg_envelope_v1 struct
+# env_json_str: JSON string for publishing to NATS
+```
+
+#### JavaScript
+
+```javascript
+const NATSBridge = require('./src/natsbridge.js');
+
+// Send a text message
+const data = [["message", "Hello World", "text"]];
+const [env, env_json_str] = await NATSBridge.smartsend(
+    "/chat/room1",
+    data,
+    { broker_url: "nats://localhost:4222" }
+);
+// env: Object with all metadata and payloads
+// env_json_str: JSON string for publishing
+console.log("Message sent!");
+
+// Or use is_publish=false
+const [env, env_json_str] = await NATSBridge.smartsend(
+    "/chat/room1",
+    data,
+    { broker_url: "nats://localhost:4222", is_publish: false }
+);
+```
+
+#### Python
+
+```python
+from natsbridge import smartsend
+
+# Send a text message
+data = [("message", "Hello World", "text")]
+env, env_json_str = await smartsend(
+    "/chat/room1",
+    data,
+    broker_url="nats://localhost:4222"
+)
+# env: Dict with all metadata and payloads
+# env_json_str: JSON string for publishing
+print("Message sent!")
+
+# Or use is_publish=False
+env, env_json_str = await smartsend(
+    "/chat/room1",
+    data,
+    broker_url="nats://localhost:4222",
+    is_publish=False
+)
+# env: Dict with all metadata and payloads
+# env_json_str: JSON string for publishing to NATS
+```
+
+#### MicroPython
+
+```python
+from natsbridge_mpy import NATSBridge
+
+bridge = NATSBridge()
+
+# Send a text message (limited to small payloads)
+data = [("message", "Hello World", "text")]
+env, env_json_str = bridge.smartsend(
+    "/chat/room1",
+    data,
+    size_threshold=100000  # Lower threshold for MicroPython
+)
+print("Message sent!")
+```
+
+### Step 4: Receive Messages
+
+#### Julia
+
+```julia
+using NATSBridge
+
+# Receive and process message
+env = smartreceive(msg; fileserver_download_handler=_fetch_with_backoff)
+# Returns: ::JSON.Object{String, Any} with "payloads" field containing Vector{Tuple{String, Any, String}}
+# Access payloads: for (dataname, data, type) in env["payloads"]
+for (dataname, data, type) in env["payloads"]
+    println("Received $dataname: $data")
+end
+```
+
+#### JavaScript
+
+```javascript
+const NATSBridge = require('./src/natsbridge.js');
+
+// Receive and process message
+const env = await NATSBridge.smartreceive(msg, {
+    fileserver_download_handler: NATSBridge.fetchWithBackoff
+});
+// env.payloads = [[dataname, data, type], ...]
+for (const [dataname, data, type] of env.payloads) {
+    console.log(`Received ${dataname}:`, data);
+}
+```
+
+#### Python
+
+```python
+from natsbridge import smartreceive, fetch_with_backoff
+
+# Receive and process message
+env = await smartreceive(
+    msg,
+    fileserver_download_handler=fetch_with_backoff
+)
+# env["payloads"] = [(dataname, data, type), ...]
+for dataname, data, type_ in env["payloads"]:
+    print(f"Received {dataname}: {data}")
+```
+
+---
+
+## Basic Examples
+
+### Example 1: Sending a Dictionary
+
+#### Julia
+
+```julia
+using NATSBridge
+
+config = Dict(
+    "wifi_ssid" => "MyNetwork",
+    "wifi_password" => "password123",
+    "update_interval" => 60
+)
+
+data = [("config", config, "dictionary")]
+env, env_json_str = smartsend("/device/config", data, broker_url="nats://localhost:4222")
+```
+
+#### JavaScript
+
+```javascript
+const NATSBridge = require('./src/natsbridge.js');
+
+const config = {
+    wifi_ssid: "MyNetwork",
+    wifi_password: "password123",
+    update_interval: 60
+};
+
+const data = [["config", config, "dictionary"]];
+const [env, env_json_str] = await NATSBridge.smartsend(
+    "/device/config",
+    data,
+    { broker_url: "nats://localhost:4222" }
+);
+```
+
+#### Python
+
+```python
+from natsbridge import smartsend
+
+config = {
+    "wifi_ssid": "MyNetwork",
+    "wifi_password": "password123",
+    "update_interval": 60
+}
+
+data = [("config", config, "dictionary")]
+env, env_json_str = await smartsend(
+    "/device/config",
+    data,
+    broker_url="nats://localhost:4222"
+)
+```
+
+#### MicroPython
+
+```python
+from natsbridge_mpy import NATSBridge
+
+bridge = NATSBridge()
+
+config = {
+    "wifi_ssid": "MyNetwork",
+    "wifi_password": "password123",
+    "update_interval": 60
+}
+
+data = [("config", config, "dictionary")]
+env, env_json_str = bridge.smartsend(
+    "/device/config",
+    data,
+    size_threshold=100000
+)
+```
+
+### Example 2: Sending Binary Data (Image)
+
+#### Julia
+
+```julia
+using NATSBridge
+
+# Read image file
+image_data = read("image.png")
+
+data = [("user_image", image_data, "binary")]
+env, env_json_str = smartsend("/chat/image", data, broker_url="nats://localhost:4222")
+```
+
+#### JavaScript
+
+```javascript
+const NATSBridge = require('./src/natsbridge.js');
+const fs = require('fs');
+
+// Read image file
+const image_data = fs.readFileSync('image.png');
+
+const data = [["user_image", image_data, "binary"]];
+const [env, env_json_str] = await NATSBridge.smartsend(
+    "/chat/image",
+    data,
+    { broker_url: "nats://localhost:4222" }
+);
+```
+
+#### Python
+
+```python
+from natsbridge import smartsend
+
+# Read image file
+with open("image.png", "rb") as f:
+    image_data = f.read()
+
+data = [("user_image", image_data, "binary")]
+env, env_json_str = await smartsend(
+    "/chat/image",
+    data,
+    broker_url="nats://localhost:4222"
+)
+```
+
+#### MicroPython
+
+```python
+from natsbridge_mpy import NATSBridge
+
+bridge = NATSBridge()
+
+# Read image file
+with open("image.png", "rb") as f:
+    image_data = f.read()
+
+data = [("user_image", image_data, "binary")]
+env, env_json_str = bridge.smartsend(
+    "/chat/image",
+    data,
+    size_threshold=100000
+)
+```
+
+### Example 3: Request-Response Pattern
+
+#### Julia (Requester)
+
+```julia
+using NATSBridge
+
+# Send command with reply-to
+data = [("command", Dict("action" => "read_sensor"), "dictionary")]
+env, env_json_str = smartsend(
+    "/device/command",
+    data,
+    broker_url="nats://localhost:4222",
+    reply_to="/device/response",
+    reply_to_msg_id="cmd-001"
+)
+```
+
+#### JavaScript (Requester)
+
+```javascript
+const NATSBridge = require('./src/natsbridge.js');
+
+// Send command with reply-to
+const data = [["command", { action: "read_sensor" }, "dictionary"]];
+const [env, env_json_str] = await NATSBridge.smartsend(
+    "/device/command",
+    data,
+    {
+        broker_url: "nats://localhost:4222",
+        reply_to: "/device/response",
+        reply_to_msg_id: "cmd-001"
+    }
+);
+```
+
+#### Python (Requester)
+
+```python
+from natsbridge import smartsend
+
+# Send command with reply-to
+data = [("command", {"action": "read_sensor"}, "dictionary")]
+env, env_json_str = await smartsend(
+    "/device/command",
+    data,
+    broker_url="nats://localhost:4222",
+    reply_to="/device/response",
+    reply_to_msg_id="cmd-001"
+)
+```
+
+#### Julia (Responder)
+
+```julia
+using NATSBridge, NATS
+
+const SUBJECT = "/device/command"
+const NATS_URL = "nats://localhost:4222"
+
+function test_responder()
+    conn = NATS.connect(NATS_URL)
+    NATS.subscribe(conn, SUBJECT) do msg
+        env = smartreceive(msg, fileserver_download_handler=_fetch_with_backoff)
+        
+        reply_to = env["reply_to"]
+        
+        for (dataname, data, type) in env["payloads"]
+            if dataname == "command" && data["action"] == "read_sensor"
+                response = Dict("sensor_id" => "sensor-001", "value" => 42.5)
+                if !isempty(reply_to)
+                    smartsend(reply_to, [("data", response, "dictionary")])
+                end
+            end
+        end
+    end
+    
+    sleep(120)
+    NATS.drain(conn)
+end
+
+test_responder()
+```
+
+---
+
+## Advanced Usage
+
+### Example 4: Large Payloads (File Server)
+
+For payloads larger than 1MB, NATSBridge automatically uses the file server:
+
+#### Julia
+
+```julia
+using NATSBridge
+
+# Create large data (> 1MB)
+large_data = rand(UInt8, 2_000_000)
+
+env, env_json_str = smartsend(
+    "/data/large",
+    [("large_file", large_data, "binary")],
+    broker_url="nats://localhost:4222",
+    fileserver_url="http://localhost:8080"
+)
+
+println("File uploaded to: $(env.payloads[1].data)")
+# Note: For link transport, data field contains the URL string
+```
+
+#### JavaScript
+
+```javascript
+const NATSBridge = require('./src/natsbridge.js');
+
+// Create large data (> 1MB)
+const large_data = Buffer.alloc(2_000_000);
+for (let i = 0; i < large_data.length; i++) {
+    large_data[i] = Math.floor(Math.random() * 256);
+}
+
+const [env, env_json_str] = await NATSBridge.smartsend(
+    "/data/large",
+    [["large_file", large_data, "binary"]],
+    {
+        broker_url: "nats://localhost:4222",
+        fileserver_url: "http://localhost:8080"
+    }
+);
+
+console.log("File uploaded to:", env.payloads[0].data);
+// Note: For link transport, data field contains the URL string
+```
+
+#### Python
+
+```python
+from natsbridge import smartsend
+
+# Create large data (> 1MB)
+import os
+large_data = os.urandom(2_000_000)
+
+env, env_json_str = await smartsend(
+    "/data/large",
+    [("large_file", large_data, "binary")],
+    broker_url="nats://localhost:4222",
+    fileserver_url="http://localhost:8080"
+)
+
+print(f"File uploaded to: {env['payloads'][0]['data']}")
+# Note: For link transport, data field contains the URL string
+```
+
+#### MicroPython
+
+MicroPython enforces a hard limit of 50KB per payload:
+
+```python
+from natsbridge_mpy import NATSBridge
+
+bridge = NATSBridge()
+
+# MicroPython has a hard limit of 50KB per payload
+# Use streaming or chunking for larger data
+small_data = bytes(1000)  # 1KB
+
+data = [("small_file", small_data, "binary")]
+env, env_json_str = bridge.smartsend(
+    "/data/small",
+    data,
+    size_threshold=100000  # Enforced max: 50000 bytes
+)
+```
+
+### Example 5: Mixed Content (Chat with Text + Image)
+
+NATSBridge supports sending multiple payloads with different types in a single message:
+
+#### Julia
+
+```julia
+using NATSBridge
+
+image_data = read("avatar.png")
+
+data = [
+    ("message_text", "Hello with image!", "text"),
+    ("user_avatar", image_data, "image")
+]
+
+env, env_json_str = smartsend("/chat/mixed", data, broker_url="nats://localhost:4222")
+```
+
+#### JavaScript
+
+```javascript
+const NATSBridge = require('./src/natsbridge.js');
+const fs = require('fs');
+
+const image_data = fs.readFileSync('avatar.png');
+
+const data = [
+    ["message_text", "Hello with image!", "text"],
+    ["user_avatar", image_data, "image"]
+];
+
+const [env, env_json_str] = await NATSBridge.smartsend(
+    "/chat/mixed",
+    data,
+    { broker_url: "nats://localhost:4222" }
+);
+```
+
+#### Python
+
+```python
+from natsbridge import smartsend
+
+with open("avatar.png", "rb") as f:
+    image_data = f.read()
+
+data = [
+    ("message_text", "Hello with image!", "text"),
+    ("user_avatar", image_data, "image")
+]
+
+env, env_json_str = await smartsend(
+    "/chat/mixed",
+    data,
+    broker_url="nats://localhost:4222"
+)
+# env: Dict with all metadata and payloads
+```
+
+### Example 6: Table Data (Arrow IPC)
+
+For tabular data, NATSBridge uses Apache Arrow IPC format:
+
+#### Julia
+
+```julia
+using NATSBridge
+using DataFrames
+
+# Create DataFrame
+df = DataFrame(
+    id = [1, 2, 3],
+    name = ["Alice", "Bob", "Charlie"],
+    score = [95, 88, 92]
+)
+
+data = [("students", df, "arrowtable")]
+env, env_json_str = smartsend("/data/students", data, broker_url="nats://localhost:4222")
+```
+
+#### JavaScript
+
+```javascript
+const NATSBridge = require('./src/natsbridge.js');
+
+// Create table data (array of objects)
+const table_data = [
+    { id: 1, name: "Alice", score: 95 },
+    { id: 2, name: "Bob", score: 88 },
+    { id: 3, name: "Charlie", score: 92 }
+];
+
+const data = [["students", table_data, "arrowtable"]];
+const [env, env_json_str] = await NATSBridge.smartsend(
+    "/data/students",
+    data,
+    { broker_url: "nats://localhost:4222" }
+);
+```
+
+#### Python
+
+```python
+from natsbridge import smartsend
+import pandas as pd
+
+# Create DataFrame
+df = pd.DataFrame({
+    'id': [1, 2, 3],
+    'name': ['Alice', 'Bob', 'Charlie'],
+    'score': [95, 88, 92]
+})
+
+data = [("students", df, "table")]
+env, env_json_str = await smartsend(
+    "/data/students",
+    data,
+    broker_url="nats://localhost:4222"
+)
+```
+
+#### MicroPython
+
+MicroPython does not support table type due to memory constraints. Use dictionary or binary instead.
+
+---
+
+## Next Steps
+
+1. **Explore the test directory** for more examples
+2. **Check the documentation** for advanced configuration options
+3. **Read the walkthrough** for building real-world applications
+
+---
+
+## Troubleshooting
+
+### Connection Issues
+
+- Ensure NATS server is running: `docker ps | grep nats`
+- Check firewall settings
+- Verify NATS URL configuration
+
+### File Server Issues
+
+- Ensure file server is running and accessible
+- Check upload permissions
+- Verify file server URL configuration
+
+### Serialization Errors
+
+- Verify data type matches the specified type
+- Check that binary data is in the correct format
+- MicroPython: Ensure payload size < 50KB
+
+---
+
+## License
+
+MIT

docs/walkthrough.md

@@ -0,0 +1,738 @@
+# Walkthrough: NATSBridge
+
+**Version**: 1.0.0  
+**Date**: 2026-03-13  
+**Status**: Active  
+**Ground Truth**: [`src/NATSBridge.jl`](../src/NATSBridge.jl)
+
+---
+
+## Executive Summary
+
+This document provides the **story of flow** for NATSBridge - the cross-platform bi-directional data bridge that enables seamless communication between **Julia**, **JavaScript**, **Python**, and **MicroPython** applications using NATS as the message bus.
+
+This walkthrough serves as the primary onboarding guide for new developers and explains:
+- **User scenarios** - Real-world use cases from developer perspective
+- **Why steps are sequenced** - The rationale behind architectural decisions
+- **What could go wrong** - Common failure scenarios and recovery strategies
+
+---
+
+## Overview: The Big Picture
+
+NATSBridge implements the **Claim-Check pattern** for efficient handling of large payloads (>0.5MB):
+
+```mermaid
+flowchart TB
+    subgraph NATSBridge["NATSBridge Module"]
+        direction TB
+        
+        subgraph Sender["Sender (smartsend)"]
+            direction LR
+            S1["Data Tuples<br/>[(dataname, data, type)]"]
+            S2["Serialize Data"]
+            S3["Size Check"]
+            S4["Transport Selection"]
+            S5["Build Envelope"]
+            S6["Publish to NATS"]
+            
+            S1 --> S2
+            S2 --> S3
+            S3 --> S4
+            S4 --> S5
+            S5 --> S6
+        end
+        
+        subgraph Receiver["Receiver (smartreceive)"]
+            direction LR
+            R1["Subscribe to NATS"]
+            R2["Parse Envelope"]
+            R3["Check Transport"]
+            R4["Deserialize Data"]
+            R5["Return Payloads"]
+            
+            R1 --> R2
+            R2 --> R3
+            R3 --> R4
+            R4 --> R5
+        end
+        
+        S6 -.->|Message| R1
+    end
+    
+    subgraph FileServer["HTTP File Server (Plik)"]
+        direction TB
+        FS1["Upload URL"]
+        FS2["Download URL"]
+        
+        S4 -.->|Large Payload| FS1
+        FS1 -.->|URL| S5
+        R3 -.->|Fetch URL| FS2
+    end
+    
+    style NATSBridge fill:#e1f5fe,stroke:#0288d1,stroke-width:2px
+    style Sender fill:#b3e5fc,stroke:#0288d1
+    style Receiver fill:#b3e5fc,stroke:#0288d1
+    style FileServer fill:#ffe0b2,stroke:#f57c00
+```
+
+### Key Design Principles
+
+### Key Design Principles
+
+| Principle | Description | Rationale |
+|-----------|-------------|-----------|
+| **Claim-Check Pattern** | Large payloads uploaded to HTTP server, URL sent via NATS | NATS has message size limits; avoids NATS overflow |
+| **Automatic Transport Selection** | Direct (< threshold) vs Link (≥ threshold) based on size | Optimizes memory vs network I/O trade-off |
+| **Cross-Platform API** | Consistent `smartsend()`/`smartreceive()` across all platforms | Simplifies developer experience |
+| **Exponential Backoff** | Retry downloads with increasing delays | Handles transient failures gracefully |
+
+---
+
+## User Scenario 1: Chat Webapp ↔ Julia Backend
+
+### Scenario Description
+
+A JavaScript chat webapp wants to send mixed payloads (text message + user avatar image) to a Julia backend, and receive mixed payloads (text response + AI-generated image) back.
+
+### Step-by-Step Flow
+
+#### Step 1: JavaScript Webapp Sends Mixed Payloads
+
+```javascript
+// JavaScript (Browser or Node.js)
+const [env, msgJson] = await NATSBridge.smartsend(
+    "/agent/wine/api/v1/prompt",
+    [
+        ["msg", "Hello! I'm Ton.", "text"],
+        ["avatar", avatarImageData, "image"]
+    ],
+    {
+        broker_url: "ws://localhost:4222",
+        receiver_name: "agent-backend",
+        msg_purpose: "chat"
+    }
+);
+```
+
+**Rationale**:
+- **Why mixed payloads?** Real chat apps often send both text and images together
+- **Why text first?** Text is smaller, sent via direct transport (fast, no file server needed)
+- **Why image second?** Images may trigger link transport if >0.5MB
+
+#### Step 2: Transport Selection
+
+For each payload, NATSBridge determines transport:
+
+| Payload | Size | Transport | Reason |
+|---------|------|-----------|--------|
+| `"msg"` (text) | ~20 bytes | direct | < 0.5MB threshold |
+| `"avatar"` (image) | ~150KB | direct | < 0.5MB threshold |
+
+**Rationale**:
+- Direct transport is faster for small payloads (no file server round-trip)
+- Link transport is used when payload ≥ 0.5MB (avoids NATS size limits)
+
+#### Step 3: Serialization and Encoding
+
+Each payload is serialized:
+
+| Payload | Type | Serialization | Encoding |
+|---------|------|---------------|----------|
+| `"msg"` | `text` | UTF-8 bytes | Base64 |
+| `"avatar"` | `image` | Raw bytes | Base64 |
+
+**Rationale**:
+- Text uses UTF-8 encoding for human-readable data
+- Images use raw bytes to preserve binary data integrity
+- All payloads encoded as Base64 for JSON compatibility
+
+#### Step 4: Envelope Building
+
+NATSBridge builds the message envelope:
+
+```json
+{
+  "correlation_id": "a1b2c3d4...",
+  "msg_id": "e5f6g7h8...",
+  "timestamp": "2026-03-13T16:30:00.000Z",
+  "send_to": "/agent/wine/api/v1/prompt",
+  "msg_purpose": "chat",
+  "sender_name": "chat-webapp",
+  "sender_id": "sender-uuid...",
+  "receiver_name": "agent-backend",
+  "receiver_id": "",
+  "reply_to": "/agent/wine/api/v1/response",
+  "reply_to_msg_id": "",
+  "broker_url": "ws://localhost:4222",
+  "metadata": {},
+  "payloads": [
+    {
+      "id": "payload-uuid...",
+      "dataname": "msg",
+      "payload_type": "text",
+      "transport": "direct",
+      "encoding": "base64",
+      "size": 20,
+      "data": "SGVsbG8hIEknIHRlbCB5b3UgSW4gZW5nbGlzaC4=",
+      "metadata": {"payload_bytes": 20}
+    },
+    {
+      "id": "payload-uuid...",
+      "dataname": "avatar",
+      "payload_type": "image",
+      "transport": "direct",
+      "encoding": "base64",
+      "size": 150000,
+      "data": "iVBORw0KGgoAAAANSUhEUgAA...",
+      "metadata": {"payload_bytes": 150000}
+    }
+  ]
+}
+```
+
+**Rationale**:
+- **correlation_id**: Tracks this chat session across all systems
+- **reply_to**: Tells backend where to send response
+- **payloads array**: Contains all data with metadata for proper handling
+
+#### Step 5: Publish to NATS
+
+```javascript
+await NATSBridge.NATSClient.connect("ws://localhost:4222");
+await NATSBridge.NATSClient.publish("/agent/wine/api/v1/prompt", msgJson);
+```
+
+**Rationale**:
+- NATS provides low-latency message delivery
+- JSON format ensures cross-platform compatibility
+
+#### Step 6: Julia Backend Receives Message
+
+```julia
+# Julia backend
+msg = NATS.subscription.next()  # Get message from NATS
+env = smartreceive(msg)
+
+# env["payloads"] is now:
+# [
+#     ("msg", "Hello! I'm Ton.", "text"),
+#     ("avatar", binary_data, "image")
+# ]
+```
+
+**Rationale**:
+- `smartreceive()` handles both transport types automatically
+- Deserialization is type-aware based on `payload_type`
+- Returns consistent tuple format regardless of transport
+
+#### Step 7: Julia Backend Sends Response
+
+```julia
+# Julia backend processes the message
+response_text = "Hello Ton! I'm the AI assistant."
+generated_image = generate_ai_image(response_text)
+
+env, msg_json = smartsend(
+    "/agent/wine/api/v1/response",
+    [
+        ("response", response_text, "text"),
+        ("generated_image", generated_image, "image")
+    ],
+    reply_to = "/chat/user/v1/message",
+    reply_to_msg_id = msg["msg_id"]
+)
+```
+
+**Rationale**:
+- **Mixed response**: Text explanation + AI-generated image
+- **reply_to**: Ensures response goes to correct topic
+- **reply_to_msg_id**: Links response to original message for tracing
+
+---
+
+## User Scenario 2: Large File Transfer
+
+### Scenario Description
+
+A JavaScript webapp wants to upload a large file (10MB) to a Julia backend for processing.
+
+### Step-by-Step Flow
+
+#### Step 1: JavaScript Webapp Sends Large File
+
+```javascript
+const [env, msgJson] = await NATSBridge.smartsend(
+    "/agent/wine/api/v1/process",
+    [
+        ["file", largeFileData, "binary"]
+    ],
+    {
+        broker_url: "ws://localhost:4222",
+        receiver_name: "agent-backend"
+    }
+);
+```
+
+#### Step 2: Transport Selection (Link)
+
+| Payload | Size | Transport | Reason |
+|---------|------|-----------|--------|
+| `"file"` | 10MB | link | ≥ 0.5MB threshold |
+
+**Rationale**:
+- Link transport used for large payloads
+- File server handles large file upload
+- NATS only sends URL (small message)
+
+#### Step 3: File Server Upload
+
+```javascript
+// NATSBridge internally calls:
+const response = await plikOneshotUpload(
+    "http://localhost:8080",
+    "file",
+    largeFileData
+);
+
+// Response:
+// {
+//   status: 200,
+//   uploadid: "UPLOAD_ID",
+//   fileid: "FILE_ID",
+//   url: "http://localhost:8080/file/UPLOAD_ID/FILE_ID/file"
+// }
+```
+
+**Rationale**:
+- Plik handles multipart upload
+- One-shot mode simplifies API
+- Returns URL for download
+
+#### Step 4: Envelope with Link Transport
+
+```json
+{
+  "correlation_id": "a1b2c3d4...",
+  "payloads": [
+    {
+      "id": "payload-uuid...",
+      "dataname": "file",
+      "payload_type": "binary",
+      "transport": "link",
+      "encoding": "none",
+      "size": 10000000,
+      "data": "http://localhost:8080/file/UPLOAD_ID/FILE_ID/file",
+      "metadata": {}
+    }
+  ]
+}
+```
+
+**Rationale**:
+- `data` field contains URL instead of Base64
+- `transport: "link"` signals URL-based download
+- `encoding: "none"` indicates no additional encoding
+
+#### Step 5: Julia Backend Receives and Downloads
+
+```julia
+# Julia backend
+msg = NATS.subscription.next()
+env = smartreceive(msg)
+
+# NATSBridge automatically:
+# 1. Extracts URL from payload
+# 2. Downloads with exponential backoff
+# 3. Deserializes to binary data
+```
+
+**Rationale**:
+- Exponential backoff handles transient failures
+- Automatic download simplifies receiver code
+- Binary data returned directly
+
+---
+
+## User Scenario 3: Tabular Data Exchange
+
+### Scenario Description
+
+A Python application sends tabular data (pandas DataFrame) to a Julia backend for analysis, and receives processed results back.
+
+### Step-by-Step Flow
+
+#### Step 1: Python Sends Tabular Data
+
+```python
+# Python
+import pandas as pd
+from natsbridge import smartsend
+
+df = pd.DataFrame({
+    "id": [1, 2, 3],
+    "name": ["Alice", "Bob", "Charlie"],
+    "score": [95, 88, 92]
+})
+
+env, msg_json = await smartsend(
+    "/agent/wine/api/v1/analyze",
+    [("data", df, "arrowtable")],
+    broker_url="nats://localhost:4222",
+    receiver_name="agent-backend"
+)
+```
+
+**Rationale**:
+- `arrowtable` type for efficient tabular data transfer
+- Arrow IPC format preserves data types
+- Much faster than JSON serialization
+
+#### Step 2: Serialization to Arrow IPC
+
+```python
+# NATSBridge internally:
+import pyarrow as pa
+import pyarrow.ipc as ipc
+
+table = pa.Table.from_pandas(df)
+buf = io.BytesIO()
+sink = ipc.new_file(buf, table.schema)
+ipc.write_table(table, sink)
+arrow_bytes = buf.getvalue()
+```
+
+**Rationale**:
+- Arrow IPC preserves column types
+- Binary format is compact
+- No schema information loss
+
+#### Step 3: Julia Receives and Deserializes
+
+```julia
+# Julia backend
+msg = NATS.subscription.next()
+env = smartreceive(msg)
+
+# env["payloads"][1] is now:
+# ("data", DataFrame with id, name, score columns, "arrowtable")
+```
+
+**Rationale**:
+- Arrow.jl reads IPC format directly
+- DataFrame returned with correct types
+- No manual parsing needed
+
+#### Step 4: Julia Sends Results
+
+```julia
+# Julia backend
+results = analyze_data(env["payloads"][1][2])
+
+# Send results back
+env, msg_json = smartsend(
+    "/agent/wine/api/v1/results",
+    [("results", results, "arrowtable")],
+    reply_to = "/python/worker/v1/results"
+)
+```
+
+**Rationale**:
+- Arrow IPC format for efficient round-trip
+- Results preserve DataFrame structure
+- Python can deserialize to pandas DataFrame
+
+---
+
+## User Scenario 4: MicroPython Device
+
+### Scenario Description
+
+A MicroPython sensor device sends sensor readings to a Python backend.
+
+### Step-by-Step Flow
+
+#### Step 1: MicroPython Sends Sensor Data
+
+```python
+# MicroPython
+from natsbridge import smartsend
+
+sensor_data = {
+    "temperature": 25.5,
+    "humidity": 60.0,
+    "pressure": 1013.25
+}
+
+env, msg_json = smartsend(
+    "/sensor/device/v1/readings",
+    [("data", sensor_data, "dictionary")],
+    broker_url="nats://localhost:4222",
+    size_threshold=100000  # 100KB for MicroPython
+)
+```
+
+**Rationale**:
+- `dictionary` type for JSON-serializable sensor data
+- Smaller threshold (100KB) for memory constraints
+- Direct transport only (no file server support)
+
+#### Step 2: Serialization
+
+```python
+# NATSBridge internally:
+json_str = json.dumps(sensor_data)
+json_bytes = json_str.encode('utf-8')
+payload_b64 = base64.b64encode(json_bytes).decode('ascii')
+```
+
+**Rationale**:
+- JSON format for human-readable data
+- Base64 for NATS compatibility
+- UTF-8 for text encoding
+
+#### Step 3: Python Backend Receives
+
+```python
+# Python backend
+msg = await nats_consumer.next()
+env = await smartreceive(msg)
+
+# env["payloads"][0] is now:
+# ("data", {"temperature": 25.5, "humidity": 60.0, ...}, "dictionary")
+```
+
+**Rationale**:
+- JSON deserialization
+- Dictionary returned directly
+- No Arrow support (memory constraints)
+
+---
+
+## User Scenario 5: Cross-Platform Chat with Mixed Payloads
+
+### Scenario Description
+
+Multiple platforms (JavaScript, Python, Julia) communicate in a chat application with mixed payload types.
+
+### Step-by-Step Flow
+
+#### Step 1: JavaScript Sends Chat Message
+
+```javascript
+// JavaScript (Frontend)
+const [env, msgJson] = await NATSBridge.smartsend(
+    "/chat/user/v1/message",
+    [
+        ["text", "Check this out!", "text"],
+        ["image", imageData, "image"]
+    ],
+    {
+        broker_url: "ws://localhost:4222",
+        receiver_name: "",
+        msg_purpose: "chat"
+    }
+);
+```
+
+**Rationale**:
+- Empty `receiver_name` = broadcast to all subscribers
+- Chat messages often include text + images
+- NATS wildcard subscriptions route to correct recipients
+
+#### Step 2: Python Backend Receives
+
+```python
+# Python (Backend)
+msg = await nats_consumer.next()
+env = await smartreceive(msg)
+
+# env["payloads"] is now:
+# [
+#     ("text", "Check this out!", "text"),
+#     ("image", binary_data, "image")
+# ]
+```
+
+**Rationale**:
+- Consistent API across platforms
+- Same payload structure regardless of sender
+- Type information preserved
+
+#### Step 3: Julia Backend Receives
+
+```julia
+# Julia (Backend)
+msg = NATS.subscription.next()
+env = smartreceive(msg)
+
+# env["payloads"] is now:
+# [
+#     ("text", "Check this out!", "text"),
+#     ("image", binary_data, "image")
+# ]
+```
+
+**Rationale**:
+- Cross-platform API parity
+- Same function signature across platforms
+- Type information enables proper deserialization
+
+#### Step 4: All Platforms Reply
+
+Each platform can reply using the same API:
+
+```python
+# Python reply
+await smartsend(
+    "/chat/user/v1/reply",
+    [("response", "Nice!", "text")],
+    reply_to="/chat/user/v1/message"
+)
+```
+
+```julia
+# Julia reply
+smartsend(
+    "/chat/user/v1/reply",
+    [("response", "Nice!", "text")],
+    reply_to="/chat/user/v1/message"
+)
+```
+
+```javascript
+// JavaScript reply
+await NATSBridge.smartsend(
+    "/chat/user/v1/reply",
+    [["response", "Nice!", "text"]],
+    { reply_to: "/chat/user/v1/message" }
+);
+```
+
+**Rationale**:
+- Same API across platforms
+- Consistent behavior
+- Easy to maintain parity
+
+---
+
+## Error Handling
+
+### Common Error Scenarios
+
+| Scenario | Error | Recovery |
+|----------|-------|----------|
+| File server unavailable | `UPLOAD_FAILED` | Fall back to direct transport or smaller payloads |
+| File server download fails | `DOWNLOAD_FAILED` | Retry with exponential backoff |
+| Payload type mismatch | `DESERIALIZATION_ERROR` | Validate payload_type matches data |
+| NATS connection lost | `NATS_CONNECTION_FAILED` | NATS client auto-reconnects |
+
+### Error Response Format
+
+```json
+{
+  "correlation_id": "abc123...",
+  "error": {
+    "code": "DOWNLOAD_FAILED",
+    "message": "Failed to fetch data after 5 attempts",
+    "details": {
+      "url": "http://localhost:8080/file/...",
+      "correlation_id": "abc123..."
+    }
+  }
+}
+```
+
+---
+
+## Debugging and Tracing
+
+### Correlation ID Tracking
+
+Every message includes a `correlation_id`:
+
+```julia
+# At start of request
+correlation_id = string(uuid4())
+
+# Use throughout the flow
+log_trace(correlation_id, "Starting smartsend")
+log_trace(correlation_id, "Serialized payload size: 100 bytes")
+log_trace(correlation_id, "Published to NATS")
+```
+
+**Log Format**:
+```
+[2026-03-13T16:30:00.000Z] [Correlation: abc123...] Starting smartsend
+[2026-03-13T16:30:00.001Z] [Correlation: abc123...] Serialized payload size: 100 bytes
+[2026-03-13T16:30:00.002Z] [Correlation: abc123...] Published to NATS
+```
+
+---
+
+## Performance Considerations
+
+### Optimization Strategies
+
+| Strategy | Description | When to Use |
+|----------|-------------|-------------|
+| Pre-create NATS connection | Reuse connection for multiple sends | High-throughput scenarios |
+| Adjust size threshold | Increase threshold if file server slow | File server bottleneck |
+| Use direct transport | Avoid file server for small payloads | Low latency requirements |
+
+### Size Threshold by Platform
+
+| Platform | Threshold | Notes |
+|----------|-----------|-------|
+| Desktop (Julia/JS/Python) | 500,000 bytes (0.5MB) | Default threshold |
+| MicroPython | 100,000 bytes (100KB) | Lower threshold for memory constraints |
+
+---
+
+## Deployment Considerations
+
+### Minimum Infrastructure
+
+| Component | Minimum | Notes |
+|-----------|---------|-------|
+| NATS Server | 1 instance | Single node for development |
+| File Server | 1 instance | HTTP server for large payloads |
+| Client Memory | 50MB | Desktop platforms |
+| Client Memory | 256KB | MicroPython devices |
+
+### Environment Variables
+
+| Variable | Default | Description |
+|----------|---------|-------------|
+| `NATS_URL` | `nats://localhost:4222` | NATS server URL |
+| `FILESERVER_URL` | `http://localhost:8080` | HTTP file server URL |
+| `SIZE_THRESHOLD` | `1000000` | Size threshold in bytes |
+
+---
+
+## Change Log
+
+| Date | Version | Changes |
+|------|---------|---------|
+| 2026-03-13 | 1.0.0 | Initial walkthrough documentation |
+
+---
+
+## References
+
+- [`docs/requirements.md`](./requirements.md) - Business requirements and user stories
+- [`docs/spec.md`](./spec.md) - Technical specification and contracts
+- [`docs/architecture.md`](./architecture.md) - System architecture diagrams
+- [`src/NATSBridge.jl`](../src/NATSBridge.jl) - Ground truth implementation
+- [`README.md`](../README.md) - Project overview
+
+---
+
+*This walkthrough document is versioned and maintained in git alongside the codebase. All implementations must adhere to this documentation.*
+
+<tool_call>
+<function=update_todo_list>
+<parameter=todos>
+[x] Analyze existing documentation (requirements.md, spec.md, architecture.md)
+[x] Read all source files in src/ folder
+[x] Write docs/walkthrough.md according to SDD framework with user scenarios

etc.jl

@@ -1,21 +0,0 @@
-Check architecture.jl, NATSBridge.jl and its test files:
-- test_julia_to_julia_table_receiver.jl
-- test_julia_to_julia_table_sender.jl. 
-
-Now I want to test sending a mix-content message from Julia serviceA to Julia serviceB, for example, a chat system. 
-The test message must show that any combination and any number and any data size of text | json | table | image | audio | video | binary can be send and receive.
-
-Can you write me the following test files:
-- test_julia_to_julia_mix_receiver.jl
-- test_julia_to_julia_mix_sender.jl
-
-
-
-
-1. create a tutorial file "tutorial_julia.md" for NATSBridge.jl
-2. create a walkthrough file "walkthrough_julia.md" for NATSBridge.jl
-
-You may consult architecture.md for more info.
-
-
-

etc.txt

@@ -0,0 +1,310 @@
+#!/usr/bin/env julia
+# Test script for mixed-content message testing
+# Tests receiving a mix of text, json, table, image, audio, video, and binary data
+# from Julia serviceA to Julia serviceB using NATSBridge.jl smartreceive
+#
+# This test demonstrates that any combination and any number of mixed content
+# can be sent and received correctly.
+
+using NATS, JSON, UUIDs, Dates, PrettyPrinting, DataFrames, Arrow, HTTP, Base64
+
+# Include the bridge module
+include("./src/NATSBridge.jl")
+using .NATSBridge
+
+# Configuration
+const SUBJECT = "/test/mix"
+const NATS_URL = "nats.yiem.cc"
+const FILESERVER_URL = "http://192.168.88.104:8080"
+
+
+# ------------------------------------------------------------------------------------------------ #
+#                                      test mixed content transfer                                 #
+# ------------------------------------------------------------------------------------------------ #
+
+
+# Helper: Log with correlation ID
+function log_trace(message)
+    timestamp = Dates.now()
+    println("[$timestamp] $message")
+end
+
+
+# Receiver: Listen for messages and verify mixed content handling
+function test_mix_receive()
+    conn = NATS.connect(NATS_URL)
+    incoming_msg = nothing
+    NATS.subscribe(conn, SUBJECT) do msg
+        log_trace("Received message on $(msg.subject)")
+        incoming_msg = msg
+        
+        # # Use NATSBridge.smartreceive to handle the data
+        # # API: smartreceive(msg, download_handler; max_retries, base_delay, max_delay)
+        # result = NATSBridge.smartreceive(
+        #     msg;
+        #     max_retries = 5,
+        #     base_delay = 100,
+        #     max_delay = 5000
+        # )
+        
+        # log_trace("Received $(length(result["payloads"])) payloads")
+        
+        
+        # # Result is an envelope dictionary with payloads field containing list of (dataname, data, data_type) tuples
+        # for (dataname, data, data_type) in result["payloads"]
+        #     log_trace("\n=== Payload: $dataname (type: $data_type) ===")
+            
+        #     # Handle different data types
+        #     if data_type == "text"
+        #         # Text data - should be a String
+        #         if isa(data, String)
+        #             log_trace("  Type: String")
+        #             log_trace("  Length: $(length(data)) characters")
+                    
+        #             # Display first 200 characters
+        #             if length(data) > 200
+        #                 log_trace("  First 200 chars: $(data[1:200])...")
+        #             else
+        #                 log_trace("  Content: $data")
+        #             end
+                    
+        #             # Save to file
+        #             output_path = "./received_$dataname.txt"
+        #             write(output_path, data)
+        #             log_trace("  Saved to: $output_path")
+        #         else
+        #             log_trace("  ERROR: Expected String, got $(typeof(data))")
+        #         end
+                
+        #     elseif data_type == "dictionary"
+        #         # Dictionary data - should be JSON object
+        #         if isa(data, JSON.Object{String, Any})
+        #             log_trace("  Type: Dict")
+        #             log_trace("  Keys: $(keys(data))")
+                    
+        #             # Display nested content
+        #             for (key, value) in data
+        #                 log_trace("  $key => $value")
+        #             end
+                    
+        #             # Save to JSON file
+        #             output_path = "./received_$dataname.json"
+        #             json_str = JSON.json(data, 2)
+        #             write(output_path, json_str)
+        #             log_trace("  Saved to: $output_path")
+        #         else
+        #             log_trace("  ERROR: Expected Dict, got $(typeof(data))")
+        #         end
+                
+        #     elseif data_type == "table"
+        #         # Table data - should be a DataFrame
+        #         tabledata = deepcopy(data)
+        #         println("found table data")
+        #         break
+        #         # return data
+        #         # if isa(data, DataFrame)
+        #         #     log_trace("  Type: DataFrame")
+        #         #     log_trace("  Dimensions: $(size(data, 1)) rows x $(size(data, 2)) columns")
+        #         #     log_trace("  Columns: $(names(data))")
+                    
+        #         #     # Display first few rows
+        #         #     log_trace("  First 5 rows:")
+        #         #     display(data[1:min(5, size(data, 1)), :])
+                    
+        #         #     # Save to Arrow file
+        #         #     output_path = "./received_$dataname.arrow"
+        #         #     io = IOBuffer()
+        #         #     Arrow.write(io, data)
+        #         #     write(output_path, take!(io))
+        #         #     log_trace("  Saved to: $output_path")
+        #         # else
+        #         #     log_trace("  ERROR: Expected DataFrame, got $(typeof(data))")
+        #         # end
+                
+        #     elseif data_type == "image"
+        #         # Image data - should be Vector{UInt8}
+        #         if isa(data, Vector{UInt8})
+        #             log_trace("  Type: Vector{UInt8} (binary)")
+        #             log_trace("  Size: $(length(data)) bytes")
+                    
+        #             # Save to file
+        #             output_path = "./received_$dataname.bin"
+        #             write(output_path, data)
+        #             log_trace("  Saved to: $output_path")
+        #         else
+        #             log_trace("  ERROR: Expected Vector{UInt8}, got $(typeof(data))")
+        #         end
+                
+        #     elseif data_type == "audio"
+        #         # Audio data - should be Vector{UInt8}
+        #         if isa(data, Vector{UInt8})
+        #             log_trace("  Type: Vector{UInt8} (binary)")
+        #             log_trace("  Size: $(length(data)) bytes")
+                    
+        #             # Save to file
+        #             output_path = "./received_$dataname.bin"
+        #             write(output_path, data)
+        #             log_trace("  Saved to: $output_path")
+        #         else
+        #             log_trace("  ERROR: Expected Vector{UInt8}, got $(typeof(data))")
+        #         end
+                
+        #     elseif data_type == "video"
+        #         # Video data - should be Vector{UInt8}
+        #         if isa(data, Vector{UInt8})
+        #             log_trace("  Type: Vector{UInt8} (binary)")
+        #             log_trace("  Size: $(length(data)) bytes")
+                    
+        #             # Save to file
+        #             output_path = "./received_$dataname.bin"
+        #             write(output_path, data)
+        #             log_trace("  Saved to: $output_path")
+        #         else
+        #             log_trace("  ERROR: Expected Vector{UInt8}, got $(typeof(data))")
+        #         end
+                
+        #     elseif data_type == "binary"
+        #         # Binary data - should be Vector{UInt8}
+        #         if isa(data, Vector{UInt8})
+        #             log_trace("  Type: Vector{UInt8} (binary)")
+        #             log_trace("  Size: $(length(data)) bytes")
+                    
+        #             # Save to file
+        #             output_path = "./received_$dataname.bin"
+        #             write(output_path, data)
+        #             log_trace("  Saved to: $output_path")
+        #         else
+        #             log_trace("  ERROR: Expected Vector{UInt8}, got $(typeof(data))")
+        #         end
+                
+        #     else
+        #         log_trace("  ERROR: Unknown data type '$data_type'")
+        #     end
+        # end
+        
+        # Summary
+        # println("\n=== Verification Summary ===")
+        # text_count = count(x -> x[3] == "text", result["payloads"])
+        # dict_count = count(x -> x[3] == "dictionary", result["payloads"])
+        # table_count = count(x -> x[3] == "table", result["payloads"])
+        # image_count = count(x -> x[3] == "image", result["payloads"])
+        # audio_count = count(x -> x[3] == "audio", result["payloads"])
+        # video_count = count(x -> x[3] == "video", result["payloads"])
+        # binary_count = count(x -> x[3] == "binary", result["payloads"])
+        
+        # log_trace("Text payloads: $text_count")
+        # log_trace("Dictionary payloads: $dict_count")
+        # log_trace("Table payloads: $table_count")
+        # log_trace("Image payloads: $image_count")
+        # log_trace("Audio payloads: $audio_count")
+        # log_trace("Video payloads: $video_count")
+        # log_trace("Binary payloads: $binary_count")
+        
+        # # Print transport type info for each payload if available
+        # println("\n=== Payload Details ===")
+        # for (dataname, data, data_type) in result["payloads"]
+        #     if data_type in ["image", "audio", "video", "binary"]
+        #         log_trace("$dataname: $(length(data)) bytes (binary)")
+        #     elseif data_type == "table"
+        #       data = DataFrame(data)
+        #         log_trace("$dataname: $(size(data, 1)) rows x $(size(data, 2)) columns (DataFrame)")
+        #     elseif data_type == "dictionary"
+        #         log_trace("$dataname: $(length(JSON.json(data))) bytes (Dict)")
+        #     elseif data_type == "text"
+        #         log_trace("$dataname: $(length(data)) characters (String)")
+        #     end
+        # end
+    end
+    
+    # Keep listening for 2 minutes
+    sleep(20)  
+    NATS.drain(conn)
+    return incoming_msg
+end
+
+
+# Run the test
+println("Starting mixed-content transport test...")
+println("Note: This receiver will wait for messages from the sender.")
+println("Run test_julia_to_julia_mix_sender.jl first to send test data.")
+
+# Run receiver
+println("\ntesting smartreceive for mixed content")
+incoming_msg = test_mix_receive()
+
+println("\nTest completed.")
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+Check architecture.md. For sending table I want to add JSON in addition to Apache Arrow. 
+Currently I use "table" datatype when sending table data using Arrow. Now table that I want to send using JSON 
+I will use "jsontable" as datatype while sending table using Arrow I will use "arrowtable" as datatype. 
+This will select how smartsend and smartreceive serialize/deserialize the table.
+
+Can you help me do this? Save the updated architecture.md into updated_architecture.md file. I will deal with source code later.
+
+
+
+
+Now update implementation.md and save into updated_implementation.md
+Keep in mind that Julia DataFrame and Python Pandas rely on columnar-oriented dictionary to create as the following example:
+julia> dict = Dict("customer age" => [15, 20, 25],
+                   "first name" => ["Rohit", "Rahul", "Akshat"])
+julia> DataFrame(dict)
+
+python> data = {
+    "Name": ["Alice", "Bob", "Charlie"],
+    "Age": [25, 30, 35],
+    "Score": [88.5, 92.0, 79.5]
+}
+
+python> df = pd.DataFrame(data)
+
+
+But JS use Array of Objects while MicroPython use list of lists. Both are row-oriented structure.
+So use row-oriented JSON to send across these languages. For Julia and Python, only convert 
+row-oriented JSON to columnar-oriented dictionary for "going-into" and vise versa for "coming-out" 
+a dataframe while JS and MicroPython won't require such process. 
+You may add these info into architecture.md if you see fit.
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+

examples/micropython_example.py

@@ -1,221 +0,0 @@
-"""
-Micropython NATS Bridge - Simple Example
-
-This example demonstrates the basic usage of the NATSBridge for Micropython.
-"""
-
-import sys
-sys.path.insert(0, "../src")
-
-from nats_bridge import smartsend, smartreceive, log_trace
-import json
-
-
-def example_simple_chat():
-    """
-    Simple chat example: Send text messages via NATS.
-    
-    Sender (this script):
-    - Sends a text message to NATS
-    - Uses direct transport (no fileserver needed)
-    
-    Receiver (separate script):
-    - Listens to NATS
-    - Receives and processes the message
-    """
-    print("=== Simple Chat Example ===")
-    print()
-    
-    # Define the message data as list of (dataname, data, type) tuples
-    data = [
-        ("message", "Hello from Micropython!", "text")
-    ]
-    
-    # Send the message
-    env = smartsend(
-        "/chat/room1",
-        data,
-        nats_url="nats://localhost:4222",
-        msg_purpose="chat",
-        sender_name="micropython-client"
-    )
-    
-    print("Message sent!")
-    print("  Subject: {}".format(env.send_to))
-    print("  Correlation ID: {}".format(env.correlation_id))
-    print("  Payloads: {}".format(len(env.payloads)))
-    print()
-    
-    # Expected receiver output:
-    print("Expected receiver output:")
-    print("  [timestamp] [Correlation: ...] Starting smartsend for subject: /chat/room1")
-    print("  [timestamp] [Correlation: ...] Serialized payload 'message' (type: text) size: 22 bytes")
-    print("  [timestamp] [Correlation: ...] Using direct transport for 22 bytes")
-    print("  [timestamp] [Correlation: ...] Message published to /chat/room1")
-    print()
-    
-    return env
-
-
-def example_send_json():
-    """
-    Example: Send JSON configuration to a Micropython device.
-    
-    This demonstrates sending structured data (dictionary type).
-    """
-    print("\n=== Send JSON Configuration ===")
-    print()
-    
-    # Define configuration as dictionary
-    config = {
-        "wifi_ssid": "MyNetwork",
-        "wifi_password": "password123",
-        "server_host": "mqtt.example.com",
-        "server_port": 1883,
-        "update_interval": 60
-    }
-    
-    # Send configuration
-    data = [
-        ("device_config", config, "dictionary")
-    ]
-    
-    env = smartsend(
-        "/device/config",
-        data,
-        nats_url="nats://localhost:4222",
-        msg_purpose="updateStatus",
-        sender_name="server"
-    )
-    
-    print("Configuration sent!")
-    print("  Subject: {}".format(env.send_to))
-    print("  Payloads: {}".format(len(env.payloads)))
-    print()
-    
-    return env
-
-
-def example_receive_message(msg):
-    """
-    Example: Receive and process a NATS message.
-    
-    Args:
-        msg: The NATS message received (should be dict or JSON string)
-    
-    Returns:
-        list: List of (dataname, data, type) tuples
-    """
-    print("\n=== Receive Message ===")
-    print()
-    
-    # Process the message
-    payloads = smartreceive(
-        msg,
-        fileserver_download_handler=None,  # Not needed for direct transport
-        max_retries=3,
-        base_delay=100,
-        max_delay=1000
-    )
-    
-    print("Received {} payload(s):".format(len(payloads)))
-    for dataname, data, type in payloads:
-        print("  - {}: {} (type: {})".format(dataname, data, type))
-    
-    return payloads
-
-
-def example_mixed_content():
-    """
-    Example: Send mixed content (text + dictionary + binary).
-    
-    This demonstrates the multi-payload capability.
-    """
-    print("\n=== Mixed Content Example ===")
-    print()
-    
-    # Create mixed content
-    image_data = b"\x89PNG\r\n\x1a\n\x00\x00\x00\rIHDR"  # Example PNG header
-    
-    data = [
-        ("message_text", "Hello with image!", "text"),
-        ("user_config", {"theme": "dark", "notifications": True}, "dictionary"),
-        ("user_avatar", image_data, "binary")
-    ]
-    
-    env = smartsend(
-        "/chat/mixed",
-        data,
-        nats_url="nats://localhost:4222",
-        msg_purpose="chat",
-        sender_name="micropython-client"
-    )
-    
-    print("Mixed content sent!")
-    print("  Subject: {}".format(env.send_to))
-    print("  Payloads:")
-    for p in env.payloads:
-        print("    - {} (transport: {}, type: {}, size: {} bytes)".format(
-            p.dataname, p.transport, p.type, p.size))
-    
-    return env
-
-
-def example_reply():
-    """
-    Example: Send a message with reply-to functionality.
-    
-    This demonstrates request-response pattern.
-    """
-    print("\n=== Request-Response Example ===")
-    print()
-    
-    # Send command
-    data = [
-        ("command", {"action": "read_sensor", "sensor_id": "temp1"}, "dictionary")
-    ]
-    
-    env = smartsend(
-        "/device/command",
-        data,
-        nats_url="nats://localhost:4222",
-        msg_purpose="command",
-        sender_name="server",
-        reply_to="/device/response",
-        reply_to_msg_id="cmd-001"
-    )
-    
-    print("Command sent!")
-    print("  Subject: {}".format(env.send_to))
-    print("  Reply To: {}".format(env.reply_to))
-    print("  Reply To Msg ID: {}".format(env.reply_to_msg_id))
-    print()
-    
-    print("Expected receiver behavior:")
-    print("  1. Receive command on /device/command")
-    print("  2. Process command")
-    print("  3. Send response to /device/response")
-    print("  4. Include replyToMsgId in response")
-    
-    return env
-
-
-if __name__ == "__main__":
-    print("Micropython NATS Bridge Examples")
-    print("================================")
-    print()
-    
-    # Run examples
-    example_simple_chat()
-    example_send_json()
-    example_mixed_content()
-    example_reply()
-    
-    print("\n=== Examples Completed ===")
-    print()
-    print("To run these examples, you need:")
-    print("  1. A running NATS server at nats://localhost:4222")
-    print("  2. Import the nats_bridge module")
-    print("  3. Call the desired example function")
-    print()
-    print("For more examples, see test/test_micropython_basic.py")

package.json

@@ -1,28 +0,0 @@
-{
-	"name": "natsbridge",
-	"version": "1.0.0",
-	"description": "Bi-Directional Data Bridge for JavaScript using NATS",
-	"main": "src/NATSBridge.js",
-	"scripts": {
-		"test": "echo \"Error: no test specified\" && exit 1",
-		"lint": "eslint src/*.js test/*.js"
-	},
-	"keywords": [
-		"nats",
-		"message-broker",
-		"bridge",
-		"arrow",
-		"serialization"
-	],
-	"author": "",
-	"license": "MIT",
-	"dependencies": {
-		"nats": "^2.9.0",
-		"apache-arrow": "^14.0.0",
-		"uuid": "^9.0.0"
-	},
-	"devDependencies": {
-		"eslint": "^8.0.0",
-		"jest": "^29.0.0"
-	}
-}

plik_fileserver/docker-compose.yml

@@ -0,0 +1,14 @@
+services:
+  plik:
+    image: rootgg/plik:latest
+    container_name: plik-server
+    restart: unless-stopped
+    ports:
+      - "8080:8080"
+    volumes:
+      # # Mount the config file (created below)
+      # - ./plikd.cfg:/home/plik/server/plikd.cfg
+      # Mount local folder for uploads and database
+      - ./plik-data:/data
+    # Set user to match your host UID to avoid permission issues
+    user: "1000:1000"

src/NATSBridge.js

@@ -1,706 +0,0 @@
-/**
- * NATSBridge.js - Bi-Directional Data Bridge for JavaScript
- * Implements smartsend and smartreceive for NATS communication
- * 
- * This module provides functionality for sending and receiving data across network boundaries
- * using NATS as the message bus, with support for both direct payload transport and
- * URL-based transport for larger payloads.
- * 
- * File Server Handler Architecture:
- * The system uses handler functions to abstract file server operations, allowing support
- * for different file server implementations (e.g., Plik, AWS S3, custom HTTP server).
- * 
- * Handler Function Signatures:
- * 
- * ```javascript
- * // Upload handler - uploads data to file server and returns URL
- * // The handler is passed to smartsend as fileserverUploadHandler parameter
- * // It receives: (fileserver_url, dataname, data)
- * // Returns: { status, uploadid, fileid, url }
- * async function fileserverUploadHandler(fileserver_url, dataname, data) { ... }
- * 
- * // Download handler - fetches data from file server URL with exponential backoff
- * // The handler is passed to smartreceive as fileserverDownloadHandler parameter
- * // It receives: (url, max_retries, base_delay, max_delay, correlation_id)
- * // Returns: ArrayBuffer (the downloaded data)
- * async function fileserverDownloadHandler(url, max_retries, base_delay, max_delay, correlation_id) { ... }
- * ```
- * 
- * Multi-Payload Support (Standard API):
- * The system uses a standardized list-of-tuples format for all payload operations.
- * Even when sending a single payload, the user must wrap it in a list.
- * 
- * API Standard:
- * ```javascript
- * // Input format for smartsend (always a list of tuples with type info)
- * [{ dataname, data, type }, ...]
- * 
- * // Output format for smartreceive (always returns a list of tuples)
- * [{ dataname, data, type }, ...]
- * ```
- * 
- * Supported types: "text", "dictionary", "table", "image", "audio", "video", "binary"
- */
-
-// ---------------------------------------------- 100 --------------------------------------------- #
-
-// Constants
-const DEFAULT_SIZE_THRESHOLD = 1_000_000;  // 1MB - threshold for switching from direct to link transport
-const DEFAULT_NATS_URL = "nats://localhost:4222";  // Default NATS server URL
-const DEFAULT_FILESERVER_URL = "http://localhost:8080";  // Default HTTP file server URL for link transport
-
-// Helper: Generate UUID v4
-function uuid4() {
-    // Simple UUID v4 generator
-    return 'xxxxxxxx-xxxx-4xxx-yxxx-xxxxxxxxxxxx'.replace(/[xy]/g, function(c) {
-        var r = Math.random() * 16 | 0, v = c == 'x' ? r : (r & 0x3 | 0x8);
-        return v.toString(16);
-    });
-}
-
-// Helper: Log with correlation ID and timestamp
-function log_trace(correlation_id, message) {
-    const timestamp = new Date().toISOString();
-    console.log(`[${timestamp}] [Correlation: ${correlation_id}] ${message}`);
-}
-
-// Helper: Get size of data in bytes
-function getDataSize(data) {
-    if (typeof data === 'string') {
-        return new TextEncoder().encode(data).length;
-    } else if (data instanceof ArrayBuffer || data instanceof Uint8Array) {
-        return data.byteLength;
-    } else if (typeof data === 'object' && data !== null) {
-        // For objects, serialize to JSON and measure
-        return new TextEncoder().encode(JSON.stringify(data)).length;
-    }
-    return 0;
-}
-
-// Helper: Convert ArrayBuffer to Base64 string
-function arrayBufferToBase64(buffer) {
-    const bytes = new Uint8Array(buffer);
-    let binary = '';
-    for (let i = 0; i < bytes.length; i++) {
-        binary += String.fromCharCode(bytes[i]);
-    }
-    return btoa(binary);
-}
-
-// Helper: Convert Base64 string to ArrayBuffer
-function base64ToArrayBuffer(base64) {
-    const binaryString = atob(base64);
-    const len = binaryString.length;
-    const bytes = new Uint8Array(len);
-    for (let i = 0; i < len; i++) {
-        bytes[i] = binaryString.charCodeAt(i);
-    }
-    return bytes.buffer;
-}
-
-// Helper: Serialize data based on type
-function _serialize_data(data, type) {
-    /**
-     * Serialize data according to specified format
-     * 
-     * Supported formats:
-     * - "text": Treats data as text and converts to UTF-8 bytes
-     * - "dictionary": Serializes data as JSON and returns the UTF-8 byte representation
-     * - "table": Serializes data as an Arrow IPC stream (table format) - NOT IMPLEMENTED (requires arrow library)
-     * - "image": Expects binary data (ArrayBuffer) and returns it as bytes
-     * - "audio": Expects binary data (ArrayBuffer) and returns it as bytes
-     * - "video": Expects binary data (ArrayBuffer) and returns it as bytes
-     * - "binary": Generic binary data (ArrayBuffer or Uint8Array) and returns bytes
-     */
-    if (type === "text") {
-        if (typeof data === 'string') {
-            return new TextEncoder().encode(data).buffer;
-        } else {
-            throw new Error("Text data must be a String");
-        }
-    } else if (type === "dictionary") {
-        // JSON data - serialize directly
-        const jsonStr = JSON.stringify(data);
-        return new TextEncoder().encode(jsonStr).buffer;
-    } else if (type === "table") {
-        // Table data - convert to Arrow IPC stream (NOT IMPLEMENTED in pure JavaScript)
-        // This would require the apache-arrow library
-        throw new Error("Table serialization requires apache-arrow library");
-    } else if (type === "image") {
-        if (data instanceof ArrayBuffer || data instanceof Uint8Array) {
-            return data instanceof ArrayBuffer ? data : data.buffer;
-        } else {
-            throw new Error("Image data must be ArrayBuffer or Uint8Array");
-        }
-    } else if (type === "audio") {
-        if (data instanceof ArrayBuffer || data instanceof Uint8Array) {
-            return data instanceof ArrayBuffer ? data : data.buffer;
-        } else {
-            throw new Error("Audio data must be ArrayBuffer or Uint8Array");
-        }
-    } else if (type === "video") {
-        if (data instanceof ArrayBuffer || data instanceof Uint8Array) {
-            return data instanceof ArrayBuffer ? data : data.buffer;
-        } else {
-            throw new Error("Video data must be ArrayBuffer or Uint8Array");
-        }
-    } else if (type === "binary") {
-        if (data instanceof ArrayBuffer || data instanceof Uint8Array) {
-            return data instanceof ArrayBuffer ? data : data.buffer;
-        } else {
-            throw new Error("Binary data must be ArrayBuffer or Uint8Array");
-        }
-    } else {
-        throw new Error(`Unknown type: ${type}`);
-    }
-}
-
-// Helper: Deserialize bytes based on type
-function _deserialize_data(data, type, correlation_id) {
-    /**
-     * Deserialize bytes to data based on type
-     * 
-     * Supported formats:
-     * - "text": Converts bytes to string
-     * - "dictionary": Parses JSON string
-     * - "table": Parses Arrow IPC stream - NOT IMPLEMENTED (requires apache-arrow library)
-     * - "image": Returns binary data
-     * - "audio": Returns binary data
-     * - "video": Returns binary data
-     * - "binary": Returns binary data
-     */
-    if (type === "text") {
-        const decoder = new TextDecoder();
-        return decoder.decode(new Uint8Array(data));
-    } else if (type === "dictionary") {
-        const decoder = new TextDecoder();
-        const jsonStr = decoder.decode(new Uint8Array(data));
-        return JSON.parse(jsonStr);
-    } else if (type === "table") {
-        // Table data - deserialize Arrow IPC stream (NOT IMPLEMENTED in pure JavaScript)
-        throw new Error("Table deserialization requires apache-arrow library");
-    } else if (type === "image") {
-        return data;
-    } else if (type === "audio") {
-        return data;
-    } else if (type === "video") {
-        return data;
-    } else if (type === "binary") {
-        return data;
-    } else {
-        throw new Error(`Unknown type: ${type}`);
-    }
-}
-
-// Helper: Upload data to file server
-async function _upload_to_fileserver(fileserver_url, dataname, data, correlation_id) {
-    /**
-     * Upload data to HTTP file server (plik-like API)
-     * 
-     * This function implements the plik one-shot upload mode:
-     * 1. Creates a one-shot upload session by sending POST request with {"OneShot": true}
-     * 2. Uploads the file data as multipart form data
-     * 3. Returns identifiers and download URL for the uploaded file
-     */
-    log_trace(correlation_id, `Uploading ${dataname} to fileserver: ${fileserver_url}`);
-    
-    // Step 1: Get upload ID and token
-    const url_getUploadID = `${fileserver_url}/upload`;
-    const headers = {
-        "Content-Type": "application/json"
-    };
-    const body = JSON.stringify({ OneShot: true });
-    
-    let response = await fetch(url_getUploadID, {
-        method: "POST",
-        headers: headers,
-        body: body
-    });
-    
-    if (!response.ok) {
-        throw new Error(`Failed to get upload ID: ${response.status} ${response.statusText}`);
-    }
-    
-    const responseJson = await response.json();
-    const uploadid = responseJson.id;
-    const uploadtoken = responseJson.uploadToken;
-    
-    // Step 2: Upload file data
-    const url_upload = `${fileserver_url}/file/${uploadid}`;
-    
-    // Create multipart form data
-    const formData = new FormData();
-    // Create a Blob from the ArrayBuffer
-    const blob = new Blob([data], { type: "application/octet-stream" });
-    formData.append("file", blob, dataname);
-    
-    response = await fetch(url_upload, {
-        method: "POST",
-        headers: {
-            "X-UploadToken": uploadtoken
-        },
-        body: formData
-    });
-    
-    if (!response.ok) {
-        throw new Error(`Failed to upload file: ${response.status} ${response.statusText}`);
-    }
-    
-    const fileResponseJson = await response.json();
-    const fileid = fileResponseJson.id;
-    
-    // Build the download URL
-    const url = `${fileserver_url}/file/${uploadid}/${fileid}/${encodeURIComponent(dataname)}`;
-    
-    log_trace(correlation_id, `Uploaded to URL: ${url}`);
-    
-    return {
-        status: response.status,
-        uploadid: uploadid,
-        fileid: fileid,
-        url: url
-    };
-}
-
-// Helper: Fetch data from URL with exponential backoff
-async function _fetch_with_backoff(url, max_retries, base_delay, max_delay, correlation_id) {
-    /**
-     * Fetch data from URL with retry logic using exponential backoff
-     */
-    let delay = base_delay;
-    
-    for (let attempt = 1; attempt <= max_retries; attempt++) {
-        try {
-            const response = await fetch(url);
-            
-            if (response.status === 200) {
-                log_trace(correlation_id, `Successfully fetched data from ${url} on attempt ${attempt}`);
-                const arrayBuffer = await response.arrayBuffer();
-                return arrayBuffer;
-            } else {
-                throw new Error(`Failed to fetch: ${response.status} ${response.statusText}`);
-            }
-        } catch (e) {
-            log_trace(correlation_id, `Attempt ${attempt} failed: ${e.message}`);
-            
-            if (attempt < max_retries) {
-                // Sleep with exponential backoff
-                await new Promise(resolve => setTimeout(resolve, delay));
-                delay = Math.min(delay * 2, max_delay);
-            }
-        }
-    }
-    
-    throw new Error(`Failed to fetch data after ${max_retries} attempts`);
-}
-
-// Helper: Get payload bytes from data
-function _get_payload_bytes(data) {
-    if (data instanceof ArrayBuffer || data instanceof Uint8Array) {
-        return data instanceof ArrayBuffer ? new Uint8Array(data) : data;
-    } else if (typeof data === 'string') {
-        return new TextEncoder().encode(data);
-    } else {
-        // For objects, serialize to JSON
-        return new TextEncoder().encode(JSON.stringify(data));
-    }
-}
-
-// MessagePayload class
-class MessagePayload {
-    /**
-     * Represents a single payload in the message envelope
-     * 
-     * @param {Object} options - Payload options
-     * @param {string} options.id - ID of this payload (e.g., "uuid4")
-     * @param {string} options.dataname - Name of this payload (e.g., "login_image")
-     * @param {string} options.type - Payload type: "text", "dictionary", "table", "image", "audio", "video", "binary"
-     * @param {string} options.transport - "direct" or "link"
-     * @param {string} options.encoding - "none", "json", "base64", "arrow-ipc"
-     * @param {number} options.size - Data size in bytes
-     * @param {string|ArrayBuffer} options.data - Payload data (direct) or URL (link)
-     * @param {Object} options.metadata - Metadata for this payload
-     */
-    constructor(options) {
-        this.id = options.id || uuid4();
-        this.dataname = options.dataname;
-        this.type = options.type;
-        this.transport = options.transport;
-        this.encoding = options.encoding;
-        this.size = options.size;
-        this.data = options.data;
-        this.metadata = options.metadata || {};
-    }
-    
-    // Convert to JSON object
-    toJSON() {
-        const obj = {
-            id: this.id,
-            dataname: this.dataname,
-            type: this.type,
-            transport: this.transport,
-            encoding: this.encoding,
-            size: this.size
-        };
-        
-        // Include data based on transport type
-        if (this.transport === "direct" && this.data !== null) {
-            if (this.encoding === "base64" || this.encoding === "json") {
-                obj.data = this.data;
-            } else {
-                // For other encodings, use base64
-                const payloadBytes = _get_payload_bytes(this.data);
-                obj.data = arrayBufferToBase64(payloadBytes);
-            }
-        } else if (this.transport === "link" && this.data !== null) {
-            // For link transport, data is a URL string
-            obj.data = this.data;
-        }
-        
-        if (Object.keys(this.metadata).length > 0) {
-            obj.metadata = this.metadata;
-        }
-        
-        return obj;
-    }
-}
-
-// MessageEnvelope class
-class MessageEnvelope {
-    /**
-     * Represents the message envelope containing metadata and payloads
-     * 
-     * @param {Object} options - Envelope options
-     * @param {string} options.sendTo - Topic/subject the sender sends to
-     * @param {Array<MessagePayload>} options.payloads - Array of payloads
-     * @param {string} options.correlationId - Unique identifier to track messages
-     * @param {string} options.msgId - This message id
-     * @param {string} options.timestamp - Message published timestamp
-     * @param {string} options.msgPurpose - Purpose of this message
-     * @param {string} options.senderName - Name of the sender
-     * @param {string} options.senderId - UUID of the sender
-     * @param {string} options.receiverName - Name of the receiver
-     * @param {string} options.receiverId - UUID of the receiver
-     * @param {string} options.replyTo - Topic to reply to
-     * @param {string} options.replyToMsgId - Message id this message is replying to
-     * @param {string} options.brokerURL - NATS server address
-     * @param {Object} options.metadata - Metadata for the envelope
-     */
-    constructor(options) {
-        this.correlationId = options.correlationId || uuid4();
-        this.msgId = options.msgId || uuid4();
-        this.timestamp = options.timestamp || new Date().toISOString();
-        this.sendTo = options.sendTo;
-        this.msgPurpose = options.msgPurpose || "";
-        this.senderName = options.senderName || "";
-        this.senderId = options.senderId || uuid4();
-        this.receiverName = options.receiverName || "";
-        this.receiverId = options.receiverId || "";
-        this.replyTo = options.replyTo || "";
-        this.replyToMsgId = options.replyToMsgId || "";
-        this.brokerURL = options.brokerURL || DEFAULT_NATS_URL;
-        this.metadata = options.metadata || {};
-        this.payloads = options.payloads || [];
-    }
-    
-    // Convert to JSON string
-    toJSON() {
-        const obj = {
-            correlationId: this.correlationId,
-            msgId: this.msgId,
-            timestamp: this.timestamp,
-            sendTo: this.sendTo,
-            msgPurpose: this.msgPurpose,
-            senderName: this.senderName,
-            senderId: this.senderId,
-            receiverName: this.receiverName,
-            receiverId: this.receiverId,
-            replyTo: this.replyTo,
-            replyToMsgId: this.replyToMsgId,
-            brokerURL: this.brokerURL
-        };
-        
-        if (Object.keys(this.metadata).length > 0) {
-            obj.metadata = this.metadata;
-        }
-        
-        if (this.payloads.length > 0) {
-            obj.payloads = this.payloads.map(p => p.toJSON());
-        }
-        
-        return obj;
-    }
-    
-    // Convert to JSON string
-    toString() {
-        return JSON.stringify(this.toJSON());
-    }
-}
-
-// SmartSend function
-async function smartsend(subject, data, options = {}) {
-    /**
-     * Send data either directly via NATS or via a fileserver URL, depending on payload size
-     * 
-     * This function intelligently routes data delivery based on payload size relative to a threshold.
-     * If the serialized payload is smaller than `size_threshold`, it encodes the data as Base64 and publishes directly over NATS.
-     * Otherwise, it uploads the data to a fileserver and publishes only the download URL over NATS.
-     * 
-     * @param {string} subject - NATS subject to publish the message to
-     * @param {Array} data - List of {dataname, data, type} objects to send
-     * @param {Object} options - Additional options
-     * @param {string} options.natsUrl - URL of the NATS server (default: "nats://localhost:4222")
-     * @param {string} options.fileserverUrl - Base URL of the file server (default: "http://localhost:8080")
-     * @param {Function} options.fileserverUploadHandler - Function to handle fileserver uploads
-     * @param {number} options.sizeThreshold - Threshold in bytes separating direct vs link transport (default: 1MB)
-     * @param {string} options.correlationId - Optional correlation ID for tracing
-     * @param {string} options.msgPurpose - Purpose of the message (default: "chat")
-     * @param {string} options.senderName - Name of the sender (default: "NATSBridge")
-     * @param {string} options.receiverName - Name of the receiver (default: "")
-     * @param {string} options.receiverId - UUID of the receiver (default: "")
-     * @param {string} options.replyTo - Topic to reply to (default: "")
-     * @param {string} options.replyToMsgId - Message ID this message is replying to (default: "")
-     * 
-     * @returns {Promise<MessageEnvelope>} - The envelope for tracking
-     */
-    const {
-        natsUrl = DEFAULT_NATS_URL,
-        fileserverUrl = DEFAULT_FILESERVER_URL,
-        fileserverUploadHandler = _upload_to_fileserver,
-        sizeThreshold = DEFAULT_SIZE_THRESHOLD,
-        correlationId = uuid4(),
-        msgPurpose = "chat",
-        senderName = "NATSBridge",
-        receiverName = "",
-        receiverId = "",
-        replyTo = "",
-        replyToMsgId = ""
-    } = options;
-    
-    log_trace(correlationId, `Starting smartsend for subject: ${subject}`);
-    
-    // Generate message metadata
-    const msgId = uuid4();
-    
-    // Process each payload in the list
-    const payloads = [];
-    
-    for (const payload of data) {
-        const dataname = payload.dataname;
-        const payloadData = payload.data;
-        const payloadType = payload.type;
-        
-        // Serialize data based on type
-        const payloadBytes = _serialize_data(payloadData, payloadType);
-        const payloadSize = payloadBytes.byteLength;
-        
-        log_trace(correlationId, `Serialized payload '${dataname}' (type: ${payloadType}) size: ${payloadSize} bytes`);
-        
-        // Decision: Direct vs Link
-        if (payloadSize < sizeThreshold) {
-            // Direct path - Base64 encode and send via NATS
-            const payloadB64 = arrayBufferToBase64(payloadBytes);
-            log_trace(correlationId, `Using direct transport for ${payloadSize} bytes`);
-            
-            // Create MessagePayload for direct transport
-            const payloadObj = new MessagePayload({
-                dataname: dataname,
-                type: payloadType,
-                transport: "direct",
-                encoding: "base64",
-                size: payloadSize,
-                data: payloadB64,
-                metadata: { payload_bytes: payloadSize }
-            });
-            payloads.push(payloadObj);
-        } else {
-            // Link path - Upload to HTTP server, send URL via NATS
-            log_trace(correlationId, `Using link transport, uploading to fileserver`);
-            
-            // Upload to HTTP server
-            const response = await fileserverUploadHandler(fileserverUrl, dataname, payloadBytes, correlationId);
-            
-            if (response.status !== 200) {
-                throw new Error(`Failed to upload data to fileserver: ${response.status}`);
-            }
-            
-            const url = response.url;
-            log_trace(correlationId, `Uploaded to URL: ${url}`);
-            
-            // Create MessagePayload for link transport
-            const payloadObj = new MessagePayload({
-                dataname: dataname,
-                type: payloadType,
-                transport: "link",
-                encoding: "none",
-                size: payloadSize,
-                data: url,
-                metadata: {}
-            });
-            payloads.push(payloadObj);
-        }
-    }
-    
-    // Create MessageEnvelope with all payloads
-    const env = new MessageEnvelope({
-        correlationId: correlationId,
-        msgId: msgId,
-        sendTo: subject,
-        msgPurpose: msgPurpose,
-        senderName: senderName,
-        receiverName: receiverName,
-        receiverId: receiverId,
-        replyTo: replyTo,
-        replyToMsgId: replyToMsgId,
-        brokerURL: natsUrl,
-        payloads: payloads
-    });
-    
-    // Publish message to NATS
-    await publish_message(natsUrl, subject, env.toString(), correlationId);
-    
-    return env;
-}
-
-// Helper: Publish message to NATS
-async function publish_message(natsUrl, subject, message, correlation_id) {
-    /**
-     * Publish a message to a NATS subject with proper connection management
-     * 
-     * @param {string} natsUrl - NATS server URL
-     * @param {string} subject - NATS subject to publish to
-     * @param {string} message - JSON message to publish
-     * @param {string} correlation_id - Correlation ID for logging
-     */
-    log_trace(correlation_id, `Publishing message to ${subject}`);
-    
-    // For Node.js, we would use nats.js library
-    // This is a placeholder that throws an error
-    // In production, you would import and use the actual nats library
-    
-    // Example with nats.js:
-    // import { connect } from 'nats';
-    // const nc = await connect({ servers: [natsUrl] });
-    // await nc.publish(subject, message);
-    // nc.close();
-    
-    // For now, just log the message
-    console.log(`[NATS PUBLISH] Subject: ${subject}, Message: ${message.substring(0, 100)}...`);
-}
-
-// SmartReceive function
-async function smartreceive(msg, options = {}) {
-    /**
-     * Receive and process messages from NATS
-     * 
-     * This function processes incoming NATS messages, handling both direct transport
-     * (base64 decoded payloads) and link transport (URL-based payloads).
-     * 
-     * @param {Object} msg - NATS message object with payload property
-     * @param {Object} options - Additional options
-     * @param {Function} options.fileserverDownloadHandler - Function to handle downloading data from file server URLs
-     * @param {number} options.maxRetries - Maximum retry attempts for fetching URL (default: 5)
-     * @param {number} options.baseDelay - Initial delay for exponential backoff in ms (default: 100)
-     * @param {number} options.maxDelay - Maximum delay for exponential backoff in ms (default: 5000)
-     * 
-     * @returns {Promise<Array>} - List of {dataname, data, type} objects
-     */
-    const {
-        fileserverDownloadHandler = _fetch_with_backoff,
-        maxRetries = 5,
-        baseDelay = 100,
-        maxDelay = 5000
-    } = options;
-    
-    // Parse the JSON envelope
-    const jsonStr = typeof msg.payload === 'string' ? msg.payload : new TextDecoder().decode(msg.payload);
-    const json_data = JSON.parse(jsonStr);
-    
-    log_trace(json_data.correlationId, `Processing received message`);
-    
-    // Process all payloads in the envelope
-    const payloads_list = [];
-    
-    // Get number of payloads
-    const num_payloads = json_data.payloads ? json_data.payloads.length : 0;
-    
-    for (let i = 0; i < num_payloads; i++) {
-        const payload = json_data.payloads[i];
-        const transport = payload.transport;
-        const dataname = payload.dataname;
-        
-        if (transport === "direct") {
-            // Direct transport - payload is in the message
-            log_trace(json_data.correlationId, `Direct transport - decoding payload '${dataname}'`);
-            
-            // Extract base64 payload from the payload
-            const payload_b64 = payload.data;
-            
-            // Decode Base64 payload
-            const payload_bytes = base64ToArrayBuffer(payload_b64);
-            
-            // Deserialize based on type
-            const data_type = payload.type;
-            const data = _deserialize_data(payload_bytes, data_type, json_data.correlationId);
-            
-            payloads_list.push({ dataname, data, type: data_type });
-        } else if (transport === "link") {
-            // Link transport - payload is at URL
-            const url = payload.data;
-            log_trace(json_data.correlationId, `Link transport - fetching '${dataname}' from URL: ${url}`);
-            
-            // Fetch with exponential backoff using the download handler
-            const downloaded_data = await fileserverDownloadHandler(
-                url, maxRetries, baseDelay, maxDelay, json_data.correlationId
-            );
-            
-            // Deserialize based on type
-            const data_type = payload.type;
-            const data = _deserialize_data(downloaded_data, data_type, json_data.correlationId);
-            
-            payloads_list.push({ dataname, data, type: data_type });
-        } else {
-            throw new Error(`Unknown transport type for payload '${dataname}': ${transport}`);
-        }
-    }
-    
-    return payloads_list;
-}
-
-// Export for Node.js
-if (typeof module !== 'undefined' && module.exports) {
-    module.exports = {
-        MessageEnvelope,
-        MessagePayload,
-        smartsend,
-        smartreceive,
-        _serialize_data,
-        _deserialize_data,
-        _fetch_with_backoff,
-        _upload_to_fileserver,
-        DEFAULT_SIZE_THRESHOLD,
-        DEFAULT_NATS_URL,
-        DEFAULT_FILESERVER_URL,
-        uuid4,
-        log_trace
-    };
-}
-
-// Export for browser
-if (typeof window !== 'undefined') {
-    window.NATSBridge = {
-        MessageEnvelope,
-        MessagePayload,
-        smartsend,
-        smartreceive,
-        _serialize_data,
-        _deserialize_data,
-        _fetch_with_backoff,
-        _upload_to_fileserver,
-        DEFAULT_SIZE_THRESHOLD,
-        DEFAULT_NATS_URL,
-        DEFAULT_FILESERVER_URL,
-        uuid4,
-        log_trace
-    };
-}

src/README.md

@@ -1,212 +0,0 @@
-# NATSBridge for Micropython
-
-A high-performance, bi-directional data bridge for Micropython devices using NATS (Core & JetStream), implementing the Claim-Check pattern for large payloads.
-
-## Overview
-
-This module provides functionality for sending and receiving data over NATS with automatic transport selection based on payload size:
-
-- **Direct Transport**: Payloads < 1MB are sent directly via NATS (Base64 encoded)
-- **Link Transport**: Payloads >= 1MB are uploaded to an HTTP file server and referenced via URL
-
-## Features
-
-- ✅ Bi-directional NATS communication
-- ✅ Multi-payload support (mixed content in single message)
-- ✅ Automatic transport selection based on payload size
-- ✅ File server integration for large payloads
-- ✅ Exponential backoff for URL fetching
-- ✅ Correlation ID tracking
-- ✅ Reply-to support for request-response pattern
-
-## Supported Payload Types
-
-| Type | Description |
-|------|-------------|
-| `text` | Plain text strings |
-| `dictionary` | JSON-serializable dictionaries |
-| `table` | Tabular data (Arrow IPC format) |
-| `image` | Image data (PNG, JPG bytes) |
-| `audio` | Audio data (WAV, MP3 bytes) |
-| `video` | Video data (MP4, AVI bytes) |
-| `binary` | Generic binary data |
-
-## Installation
-
-1. Copy `nats_bridge.py` to your Micropython device
-2. Ensure you have the following dependencies:
-   - `urequests` for HTTP requests
-   - `ubinascii` for base64 encoding
-   - `ujson` for JSON handling
-   - `usocket` for networking
-
-## Usage
-
-### Basic Text Message
-
-```python
-from nats_bridge import smartsend, smartreceive
-
-# Sender
-data = [("message", "Hello World", "text")]
-env = smartsend("/chat/room1", data, nats_url="nats://localhost:4222")
-
-# Receiver
-payloads = smartreceive(msg)
-for dataname, data, type in payloads:
-    print("Received {}: {}".format(dataname, data))
-```
-
-### Sending JSON Configuration
-
-```python
-from nats_bridge import smartsend
-
-config = {
-    "wifi_ssid": "MyNetwork",
-    "wifi_password": "password123",
-    "update_interval": 60
-}
-
-data = [("config", config, "dictionary")]
-env = smartsend("/device/config", data, nats_url="nats://localhost:4222")
-```
-
-### Mixed Content (Chat with Text + Image)
-
-```python
-from nats_bridge import smartsend
-
-image_data = b"\x89PNG..."  # PNG bytes
-
-data = [
-    ("message_text", "Hello with image!", "text"),
-    ("user_avatar", image_data, "binary")
-]
-
-env = smartsend("/chat/mixed", data, nats_url="nats://localhost:4222")
-```
-
-### Request-Response Pattern
-
-```python
-from nats_bridge import smartsend
-
-# Send command with reply-to
-data = [("command", {"action": "read_sensor"}, "dictionary")]
-env = smartsend(
-    "/device/command",
-    data,
-    nats_url="nats://localhost:4222",
-    reply_to="/device/response",
-    reply_to_msg_id="cmd-001"
-)
-```
-
-### Large Payloads (File Server)
-
-```python
-from nats_bridge import smartsend
-
-# Large data (> 1MB)
-large_data = b"A" * 2000000  # 2MB
-
-env = smartsend(
-    "/data/large",
-    [("large_file", large_data, "binary")],
-    nats_url="nats://localhost:4222",
-    fileserver_url="http://localhost:8080",
-    size_threshold=1000000  # 1MB threshold
-)
-```
-
-## API Reference
-
-### `smartsend(subject, data, ...)`
-
-Send data via NATS with automatic transport selection.
-
-**Arguments:**
-- `subject` (str): NATS subject to publish to
-- `data` (list): List of `(dataname, data, type)` tuples
-- `nats_url` (str): NATS server URL (default: `nats://localhost:4222`)
-- `fileserver_url` (str): HTTP file server URL (default: `http://localhost:8080`)
-- `size_threshold` (int): Threshold in bytes (default: 1,000,000)
-- `correlation_id` (str): Optional correlation ID for tracing
-- `msg_purpose` (str): Message purpose (default: `"chat"`)
-- `sender_name` (str): Sender name (default: `"NATSBridge"`)
-- `receiver_name` (str): Receiver name (default: `""`)
-- `receiver_id` (str): Receiver ID (default: `""`)
-- `reply_to` (str): Reply topic (default: `""`)
-- `reply_to_msg_id` (str): Reply message ID (default: `""`)
-
-**Returns:** `MessageEnvelope` object
-
-### `smartreceive(msg, ...)`
-
-Receive and process NATS messages.
-
-**Arguments:**
-- `msg`: NATS message (dict or JSON string)
-- `fileserver_download_handler` (function): Function to fetch data from URLs
-- `max_retries` (int): Maximum retry attempts (default: 5)
-- `base_delay` (int): Initial delay in ms (default: 100)
-- `max_delay` (int): Maximum delay in ms (default: 5000)
-
-**Returns:** List of `(dataname, data, type)` tuples
-
-### `MessageEnvelope`
-
-Represents a complete NATS message envelope.
-
-**Attributes:**
-- `correlation_id`: Unique identifier for tracing
-- `msg_id`: Unique message identifier
-- `timestamp`: Message publication timestamp
-- `send_to`: NATS subject
-- `msg_purpose`: Message purpose
-- `sender_name`: Sender name
-- `sender_id`: Sender UUID
-- `receiver_name`: Receiver name
-- `receiver_id`: Receiver UUID
-- `reply_to`: Reply topic
-- `reply_to_msg_id`: Reply message ID
-- `broker_url`: NATS broker URL
-- `metadata`: Message-level metadata
-- `payloads`: List of MessagePayload objects
-
-### `MessagePayload`
-
-Represents a single payload within a message envelope.
-
-**Attributes:**
-- `id`: Unique payload identifier
-- `dataname`: Name of the payload
-- `type`: Payload type ("text", "dictionary", etc.)
-- `transport`: Transport method ("direct" or "link")
-- `encoding`: Encoding method ("none", "base64", etc.)
-- `size`: Payload size in bytes
-- `data`: Payload data (bytes for direct, URL for link)
-- `metadata`: Payload-level metadata
-
-## Examples
-
-See `examples/micropython_example.py` for more detailed examples.
-
-## Testing
-
-Run the test suite:
-
-```bash
-python test/test_micropython_basic.py
-```
-
-## Requirements
-
-- Micropython with networking support
-- NATS server (nats.io)
-- HTTP file server (optional, for large payloads)
-
-## License
-
-MIT

src/nats_bridge.py

@@ -1,664 +0,0 @@
-"""
-Micropython NATS Bridge - Bi-Directional Data Bridge for Micropython
-
-This module provides functionality for sending and receiving data over NATS
-using the Claim-Check pattern for large payloads.
-
-Supported types: "text", "dictionary", "table", "image", "audio", "video", "binary"
-"""
-
-import json
-import random
-import time
-import usocket
-import uselect
-import ustruct
-import uuid
-
-try:
-    import ussl
-    HAS_SSL = True
-except ImportError:
-    HAS_SSL = False
-
-# Constants
-DEFAULT_SIZE_THRESHOLD = 1000000  # 1MB - threshold for switching from direct to link transport
-DEFAULT_NATS_URL = "nats://localhost:4222"
-DEFAULT_FILESERVER_URL = "http://localhost:8080"
-
-# ============================================= 100 ============================================== #
-
-
-class MessagePayload:
-    """Internal message payload structure representing a single payload within a NATS message envelope."""
-    
-    def __init__(self, data, msg_type, id="", dataname="", transport="direct", 
-                 encoding="none", size=0, metadata=None):
-        """
-        Initialize a MessagePayload.
-        
-        Args:
-            data: Payload data (bytes for direct, URL string for link)
-            msg_type: Payload type ("text", "dictionary", "table", "image", "audio", "video", "binary")
-            id: Unique identifier for this payload (auto-generated if empty)
-            dataname: Name of the payload (auto-generated UUID if empty)
-            transport: Transport method ("direct" or "link")
-            encoding: Encoding method ("none", "json", "base64", "arrow-ipc")
-            size: Size of the payload in bytes
-            metadata: Optional metadata dictionary
-        """
-        self.id = id if id else self._generate_uuid()
-        self.dataname = dataname if dataname else self._generate_uuid()
-        self.type = msg_type
-        self.transport = transport
-        self.encoding = encoding
-        self.size = size
-        self.data = data
-        self.metadata = metadata if metadata else {}
-    
-    def _generate_uuid(self):
-        """Generate a UUID string."""
-        return str(uuid.uuid4())
-    
-    def to_dict(self):
-        """Convert payload to dictionary for JSON serialization."""
-        payload_dict = {
-            "id": self.id,
-            "dataname": self.dataname,
-            "type": self.type,
-            "transport": self.transport,
-            "encoding": self.encoding,
-            "size": self.size,
-        }
-        
-        # Include data based on transport type
-        if self.transport == "direct" and self.data is not None:
-            if self.encoding == "base64" or self.encoding == "json":
-                payload_dict["data"] = self.data
-            else:
-                # For other encodings, use base64
-                payload_dict["data"] = self._to_base64(self.data)
-        elif self.transport == "link" and self.data is not None:
-            # For link transport, data is a URL string
-            payload_dict["data"] = self.data
-        
-        if self.metadata:
-            payload_dict["metadata"] = self.metadata
-        
-        return payload_dict
-    
-    def _to_base64(self, data):
-        """Convert bytes to base64 string."""
-        if isinstance(data, bytes):
-            # Simple base64 encoding without library
-            import ubinascii
-            return ubinascii.b2a_base64(data).decode('utf-8').strip()
-        return data
-    
-    def _from_base64(self, data):
-        """Convert base64 string to bytes."""
-        import ubinascii
-        return ubinascii.a2b_base64(data)
-
-
-class MessageEnvelope:
-    """Internal message envelope structure containing multiple payloads with metadata."""
-    
-    def __init__(self, send_to, payloads, correlation_id="", msg_id="", timestamp="",
-                 msg_purpose="", sender_name="", sender_id="", receiver_name="",
-                 receiver_id="", reply_to="", reply_to_msg_id="", broker_url=DEFAULT_NATS_URL,
-                 metadata=None):
-        """
-        Initialize a MessageEnvelope.
-        
-        Args:
-            send_to: NATS subject/topic to publish the message to
-            payloads: List of MessagePayload objects
-            correlation_id: Unique identifier to track messages (auto-generated if empty)
-            msg_id: Unique message identifier (auto-generated if empty)
-            timestamp: Message publication timestamp
-            msg_purpose: Purpose of the message ("ACK", "NACK", "updateStatus", "shutdown", "chat", etc.)
-            sender_name: Name of the sender
-            sender_id: UUID of the sender
-            receiver_name: Name of the receiver (empty means broadcast)
-            receiver_id: UUID of the receiver (empty means broadcast)
-            reply_to: Topic where receiver should reply
-            reply_to_msg_id: Message ID this message is replying to
-            broker_url: NATS broker URL
-            metadata: Optional message-level metadata
-        """
-        self.correlation_id = correlation_id if correlation_id else self._generate_uuid()
-        self.msg_id = msg_id if msg_id else self._generate_uuid()
-        self.timestamp = timestamp if timestamp else self._get_timestamp()
-        self.send_to = send_to
-        self.msg_purpose = msg_purpose
-        self.sender_name = sender_name
-        self.sender_id = sender_id if sender_id else self._generate_uuid()
-        self.receiver_name = receiver_name
-        self.receiver_id = receiver_id if receiver_id else self._generate_uuid()
-        self.reply_to = reply_to
-        self.reply_to_msg_id = reply_to_msg_id
-        self.broker_url = broker_url
-        self.metadata = metadata if metadata else {}
-        self.payloads = payloads
-    
-    def _generate_uuid(self):
-        """Generate a UUID string."""
-        return str(uuid.uuid4())
-    
-    def _get_timestamp(self):
-        """Get current timestamp in ISO format."""
-        # Simplified timestamp - Micropython may not have full datetime
-        return "2026-02-21T" + time.strftime("%H:%M:%S", time.localtime())
-    
-    def to_json(self):
-        """Convert envelope to JSON string."""
-        obj = {
-            "correlationId": self.correlation_id,
-            "msgId": self.msg_id,
-            "timestamp": self.timestamp,
-            "sendTo": self.send_to,
-            "msgPurpose": self.msg_purpose,
-            "senderName": self.sender_name,
-            "senderId": self.sender_id,
-            "receiverName": self.receiver_name,
-            "receiverId": self.receiver_id,
-            "replyTo": self.reply_to,
-            "replyToMsgId": self.reply_to_msg_id,
-            "brokerURL": self.broker_url
-        }
-        
-        # Include metadata if not empty
-        if self.metadata:
-            obj["metadata"] = self.metadata
-        
-        # Convert payloads to JSON array
-        if self.payloads:
-            payloads_json = []
-            for payload in self.payloads:
-                payloads_json.append(payload.to_dict())
-            obj["payloads"] = payloads_json
-        
-        return json.dumps(obj)
-
-
-def log_trace(correlation_id, message):
-    """Log a trace message with correlation ID and timestamp."""
-    timestamp = time.strftime("%Y-%m-%dT%H:%M:%S", time.localtime())
-    print("[{}] [Correlation: {}] {}".format(timestamp, correlation_id, message))
-
-
-def _serialize_data(data, msg_type):
-    """Serialize data according to specified format.
-    
-    Args:
-        data: Data to serialize
-        msg_type: Target format ("text", "dictionary", "table", "image", "audio", "video", "binary")
-    
-    Returns:
-        bytes: Binary representation of the serialized data
-    """
-    if msg_type == "text":
-        if isinstance(data, str):
-            return data.encode('utf-8')
-        else:
-            raise ValueError("Text data must be a string")
-    
-    elif msg_type == "dictionary":
-        if isinstance(data, dict):
-            json_str = json.dumps(data)
-            return json_str.encode('utf-8')
-        else:
-            raise ValueError("Dictionary data must be a dict")
-    
-    elif msg_type in ("image", "audio", "video", "binary"):
-        if isinstance(data, bytes):
-            return data
-        else:
-            raise ValueError("{} data must be bytes".format(msg_type.capitalize()))
-    
-    else:
-        raise ValueError("Unknown type: {}".format(msg_type))
-
-
-def _deserialize_data(data_bytes, msg_type, correlation_id):
-    """Deserialize bytes to data based on type.
-    
-    Args:
-        data_bytes: Serialized data as bytes
-        msg_type: Data type ("text", "dictionary", "table", "image", "audio", "video", "binary")
-        correlation_id: Correlation ID for logging
-    
-    Returns:
-        Deserialized data
-    """
-    if msg_type == "text":
-        return data_bytes.decode('utf-8')
-    
-    elif msg_type == "dictionary":
-        json_str = data_bytes.decode('utf-8')
-        return json.loads(json_str)
-    
-    elif msg_type in ("image", "audio", "video", "binary"):
-        return data_bytes
-    
-    else:
-        raise ValueError("Unknown type: {}".format(msg_type))
-
-
-class NATSConnection:
-    """Simple NATS connection for Micropython."""
-    
-    def __init__(self, url=DEFAULT_NATS_URL):
-        """Initialize NATS connection.
-        
-        Args:
-            url: NATS server URL (e.g., "nats://localhost:4222")
-        """
-        self.url = url
-        self.host = "localhost"
-        self.port = 4222
-        self.conn = None
-        self._parse_url(url)
-    
-    def _parse_url(self, url):
-        """Parse NATS URL to extract host and port."""
-        if url.startswith("nats://"):
-            url = url[7:]
-        elif url.startswith("tls://"):
-            url = url[6:]
-        
-        if ":" in url:
-            self.host, port_str = url.split(":")
-            self.port = int(port_str)
-        else:
-            self.host = url
-    
-    def connect(self):
-        """Connect to NATS server."""
-        addr = usocket.getaddrinfo(self.host, self.port)[0][-1]
-        self.conn = usocket.socket()
-        self.conn.connect(addr)
-        log_trace("", "Connected to NATS server at {}:{}".format(self.host, self.port))
-    
-    def publish(self, subject, message):
-        """Publish a message to a NATS subject.
-        
-        Args:
-            subject: NATS subject to publish to
-            message: Message to publish (should be bytes or string)
-        """
-        if isinstance(message, str):
-            message = message.encode('utf-8')
-        
-        # Simple NATS protocol implementation
-        msg = "PUB {} {}\r\n".format(subject, len(message))
-        msg = msg.encode('utf-8') + message + b"\r\n"
-        self.conn.send(msg)
-        log_trace("", "Message published to {}".format(subject))
-    
-    def subscribe(self, subject, callback):
-        """Subscribe to a NATS subject.
-        
-        Args:
-            subject: NATS subject to subscribe to
-            callback: Callback function to handle incoming messages
-        """
-        log_trace("", "Subscribed to {}".format(subject))
-        # Simplified subscription - in a real implementation, you'd handle SUB/PUB messages
-        # For Micropython, we'll use a simple polling approach
-        self.subscribed_subject = subject
-        self.subscription_callback = callback
-    
-    def wait_message(self, timeout=1000):
-        """Wait for incoming message.
-        
-        Args:
-            timeout: Timeout in milliseconds
-            
-        Returns:
-            NATS message object or None if timeout
-        """
-        # Simplified message reading
-        # In a real implementation, you'd read from the socket
-        # For now, this is a placeholder
-        return None
-    
-    def close(self):
-        """Close the NATS connection."""
-        if self.conn:
-            self.conn.close()
-            self.conn = None
-            log_trace("", "NATS connection closed")
-
-
-def _fetch_with_backoff(url, max_retries=5, base_delay=100, max_delay=5000, correlation_id=""):
-    """Fetch data from URL with exponential backoff.
-    
-    Args:
-        url: URL to fetch from
-        max_retries: Maximum number of retry attempts
-        base_delay: Initial delay in milliseconds
-        max_delay: Maximum delay in milliseconds
-        correlation_id: Correlation ID for logging
-    
-    Returns:
-        bytes: Fetched data
-    
-    Raises:
-        Exception: If all retry attempts fail
-    """
-    delay = base_delay
-    for attempt in range(1, max_retries + 1):
-        try:
-            # Simple HTTP GET request
-            # This is a simplified implementation
-            # For production, you'd want a proper HTTP client
-            import urequests
-            response = urequests.get(url)
-            if response.status_code == 200:
-                log_trace(correlation_id, "Successfully fetched data from {} on attempt {}".format(url, attempt))
-                return response.content
-            else:
-                raise Exception("Failed to fetch: {}".format(response.status_code))
-        except Exception as e:
-            log_trace(correlation_id, "Attempt {} failed: {}".format(attempt, str(e)))
-            if attempt < max_retries:
-                time.sleep(delay / 1000.0)
-                delay = min(delay * 2, max_delay)
-
-
-def plik_oneshot_upload(file_server_url, filename, data):
-    """Upload a single file to a plik server using one-shot mode.
-    
-    Args:
-        file_server_url: Base URL of the plik server
-        filename: Name of the file being uploaded
-        data: Raw byte data of the file content
-    
-    Returns:
-        dict: Dictionary with keys:
-            - "status": HTTP server response status
-            - "uploadid": ID of the one-shot upload session
-            - "fileid": ID of the uploaded file within the session
-            - "url": Full URL to download the uploaded file
-    """
-    import urequests
-    import json
-    
-    # Get upload ID
-    url_get_upload_id = "{}/upload".format(file_server_url)
-    headers = {"Content-Type": "application/json"}
-    body = json.dumps({"OneShot": True})
-    
-    response = urequests.post(url_get_upload_id, headers=headers, data=body)
-    response_json = json.loads(response.content)
-    
-    uploadid = response_json.get("id")
-    uploadtoken = response_json.get("uploadToken")
-    
-    # Upload file
-    url_upload = "{}/file/{}".format(file_server_url, uploadid)
-    headers = {"X-UploadToken": uploadtoken}
-    
-    # For Micropython, we need to construct the multipart form data manually
-    # This is a simplified approach
-    boundary = "----WebKitFormBoundary{}".format(uuid.uuid4().hex[:16])
-    
-    # Create multipart body
-    part1 = "--{}\r\n".format(boundary)
-    part1 += "Content-Disposition: form-data; name=\"file\"; filename=\"{}\"\r\n".format(filename)
-    part1 += "Content-Type: application/octet-stream\r\n\r\n"
-    part1_bytes = part1.encode('utf-8')
-    
-    part2 = "\r\n--{}--".format(boundary)
-    part2_bytes = part2.encode('utf-8')
-    
-    # Combine all parts
-    full_body = part1_bytes + data + part2_bytes
-    
-    # Set content type with boundary
-    content_type = "multipart/form-data; boundary={}".format(boundary)
-    
-    response = urequests.post(url_upload, headers={"Content-Type": content_type}, data=full_body)
-    response_json = json.loads(response.content)
-    
-    fileid = response_json.get("id")
-    url = "{}/file/{}/{}".format(file_server_url, uploadid, filename)
-    
-    return {
-        "status": response.status_code,
-        "uploadid": uploadid,
-        "fileid": fileid,
-        "url": url
-    }
-
-
-def smartsend(subject, data, nats_url=DEFAULT_NATS_URL, fileserver_url=DEFAULT_FILESERVER_URL,
-              fileserver_upload_handler=plik_oneshot_upload, size_threshold=DEFAULT_SIZE_THRESHOLD,
-              correlation_id=None, msg_purpose="chat", sender_name="NATSBridge",
-              receiver_name="", receiver_id="", reply_to="", reply_to_msg_id=""):
-    """Send data either directly via NATS or via a fileserver URL, depending on payload size.
-    
-    This function intelligently routes data delivery based on payload size relative to a threshold.
-    If the serialized payload is smaller than `size_threshold`, it encodes the data as Base64 and 
-    publishes directly over NATS. Otherwise, it uploads the data to a fileserver and publishes 
-    only the download URL over NATS.
-    
-    Args:
-        subject: NATS subject to publish the message to
-        data: List of (dataname, data, type) tuples to send
-        nats_url: URL of the NATS server
-        fileserver_url: URL of the HTTP file server
-        fileserver_upload_handler: Function to handle fileserver uploads
-        size_threshold: Threshold in bytes separating direct vs link transport
-        correlation_id: Optional correlation ID for tracing
-        msg_purpose: Purpose of the message
-        sender_name: Name of the sender
-        receiver_name: Name of the receiver
-        receiver_id: UUID of the receiver
-        reply_to: Topic to reply to
-        reply_to_msg_id: Message ID this message is replying to
-    
-    Returns:
-        MessageEnvelope: The envelope object for tracking
-    """
-    # Generate correlation ID if not provided
-    cid = correlation_id if correlation_id else str(uuid.uuid4())
-    
-    log_trace(cid, "Starting smartsend for subject: {}".format(subject))
-    
-    # Generate message metadata
-    msg_id = str(uuid.uuid4())
-    
-    # Process each payload in the list
-    payloads = []
-    
-    for dataname, payload_data, payload_type in data:
-        # Serialize data based on type
-        payload_bytes = _serialize_data(payload_data, payload_type)
-        
-        payload_size = len(payload_bytes)
-        log_trace(cid, "Serialized payload '{}' (type: {}) size: {} bytes".format(
-            dataname, payload_type, payload_size))
-        
-        # Decision: Direct vs Link
-        if payload_size < size_threshold:
-            # Direct path - Base64 encode and send via NATS
-            payload_b64 = _serialize_data(payload_bytes, "binary")  # Already bytes
-            # Convert to base64 string for JSON
-            import ubinascii
-            payload_b64_str = ubinascii.b2a_base64(payload_bytes).decode('utf-8').strip()
-            
-            log_trace(cid, "Using direct transport for {} bytes".format(payload_size))
-            
-            # Create MessagePayload for direct transport
-            payload = MessagePayload(
-                payload_b64_str,
-                payload_type,
-                id=str(uuid.uuid4()),
-                dataname=dataname,
-                transport="direct",
-                encoding="base64",
-                size=payload_size,
-                metadata={"payload_bytes": payload_size}
-            )
-            payloads.append(payload)
-        else:
-            # Link path - Upload to HTTP server, send URL via NATS
-            log_trace(cid, "Using link transport, uploading to fileserver")
-            
-            # Upload to HTTP server
-            response = fileserver_upload_handler(fileserver_url, dataname, payload_bytes)
-            
-            if response["status"] != 200:
-                raise Exception("Failed to upload data to fileserver: {}".format(response["status"]))
-            
-            url = response["url"]
-            log_trace(cid, "Uploaded to URL: {}".format(url))
-            
-            # Create MessagePayload for link transport
-            payload = MessagePayload(
-                url,
-                payload_type,
-                id=str(uuid.uuid4()),
-                dataname=dataname,
-                transport="link",
-                encoding="none",
-                size=payload_size,
-                metadata={}
-            )
-            payloads.append(payload)
-    
-    # Create MessageEnvelope with all payloads
-    env = MessageEnvelope(
-        subject,
-        payloads,
-        correlation_id=cid,
-        msg_id=msg_id,
-        msg_purpose=msg_purpose,
-        sender_name=sender_name,
-        sender_id=str(uuid.uuid4()),
-        receiver_name=receiver_name,
-        receiver_id=receiver_id,
-        reply_to=reply_to,
-        reply_to_msg_id=reply_to_msg_id,
-        broker_url=nats_url,
-        metadata={}
-    )
-    
-    msg_json = env.to_json()
-    
-    # Publish to NATS
-    nats_conn = NATSConnection(nats_url)
-    nats_conn.connect()
-    nats_conn.publish(subject, msg_json)
-    nats_conn.close()
-    
-    return env
-
-
-def smartreceive(msg, fileserver_download_handler=_fetch_with_backoff, max_retries=5,
-                 base_delay=100, max_delay=5000):
-    """Receive and process messages from NATS.
-    
-    This function processes incoming NATS messages, handling both direct transport
-    (base64 decoded payloads) and link transport (URL-based payloads).
-    
-    Args:
-        msg: NATS message to process (dict with payload data)
-        fileserver_download_handler: Function to handle downloading data from file server URLs
-        max_retries: Maximum retry attempts for fetching URL
-        base_delay: Initial delay for exponential backoff in ms
-        max_delay: Maximum delay for exponential backoff in ms
-    
-    Returns:
-        list: List of (dataname, data, type) tuples
-    """
-    # Parse the JSON envelope
-    json_data = msg if isinstance(msg, dict) else json.loads(msg)
-    log_trace(json_data.get("correlationId", ""), "Processing received message")
-    
-    # Process all payloads in the envelope
-    payloads_list = []
-    
-    # Get number of payloads
-    num_payloads = len(json_data.get("payloads", []))
-    
-    for i in range(num_payloads):
-        payload = json_data["payloads"][i]
-        transport = payload.get("transport", "")
-        dataname = payload.get("dataname", "")
-        
-        if transport == "direct":
-            log_trace(json_data.get("correlationId", ""), 
-                     "Direct transport - decoding payload '{}'".format(dataname))
-            
-            # Extract base64 payload from the payload
-            payload_b64 = payload.get("data", "")
-            
-            # Decode Base64 payload
-            import ubinascii
-            payload_bytes = ubinascii.a2b_base64(payload_b64.encode('utf-8'))
-            
-            # Deserialize based on type
-            data_type = payload.get("type", "")
-            data = _deserialize_data(payload_bytes, data_type, json_data.get("correlationId", ""))
-            
-            payloads_list.append((dataname, data, data_type))
-            
-        elif transport == "link":
-            # Extract download URL from the payload
-            url = payload.get("data", "")
-            log_trace(json_data.get("correlationId", ""),
-                     "Link transport - fetching '{}' from URL: {}".format(dataname, url))
-            
-            # Fetch with exponential backoff
-            downloaded_data = fileserver_download_handler(
-                url, max_retries, base_delay, max_delay, json_data.get("correlationId", "")
-            )
-            
-            # Deserialize based on type
-            data_type = payload.get("type", "")
-            data = _deserialize_data(downloaded_data, data_type, json_data.get("correlationId", ""))
-            
-            payloads_list.append((dataname, data, data_type))
-            
-        else:
-            raise ValueError("Unknown transport type for payload '{}': {}".format(dataname, transport))
-    
-    return payloads_list
-
-
-# Utility functions
-def generate_uuid():
-    """Generate a UUID string."""
-    return str(uuid.uuid4())
-
-
-def get_timestamp():
-    """Get current timestamp in ISO format."""
-    return time.strftime("%Y-%m-%dT%H:%M:%S", time.localtime())
-
-
-# Example usage
-if __name__ == "__main__":
-    print("NATSBridge for Micropython")
-    print("=========================")
-    print("This module provides:")
-    print("  - MessageEnvelope: Message envelope structure")
-    print("  - MessagePayload: Payload structure")
-    print("  - smartsend: Send data via NATS with automatic transport selection")
-    print("  - smartreceive: Receive and process messages from NATS")
-    print("  - plik_oneshot_upload: Upload files to HTTP file server")
-    print("  - _fetch_with_backoff: Fetch data from URLs with retry logic")
-    print()
-    print("Usage:")
-    print("  from nats_bridge import smartsend, smartreceive")
-    print("  data = [(\"message\", \"Hello World\", \"text\")]")
-    print("  env = smartsend(\"my.subject\", data)")
-    print()
-    print("  # On receiver:")
-    print("  payloads = smartreceive(msg)")
-    print("  for dataname, data, type in payloads:")
-    print("      print(f\"Received {dataname} of type {type}: {data}\")")

src/natsbridge.py

@@ -0,0 +1,843 @@
+"""
+NATSBridge - Cross-Platform Bi-Directional Data Bridge
+Python Desktop Implementation
+
+This module provides functionality for sending and receiving data across network boundaries
+using NATS as the message bus, with support for both direct payload transport and
+URL-based transport for larger payloads.
+
+@package natsbridge
+"""
+
+import asyncio
+import base64
+import json
+import uuid
+from datetime import datetime
+from typing import Any, Callable, Dict, List, Tuple, Union
+import aiohttp
+
+try:
+    import pyarrow as arrow
+    import pyarrow.ipc as ipc
+    ARROW_AVAILABLE = True
+except ImportError:
+    ARROW_AVAILABLE = False
+
+try:
+    import nats
+    from nats.aio.client import Client as NATSClient
+    NATS_AVAILABLE = True
+except ImportError:
+    NATS_AVAILABLE = False
+
+# ---------------------------------------------- Constants ---------------------------------------------- #
+
+"""
+Default size threshold for switching from direct to link transport (0.5MB)
+"""
+DEFAULT_SIZE_THRESHOLD = 500_000
+
+"""
+Default NATS server URL
+"""
+DEFAULT_BROKER_URL = "nats://localhost:4222"
+
+"""
+Default HTTP file server URL for link transport
+"""
+DEFAULT_FILESERVER_URL = "http://localhost:8080"
+
+
+# ---------------------------------------------- Utility Functions ---------------------------------------------- #
+
+def log_trace(correlation_id: str, message: str) -> None:
+    """
+    Log a trace message with correlation ID and timestamp.
+    
+    Args:
+        correlation_id: Correlation ID for tracing
+        message: Message content to log
+    """
+    timestamp = datetime.utcnow().isoformat() + 'Z'
+    print(f"[{timestamp}] [Correlation: {correlation_id}] {message}")
+
+
+# ---------------------------------------------- Serialization Functions ---------------------------------------------- #
+
+def _serialize_data(data: Any, payload_type: str) -> bytes:
+    """
+    Serialize data according to specified format.
+    
+    Args:
+        data: Data to serialize (string for "text", JSON-serializable for "dictionary",
+              table-like for "arrowtable"/"jsontable", binary for "image", "audio", "video", "binary")
+        payload_type: Target format: "text", "dictionary", "arrowtable", "jsontable",
+                      "image", "audio", "video", "binary"
+    
+    Returns:
+        Binary representation of the serialized data
+    
+    Raises:
+        Error: If payload_type is not one of the supported types
+        Error: If payload_type is "image", "audio", or "video" but data is not bytes
+        Error: If payload_type is "arrowtable" but data is not a pandas DataFrame or pyarrow Table
+        Error: If payload_type is "jsontable" but data is not a list of dicts
+    """
+    if payload_type == 'text':
+        if isinstance(data, str):
+            return data.encode('utf-8')
+        else:
+            raise ValueError('Text data must be a string')
+    elif payload_type == 'dictionary':
+        json_str = json.dumps(data)
+        return json_str.encode('utf-8')
+    elif payload_type == 'arrowtable':
+        if not ARROW_AVAILABLE:
+            raise RuntimeError('pyarrow not available for arrowtable serialization')
+        
+        import io
+        buf = io.BytesIO()
+        
+        import pandas as pd
+        if isinstance(data, pd.DataFrame):
+            table = arrow.Table.from_pandas(data)
+            sink = ipc.new_file(buf, table.schema)
+            ipc.write_table(table, sink)
+            sink.close()
+            return buf.getvalue()
+        elif isinstance(data, arrow.Table):
+            sink = ipc.new_file(buf, data.schema)
+            ipc.write_table(data, sink)
+            sink.close()
+            return buf.getvalue()
+        else:
+            raise ValueError('Arrow table data must be a pandas DataFrame or pyarrow Table')
+    elif payload_type == 'jsontable':
+        # Serialize list of dicts to JSON format
+        if isinstance(data, list) and all(isinstance(row, dict) for row in data):
+            json_str = json.dumps(data)
+            return json_str.encode('utf-8')
+        else:
+            raise ValueError('JSON table data must be a list of dicts')
+    elif payload_type == 'image':
+        if isinstance(data, (bytes, bytearray)):
+            return bytes(data)
+        else:
+            raise ValueError('Image data must be bytes')
+    elif payload_type == 'audio':
+        if isinstance(data, (bytes, bytearray)):
+            return bytes(data)
+        else:
+            raise ValueError('Audio data must be bytes')
+    elif payload_type == 'video':
+        if isinstance(data, (bytes, bytearray)):
+            return bytes(data)
+        else:
+            raise ValueError('Video data must be bytes')
+    elif payload_type == 'binary':
+        if isinstance(data, (bytes, bytearray)):
+            return bytes(data)
+        else:
+            raise ValueError('Binary data must be bytes')
+    else:
+        raise ValueError(f'Unknown payload_type: {payload_type}')
+
+
+def _deserialize_data(data: bytes, payload_type: str, correlation_id: str) -> Any:
+    """
+    Deserialize bytes to data based on type.
+    
+    Args:
+        data: Serialized data as bytes
+        payload_type: Data type ("text", "dictionary", "arrowtable", "jsontable",
+                      "image", "audio", "video", "binary")
+        correlation_id: Correlation ID for logging
+    
+    Returns:
+        Deserialized data (String for "text", DataFrame for "arrowtable",
+        Vector{Dict} for "jsontable"/"dictionary", bytes for "image", "audio", "video", "binary")
+    
+    Raises:
+        Error: If payload_type is not one of the supported types
+    """
+    if payload_type == 'text':
+        return data.decode('utf-8')
+    elif payload_type == 'dictionary':
+        json_str = data.decode('utf-8')
+        return json.loads(json_str)
+    elif payload_type == 'arrowtable':
+        if not ARROW_AVAILABLE:
+            raise RuntimeError('pyarrow not available for arrowtable deserialization')
+        
+        import io
+        buf = io.BytesIO(data)
+        reader = ipc.open_file(buf)
+        return reader.read_all().to_pandas()
+    elif payload_type == 'jsontable':
+        # Deserialize JSON to list of dicts
+        json_str = data.decode('utf-8')
+        return json.loads(json_str)
+    elif payload_type == 'image':
+        return data
+    elif payload_type == 'audio':
+        return data
+    elif payload_type == 'video':
+        return data
+    elif payload_type == 'binary':
+        return data
+    else:
+        raise ValueError(f'Unknown payload_type: {payload_type}')
+
+
+# ---------------------------------------------- File Server Handlers ---------------------------------------------- #
+
+async def plik_oneshot_upload(
+    file_server_url: str,
+    dataname: str,
+    data: bytes
+) -> Dict[str, Any]:
+    """
+    Upload data to plik server in one-shot mode.
+    
+    This function uploads a raw byte array to a plik server in one-shot mode (no upload session).
+    It first creates a one-shot upload session by sending a POST request with {"OneShot": true},
+    retrieves an upload ID and token, then uploads the file data as multipart form data using the token.
+    
+    Args:
+        file_server_url: Base URL of the plik server (e.g., "http://localhost:8080")
+        dataname: Name of the file being uploaded
+        data: Raw byte data of the file content
+    
+    Returns:
+        Dict with keys:
+            - "status": HTTP server response status
+            - "uploadid": ID of the one-shot upload session
+            - "fileid": ID of the uploaded file within the session
+            - "url": Full URL to download the uploaded file
+    
+    Example:
+        >>> fileserver_url = "http://localhost:8080"
+        >>> dataname = "test.txt"
+        >>> data = b"hello world"
+        >>> result = await plik_oneshot_upload(file_server_url, dataname, data)
+        >>> result["status"], result["uploadid"], result["fileid"], result["url"]
+    """
+    async with aiohttp.ClientSession() as session:
+        # Get upload id
+        url_getUploadID = f"{file_server_url}/upload"
+        headers = {'Content-Type': 'application/json'}
+        body = json.dumps({"OneShot": True})
+        
+        async with session.post(url_getUploadID, headers=headers, data=body) as response:
+            response_json = await response.json()
+            uploadid = response_json['id']
+            uploadtoken = response_json['uploadToken']
+
+        # Upload file
+        url_upload = f"{file_server_url}/file/{uploadid}"
+        headers = {'X-UploadToken': uploadtoken}
+        
+        form = aiohttp.FormData()
+        form.add_field('file', data, filename=dataname, content_type='application/octet-stream')
+        
+        async with session.post(url_upload, headers=headers, data=form) as upload_response:
+            upload_json = await upload_response.json()
+            fileid = upload_json['id']
+
+    url = f"{file_server_url}/file/{uploadid}/{fileid}/{dataname}"
+
+    return {
+        'status': upload_response.status,
+        'uploadid': uploadid,
+        'fileid': fileid,
+        'url': url
+    }
+
+
+async def fetch_with_backoff(
+    url: str,
+    max_retries: int,
+    base_delay: int,
+    max_delay: int,
+    correlation_id: str
+) -> bytes:
+    """
+    Fetch data from URL with exponential backoff.
+    
+    This internal function retrieves data from a URL with retry logic using
+    exponential backoff to handle transient failures.
+    
+    Args:
+        url: URL to fetch from
+        max_retries: Maximum number of retry attempts
+        base_delay: Initial delay in milliseconds
+        max_delay: Maximum delay in milliseconds
+        correlation_id: Correlation ID for logging
+    
+    Returns:
+        Fetched data as bytes
+    
+    Raises:
+        Error: If all retry attempts fail
+    
+    Example:
+        >>> data = await fetch_with_backoff("http://example.com/file.zip", 5, 100, 5000, "correlation123")
+    """
+    delay = base_delay
+    
+    for attempt in range(1, max_retries + 1):
+        try:
+            async with aiohttp.ClientSession() as session:
+                async with session.get(url) as response:
+                    if response.status == 200:
+                        log_trace(correlation_id, f"Successfully fetched data from {url} on attempt {attempt}")
+                        return await response.read()
+                    else:
+                        raise Exception(f"Failed to fetch: {response.status}")
+        except Exception as e:
+            log_trace(correlation_id, f"Attempt {attempt} failed: {type(e).__name__}")
+            
+            if attempt < max_retries:
+                await asyncio.sleep(delay / 1000.0)
+                delay = min(delay * 2, max_delay)
+    
+    raise Exception(f"Failed to fetch data after {max_retries} attempts")
+
+
+# ---------------------------------------------- NATS Client ---------------------------------------------- #
+
+class NATSClient:
+    """NATS client wrapper for connection management."""
+    
+    def __init__(self, url: str = DEFAULT_BROKER_URL):
+        """
+        Create a new NATS client.
+        
+        Args:
+            url: NATS server URL
+        """
+        self.url = url
+        self._client: NATSClient = None
+    
+    async def connect(self) -> NATSClient:
+        """
+        Connect to NATS server.
+        
+        Returns:
+            NATS client instance
+        """
+        if NATS_AVAILABLE:
+            self._client = nats.connect(self.url)
+            await self._client
+        else:
+            raise RuntimeError('nats-py not available')
+        return self._client
+    
+    async def publish(self, subject: str, message: str, correlation_id: str = "") -> None:
+        """
+        Publish message to NATS subject.
+        
+        Args:
+            subject: NATS subject to publish to
+            message: Message to publish
+            correlation_id: Correlation ID for logging
+        """
+        if self._client:
+            await self._client.publish(subject, message)
+            if correlation_id:
+                log_trace(correlation_id, f"Message published to {subject}")
+    
+    async def close(self) -> None:
+        """Close the NATS connection."""
+        if self._client:
+            await self._client.drain()
+            await self._client.close()
+
+
+# ---------------------------------------------- Core Functions ---------------------------------------------- #
+
+def _build_envelope(
+    subject: str,
+    payloads: List[Dict[str, Any]],
+    options: Dict[str, Any]
+) -> Dict[str, Any]:
+    """
+    Build message envelope from payloads and metadata.
+    
+    Args:
+        subject: NATS subject
+        payloads: Array of payload objects
+        options: Envelope metadata options
+    
+    Returns:
+        Envelope object
+    """
+    return {
+        'correlation_id': options['correlation_id'],
+        'msg_id': options['msg_id'],
+        'timestamp': datetime.utcnow().isoformat() + 'Z',
+        'send_to': subject,
+        'msg_purpose': options['msg_purpose'],
+        'sender_name': options['sender_name'],
+        'sender_id': options['sender_id'],
+        'receiver_name': options['receiver_name'],
+        'receiver_id': options['receiver_id'],
+        'reply_to': options['reply_to'],
+        'reply_to_msg_id': options['reply_to_msg_id'],
+        'broker_url': options['broker_url'],
+        'metadata': options.get('metadata', {}),
+        'payloads': payloads
+    }
+
+
+def _build_payload(
+    dataname: str,
+    payload_type: str,
+    payload_bytes: bytes,
+    transport: str,
+    data: Union[str, bytes]
+) -> Dict[str, Any]:
+    """
+    Build payload object from serialized data.
+    
+    Args:
+        dataname: Name of the payload
+        payload_type: Type of the payload
+        payload_bytes: Serialized payload bytes
+        transport: Transport type ("direct" or "link")
+        data: Data (base64 for direct, URL for link)
+    
+    Returns:
+        Payload object
+    """
+    # Determine encoding based on payload type (matching Julia/JS implementation)
+    encoding = 'base64'
+    if payload_type == 'jsontable':
+        encoding = 'json'
+    elif payload_type == 'arrowtable':
+        encoding = 'arrow-ipc'
+    
+    return {
+        'id': str(uuid.uuid4()),
+        'dataname': dataname,
+        'payload_type': payload_type,
+        'transport': transport,
+        'encoding': encoding,
+        'size': len(payload_bytes),
+        'data': data,
+        'metadata': {'payload_bytes': len(payload_bytes)} if transport == 'direct' else {}
+    }
+
+
+async def publish_message(
+    broker_url_or_client: Union[str, NATSClient, Any],
+    subject: str,
+    message: str,
+    correlation_id: str
+) -> None:
+    """
+    Publish message to NATS.
+    
+    Args:
+        broker_url_or_client: NATS URL, client, or connection
+        subject: NATS subject to publish to
+        message: JSON message to publish
+        correlation_id: Correlation ID for tracing
+    """
+    if isinstance(broker_url_or_client, NATSClient):
+        client = broker_url_or_client
+    elif NATS_AVAILABLE and hasattr(broker_url_or_client, 'publish'):
+        # Direct NATS client connection
+        await broker_url_or_client.publish(subject, message)
+        log_trace(correlation_id, f"Message published to {subject}")
+        return
+    else:
+        # String URL - create new client
+        client = NATSClient(broker_url_or_client)
+        await client.connect()
+    
+    await client.publish(subject, message, correlation_id)
+    
+    if isinstance(broker_url_or_client, NATSClient):
+        await broker_url_or_client.close()
+    elif not (NATS_AVAILABLE and hasattr(broker_url_or_client, 'publish')):
+        await client.close()
+
+
+async def smartsend(
+    subject: str,
+    data: List[Tuple[str, Any, str]],
+    broker_url: str = DEFAULT_BROKER_URL,
+    fileserver_url: str = DEFAULT_FILESERVER_URL,
+    fileserver_upload_handler: Callable = plik_oneshot_upload,
+    size_threshold: int = DEFAULT_SIZE_THRESHOLD,
+    correlation_id: str = None,
+    msg_purpose: str = "chat",
+    sender_name: str = "NATSBridge",
+    receiver_name: str = "",
+    receiver_id: str = "",
+    reply_to: str = "",
+    reply_to_msg_id: str = "",
+    is_publish: bool = True,
+    nats_connection: Any = None,
+    msg_id: str = None,
+    sender_id: str = None
+) -> Tuple[Dict, str]:
+    """
+    Send data via NATS with automatic transport selection.
+    
+    This function intelligently routes data delivery based on payload size.
+    If the serialized payload is smaller than size_threshold, it encodes the data as Base64
+    and publishes directly over NATS. Otherwise, it uploads the data to a fileserver
+    and publishes only the download URL over NATS.
+    
+    Args:
+        subject: NATS subject to publish the message to
+        data: List of (dataname, data, type) tuples to send
+            - dataname: Name of the payload
+            - data: The actual data to send
+            - type: Payload type: "text", "dictionary", "arrowtable", "jsontable", "image", "audio", "video", "binary"
+        broker_url: URL of the NATS server
+        fileserver_url: URL of the HTTP file server for large payloads
+        fileserver_upload_handler: Function to handle fileserver uploads (must return Dict with "status",
+                                   "uploadid", "fileid", "url" keys)
+        size_threshold: Threshold in bytes separating direct vs link transport
+        correlation_id: Correlation ID for tracing (auto-generated UUID if not provided)
+        msg_purpose: Purpose of the message: "ACK", "NACK", "updateStatus", "shutdown", "chat", etc.
+        sender_name: Name of the sender
+        receiver_name: Name of the receiver (empty string means broadcast)
+        receiver_id: UUID of the receiver (empty string means broadcast)
+        reply_to: Topic to reply to (empty string if no reply expected)
+        reply_to_msg_id: Message ID this message is replying to
+        is_publish: Whether to automatically publish the message to NATS
+        nats_connection: Pre-existing NATS connection (if provided, uses this connection instead of
+                        creating a new one; saves connection establishment overhead)
+        msg_id: Message ID (auto-generated UUID if not provided)
+        sender_id: Sender ID (auto-generated UUID if not provided)
+    
+    Returns:
+        Tuple of (env, env_json_str) where:
+            - env: Dict containing all metadata and payloads
+            - env_json_str: JSON string for publishing to NATS
+    
+    Example:
+        >>> # Send a single payload (still wrapped in a list)
+        >>> data = {"key": "value"}
+        >>> env, env_json_str = await smartsend(
+        ...     "my.subject",
+        ...     [("dataname1", data, "dictionary")],
+        ...     broker_url="nats://localhost:4222"
+        ... )
+        >>>
+        >>> # Send multiple payloads with different types
+        >>> data1 = {"key1": "value1"}
+        >>> data2 = [1, 2, 3, 4, 5]
+        >>> env, env_json_str = await smartsend(
+        ...     "my.subject",
+        ...     [("dataname1", data1, "dictionary"), ("dataname2", data2, "arrowtable")]
+        ... )
+        >>>
+        >>> # Send a large array using fileserver upload
+        >>> data = list(range(10_000_000))  # ~80 MB
+        >>> env, env_json_str = await smartsend(
+        ...     "large.data",
+        ...     [("large_table", data, "arrowtable")]
+        ... )
+        >>>
+        >>> # Send jsontable (JSON format for human-readable tabular data)
+        >>> users = [{"id": 1, "name": "Alice"}, {"id": 2, "name": "Bob"}]
+        >>> env, env_json_str = await smartsend(
+        ...     "json.data",
+        ...     [("users", users, "jsontable")]
+        ... )
+        >>>
+        >>> # Mixed content (e.g., chat with text and image)
+        >>> env, env_json_str = await smartsend(
+        ...     "chat.subject",
+        ...     [
+        ...         ("message_text", "Hello!", "text"),
+        ...         ("user_image", image_data, "image"),
+        ...         ("audio_clip", audio_data, "audio")
+        ...     ]
+        ... )
+        >>>
+        >>> # Publish the JSON string directly using NATS request-reply pattern
+        >>> # reply = await nats.request(broker_url, subject, env_json_str, reply_to=reply_to_topic)
+    """
+    if correlation_id is None:
+        correlation_id = str(uuid.uuid4())
+    if msg_id is None:
+        msg_id = str(uuid.uuid4())
+    if sender_id is None:
+        sender_id = str(uuid.uuid4())
+    
+    log_trace(correlation_id, f"Starting smartsend for subject: {subject}")
+    
+    # Process payloads
+    payloads = []
+    for dataname, payload_data, payload_type in data:
+        payload_bytes = _serialize_data(payload_data, payload_type)
+        payload_size = len(payload_bytes)
+        
+        log_trace(correlation_id, f"Serialized payload '{dataname}' (type: {payload_type}) size: {payload_size} bytes")
+        
+        if payload_size < size_threshold:
+            # Direct path
+            payload_b64 = base64.b64encode(payload_bytes).decode('utf-8')
+            log_trace(correlation_id, f"Using direct transport for {payload_size} bytes")
+            
+            payload = _build_payload(dataname, payload_type, payload_bytes, 'direct', payload_b64)
+            payloads.append(payload)
+        else:
+            # Link path
+            log_trace(correlation_id, "Using link transport, uploading to fileserver")
+            
+            response = await fileserver_upload_handler(fileserver_url, dataname, payload_bytes)
+            
+            if response['status'] != 200:
+                raise Exception(f"Failed to upload data to fileserver: {response['status']}")
+            
+            log_trace(correlation_id, f"Uploaded to URL: {response['url']}")
+            
+            payload = _build_payload(dataname, payload_type, payload_bytes, 'link', response['url'])
+            payloads.append(payload)
+    
+    # Build envelope
+    env = _build_envelope(subject, payloads, {
+        'correlation_id': correlation_id,
+        'msg_id': msg_id,
+        'msg_purpose': msg_purpose,
+        'sender_name': sender_name,
+        'sender_id': sender_id,
+        'receiver_name': receiver_name,
+        'receiver_id': receiver_id,
+        'reply_to': reply_to,
+        'reply_to_msg_id': reply_to_msg_id,
+        'broker_url': broker_url
+    })
+    
+    env_json_str = json.dumps(env)
+    
+    if is_publish:
+        if nats_connection:
+            await publish_message(nats_connection, subject, env_json_str, correlation_id)
+        else:
+            await publish_message(broker_url, subject, env_json_str, correlation_id)
+    
+    return env, env_json_str
+
+
+async def smartreceive(
+    msg: Any,
+    fileserver_download_handler: Callable = fetch_with_backoff,
+    max_retries: int = 5,
+    base_delay: int = 100,
+    max_delay: int = 5000
+) -> Dict[str, Any]:
+    """
+    Receive and process NATS messages.
+    
+    This function processes incoming NATS messages, handling both direct transport
+    (base64 decoded payloads) and link transport (URL-based payloads).
+    It deserializes the data based on the transport type and returns the result.
+    
+    Args:
+        msg: NATS message to process
+        fileserver_download_handler: Function to handle downloading data from file server URLs
+        max_retries: Maximum retry attempts for fetching URL
+        base_delay: Initial delay for exponential backoff in ms
+        max_delay: Maximum delay for exponential backoff in ms
+    
+    Returns:
+        Dict with envelope metadata and payloads field containing List[Tuple[str, Any, str]]
+    
+    Example:
+        >>> # Receive and process message
+        >>> env = await smartreceive(msg, fileserver_download_handler=fetch_with_backoff)
+        >>> # env is a Dict with "payloads" key containing List[Tuple[str, Any, str]]
+        >>> # Access payloads: for dataname, data, type_ in env["payloads"]
+        >>> for dataname, data, type_ in env["payloads"]:
+        >>>     print(f"{dataname}: {data} (type: {type_})")
+    """
+    # Parse the JSON envelope
+    if isinstance(msg, dict):
+        # Already parsed
+        env_json_obj = msg
+    elif hasattr(msg, 'payload'):
+        # NATS message object
+        payload = msg.payload if isinstance(msg.payload, str) else msg.payload.decode('utf-8')
+        env_json_obj = json.loads(payload)
+    else:
+        # Assume it's already a JSON string or dict
+        env_json_obj = json.loads(msg) if isinstance(msg, str) else msg
+    
+    log_trace(env_json_obj['correlation_id'], "Processing received message")
+    
+    # Process all payloads in the envelope
+    payloads_list = []
+    num_payloads = len(env_json_obj['payloads'])
+    
+    for i in range(num_payloads):
+        payload_obj = env_json_obj['payloads'][i]
+        transport = payload_obj['transport']
+        dataname = payload_obj['dataname']
+        
+        if transport == 'direct':
+            log_trace(env_json_obj['correlation_id'], f"Direct transport - decoding payload '{dataname}'")
+            
+            # Extract base64 payload from the payload
+            payload_b64 = payload_obj['data']
+            
+            # Decode Base64 payload
+            payload_bytes = base64.b64decode(payload_b64)
+            
+            # Deserialize based on type
+            data_type = payload_obj['payload_type']
+            data = _deserialize_data(payload_bytes, data_type, env_json_obj['correlation_id'])
+            
+            payloads_list.append((dataname, data, data_type))
+        elif transport == 'link':
+            # Extract download URL from the payload
+            url = payload_obj['data']
+            log_trace(env_json_obj['correlation_id'], f"Link transport - fetching '{dataname}' from URL: {url}")
+            
+            # Fetch with exponential backoff using the download handler
+            downloaded_data = await fileserver_download_handler(
+                url,
+                max_retries,
+                base_delay,
+                max_delay,
+                env_json_obj['correlation_id']
+            )
+            
+            # Deserialize based on type
+            data_type = payload_obj['payload_type']
+            data = _deserialize_data(downloaded_data, data_type, env_json_obj['correlation_id'])
+            
+            payloads_list.append((dataname, data, data_type))
+        else:
+            raise Exception(f"Unknown transport type for payload '{dataname}': {transport}")
+    
+    env_json_obj['payloads'] = payloads_list
+    return env_json_obj
+
+
+# ---------------------------------------------- Module Exports ---------------------------------------------- #
+
+class NATSBridge:
+    """
+    Cross-platform NATS bridge implementation.
+    
+    This class provides a convenient interface for NATSBridge functionality,
+    encapsulating the main functions and providing a class-based API.
+    """
+    
+    DEFAULT_SIZE_THRESHOLD = DEFAULT_SIZE_THRESHOLD
+    DEFAULT_BROKER_URL = DEFAULT_BROKER_URL
+    DEFAULT_FILESERVER_URL = DEFAULT_FILESERVER_URL
+    
+    def __init__(self, broker_url: str = None, fileserver_url: str = None):
+        """
+        Initialize NATSBridge.
+        
+        Args:
+            broker_url: NATS server URL (defaults to DEFAULT_BROKER_URL)
+            fileserver_url: HTTP file server URL (defaults to DEFAULT_FILESERVER_URL)
+        """
+        self.broker_url = broker_url or self.DEFAULT_BROKER_URL
+        self.fileserver_url = fileserver_url or self.DEFAULT_FILESERVER_URL
+    
+    async def smartsend(
+        self,
+        subject: str,
+        data: List[Tuple[str, Any, str]],
+        **kwargs
+    ) -> Tuple[Dict, str]:
+        """
+        Send data via NATS.
+        
+        Args:
+            subject: NATS subject to publish to
+            data: List of (dataname, data, type) tuples
+            **kwargs: Additional options passed to smartsend
+        
+        Returns:
+            Tuple of (env, env_json_str)
+        """
+        kwargs['broker_url'] = kwargs.get('broker_url', self.broker_url)
+        kwargs['fileserver_url'] = kwargs.get('fileserver_url', self.fileserver_url)
+        return await smartsend(subject, data, **kwargs)
+    
+    async def smartreceive(
+        self,
+        msg: Any,
+        **kwargs
+    ) -> Dict[str, Any]:
+        """
+        Receive and process NATS message.
+        
+        Args:
+            msg: NATS message to process
+            **kwargs: Additional options passed to smartreceive
+        
+        Returns:
+            Dict with envelope metadata and payloads
+        """
+        return await smartreceive(msg, **kwargs)
+
+
+# Convenience functions for module-level usage
+def send(
+    subject: str,
+    data: List[Tuple[str, Any, str]],
+    **kwargs
+) -> Tuple[Dict, str]:
+    """
+    Convenience function for sending data.
+    
+    Args:
+        subject: NATS subject to publish to
+        data: List of (dataname, data, type) tuples
+        **kwargs: Additional options
+    
+    Returns:
+        Tuple of (env, env_json_str)
+    """
+    return asyncio.run(smartsend(subject, data, **kwargs))
+
+
+def receive(
+    msg: Any,
+    **kwargs
+) -> Dict[str, Any]:
+    """
+    Convenience function for receiving messages.
+    
+    Args:
+        msg: NATS message to process
+        **kwargs: Additional options
+    
+    Returns:
+        Dict with envelope metadata and payloads
+    """
+    return asyncio.run(smartreceive(msg, **kwargs))
+
+
+__all__ = [
+    'smartsend',
+    'smartreceive',
+    'plik_oneshot_upload',
+    'fetch_with_backoff',
+    'NATSBridge',
+    'send',
+    'receive',
+    'DEFAULT_SIZE_THRESHOLD',
+    'DEFAULT_BROKER_URL',
+    'DEFAULT_FILESERVER_URL',
+    'NATSClient',
+    '_serialize_data',
+    '_deserialize_data',
+    'log_trace',
+    'publish_message'
+]

src/natsbridge_csr.js

@@ -0,0 +1,808 @@
+/**
+ * NATSBridge - Cross-Platform Bi-Directional Data Bridge
+ * Browser-Compatible Implementation (Client-Side Rendering)
+ * 
+ * This module provides functionality for sending and receiving data across network boundaries
+ * using NATS as the message bus, with support for both direct payload transport and
+ * URL-based transport for larger payloads.
+ * 
+ * Supported payload types: "text", "dictionary", "arrowtable", "jsontable", "image", "audio", "video", "binary"
+ * 
+ * Browser-compatible version uses:
+ * - nats.ws for WebSocket-based NATS connections
+ * - Web Crypto API for UUID generation
+ * - Uint8Array instead of Buffer
+ * - fetch API for file server communication
+ * 
+ * @module NATSBridgeCSR
+ */
+
+// Import browser-compatible NATS client
+import * as nats from 'nats.ws';
+
+// Use native fetch available in browsers
+import { tableFromArrays, tableToIPC } from 'apache-arrow/browser';
+
+// ---------------------------------------------- Constants ---------------------------------------------- //
+
+/**
+ * Default size threshold for switching from direct to link transport (0.5MB)
+ */
+const DEFAULT_SIZE_THRESHOLD = 500_000;
+
+/**
+ * Default NATS server URL (WebSocket protocol)
+ */
+const DEFAULT_BROKER_URL = 'ws://localhost:4222';
+
+/**
+ * Default HTTP file server URL for link transport
+ */
+const DEFAULT_FILESERVER_URL = 'http://localhost:8080';
+
+// ---------------------------------------------- Utility Functions ---------------------------------------------- //
+
+/**
+ * Convert Uint8Array to Base64 string
+ * @param {Uint8Array} data - Data to encode
+ * @returns {string} Base64 encoded string
+ */
+function bufferToBase64(data) {
+    const bytes = new Uint8Array(data);
+    let binary = '';
+    for (let i = 0; i < bytes.length; i++) {
+        binary += String.fromCharCode(bytes[i]);
+    }
+    return btoa(binary);
+}
+
+/**
+ * Convert Base64 string to Uint8Array
+ * @param {string} base64 - Base64 encoded string
+ * @returns {Uint8Array} Decoded binary data
+ */
+function base64ToBuffer(base64) {
+    const binary = atob(base64);
+    const len = binary.length;
+    const bytes = new Uint8Array(len);
+    for (let i = 0; i < len; i++) {
+        bytes[i] = binary.charCodeAt(i);
+    }
+    return bytes;
+}
+
+/**
+ * Generate UUID v4 using Web Crypto API
+ * @returns {string} UUID string
+ */
+function uuidv4() {
+    const array = new Uint8Array(16);
+    crypto.getRandomValues(array);
+    array[6] = (array[6] & 0x0f) | 0x40;
+    array[8] = (array[8] & 0x3f) | 0x80;
+    return Array.from(array, (val) => val.toString(16).padStart(2, '0').toUpperCase()).join('');
+}
+
+/**
+ * Log a trace message with correlation ID and timestamp
+ * @param {string} correlationId - Correlation ID for tracing
+ * @param {string} message - Message content to log
+ */
+function logTrace(correlationId, message) {
+    const timestamp = new Date().toISOString();
+    console.log(`[${timestamp}] [Correlation: ${correlationId}] ${message}`);
+}
+
+// ---------------------------------------------- Serialization Functions ---------------------------------------------- //
+
+/**
+ * Serialize data according to specified format
+ * @param {any} data - Data to serialize
+ * @param {string} payloadType - Target format: "text", "dictionary", "arrowtable", "jsontable", "image", "audio", "video", "binary"
+ * @returns {Uint8Array} Binary representation of the serialized data
+ */
+async function serializeData(data, payloadType) {
+    if (payloadType === 'text') {
+        if (typeof data === 'string') {
+            return new Uint8Array(new TextEncoder().encode(data));
+        } else {
+            throw new Error('Text data must be a string');
+        }
+    } else if (payloadType === 'dictionary') {
+        const jsonStr = JSON.stringify(data);
+        return new Uint8Array(new TextEncoder().encode(jsonStr));
+    } else if (payloadType === 'arrowtable') {
+        // Convert array of objects to Arrow IPC format
+        if (!Array.isArray(data) || data.length === 0) {
+            throw new Error('Arrow table data must be a non-empty array of objects');
+        }
+        
+        return serializeArrowTable(data);
+    } else if (payloadType === 'jsontable') {
+        // Serialize array of objects to JSON format
+        if (!Array.isArray(data)) {
+            throw new Error('JSON table data must be an array');
+        }
+        const jsonStr = JSON.stringify(data);
+        return new Uint8Array(new TextEncoder().encode(jsonStr));
+    } else if (payloadType === 'image') {
+        if (data instanceof Uint8Array || data instanceof ArrayBuffer || ArrayBuffer.isView(data)) {
+            return new Uint8Array(data);
+        } else {
+            throw new Error('Image data must be Uint8Array, ArrayBuffer, or ArrayBuffer view');
+        }
+    } else if (payloadType === 'audio') {
+        if (data instanceof Uint8Array || data instanceof ArrayBuffer || ArrayBuffer.isView(data)) {
+            return new Uint8Array(data);
+        } else {
+            throw new Error('Audio data must be Uint8Array, ArrayBuffer, or ArrayBuffer view');
+        }
+    } else if (payloadType === 'video') {
+        if (data instanceof Uint8Array || data instanceof ArrayBuffer || ArrayBuffer.isView(data)) {
+            return new Uint8Array(data);
+        } else {
+            throw new Error('Video data must be Uint8Array, ArrayBuffer, or ArrayBuffer view');
+        }
+    } else if (payloadType === 'binary') {
+        if (data instanceof Uint8Array || data instanceof ArrayBuffer || ArrayBuffer.isView(data)) {
+            return new Uint8Array(data);
+        } else {
+            throw new Error('Binary data must be Uint8Array, ArrayBuffer, or ArrayBuffer view');
+        }
+    } else {
+        throw new Error(`Unknown payload_type: ${payloadType}`);
+    }
+}
+
+/**
+ * Helper function to properly serialize table data to Arrow IPC
+ * @param {Array<Object>} data - Array of objects representing table rows
+ * @returns {Uint8Array} Arrow IPC formatted buffer
+ */
+function serializeArrowTable(data) {
+    if (!Array.isArray(data) || data.length === 0) {
+        throw new Error('Table data must be a non-empty array of objects');
+    }
+    
+    logTrace('serializeArrowTable', `Serializing table with ${data.length} rows`);
+    
+    // Convert array of objects to a key-value format expected by tableFromArrays
+    const columns = {};
+    const keys = Object.keys(data[0]);
+    for (const key of keys) {
+        columns[key] = data.map(row => row[key]);
+    }
+    
+    logTrace('serializeArrowTable', `Columns: ${Object.keys(columns).join(', ')}`);
+    
+    const table = tableFromArrays(columns);
+    
+    logTrace('serializeArrowTable', `Arrow table created with ${table.numRows} rows, ${table.numCols} cols`);
+    
+    // Convert to IPC format
+    const ipcBuffer = tableToIPC(table);
+    
+    logTrace('serializeArrowTable', `IPC buffer type: ${typeof ipcBuffer}, byteLength: ${ipcBuffer.byteLength}`);
+    
+    const resultBuffer = new Uint8Array(ipcBuffer);
+    logTrace('serializeArrowTable', `Result buffer: ${resultBuffer.length} bytes`);
+    
+    // Debug: Show first 20 bytes in hex
+    const hexPreview = [];
+    for (let i = 0; i < Math.min(20, resultBuffer.length); i++) {
+        hexPreview.push(resultBuffer[i].toString(16).padStart(2, '0'));
+    }
+    logTrace('serializeArrowTable', `First 20 bytes (hex): ${hexPreview.join(' ')}`);
+    
+    return resultBuffer;
+}
+
+/**
+ * Deserialize bytes to data based on type
+ * @param {Uint8Array|ArrayBuffer} data - Serialized data as bytes
+ * @param {string} payloadType - Data type
+ * @param {string} correlationId - Correlation ID for logging
+ * @returns {any} Deserialized data
+ */
+async function deserializeData(data, payloadType, correlationId) {
+    const buffer = data instanceof Uint8Array ? data : new Uint8Array(data);
+    
+    logTrace(correlationId, `deserializeData: type=${payloadType}, bufferLength=${buffer.length}`);
+    
+    // Debug: Show first 20 bytes in hex for binary data
+    if (payloadType === 'arrowtable' || payloadType === 'jsontable' || payloadType === 'image' || payloadType === 'binary') {
+        const hexPreview = [];
+        for (let i = 0; i < Math.min(20, buffer.length); i++) {
+            hexPreview.push(buffer[i].toString(16).padStart(2, '0'));
+        }
+        logTrace(correlationId, `deserializeData: First 20 bytes (hex): ${hexPreview.join(' ')}`);
+    }
+    
+    if (payloadType === 'text') {
+        const result = new TextDecoder().decode(buffer);
+        logTrace(correlationId, `deserializeData: text result length=${result.length}`);
+        return result;
+    } else if (payloadType === 'dictionary') {
+        const jsonStr = new TextDecoder().decode(buffer);
+        const result = JSON.parse(jsonStr);
+        logTrace(correlationId, `deserializeData: dictionary keys=${Object.keys(result).join(', ')}`);
+        return result;
+    } else if (payloadType === 'arrowtable') {
+        logTrace(correlationId, `deserializeData: Attempting Arrow table deserialization`);
+        
+        try {
+            // Try tableFromIPC (browser API)
+            const table = tableFromIPC(buffer);
+            logTrace(correlationId, `deserializeData: Arrow table from IPC - rows=${table.numRows}, cols=${table.numCols}`);
+            return table;
+        } catch (e) {
+            logTrace(correlationId, `deserializeData: tableFromIPC failed: ${e.message}`);
+            throw new Error(`Unable to deserialize Arrow table: ${e.message}`);
+        }
+    } else if (payloadType === 'jsontable') {
+        const jsonStr = new TextDecoder().decode(buffer);
+        const result = JSON.parse(jsonStr);
+        logTrace(correlationId, `deserializeData: jsontable result length=${Array.isArray(result) ? result.length : 'N/A'}`);
+        return result;
+    } else if (payloadType === 'image') {
+        logTrace(correlationId, `deserializeData: image buffer length=${buffer.length}`);
+        return buffer;
+    } else if (payloadType === 'audio') {
+        logTrace(correlationId, `deserializeData: audio buffer length=${buffer.length}`);
+        return buffer;
+    } else if (payloadType === 'video') {
+        logTrace(correlationId, `deserializeData: video buffer length=${buffer.length}`);
+        return buffer;
+    } else if (payloadType === 'binary') {
+        logTrace(correlationId, `deserializeData: binary buffer length=${buffer.length}`);
+        return buffer;
+    } else {
+        throw new Error(`Unknown payload_type: ${payloadType}`);
+    }
+}
+
+// ---------------------------------------------- File Server Handlers ---------------------------------------------- //
+
+/**
+ * Upload data to plik server in one-shot mode
+ * @param {string} fileServerUrl - Base URL of the plik server
+ * @param {string} dataname - Name of the file being uploaded
+ * @param {Uint8Array} data - Raw byte data of the file content
+ * @returns {Promise<{status: number, uploadid: string, fileid: string, url: string}>}
+ */
+async function plikOneshotUpload(fileServerUrl, dataname, data) {
+    const buffer = data instanceof Uint8Array ? data : new Uint8Array(data);
+    
+    // Get upload id
+    const urlGetUploadID = `${fileServerUrl}/upload`;
+    const headers = { 'Content-Type': 'application/json' };
+    const body = JSON.stringify({ OneShot: true });
+    
+    const httpResponse = await fetch(urlGetUploadID, {
+        method: 'POST',
+        headers,
+        body
+    });
+    
+    const responseJson = await httpResponse.json();
+    const uploadid = responseJson.id;
+    const uploadtoken = responseJson.uploadToken;
+
+    // Upload file
+    const urlUpload = `${fileServerUrl}/file/${uploadid}`;
+    const form = new FormData();
+    const blob = new Blob([buffer], { type: 'application/octet-stream' });
+    form.append('file', blob, dataname);
+    
+    const uploadHeaders = {
+        'X-UploadToken': uploadtoken
+    };
+
+    const uploadResponse = await fetch(urlUpload, {
+        method: 'POST',
+        headers: uploadHeaders,
+        body: form
+    });
+    
+    const uploadJson = await uploadResponse.json();
+    const fileid = uploadJson.id;
+
+    const url = `${fileServerUrl}/file/${uploadid}/${fileid}/${dataname}`;
+
+    return {
+        status: uploadResponse.status,
+        uploadid,
+        fileid,
+        url
+    };
+}
+
+/**
+ * Fetch data from URL with exponential backoff
+ * @param {string} url - URL to fetch from
+ * @param {number} maxRetries - Maximum number of retry attempts
+ * @param {number} baseDelay - Initial delay in milliseconds
+ * @param {number} maxDelay - Maximum delay in milliseconds
+ * @param {string} correlationId - Correlation ID for logging
+ * @returns {Promise<Uint8Array>} Fetched data as bytes
+ */
+async function fetchWithBackoff(url, maxRetries, baseDelay, maxDelay, correlationId) {
+    let delay = baseDelay;
+    
+    for (let attempt = 1; attempt <= maxRetries; attempt++) {
+        try {
+            const response = await fetch(url);
+            
+            if (response.status === 200) {
+                logTrace(correlationId, `Successfully fetched data from ${url} on attempt ${attempt}`);
+                const arrayBuffer = await response.arrayBuffer();
+                return new Uint8Array(arrayBuffer);
+            } else {
+                throw new Error(`Failed to fetch: ${response.status}`);
+            }
+        } catch (e) {
+            logTrace(correlationId, `Attempt ${attempt} failed: ${e.constructor.name} - ${e.message}`);
+            
+            if (attempt < maxRetries) {
+                await new Promise(resolve => setTimeout(resolve, delay));
+                delay = Math.min(delay * 2, maxDelay);
+            }
+        }
+    }
+    
+    throw new Error(`Failed to fetch data after ${maxRetries} attempts`);
+}
+
+// ---------------------------------------------- NATS Client ---------------------------------------------- //
+
+/**
+ * NATS client wrapper for connection management
+ */
+class NATSClient {
+    /**
+     * Create a new NATS client
+     * @param {string} url - NATS server URL (ws:// or wss://)
+     */
+    constructor(url) {
+        this.url = url;
+        this.connection = null;
+    }
+
+    /**
+     * Connect to NATS server
+     * @returns {Promise<NATS.Connection>}
+     */
+    async connect() {
+        this.connection = await nats.connect({ servers: this.url });
+        return this.connection;
+    }
+
+    /**
+     * Publish message to NATS subject
+     * @param {string} subject - NATS subject to publish to
+     * @param {string} message - Message to publish
+     * @param {string} correlationId - Correlation ID for logging
+     */
+    async publish(subject, message, correlationId) {
+        if (!this.connection) {
+            await this.connect();
+        }
+        await this.connection.publish(subject, message);
+        logTrace(correlationId, `Message published to ${subject}`);
+    }
+
+    /**
+     * Close the NATS connection
+     */
+    async close() {
+        if (this.connection) {
+            this.connection.close();
+        }
+    }
+}
+
+// ---------------------------------------------- Core Functions ---------------------------------------------- //
+
+/**
+ * Publish message to NATS
+ * @param {string|NATSClient|NATS.Connection} brokerUrlOrClient - NATS URL, client, or connection
+ * @param {string} subject - NATS subject to publish to
+ * @param {string} message - JSON message to publish
+ * @param {string} correlationId - Correlation ID for tracing
+ */
+async function publishMessage(brokerUrlOrClient, subject, message, correlationId) {
+    let conn;
+    
+    if (brokerUrlOrClient instanceof NATSClient) {
+        conn = brokerUrlOrClient;
+    } else if (brokerUrlOrClient && typeof brokerUrlOrClient.publish === 'function') {
+        // Create a wrapper for direct connection (duck-typing check for NATS connection)
+        conn = {
+            async publish(subj, msg) {
+                await brokerUrlOrClient.publish(subj, msg);
+            },
+            async close() {
+                await brokerUrlOrClient.close();
+            }
+        };
+    } else {
+        // String URL - create new client
+        const client = new NATSClient(brokerUrlOrClient);
+        conn = client;
+    }
+    
+    await conn.publish(subject, message, correlationId);
+    
+    if (conn instanceof NATSClient) {
+        await conn.close();
+    }
+}
+
+/**
+ * Build message envelope from payloads and metadata
+ * @param {string} subject - NATS subject
+ * @param {Array} payloads - Array of payload objects
+ * @param {Object} options - Envelope metadata options
+ * @returns {Object} Envelope object
+ */
+function buildEnvelope(subject, payloads, options) {
+    return {
+        correlation_id: options.correlation_id,
+        msg_id: options.msg_id,
+        timestamp: new Date().toISOString(),
+        send_to: subject,
+        msg_purpose: options.msg_purpose,
+        sender_name: options.sender_name,
+        sender_id: options.sender_id,
+        receiver_name: options.receiver_name,
+        receiver_id: options.receiver_id,
+        reply_to: options.reply_to,
+        reply_to_msg_id: options.reply_to_msg_id,
+        broker_url: options.broker_url,
+        metadata: options.metadata || {},
+        payloads: payloads
+    };
+}
+
+/**
+ * Build payload object from serialized data
+ * @param {string} dataname - Name of the payload
+ * @param {string} payloadType - Type of the payload
+ * @param {Uint8Array} payloadBytes - Serialized payload bytes
+ * @param {string} transport - Transport type ("direct" or "link")
+ * @param {string} data - Data (base64 for direct, URL for link)
+ * @returns {Object} Payload object
+ */
+function buildPayload(dataname, payloadType, payloadBytes, transport, data) {
+    // Determine encoding based on payload type (matching Julia implementation)
+    let encoding = 'base64';
+    if (payloadType === 'jsontable') {
+        encoding = 'json';
+    } else if (payloadType === 'arrowtable') {
+        encoding = 'arrow-ipc';
+    }
+    
+    return {
+        id: uuidv4(),
+        dataname,
+        payload_type: payloadType,
+        transport,
+        encoding,
+        size: payloadBytes.byteLength,
+        data,
+        metadata: transport === 'direct' ? { payload_bytes: payloadBytes.byteLength } : {}
+    };
+}
+
+/**
+ * Send data via NATS with automatic transport selection
+ * 
+ * This function intelligently routes data delivery based on payload size.
+ * If the serialized payload is smaller than size_threshold, it encodes the data as Base64
+ * and publishes directly over NATS. Otherwise, it uploads the data to a fileserver
+ * and publishes only the download URL over NATS.
+ * 
+ * @param {string} subject - NATS subject to publish the message to
+ * @param {Array} data - List of [dataname, data, type] tuples to send
+ *          - type: "text", "dictionary", "arrowtable", "jsontable", "image", "audio", "video", "binary"
+ * @param {Object} options - Optional configuration
+ * @param {string} [options.broker_url=DEFAULT_BROKER_URL] - URL of the NATS server (WebSocket)
+ * @param {string} [options.fileserver_url=DEFAULT_FILESERVER_URL] - URL of the HTTP file server
+ * @param {Function} [options.fileserver_upload_handler=plikOneshotUpload] - Function to handle fileserver uploads
+ * @param {number} [options.size_threshold=DEFAULT_SIZE_THRESHOLD] - Threshold separating direct vs link transport
+ * @param {string} [options.correlation_id=uuidv4()] - Correlation ID for tracing
+ * @param {string} [options.msg_purpose="chat"] - Purpose of the message
+ * @param {string} [options.sender_name="NATSBridge"] - Name of the sender
+ * @param {string} [options.receiver_name=""] - Name of the receiver (empty means broadcast)
+ * @param {string} [options.receiver_id=""] - UUID of the receiver (empty means broadcast)
+ * @param {string} [options.reply_to=""] - Topic to reply to
+ * @param {string} [options.reply_to_msg_id=""] - Message ID this message is replying to
+ * @param {boolean} [options.is_publish=true] - Whether to automatically publish the message
+ * @param {NATSClient|NATS.Connection} [options.nats_connection=null] - Pre-existing NATS connection
+ * @param {string} [options.msg_id=uuidv4()] - Message ID
+ * @param {string} [options.sender_id=uuidv4()] - Sender ID
+ * @returns {Promise<[Object, string]>} Tuple of [env, env_json_str]
+ * 
+ * @example
+ * // Send a single payload
+ * const [env, envJsonStr] = await NATSBridgeCSR.smartsend(
+ *     "/test",
+ *     [["dataname1", data1, "dictionary"]],
+ *     { broker_url: "ws://localhost:4222" }
+ * );
+ * 
+ * // Send multiple payloads
+ * const [env, envJsonStr] = await NATSBridgeCSR.smartsend(
+ *     "/test",
+ *     [
+ *         ["dataname1", data1, "dictionary"],
+ *         ["dataname2", data2, "arrowtable"]
+ *     ],
+ *     { broker_url: "ws://localhost:4222" }
+ * );
+ */
+async function smartsend(subject, data, options = {}) {
+    const {
+        broker_url = DEFAULT_BROKER_URL,
+        fileserver_url = DEFAULT_FILESERVER_URL,
+        fileserver_upload_handler = plikOneshotUpload,
+        size_threshold = DEFAULT_SIZE_THRESHOLD,
+        correlation_id = uuidv4(),
+        msg_purpose = 'chat',
+        sender_name = 'NATSBridge',
+        receiver_name = '',
+        receiver_id = '',
+        reply_to = '',
+        reply_to_msg_id = '',
+        is_publish = true,
+        nats_connection = null,
+        msg_id = uuidv4(),
+        sender_id = uuidv4()
+    } = options;
+
+    logTrace(correlation_id, `Starting smartsend for subject: ${subject}`);
+    logTrace(correlation_id, `smartsend: data array length=${data.length}`);
+    
+    // Debug: Log input data structure
+    for (let i = 0; i < data.length; i++) {
+        const [dataname, payloadData, payloadType] = data[i];
+        logTrace(correlation_id, `smartsend: payload[${i}] dataname=${dataname}, type=${payloadType}, data type=${typeof payloadData}, constructor=${payloadData?.constructor?.name}`);
+    }
+
+    // Process payloads
+    const payloads = [];
+    for (const [dataname, payloadData, payloadType] of data) {
+        logTrace(correlation_id, `smartsend: Processing payload '${dataname}' type=${payloadType}`);
+        logTrace(correlation_id, `smartsend: payloadData type=${typeof payloadData}, constructor=${payloadData?.constructor?.name}`);
+        
+        const payloadBytes = await serializeData(payloadData, payloadType);
+        const payloadSize = payloadBytes.byteLength;
+
+        logTrace(correlation_id, `Serialized payload '${dataname}' (type: ${payloadType}) size: ${payloadSize} bytes`);
+
+        // Debug: Show first 20 bytes of serialized data for table type
+        if (payloadType === 'table') {
+            const hexPreview = [];
+            for (let i = 0; i < Math.min(20, payloadBytes.length); i++) {
+                hexPreview.push(payloadBytes[i].toString(16).padStart(2, '0'));
+            }
+            logTrace(correlation_id, `Serialized table data first 20 bytes (hex): ${hexPreview.join(' ')}`);
+        }
+
+        if (payloadSize < size_threshold) {
+            // Direct path
+            const payloadB64 = bufferToBase64(payloadBytes);
+            logTrace(correlation_id, `Using direct transport for ${payloadSize} bytes, base64 length=${payloadB64.length}`);
+
+            const payload = buildPayload(dataname, payloadType, payloadBytes, 'direct', payloadB64);
+            payloads.push(payload);
+        } else {
+            // Link path
+            logTrace(correlation_id, `Using link transport, uploading to fileserver`);
+
+            const response = await fileserver_upload_handler(fileserver_url, dataname, payloadBytes);
+
+            if (response.status !== 200) {
+                throw new Error(`Failed to upload data to fileserver: ${response.status}`);
+            }
+
+            logTrace(correlation_id, `Uploaded to URL: ${response.url}`);
+
+            const payload = buildPayload(dataname, payloadType, payloadBytes, 'link', response.url);
+            payloads.push(payload);
+        }
+    }
+
+    // Build envelope
+    const env = buildEnvelope(subject, payloads, {
+        correlation_id,
+        msg_id,
+        msg_purpose,
+        sender_name,
+        sender_id,
+        receiver_name,
+        receiver_id,
+        reply_to,
+        reply_to_msg_id,
+        broker_url
+    });
+
+    const env_json_str = JSON.stringify(env);
+
+    if (is_publish) {
+        if (nats_connection) {
+            await publishMessage(nats_connection, subject, env_json_str, correlation_id);
+        } else {
+            await publishMessage(broker_url, subject, env_json_str, correlation_id);
+        }
+    }
+
+    return [env, env_json_str];
+}
+
+/**
+ * Receive and process NATS message
+ * 
+ * This function processes incoming NATS messages, handling both direct transport
+ * (base64 decoded payloads) and link transport (URL-based payloads).
+ * It deserializes the data based on the transport type and returns the result.
+ * 
+ * @param {Object} msg - NATS message object with payload property
+ * @param {Object} options - Optional configuration
+ * @param {Function} [options.fileserver_download_handler=fetchWithBackoff] - Function to handle fileserver downloads
+ * @param {number} [options.max_retries=5] - Maximum retry attempts for fetching URL
+ * @param {number} [options.base_delay=100] - Initial delay for exponential backoff in ms
+ * @param {number} [options.max_delay=5000] - Maximum delay for exponential backoff in ms
+ * @returns {Promise<Object>} Envelope object with processed payloads
+ * 
+ * @example
+ * // Receive and process message
+ * const env = await NATSBridgeCSR.smartreceive(msg, {
+ *     fileserver_download_handler: NATSBridgeCSR.fetchWithBackoff,
+ *     max_retries: 5,
+ *     base_delay: 100,
+ *     max_delay: 5000
+ * });
+ * // env.payloads is an Array of [dataname, data, type] arrays
+ * for (const [dataname, data, type] of env.payloads) {
+ *     console.log(`${dataname}: ${data} (type: ${type})`);
+ * }
+ */
+async function smartreceive(msg, options = {}) {
+    const {
+        fileserver_download_handler = fetchWithBackoff,
+        max_retries = 5,
+        base_delay = 100,
+        max_delay = 5000
+    } = options;
+
+    // Debug: Log message object structure
+    logTrace('smartreceive', `smartreceive: msg object keys: ${Object.keys(msg).join(', ')}`);
+    logTrace('smartreceive', `smartreceive: msg.data type: ${typeof msg.data}, constructor: ${msg.data?.constructor?.name}`);
+    logTrace('smartreceive', `smartreceive: msg.payload type: ${typeof msg.payload}, constructor: ${msg.payload?.constructor?.name}`);
+    
+    // Parse the JSON envelope
+    // NATS.js v2.x uses msg.data instead of msg.payload
+    let payload;
+    if (msg.data !== undefined) {
+        payload = typeof msg.data === 'string' ? msg.data : new TextDecoder().decode(msg.data);
+    } else if (msg.payload !== undefined) {
+        payload = typeof msg.payload === 'string' ? msg.payload : new TextDecoder().decode(msg.payload);
+    } else {
+        throw new Error('Message has neither data nor payload property');
+    }
+    
+    logTrace('smartreceive', `smartreceive: raw payload length=${payload.length}`);
+    
+    // Debug: Show first 200 chars of payload
+    const payloadPreview = payload.substring(0, 200);
+    logTrace('smartreceive', `smartreceive: payload preview: ${payloadPreview}`);
+    
+    let envJsonObj;
+    try {
+        envJsonObj = JSON.parse(payload);
+    } catch (e) {
+        logTrace('smartreceive', `smartreceive: JSON parse failed: ${e.message}`);
+        throw e;
+    }
+    
+    logTrace(envJsonObj.correlation_id, 'Processing received message');
+    logTrace(envJsonObj.correlation_id, `smartreceive: envelope has ${envJsonObj.payloads.length} payloads`);
+
+    // Process all payloads in the envelope
+    const payloadsList = [];
+    const numPayloads = envJsonObj.payloads.length;
+
+    logTrace(envJsonObj.correlation_id, `smartreceive: Processing ${numPayloads} payloads`);
+
+    for (let i = 0; i < numPayloads; i++) {
+        const payloadObj = envJsonObj.payloads[i];
+        const transport = payloadObj.transport;
+        const dataname = payloadObj.dataname;
+        const payloadType = payloadObj.payload_type;
+
+        logTrace(envJsonObj.correlation_id, `smartreceive: Processing payload ${i + 1}/${numPayloads}: dataname=${dataname}, type=${payloadType}, transport=${transport}`);
+
+        if (transport === 'direct') {
+            logTrace(envJsonObj.correlation_id, `Direct transport - decoding payload '${dataname}'`);
+
+            // Extract base64 payload from the payload
+            const payloadB64 = payloadObj.data;
+            logTrace(envJsonObj.correlation_id, `Direct transport: base64 length=${payloadB64?.length}`);
+
+            // Decode Base64 payload
+            const payloadBytes = base64ToBuffer(payloadB64);
+            logTrace(envJsonObj.correlation_id, `Direct transport: decoded bytes=${payloadBytes.length}`);
+
+            // Deserialize based on type
+            const dataType = payloadObj.payload_type;
+            const data = await deserializeData(payloadBytes, dataType, envJsonObj.correlation_id);
+            logTrace(envJsonObj.correlation_id, `Direct transport: deserialized data type=${typeof data}, constructor=${data?.constructor?.name}`);
+
+            payloadsList.push([dataname, data, dataType]);
+        } else if (transport === 'link') {
+            // Extract download URL from the payload
+            const url = payloadObj.data;
+            logTrace(envJsonObj.correlation_id, `Link transport - fetching '${dataname}' from URL: ${url}`);
+
+            // Fetch with exponential backoff using the download handler
+            const downloadedData = await fileserver_download_handler(
+                url,
+                max_retries,
+                base_delay,
+                max_delay,
+                envJsonObj.correlation_id
+            );
+
+            // Deserialize based on type
+            const dataType = payloadObj.payload_type;
+            const data = await deserializeData(downloadedData, dataType, envJsonObj.correlation_id);
+
+            payloadsList.push([dataname, data, dataType]);
+        } else {
+            throw new Error(`Unknown transport type for payload '${dataname}': ${transport}`);
+        }
+    }
+
+    logTrace(envJsonObj.correlation_id, `smartreceive: Successfully processed all ${payloadsList.length} payloads`);
+    envJsonObj.payloads = payloadsList;
+    return envJsonObj;
+}
+
+// ---------------------------------------------- Module Exports ---------------------------------------------- //
+
+const NATSBridgeCSR = {
+    /**
+     * NATS client class for connection management
+     */
+    NATSClient,
+
+    /**
+     * Send data via NATS with automatic transport selection
+     */
+    smartsend,
+
+    /**
+     * Receive and process NATS message
+     */
+    smartreceive,
+
+    /**
+     * Upload data to plik server in one-shot mode
+     */
+    plikOneshotUpload,
+
+    /**
+     * Fetch data from URL with exponential backoff
+     */
+    fetchWithBackoff,
+
+    /**
+     * Default constants
+     */
+    DEFAULT_SIZE_THRESHOLD,
+    DEFAULT_BROKER_URL,
+    DEFAULT_FILESERVER_URL
+};
+
+export default NATSBridgeCSR;

src/natsbridge_mpy.py

@@ -0,0 +1,673 @@
+"""
+NATSBridge - Cross-Platform Bi-Directional Data Bridge
+MicroPython Implementation
+
+This module provides functionality for sending and receiving data across network boundaries
+using NATS as the message bus, with support for both direct payload transport and
+URL-based transport for larger payloads.
+
+Note: MicroPython has significant constraints compared to desktop implementations:
+- Limited memory (~256KB - 1MB)
+- No Arrow IPC support (memory constraints)
+- Synchronous API (no async/await)
+- Lower size threshold for direct transport
+"""
+
+import network
+import time
+import json
+import base64
+import uos
+import struct
+import random
+
+# ---------------------------------------------- Constants ---------------------------------------------- #
+
+"""
+Default size threshold for switching from direct to link transport (100KB for MicroPython)
+"""
+DEFAULT_SIZE_THRESHOLD = 100000
+
+"""
+Default NATS server URL
+"""
+DEFAULT_BROKER_URL = "nats://localhost:4222"
+
+"""
+Default HTTP file server URL for link transport
+"""
+DEFAULT_FILESERVER_URL = "http://localhost:8080"
+
+"""
+Hard limit for payload size in MicroPython (50KB)
+"""
+MAX_PAYLOAD_SIZE = 50000
+
+
+# ---------------------------------------------- Utility Functions ---------------------------------------------- #
+
+def log_trace(correlation_id, message):
+    """
+    Log a trace message with correlation ID and timestamp.
+    
+    Args:
+        correlation_id: Correlation ID for tracing
+        message: Message content to log
+    """
+    timestamp = time.strftime('%Y-%m-%dT%H:%M:%SZ', time.localtime())
+    print(f"[{timestamp}] [Correlation: {correlation_id}] {message}")
+
+
+def _generate_uuid():
+    """
+    Generate a simple UUID compatible with MicroPython.
+    
+    Returns:
+        UUID string
+    """
+    # Generate a simple UUID-like string
+    # Format: xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
+    hex_chars = '0123456789abcdef'
+    uuid_str = ''.join([random.choice(hex_chars) for _ in range(32)])
+    # Insert hyphens at proper positions
+    return f"{uuid_str[:8]}-{uuid_str[8:12]}-{uuid_str[12:16]}-{uuid_str[16:20]}-{uuid_str[20:]}"
+
+
+# ---------------------------------------------- Serialization Functions ---------------------------------------------- #
+
+def _serialize_data(data, payload_type):
+    """
+    Serialize data according to specified format.
+    
+    Args:
+        data: Data to serialize (string for "text", dict for "dictionary",
+              bytes for "image", "audio", "video", "binary")
+        payload_type: Target format: "text", "dictionary", "image", "audio", "video", "binary"
+    
+    Returns:
+        Binary representation of the serialized data
+    
+    Note:
+        MicroPython does not support "table" type due to memory constraints.
+    
+    Raises:
+        ValueError: If payload_type is not one of the supported types
+    """
+    if payload_type == 'text':
+        if isinstance(data, str):
+            return data.encode('utf-8')
+        else:
+            raise ValueError('Text data must be a string')
+    elif payload_type == 'dictionary':
+        json_str = json.dumps(data)
+        return json_str.encode('utf-8')
+    elif payload_type in ('image', 'audio', 'video', 'binary'):
+        if isinstance(data, (bytes, bytearray, memoryview)):
+            return bytes(data)
+        else:
+            raise ValueError(f'{payload_type} data must be bytes')
+    else:
+        raise ValueError(f'Unknown payload_type: {payload_type}')
+
+
+def _deserialize_data(data, payload_type):
+    """
+    Deserialize bytes to data based on type.
+    
+    Args:
+        data: Serialized data as bytes
+        payload_type: Data type ("text", "dictionary", "image", "audio", "video", "binary")
+    
+    Returns:
+        Deserialized data (String for "text", dict for "dictionary", bytes for others)
+    
+    Note:
+        MicroPython does not support "table" type due to memory constraints.
+    
+    Raises:
+        ValueError: If payload_type is not one of the supported types
+    """
+    if payload_type == 'text':
+        return data.decode('utf-8')
+    elif payload_type == 'dictionary':
+        json_str = data.decode('utf-8')
+        return json.loads(json_str)
+    elif payload_type in ('image', 'audio', 'video', 'binary'):
+        return data
+    else:
+        raise ValueError(f'Unknown payload_type: {payload_type}')
+
+
+# ---------------------------------------------- File Server Handlers ---------------------------------------------- #
+
+def _sync_fileserver_upload(file_server_url, dataname, data):
+    """
+    Synchronous file upload to HTTP server.
+    
+    Note:
+        This is a simplified implementation for MicroPython.
+        In practice, would use network.HTTP or similar.
+        Currently raises NotImplementedError as file upload is not fully supported.
+    
+    Args:
+        file_server_url: Base URL of the file server
+        dataname: Name of the file being uploaded
+        data: Raw byte data of the file content
+    
+    Returns:
+        Dict with keys: 'status', 'url'
+    
+    Raises:
+        NotImplementedError: File upload is not implemented in MicroPython
+    """
+    raise NotImplementedError("File upload not fully implemented in MicroPython. "
+                              "Use direct transport only for memory-constrained devices.")
+
+
+def _sync_fileserver_download(url, max_retries, base_delay, max_delay, correlation_id):
+    """
+    Synchronous file download with exponential backoff.
+    
+    Note:
+        This is a simplified implementation for MicroPython.
+        In practice, would use network.HTTP or similar.
+        Currently raises NotImplementedError as file download is not fully supported.
+    
+    Args:
+        url: URL to download from
+        max_retries: Maximum retry attempts
+        base_delay: Initial delay in ms
+        max_delay: Maximum delay in ms
+        correlation_id: Correlation ID for logging
+    
+    Returns:
+        Downloaded bytes
+    
+    Raises:
+        NotImplementedError: File download is not implemented in MicroPython
+    """
+    raise NotImplementedError("File download not fully implemented in MicroPython. "
+                              "Use direct transport only for memory-constrained devices.")
+
+
+# ---------------------------------------------- NATS Client ---------------------------------------------- #
+
+class NATSClient:
+    """
+    NATS client wrapper for MicroPython.
+    
+    Note:
+        This is a simplified implementation for MicroPython.
+        Full NATS client implementation would require additional network stack support.
+    """
+    
+    def __init__(self, url=DEFAULT_BROKER_URL):
+        """
+        Initialize NATS client.
+        
+        Args:
+            url: NATS server URL
+        """
+        self.url = url
+        self._connected = False
+    
+    def connect(self):
+        """
+        Connect to NATS server.
+        
+        Note:
+            This is a placeholder implementation.
+            Actual NATS client would require network stack support.
+        
+        Returns:
+            True if connected, False otherwise
+        """
+        # Placeholder - actual implementation would connect to NATS server
+        self._connected = True
+        return self._connected
+    
+    def publish(self, subject, message):
+        """
+        Publish message to NATS subject.
+        
+        Note:
+            This is a placeholder implementation.
+            Actual NATS client would require network stack support.
+        
+        Args:
+            subject: NATS subject to publish to
+            message: Message to publish
+        """
+        if not self._connected:
+            raise RuntimeError("Not connected to NATS server")
+        # Placeholder - actual implementation would publish to NATS
+        print(f"[NATS] Publish to {subject}: {message[:50]}...")
+    
+    def close(self):
+        """Close the NATS connection."""
+        self._connected = False
+
+
+# ---------------------------------------------- Core Functions ---------------------------------------------- #
+
+def _build_envelope(subject, payloads, options):
+    """
+    Build message envelope from payloads and metadata.
+    
+    Args:
+        subject: NATS subject
+        payloads: Array of payload objects
+        options: Envelope metadata options
+    
+    Returns:
+        Envelope dict
+    """
+    return {
+        'correlation_id': options['correlation_id'],
+        'msg_id': options['msg_id'],
+        'timestamp': time.strftime('%Y-%m-%dT%H:%M:%SZ', time.localtime()),
+        'send_to': subject,
+        'msg_purpose': options['msg_purpose'],
+        'sender_name': options['sender_name'],
+        'sender_id': options['sender_id'],
+        'receiver_name': options['receiver_name'],
+        'receiver_id': options['receiver_id'],
+        'reply_to': options['reply_to'],
+        'reply_to_msg_id': options['reply_to_msg_id'],
+        'broker_url': options['broker_url'],
+        'metadata': {},
+        'payloads': payloads
+    }
+
+
+def _build_payload(dataname, payload_type, payload_bytes, transport, data):
+    """
+    Build payload object from serialized data.
+    
+    Args:
+        dataname: Name of the payload
+        payload_type: Type of the payload
+        payload_bytes: Serialized payload bytes
+        transport: Transport type ("direct" or "link")
+        data: Data (base64 for direct, URL for link)
+    
+    Returns:
+        Payload dict
+    """
+    return {
+        'id': _generate_uuid(),
+        'dataname': dataname,
+        'payload_type': payload_type,
+        'transport': transport,
+        'encoding': 'base64' if transport == 'direct' else 'none',
+        'size': len(payload_bytes),
+        'data': data,
+        'metadata': {'payload_bytes': len(payload_bytes)} if transport == 'direct' else {}
+    }
+
+
+def _publish(subject, message, correlation_id):
+    """
+    Publish message to NATS.
+    
+    Note:
+        This is a simplified implementation for MicroPython.
+    
+    Args:
+        subject: NATS subject to publish to
+        message: JSON message to publish
+        correlation_id: Correlation ID for logging
+    """
+    log_trace(correlation_id, f"Publishing to {subject}")
+    # Placeholder - actual implementation would use NATSClient
+    # client = NATSClient()
+    # client.connect()
+    # client.publish(subject, message)
+    # client.close()
+
+
+def smartsend(subject, data, **kwargs):
+    """
+    Send data via NATS with automatic transport selection.
+    
+    This function intelligently routes data delivery based on payload size.
+    If the serialized payload is smaller than size_threshold, it encodes the data as Base64
+    and publishes directly over NATS. Otherwise, it uploads the data to a fileserver
+    and publishes only the download URL over NATS.
+    
+    Note:
+        MicroPython has memory constraints, so the default size_threshold is lower (100KB).
+        Table type is not supported due to memory constraints.
+    
+    Args:
+        subject: NATS subject to publish the message to
+        data: List of (dataname, data, type) tuples to send
+            - dataname: Name of the payload
+            - data: The actual data to send
+            - type: Payload type: "text", "dictionary", "image", "audio", "video", "binary"
+        broker_url: NATS server URL (default: DEFAULT_BROKER_URL)
+        fileserver_url: HTTP file server URL (default: DEFAULT_FILESERVER_URL)
+        fileserver_upload_handler: Function to handle fileserver uploads (default: _sync_fileserver_upload)
+        size_threshold: Threshold in bytes separating direct vs link transport (default: 100000)
+        correlation_id: Correlation ID for tracing (auto-generated if not provided)
+        msg_purpose: Purpose of the message (default: "chat")
+        sender_name: Name of the sender (default: "NATSBridge")
+        receiver_name: Name of the receiver (empty means broadcast)
+        receiver_id: UUID of the receiver (empty means broadcast)
+        reply_to: Topic to reply to (empty if no reply expected)
+        reply_to_msg_id: Message ID this message is replying to
+        is_publish: Whether to automatically publish the message (default: True)
+        msg_id: Message ID (auto-generated if not provided)
+        sender_id: Sender ID (auto-generated if not provided)
+    
+    Returns:
+        Tuple of (env, env_json_str) where:
+            - env: Dict containing all metadata and payloads
+            - env_json_str: JSON string for publishing to NATS
+    
+    Example:
+        >>> # Send text payload
+        >>> env, env_json_str = NATSBridge.smartsend(
+        ...     "/chat",
+        ...     [("message", "Hello!", "text")],
+        ...     broker_url="nats://localhost:4222"
+        ... )
+        >>>
+        >>> # Send dictionary payload
+        >>> env, env_json_str = NATSBridge.smartsend(
+        ...     "/config",
+        ...     [("config", {"key": "value"}, "dictionary")],
+        ...     broker_url="nats://localhost:4222"
+        ... )
+        >>>
+        >>> # Send binary payload (image, audio, video)
+        >>> env, env_json_str = NATSBridge.smartsend(
+        ...     "/media",
+        ...     [("image", image_bytes, "image")],
+        ...     broker_url="nats://localhost:4222"
+        ... )
+    """
+    # Extract options with defaults
+    correlation_id = kwargs.get('correlation_id', _generate_uuid())
+    msg_id = kwargs.get('msg_id', _generate_uuid())
+    sender_id = kwargs.get('sender_id', _generate_uuid())
+    broker_url = kwargs.get('broker_url', DEFAULT_BROKER_URL)
+    fileserver_url = kwargs.get('fileserver_url', DEFAULT_FILESERVER_URL)
+    size_threshold = kwargs.get('size_threshold', DEFAULT_SIZE_THRESHOLD)
+    msg_purpose = kwargs.get('msg_purpose', 'chat')
+    sender_name = kwargs.get('sender_name', 'NATSBridge')
+    receiver_name = kwargs.get('receiver_name', '')
+    receiver_id = kwargs.get('receiver_id', '')
+    reply_to = kwargs.get('reply_to', '')
+    reply_to_msg_id = kwargs.get('reply_to_msg_id', '')
+    is_publish = kwargs.get('is_publish', True)
+    fileserver_upload_handler = kwargs.get('fileserver_upload_handler', _sync_fileserver_upload)
+    
+    log_trace(correlation_id, f"Starting smartsend for subject: {subject}")
+    
+    # Process payloads
+    payloads = []
+    for dataname, payload_data, payload_type in data:
+        payload_bytes = _serialize_data(payload_data, payload_type)
+        payload_size = len(payload_bytes)
+        
+        # Check against hard limit for MicroPython
+        if payload_size > MAX_PAYLOAD_SIZE:
+            raise MemoryError(f"Payload '{dataname}' exceeds max size {MAX_PAYLOAD_SIZE} bytes")
+        
+        log_trace(correlation_id, f"Serialized payload '{dataname}' (type: {payload_type}) size: {payload_size} bytes")
+        
+        if payload_size < size_threshold:
+            # Direct path
+            payload_b64 = base64.b64encode(payload_bytes).decode('ascii')
+            log_trace(correlation_id, f"Using direct transport for {payload_size} bytes")
+            
+            payload = _build_payload(dataname, payload_type, payload_bytes, 'direct', payload_b64)
+            payloads.append(payload)
+        else:
+            # Link path (limited support)
+            log_trace(correlation_id, "Using link transport, uploading to fileserver")
+            
+            try:
+                response = fileserver_upload_handler(fileserver_url, dataname, payload_bytes)
+                log_trace(correlation_id, f"Uploaded to URL: {response['url']}")
+                
+                payload = _build_payload(dataname, payload_type, payload_bytes, 'link', response['url'])
+                payloads.append(payload)
+            except NotImplementedError:
+                # Fall back to direct transport if file upload not available
+                log_trace(correlation_id, "File upload not available, using direct transport")
+                payload_b64 = base64.b64encode(payload_bytes).decode('ascii')
+                payload = _build_payload(dataname, payload_type, payload_bytes, 'direct', payload_b64)
+                payloads.append(payload)
+    
+    # Build envelope
+    env = _build_envelope(subject, payloads, {
+        'correlation_id': correlation_id,
+        'msg_id': msg_id,
+        'msg_purpose': msg_purpose,
+        'sender_name': sender_name,
+        'sender_id': sender_id,
+        'receiver_name': receiver_name,
+        'receiver_id': receiver_id,
+        'reply_to': reply_to,
+        'reply_to_msg_id': reply_to_msg_id,
+        'broker_url': broker_url
+    })
+    
+    env_json_str = json.dumps(env)
+    
+    if is_publish:
+        _publish(subject, env_json_str, correlation_id)
+    
+    return env, env_json_str
+
+
+def smartreceive(msg, **kwargs):
+    """
+    Receive and process NATS message.
+    
+    This function processes incoming NATS messages, handling both direct transport
+    (base64 decoded payloads) and link transport (URL-based payloads).
+    It deserializes the data based on the transport type and returns the result.
+    
+    Note:
+        MicroPython has memory constraints, so large payloads should be avoided.
+        Table type is not supported due to memory constraints.
+    
+    Args:
+        msg: NATS message to process (can be string, dict, or object with 'payload' attribute)
+        fileserver_download_handler: Function to handle downloading data from file server URLs
+        max_retries: Maximum retry attempts (default: 3)
+        base_delay: Initial delay in ms (default: 100)
+        max_delay: Maximum delay in ms (default: 1000)
+    
+    Returns:
+        Dict with envelope metadata and payloads field containing List[Tuple[str, Any, str]]
+    
+    Example:
+        >>> # Receive and process message
+        >>> env = NATSBridge.smartreceive(msg, fileserver_download_handler=_sync_fileserver_download)
+        >>> # env is a Dict with "payloads" key containing List[Tuple[str, Any, str]]
+        >>> for dataname, data, type_ in env["payloads"]:
+        ...     print(f"{dataname}: {data} (type: {type_})")
+    """
+    # Parse the JSON envelope
+    if isinstance(msg, dict):
+        # Already parsed
+        env_json_obj = msg
+    elif hasattr(msg, 'payload'):
+        # Object with payload attribute
+        payload = msg.payload if isinstance(msg.payload, str) else msg.payload.decode('utf-8')
+        env_json_obj = json.loads(payload)
+    else:
+        # Assume it's already a JSON string or dict
+        env_json_obj = json.loads(msg) if isinstance(msg, str) else msg
+    
+    correlation_id = env_json_obj['correlation_id']
+    log_trace(correlation_id, "Processing received message")
+    
+    # Process all payloads in the envelope
+    payloads_list = []
+    num_payloads = len(env_json_obj['payloads'])
+    
+    for i in range(num_payloads):
+        payload_obj = env_json_obj['payloads'][i]
+        transport = payload_obj['transport']
+        dataname = payload_obj['dataname']
+        
+        if transport == 'direct':
+            log_trace(correlation_id, f"Direct transport - decoding payload '{dataname}'")
+            
+            # Extract base64 payload from the payload
+            payload_b64 = payload_obj['data']
+            
+            # Decode Base64 payload
+            payload_bytes = base64.b64decode(payload_b64)
+            
+            # Deserialize based on type
+            data_type = payload_obj['payload_type']
+            data = _deserialize_data(payload_bytes, data_type)
+            
+            payloads_list.append((dataname, data, data_type))
+        elif transport == 'link':
+            # Extract download URL from the payload
+            url = payload_obj['data']
+            log_trace(correlation_id, f"Link transport - fetching '{dataname}' from URL: {url}")
+            
+            # Fetch with exponential backoff using the download handler
+            fileserver_download_handler = kwargs.get('fileserver_download_handler', _sync_fileserver_download)
+            max_retries = kwargs.get('max_retries', 3)
+            base_delay = kwargs.get('base_delay', 100)
+            max_delay = kwargs.get('max_delay', 1000)
+            
+            downloaded_data = fileserver_download_handler(
+                url,
+                max_retries,
+                base_delay,
+                max_delay,
+                correlation_id
+            )
+            
+            # Deserialize based on type
+            data_type = payload_obj['payload_type']
+            data = _deserialize_data(downloaded_data, data_type)
+            
+            payloads_list.append((dataname, data, data_type))
+        else:
+            raise ValueError(f"Unknown transport type for payload '{dataname}': {transport}")
+    
+    env_json_obj['payloads'] = payloads_list
+    return env_json_obj
+
+
+# ---------------------------------------------- Module Exports ---------------------------------------------- #
+
+class NATSBridge:
+    """
+    MicroPython NATS bridge implementation.
+    
+    This class provides a convenient interface for NATSBridge functionality,
+    encapsulating the main functions and providing a class-based API.
+    
+    Note:
+        MicroPython has significant constraints:
+        - No Arrow IPC support (memory constraints)
+        - Only direct transport (< 100KB threshold enforced)
+        - Simplified UUID generation
+        - No async/await (synchronous API)
+    """
+    
+    DEFAULT_SIZE_THRESHOLD = DEFAULT_SIZE_THRESHOLD
+    DEFAULT_BROKER_URL = DEFAULT_BROKER_URL
+    DEFAULT_FILESERVER_URL = DEFAULT_FILESERVER_URL
+    MAX_PAYLOAD_SIZE = MAX_PAYLOAD_SIZE
+    
+    def __init__(self, broker_url=None, fileserver_url=None):
+        """
+        Initialize NATSBridge.
+        
+        Args:
+            broker_url: NATS server URL (defaults to DEFAULT_BROKER_URL)
+            fileserver_url: HTTP file server URL (defaults to DEFAULT_FILESERVER_URL)
+        """
+        self.broker_url = broker_url or self.DEFAULT_BROKER_URL
+        self.fileserver_url = fileserver_url or self.DEFAULT_FILESERVER_URL
+    
+    def smartsend(self, subject, data, **kwargs):
+        """
+        Send data via NATS.
+        
+        Args:
+            subject: NATS subject to publish to
+            data: List of (dataname, data, type) tuples
+            **kwargs: Additional options passed to smartsend
+        
+        Returns:
+            Tuple of (env, env_json_str)
+        """
+        kwargs['broker_url'] = kwargs.get('broker_url', self.broker_url)
+        kwargs['fileserver_url'] = kwargs.get('fileserver_url', self.fileserver_url)
+        return smartsend(subject, data, **kwargs)
+    
+    def smartreceive(self, msg, **kwargs):
+        """
+        Receive and process NATS message.
+        
+        Args:
+            msg: NATS message to process
+            **kwargs: Additional options passed to smartreceive
+        
+        Returns:
+            Dict with envelope metadata and payloads
+        """
+        return smartreceive(msg, **kwargs)
+
+
+# Convenience functions for module-level usage
+def send(subject, data, **kwargs):
+    """
+    Convenience function for sending data.
+    
+    Args:
+        subject: NATS subject to publish to
+        data: List of (dataname, data, type) tuples
+        **kwargs: Additional options
+    
+    Returns:
+        Tuple of (env, env_json_str)
+    """
+    return smartsend(subject, data, **kwargs)
+
+
+def receive(msg, **kwargs):
+    """
+    Convenience function for receiving messages.
+    
+    Args:
+        msg: NATS message to process
+        **kwargs: Additional options
+    
+    Returns:
+        Dict with envelope metadata and payloads
+    """
+    return smartreceive(msg, **kwargs)
+
+
+__all__ = [
+    'smartsend',
+    'smartreceive',
+    'NATSBridge',
+    'send',
+    'receive',
+    'DEFAULT_SIZE_THRESHOLD',
+    'DEFAULT_BROKER_URL',
+    'DEFAULT_FILESERVER_URL',
+    'MAX_PAYLOAD_SIZE',
+    'NATSClient',
+    '_serialize_data',
+    '_deserialize_data',
+    'log_trace',
+    '_sync_fileserver_upload',
+    '_sync_fileserver_download'
+]

src/natsbridge_ssr.js

@@ -0,0 +1,798 @@
+/**
+ * NATSBridge - Cross-Platform Bi-Directional Data Bridge
+ * JavaScript/Node.js Implementation (Client-Side Rendering)
+ * 
+ * This module provides functionality for sending and receiving data across network boundaries
+ * using NATS as the message bus, with support for both direct payload transport and
+ * URL-based transport for larger payloads.
+ * 
+ * Supported payload types: "text", "dictionary", "arrowtable", "jsontable", "image", "audio", "video", "binary"
+ * 
+ * @module NATSBridge
+ */
+
+const nats = require('nats');
+const crypto = require('crypto');
+// Use native fetch available in Node.js 18+
+const arrow = require('apache-arrow');
+
+// ---------------------------------------------- UUID Helper ---------------------------------------------- //
+
+/**
+ * Generate UUID v4 using crypto module (Node.js compatible)
+ * @returns {string} UUID string
+ */
+function uuidv4() {
+    return crypto.randomUUID();
+}
+
+// ---------------------------------------------- Constants ---------------------------------------------- //
+
+/**
+ * Default size threshold for switching from direct to link transport (0.5MB)
+ */
+const DEFAULT_SIZE_THRESHOLD = 500_000;
+
+/**
+ * Default NATS server URL
+ */
+const DEFAULT_BROKER_URL = 'nats://localhost:4222';
+
+/**
+ * Default HTTP file server URL for link transport
+ */
+const DEFAULT_FILESERVER_URL = 'http://localhost:8080';
+
+// ---------------------------------------------- Utility Functions ---------------------------------------------- //
+
+/**
+ * Convert Buffer to Base64 string
+ * @param {Buffer} buffer - Buffer to encode
+ * @returns {string} Base64 encoded string
+ */
+function bufferToBase64(buffer) {
+    return buffer.toString('base64');
+}
+
+/**
+ * Log a trace message with correlation ID and timestamp
+ * @param {string} correlationId - Correlation ID for tracing
+ * @param {string} message - Message content to log
+ */
+function logTrace(correlationId, message) {
+    const timestamp = new Date().toISOString();
+    console.log(`[${timestamp}] [Correlation: ${correlationId}] ${message}`);
+}
+
+// ---------------------------------------------- Serialization Functions ---------------------------------------------- //
+
+/**
+ * Serialize data according to specified format
+ * @param {any} data - Data to serialize
+ * @param {string} payloadType - Target format: "text", "dictionary", "arrowtable", "jsontable", "image", "audio", "video", "binary"
+ * @returns {Buffer} Binary representation of the serialized data
+ */
+async function serializeData(data, payloadType) {
+    if (payloadType === 'text') {
+        if (typeof data === 'string') {
+            return Buffer.from(data, 'utf8');
+        } else {
+            throw new Error('Text data must be a string');
+        }
+    } else if (payloadType === 'dictionary') {
+        const jsonStr = JSON.stringify(data);
+        return Buffer.from(jsonStr, 'utf8');
+    } else if (payloadType === 'arrowtable') {
+        // Convert array of objects to Arrow IPC format
+        if (!Array.isArray(data) || data.length === 0) {
+            throw new Error('Arrow table data must be a non-empty array of objects');
+        }
+        
+        return serializeArrowTable(data);
+    } else if (payloadType === 'jsontable') {
+        // Serialize array of objects to JSON format
+        if (!Array.isArray(data)) {
+            throw new Error('JSON table data must be an array');
+        }
+        const jsonStr = JSON.stringify(data);
+        return Buffer.from(jsonStr, 'utf8');
+    } else if (payloadType === 'image') {
+        if (data instanceof Uint8Array || Buffer.isBuffer(data)) {
+            return Buffer.from(data);
+        } else {
+            throw new Error('Image data must be Uint8Array or Buffer');
+        }
+    } else if (payloadType === 'audio') {
+        if (data instanceof Uint8Array || Buffer.isBuffer(data)) {
+            return Buffer.from(data);
+        } else {
+            throw new Error('Audio data must be Uint8Array or Buffer');
+        }
+    } else if (payloadType === 'video') {
+        if (data instanceof Uint8Array || Buffer.isBuffer(data)) {
+            return Buffer.from(data);
+        } else {
+            throw new Error('Video data must be Uint8Array or Buffer');
+        }
+    } else if (payloadType === 'binary') {
+        if (data instanceof Uint8Array || Buffer.isBuffer(data)) {
+            return Buffer.from(data);
+        } else {
+            throw new Error('Binary data must be Uint8Array or Buffer');
+        }
+    } else {
+        throw new Error(`Unknown payload_type: ${payloadType}`);
+    }
+}
+
+/**
+ * Helper function to properly serialize table data to Arrow IPC
+ * @param {Array<Object>} data - Array of objects representing table rows
+ * @returns {Buffer} Arrow IPC formatted buffer
+ */
+function serializeArrowTable(data) {
+    if (!Array.isArray(data) || data.length === 0) {
+        throw new Error('Table data must be a non-empty array of objects');
+    }
+    
+    logTrace('serializeArrowTable', `Serializing table with ${data.length} rows`);
+    
+    // Use arrow.tableFromArrays which handles the conversion properly
+    // Convert array of objects to a key-value format expected by tableFromArrays
+    const columns = {};
+    for (const key of Object.keys(data[0])) {
+        columns[key] = data.map(row => row[key]);
+    }
+    
+    logTrace('serializeArrowTable', `Columns: ${Object.keys(columns).join(', ')}`);
+    
+    const table = arrow.tableFromArrays(columns);
+    
+    logTrace('serializeArrowTable', `Arrow table created with ${table.numRows} rows, ${table.numCols} cols`);
+    
+    // Convert to IPC format
+    const ipcBuffer = arrow.tableToIPC(table);
+    
+    logTrace('serializeArrowTable', `IPC buffer type: ${typeof ipcBuffer}, length: ${ipcBuffer.byteLength}`);
+    
+    const resultBuffer = Buffer.from(ipcBuffer);
+    logTrace('serializeArrowTable', `Result buffer: ${resultBuffer.length} bytes`);
+    
+    // Debug: Show first 20 bytes in hex
+    const hexPreview = resultBuffer.slice(0, 20).toString('hex');
+    logTrace('serializeArrowTable', `First 20 bytes (hex): ${hexPreview}`);
+    
+    return resultBuffer;
+}
+
+/**
+ * Deserialize bytes to data based on type
+ * @param {Buffer|Uint8Array} data - Serialized data as bytes
+ * @param {string} payloadType - Data type
+ * @param {string} correlationId - Correlation ID for logging
+ * @returns {any} Deserialized data
+ */
+async function deserializeData(data, payloadType, correlationId) {
+    const buffer = Buffer.isBuffer(data) ? data : Buffer.from(data);
+    
+    logTrace(correlationId, `deserializeData: type=${payloadType}, bufferLength=${buffer.length}`);
+    
+    // Debug: Show first 20 bytes in hex for binary data
+    if (payloadType === 'arrowtable' || payloadType === 'jsontable' || payloadType === 'image' || payloadType === 'binary') {
+        const hexPreview = buffer.slice(0, 20).toString('hex');
+        logTrace(correlationId, `deserializeData: First 20 bytes (hex): ${hexPreview}`);
+    }
+    
+    if (payloadType === 'text') {
+        const result = buffer.toString('utf8');
+        logTrace(correlationId, `deserializeData: text result length=${result.length}`);
+        return result;
+    } else if (payloadType === 'dictionary') {
+        const jsonStr = buffer.toString('utf8');
+        const result = JSON.parse(jsonStr);
+        logTrace(correlationId, `deserializeData: dictionary keys=${Object.keys(result).join(', ')}`);
+        return result;
+    } else if (payloadType === 'arrowtable') {
+        logTrace(correlationId, `deserializeData: Attempting Arrow table deserialization`);
+        
+        // Debug: Check available arrow methods
+        logTrace(correlationId, `deserializeData: arrow.tableFromRawBytes exists: ${typeof arrow.tableFromRawBytes}`);
+        logTrace(correlationId, `deserializeData: arrow.tableFromIPC exists: ${typeof arrow.tableFromIPC}`);
+        
+        try {
+            // Try tableFromRawBytes first (older API)
+            if (typeof arrow.tableFromRawBytes === 'function') {
+                logTrace(correlationId, `deserializeData: Using tableFromRawBytes`);
+                const table = arrow.tableFromRawBytes(buffer);
+                logTrace(correlationId, `deserializeData: Arrow table - rows=${table.numRows}, cols=${table.numCols}`);
+                return table;
+            }
+        } catch (e) {
+            logTrace(correlationId, `deserializeData: tableFromRawBytes failed: ${e.message}`);
+        }
+        
+        try {
+            // Try tableFromIPC (newer API)
+            if (typeof arrow.tableFromIPC === 'function') {
+                logTrace(correlationId, `deserializeData: Using tableFromIPC`);
+                const table = arrow.tableFromIPC(buffer);
+                logTrace(correlationId, `deserializeData: Arrow table from IPC - rows=${table.numRows}, cols=${table.numCols}`);
+                return table;
+            }
+        } catch (e) {
+            logTrace(correlationId, `deserializeData: tableFromIPC failed: ${e.message}`);
+        }
+        
+        throw new Error(`Unable to deserialize Arrow table: neither tableFromRawBytes nor tableFromIPC worked`);
+    } else if (payloadType === 'jsontable') {
+        const jsonStr = buffer.toString('utf8');
+        const result = JSON.parse(jsonStr);
+        logTrace(correlationId, `deserializeData: jsontable result length=${Array.isArray(result) ? result.length : 'N/A'}`);
+        return result;
+    } else if (payloadType === 'image') {
+        logTrace(correlationId, `deserializeData: image buffer length=${buffer.length}`);
+        return buffer;
+    } else if (payloadType === 'audio') {
+        logTrace(correlationId, `deserializeData: audio buffer length=${buffer.length}`);
+        return buffer;
+    } else if (payloadType === 'video') {
+        logTrace(correlationId, `deserializeData: video buffer length=${buffer.length}`);
+        return buffer;
+    } else if (payloadType === 'binary') {
+        logTrace(correlationId, `deserializeData: binary buffer length=${buffer.length}`);
+        return buffer;
+    } else {
+        throw new Error(`Unknown payload_type: ${payloadType}`);
+    }
+}
+
+// ---------------------------------------------- File Server Handlers ---------------------------------------------- //
+
+/**
+ * Upload data to plik server in one-shot mode
+ * @param {string} fileServerUrl - Base URL of the plik server
+ * @param {string} dataname - Name of the file being uploaded
+ * @param {Buffer|Uint8Array} data - Raw byte data of the file content
+ * @returns {Promise<{status: number, uploadid: string, fileid: string, url: string}>}
+ */
+async function plikOneshotUpload(fileServerUrl, dataname, data) {
+    const buffer = Buffer.isBuffer(data) ? data : Buffer.from(data);
+    
+    // Get upload id
+    const urlGetUploadID = `${fileServerUrl}/upload`;
+    const headers = { 'Content-Type': 'application/json' };
+    const body = JSON.stringify({ OneShot: true });
+    
+    const httpResponse = await fetch(urlGetUploadID, {
+        method: 'POST',
+        headers,
+        body
+    });
+    
+    const responseJson = await httpResponse.json();
+    const uploadid = responseJson.id;
+    const uploadtoken = responseJson.uploadToken;
+
+    // Upload file
+    const urlUpload = `${fileServerUrl}/file/${uploadid}`;
+    const form = new FormData();
+    const blob = new Blob([buffer], { type: 'application/octet-stream' });
+    form.append('file', blob, dataname);
+    
+    const uploadHeaders = {
+        'X-UploadToken': uploadtoken
+    };
+
+    const uploadResponse = await fetch(urlUpload, {
+        method: 'POST',
+        headers: uploadHeaders,
+        body: form
+    });
+    
+    const uploadJson = await uploadResponse.json();
+    const fileid = uploadJson.id;
+
+    const url = `${fileServerUrl}/file/${uploadid}/${fileid}/${dataname}`;
+
+    return {
+        status: uploadResponse.status,
+        uploadid,
+        fileid,
+        url
+    };
+}
+
+/**
+ * Fetch data from URL with exponential backoff
+ * @param {string} url - URL to fetch from
+ * @param {number} maxRetries - Maximum number of retry attempts
+ * @param {number} baseDelay - Initial delay in milliseconds
+ * @param {number} maxDelay - Maximum delay in milliseconds
+ * @param {string} correlationId - Correlation ID for logging
+ * @returns {Promise<Uint8Array>} Fetched data as bytes
+ */
+async function fetchWithBackoff(url, maxRetries, baseDelay, maxDelay, correlationId) {
+    let delay = baseDelay;
+    
+    for (let attempt = 1; attempt <= maxRetries; attempt++) {
+        try {
+            const response = await fetch(url);
+            
+            if (response.status === 200) {
+                logTrace(correlationId, `Successfully fetched data from ${url} on attempt ${attempt}`);
+                const arrayBuffer = await response.arrayBuffer();
+                return new Uint8Array(arrayBuffer);
+            } else {
+                throw new Error(`Failed to fetch: ${response.status}`);
+            }
+        } catch (e) {
+            logTrace(correlationId, `Attempt ${attempt} failed: ${e.constructor.name} - ${e.message}`);
+            
+            if (attempt < maxRetries) {
+                await new Promise(resolve => setTimeout(resolve, delay));
+                delay = Math.min(delay * 2, maxDelay);
+            }
+        }
+    }
+    
+    throw new Error(`Failed to fetch data after ${maxRetries} attempts`);
+}
+
+// ---------------------------------------------- NATS Client ---------------------------------------------- //
+
+/**
+ * NATS client wrapper for connection management
+ */
+class NATSClient {
+    /**
+     * Create a new NATS client
+     * @param {string} url - NATS server URL
+     */
+    constructor(url) {
+        this.url = url;
+        this.connection = null;
+    }
+
+    /**
+     * Connect to NATS server
+     * @returns {Promise<NATS.Connection>}
+     */
+    async connect() {
+        this.connection = await nats.connect({ servers: this.url });
+        return this.connection;
+    }
+
+    /**
+     * Publish message to NATS subject
+     * @param {string} subject - NATS subject to publish to
+     * @param {string} message - Message to publish
+     * @param {string} correlationId - Correlation ID for logging
+     */
+    async publish(subject, message, correlationId) {
+        if (!this.connection) {
+            await this.connect();
+        }
+        await this.connection.publish(subject, message);
+        logTrace(correlationId, `Message published to ${subject}`);
+    }
+
+    /**
+     * Close the NATS connection
+     */
+    async close() {
+        if (this.connection) {
+            this.connection.close();
+        }
+    }
+}
+
+// ---------------------------------------------- Core Functions ---------------------------------------------- //
+
+/**
+ * Publish message to NATS
+ * @param {string|NATSClient|NATS.Connection} brokerUrlOrClient - NATS URL, client, or connection
+ * @param {string} subject - NATS subject to publish to
+ * @param {string} message - JSON message to publish
+ * @param {string} correlationId - Correlation ID for tracing
+ */
+async function publishMessage(brokerUrlOrClient, subject, message, correlationId) {
+    let conn;
+    
+    if (brokerUrlOrClient instanceof NATSClient) {
+        conn = brokerUrlOrClient;
+    } else if (brokerUrlOrClient && typeof brokerUrlOrClient.publish === 'function') {
+        // Create a wrapper for direct connection (duck-typing check for NATS connection)
+        conn = {
+            async publish(subj, msg) {
+                await brokerUrlOrClient.publish(subj, msg);
+            },
+            async close() {
+                await brokerUrlOrClient.close();
+            }
+        };
+    } else {
+        // String URL - create new client
+        const client = new NATSClient(brokerUrlOrClient);
+        conn = client;
+    }
+    
+    await conn.publish(subject, message, correlationId);
+    
+    if (conn instanceof NATSClient) {
+        await conn.close();
+    }
+}
+
+/**
+ * Build message envelope from payloads and metadata
+ * @param {string} subject - NATS subject
+ * @param {Array} payloads - Array of payload objects
+ * @param {Object} options - Envelope metadata options
+ * @returns {Object} Envelope object
+ */
+function buildEnvelope(subject, payloads, options) {
+    return {
+        correlation_id: options.correlation_id,
+        msg_id: options.msg_id,
+        timestamp: new Date().toISOString(),
+        send_to: subject,
+        msg_purpose: options.msg_purpose,
+        sender_name: options.sender_name,
+        sender_id: options.sender_id,
+        receiver_name: options.receiver_name,
+        receiver_id: options.receiver_id,
+        reply_to: options.reply_to,
+        reply_to_msg_id: options.reply_to_msg_id,
+        broker_url: options.broker_url,
+        metadata: options.metadata || {},
+        payloads: payloads
+    };
+}
+
+/**
+ * Build payload object from serialized data
+ * @param {string} dataname - Name of the payload
+ * @param {string} payloadType - Type of the payload
+ * @param {Buffer} payloadBytes - Serialized payload bytes
+ * @param {string} transport - Transport type ("direct" or "link")
+ * @param {string} data - Data (base64 for direct, URL for link)
+ * @returns {Object} Payload object
+ */
+function buildPayload(dataname, payloadType, payloadBytes, transport, data) {
+    // Determine encoding based on payload type (matching Julia implementation)
+    let encoding = 'base64';
+    if (payloadType === 'jsontable') {
+        encoding = 'json';
+    } else if (payloadType === 'arrowtable') {
+        encoding = 'arrow-ipc';
+    }
+    
+    return {
+        id: uuidv4(),
+        dataname,
+        payload_type: payloadType,
+        transport,
+        encoding,
+        size: payloadBytes.byteLength,
+        data,
+        metadata: transport === 'direct' ? { payload_bytes: payloadBytes.byteLength } : {}
+    };
+}
+
+/**
+ * Send data via NATS with automatic transport selection
+ * 
+ * This function intelligently routes data delivery based on payload size.
+ * If the serialized payload is smaller than size_threshold, it encodes the data as Base64
+ * and publishes directly over NATS. Otherwise, it uploads the data to a fileserver
+ * and publishes only the download URL over NATS.
+ * 
+ * @param {string} subject - NATS subject to publish the message to
+ * @param {Array} data - List of [dataname, data, type] tuples to send
+ *          - type: "text", "dictionary", "arrowtable", "jsontable", "image", "audio", "video", "binary"
+ * @param {Object} options - Optional configuration
+ * @param {string} [options.broker_url=DEFAULT_BROKER_URL] - URL of the NATS server
+ * @param {string} [options.fileserver_url=DEFAULT_FILESERVER_URL] - URL of the HTTP file server
+ * @param {Function} [options.fileserver_upload_handler=plikOneshotUpload] - Function to handle fileserver uploads
+ * @param {number} [options.size_threshold=DEFAULT_SIZE_THRESHOLD] - Threshold separating direct vs link transport
+ * @param {string} [options.correlation_id=crypto.randomUUID()] - Correlation ID for tracing
+ * @param {string} [options.msg_purpose="chat"] - Purpose of the message
+ * @param {string} [options.sender_name="NATSBridge"] - Name of the sender
+ * @param {string} [options.receiver_name=""] - Name of the receiver (empty means broadcast)
+ * @param {string} [options.receiver_id=""] - UUID of the receiver (empty means broadcast)
+ * @param {string} [options.reply_to=""] - Topic to reply to
+ * @param {string} [options.reply_to_msg_id=""] - Message ID this message is replying to
+ * @param {boolean} [options.is_publish=true] - Whether to automatically publish the message
+ * @param {NATSClient|NATS.Connection} [options.nats_connection=null] - Pre-existing NATS connection
+ * @param {string} [options.msg_id=crypto.randomUUID()] - Message ID
+ * @param {string} [options.sender_id=crypto.randomUUID()] - Sender ID
+ * @returns {Promise<[Object, string]>} Tuple of [env, env_json_str]
+ * 
+ * @example
+ * // Send a single payload
+ * const [env, envJsonStr] = await smartsend(
+ *     "/test",
+ *     [["dataname1", data1, "dictionary"]],
+ *     { broker_url: "nats://localhost:4222" }
+ * );
+ * 
+ * // Send multiple payloads
+ * const [env, envJsonStr] = await smartsend(
+ *     "/test",
+ *     [
+ *         ["dataname1", data1, "dictionary"],
+ *         ["dataname2", data2, "arrowtable"]
+ *     ],
+ *     { broker_url: "nats://localhost:4222" }
+ * );
+ * 
+ * // Send with pre-existing connection
+ * const client = await NATSBridge.NATSClient.connect("nats://localhost:4222");
+ * const [env, envJsonStr] = await smartsend(
+ *     "/test",
+ *     [["data", myData, "text"]],
+ *     { nats_connection: client }
+ * );
+ */
+async function smartsend(subject, data, options = {}) {
+    const {
+        broker_url = DEFAULT_BROKER_URL,
+        fileserver_url = DEFAULT_FILESERVER_URL,
+        fileserver_upload_handler = plikOneshotUpload,
+        size_threshold = DEFAULT_SIZE_THRESHOLD,
+        correlation_id = uuidv4(),
+        msg_purpose = 'chat',
+        sender_name = 'NATSBridge',
+        receiver_name = '',
+        receiver_id = '',
+        reply_to = '',
+        reply_to_msg_id = '',
+        is_publish = true,
+        nats_connection = null,
+        msg_id = uuidv4(),
+        sender_id = uuidv4()
+    } = options;
+
+    logTrace(correlation_id, `Starting smartsend for subject: ${subject}`);
+    logTrace(correlation_id, `smartsend: data array length=${data.length}`);
+    
+    // Debug: Log input data structure
+    for (let i = 0; i < data.length; i++) {
+        const [dataname, payloadData, payloadType] = data[i];
+        logTrace(correlation_id, `smartsend: payload[${i}] dataname=${dataname}, type=${payloadType}, data type=${typeof payloadData}, constructor=${payloadData?.constructor?.name}`);
+    }
+
+    // Process payloads
+    const payloads = [];
+    for (const [dataname, payloadData, payloadType] of data) {
+        logTrace(correlation_id, `smartsend: Processing payload '${dataname}' type=${payloadType}`);
+        logTrace(correlation_id, `smartsend: payloadData type=${typeof payloadData}, constructor=${payloadData?.constructor?.name}`);
+        
+        const payloadBytes = await serializeData(payloadData, payloadType);
+        const payloadSize = payloadBytes.byteLength;
+
+        logTrace(correlation_id, `Serialized payload '${dataname}' (type: ${payloadType}) size: ${payloadSize} bytes`);
+
+        // Debug: Show first 20 bytes of serialized data for table type
+        if (payloadType === 'table') {
+            const hexPreview = payloadBytes.slice(0, 20).toString('hex');
+            logTrace(correlation_id, `Serialized table data first 20 bytes (hex): ${hexPreview}`);
+        }
+
+        if (payloadSize < size_threshold) {
+            // Direct path
+            const payloadB64 = bufferToBase64(payloadBytes);
+            logTrace(correlation_id, `Using direct transport for ${payloadSize} bytes, base64 length=${payloadB64.length}`);
+
+            const payload = buildPayload(dataname, payloadType, payloadBytes, 'direct', payloadB64);
+            payloads.push(payload);
+        } else {
+            // Link path
+            logTrace(correlation_id, `Using link transport, uploading to fileserver`);
+
+            const response = await fileserver_upload_handler(fileserver_url, dataname, payloadBytes);
+
+            if (response.status !== 200) {
+                throw new Error(`Failed to upload data to fileserver: ${response.status}`);
+            }
+
+            logTrace(correlation_id, `Uploaded to URL: ${response.url}`);
+
+            const payload = buildPayload(dataname, payloadType, payloadBytes, 'link', response.url);
+            payloads.push(payload);
+        }
+    }
+
+    // Build envelope
+    const env = buildEnvelope(subject, payloads, {
+        correlation_id,
+        msg_id,
+        msg_purpose,
+        sender_name,
+        sender_id,
+        receiver_name,
+        receiver_id,
+        reply_to,
+        reply_to_msg_id,
+        broker_url
+    });
+
+    const env_json_str = JSON.stringify(env);
+
+    if (is_publish) {
+        if (nats_connection) {
+            await publishMessage(nats_connection, subject, env_json_str, correlation_id);
+        } else {
+            await publishMessage(broker_url, subject, env_json_str, correlation_id);
+        }
+    }
+
+    return [env, env_json_str];
+}
+
+/**
+ * Receive and process NATS message
+ * 
+ * This function processes incoming NATS messages, handling both direct transport
+ * (base64 decoded payloads) and link transport (URL-based payloads).
+ * It deserializes the data based on the transport type and returns the result.
+ * 
+ * @param {Object} msg - NATS message object with payload property
+ * @param {Object} options - Optional configuration
+ * @param {Function} [options.fileserver_download_handler=fetchWithBackoff] - Function to handle fileserver downloads
+ * @param {number} [options.max_retries=5] - Maximum retry attempts for fetching URL
+ * @param {number} [options.base_delay=100] - Initial delay for exponential backoff in ms
+ * @param {number} [options.max_delay=5000] - Maximum delay for exponential backoff in ms
+ * @returns {Promise<Object>} Envelope object with processed payloads
+ * 
+ * @example
+ * // Receive and process message
+ * const env = await smartreceive(msg, {
+ *     fileserver_download_handler: fetchWithBackoff,
+ *     max_retries: 5,
+ *     base_delay: 100,
+ *     max_delay: 5000
+ * });
+ * // env.payloads is an Array of [dataname, data, type] arrays
+ * for (const [dataname, data, type] of env.payloads) {
+ *     console.log(`${dataname}: ${data} (type: ${type})`);
+ * }
+ */
+async function smartreceive(msg, options = {}) {
+    const {
+        fileserver_download_handler = fetchWithBackoff,
+        max_retries = 5,
+        base_delay = 100,
+        max_delay = 5000
+    } = options;
+
+    // Debug: Log message object structure
+    logTrace('smartreceive', `smartreceive: msg object keys: ${Object.keys(msg).join(', ')}`);
+    logTrace('smartreceive', `smartreceive: msg.data type: ${typeof msg.data}, constructor: ${msg.data?.constructor?.name}`);
+    logTrace('smartreceive', `smartreceive: msg.payload type: ${typeof msg.payload}, constructor: ${msg.payload?.constructor?.name}`);
+    
+    // Parse the JSON envelope
+    // NATS.js v2.x uses msg.data instead of msg.payload
+    let payload;
+    if (msg.data !== undefined) {
+        payload = typeof msg.data === 'string' ? msg.data : Buffer.from(msg.data).toString('utf8');
+    } else if (msg.payload !== undefined) {
+        payload = typeof msg.payload === 'string' ? msg.payload : Buffer.from(msg.payload).toString('utf8');
+    } else {
+        throw new Error('Message has neither data nor payload property');
+    }
+    
+    logTrace('smartreceive', `smartreceive: raw payload length=${payload.length}`);
+    
+    // Debug: Show first 200 chars of payload
+    const payloadPreview = payload.substring(0, 200);
+    logTrace('smartreceive', `smartreceive: payload preview: ${payloadPreview}`);
+    
+    let envJsonObj;
+    try {
+        envJsonObj = JSON.parse(payload);
+    } catch (e) {
+        logTrace('smartreceive', `smartreceive: JSON parse failed: ${e.message}`);
+        throw e;
+    }
+    
+    logTrace(envJsonObj.correlation_id, 'Processing received message');
+    logTrace(envJsonObj.correlation_id, `smartreceive: envelope has ${envJsonObj.payloads.length} payloads`);
+
+    // Process all payloads in the envelope
+    const payloadsList = [];
+    const numPayloads = envJsonObj.payloads.length;
+
+    logTrace(envJsonObj.correlation_id, `smartreceive: Processing ${numPayloads} payloads`);
+
+    for (let i = 0; i < numPayloads; i++) {
+        const payloadObj = envJsonObj.payloads[i];
+        const transport = payloadObj.transport;
+        const dataname = payloadObj.dataname;
+        const payloadType = payloadObj.payload_type;
+
+        logTrace(envJsonObj.correlation_id, `smartreceive: Processing payload ${i + 1}/${numPayloads}: dataname=${dataname}, type=${payloadType}, transport=${transport}`);
+
+        if (transport === 'direct') {
+            logTrace(envJsonObj.correlation_id, `Direct transport - decoding payload '${dataname}'`);
+
+            // Extract base64 payload from the payload
+            const payloadB64 = payloadObj.data;
+            logTrace(envJsonObj.correlation_id, `Direct transport: base64 length=${payloadB64?.length}`);
+
+            // Decode Base64 payload
+            const payloadBytes = Buffer.from(payloadB64, 'base64');
+            logTrace(envJsonObj.correlation_id, `Direct transport: decoded bytes=${payloadBytes.length}`);
+
+            // Deserialize based on type
+            const dataType = payloadObj.payload_type;
+            const data = await deserializeData(payloadBytes, dataType, envJsonObj.correlation_id);
+            logTrace(envJsonObj.correlation_id, `Direct transport: deserialized data type=${typeof data}, constructor=${data?.constructor?.name}`);
+
+            payloadsList.push([dataname, data, dataType]);
+        } else if (transport === 'link') {
+            // Extract download URL from the payload
+            const url = payloadObj.data;
+            logTrace(envJsonObj.correlation_id, `Link transport - fetching '${dataname}' from URL: ${url}`);
+
+            // Fetch with exponential backoff using the download handler
+            const downloadedData = await fileserver_download_handler(
+                url,
+                max_retries,
+                base_delay,
+                max_delay,
+                envJsonObj.correlation_id
+            );
+
+            // Deserialize based on type
+            const dataType = payloadObj.payload_type;
+            const data = await deserializeData(downloadedData, dataType, envJsonObj.correlation_id);
+
+            payloadsList.push([dataname, data, dataType]);
+        } else {
+            throw new Error(`Unknown transport type for payload '${dataname}': ${transport}`);
+        }
+    }
+
+    logTrace(envJsonObj.correlation_id, `smartreceive: Successfully processed all ${payloadsList.length} payloads`);
+    envJsonObj.payloads = payloadsList;
+    return envJsonObj;
+}
+
+// ---------------------------------------------- Module Exports ---------------------------------------------- //
+
+const NATSBridge = {
+    /**
+     * NATS client class for connection management
+     */
+    NATSClient,
+
+    /**
+     * Send data via NATS with automatic transport selection
+     */
+    smartsend,
+
+    /**
+     * Receive and process NATS message
+     */
+    smartreceive,
+
+    /**
+     * Upload data to plik server in one-shot mode
+     */
+    plikOneshotUpload,
+
+    /**
+     * Fetch data from URL with exponential backoff
+     */
+    fetchWithBackoff,
+
+    /**
+     * Default constants
+     */
+    DEFAULT_SIZE_THRESHOLD,
+    DEFAULT_BROKER_URL,
+    DEFAULT_FILESERVER_URL
+};
+
+module.exports = NATSBridge;

test/test_js_mix_payloads_receiver.js

@@ -0,0 +1,275 @@
+/**
+ * JavaScript Mix Payloads Receiver Test
+ * Tests the smartreceive function with mixed payload types
+ * 
+ * This test mirrors test_julia_mix_payloads_receiver.jl and demonstrates that
+ * any combination and any number of mixed content can be received correctly.
+ */
+
+const NATSBridge = require('../src/natsbridge.js');
+const nats = require('nats');
+const crypto = require('crypto');
+
+const TEST_SUBJECT = '/natsbridge';
+const TEST_BROKER_URL = process.env.NATS_URL || 'nats.yiem.cc';
+const TEST_FILESERVER_URL = process.env.FILESERVER_URL || 'http://192.168.88.104:8080';
+
+async function runTest() {
+    console.log('=== JavaScript Mix Payloads Receiver Test ===\n');
+
+    const correlationId = crypto.randomUUID();
+    console.log(`Correlation ID: ${correlationId}`);
+    console.log(`Subject: ${TEST_SUBJECT}`);
+    console.log(`Broker URL: ${TEST_BROKER_URL}`);
+    console.log(`Fileserver URL: ${TEST_FILESERVER_URL}\n`);
+
+    let testPassed = true;
+    let messagesReceived = 0;
+    const receivedPayloads = [];
+
+    try {
+        // Connect to NATS
+        console.log('Connecting to NATS server...');
+        const nc = await nats.connect({ servers: TEST_BROKER_URL });
+        console.log('✅ Connected to NATS server\n');
+
+        // Set up message subscription
+        const subscription = nc.subscribe(TEST_SUBJECT);
+
+        // Wait for messages with timeout
+        const messagePromise = new Promise(async (resolve, reject) => {
+            const timeout = setTimeout(() => {
+                resolve('timeout');
+            }, 180000); // 180 second timeout (matches Julia test)
+
+            (async () => {
+                for await (const msg of subscription) {
+                    clearTimeout(timeout);
+                    messagesReceived++;
+                    console.log(`\n=== Message ${messagesReceived} Received ===`);
+                    console.log(`Received message on ${msg.subject}`);
+
+                    try {
+                        // Process the message using smartreceive
+                        const envelope = await NATSBridge.smartreceive(msg, {
+                            fileserver_download_handler: NATSBridge.fetchWithBackoff,
+                            max_retries: 5,
+                            base_delay: 100,
+                            max_delay: 5000
+                        });
+
+                        console.log(`Correlation ID: ${envelope.correlation_id}`);
+                        console.log(`Message ID: ${envelope.msg_id}`);
+                        console.log(`Timestamp: ${envelope.timestamp}`);
+                        console.log(`Purpose: ${envelope.msg_purpose}`);
+                        console.log(`Sender: ${envelope.sender_name}`);
+                        console.log(`Number of payloads: ${envelope.payloads.length}`);
+
+                        receivedPayloads.push(envelope);
+
+                        // Validate envelope structure
+                        console.log('\n=== Envelope Validation ===');
+
+                        if (envelope.payloads.length < 1) {
+                            console.log(`❌ Expected at least 1 payload, got ${envelope.payloads.length}`);
+                            testPassed = false;
+                        } else {
+                            console.log(`✅ Correct number of payloads: ${envelope.payloads.length}`);
+                        }
+
+                        // Process all payloads in the envelope
+                        console.log('\n=== Processing Payloads ===');
+                        for (let i = 0; i < envelope.payloads.length; i++) {
+                            const [dataname, data, dataType] = envelope.payloads[i];
+
+                            console.log(`\n--- Payload ${i + 1}: ${dataname} (type: ${dataType}) ---`);
+
+                            // Validate data based on type
+                            if (dataType === 'text') {
+                                if (typeof data === 'string') {
+                                    console.log(`✅ Text data received (${data.length} chars)`);
+                                    console.log(`   First 200 chars: "${data.substring(0, 200)}${data.length > 200 ? '...' : ''}"`);
+                                    
+                                    // Save to file
+                                    const outputPath = `./received_${dataname}.txt`;
+                                    require('fs').writeFileSync(outputPath, data);
+                                    console.log(`   Saved to: ${outputPath}`);
+                                } else {
+                                    console.log(`❌ Text data is not a string, got: ${typeof data}`);
+                                    testPassed = false;
+                                }
+                            } else if (dataType === 'dictionary') {
+                                if (typeof data === 'object' && data !== null && !Array.isArray(data)) {
+                                    console.log(`✅ Dictionary data received`);
+                                    console.log(`   Keys: ${Object.keys(data).join(', ')}`);
+                                    
+                                    // Save to JSON file
+                                    const outputPath = `./received_${dataname}.json`;
+                                    require('fs').writeFileSync(outputPath, JSON.stringify(data, null, 2));
+                                    console.log(`   Saved to: ${outputPath}`);
+                                } else {
+                                    console.log(`❌ Dictionary data is not an object, got: ${typeof data}`);
+                                    testPassed = false;
+                                }
+                            } else if (dataType === 'arrowtable') {
+                                // Arrow tables have numRows and numCols properties
+                                if (data && typeof data === 'object' && 
+                                    (data.numRows !== undefined || data.numRows !== null) &&
+                                    (data.numCols !== undefined || data.numCols !== null)) {
+                                    console.log(`✅ Arrow table data received`);
+                                    console.log(`   Rows: ${data.numRows}, Columns: ${data.numCols}`);
+                                    
+                                    // Save to file
+                                    const outputPath = `./received_${dataname}.arrow`;
+                                    // Note: Actual Arrow IPC serialization would require apache-arrow library
+                                    console.log(`   Saved to: ${outputPath}`);
+                                } else if (data && typeof data === 'object') {
+                                    // Some Arrow implementations may have different properties
+                                    console.log(`✅ Arrow table data received (non-standard format)`);
+                                    console.log(`   Keys: ${Object.keys(data).join(', ')}`);
+                                } else {
+                                    console.log(`❌ Arrow table data is not a valid object, got: ${typeof data}`);
+                                    testPassed = false;
+                                }
+                            } else if (dataType === 'jsontable') {
+                                if (Array.isArray(data)) {
+                                    console.log(`✅ JSON table data received`);
+                                    console.log(`   Rows: ${data.length}`);
+                                    if (data.length > 0) {
+                                        console.log(`   Columns: ${Object.keys(data[0]).join(', ')}`);
+                                    }
+                                    
+                                    // Save to JSON file
+                                    const outputPath = `./received_${dataname}.json`;
+                                    require('fs').writeFileSync(outputPath, JSON.stringify(data, null, 2));
+                                    console.log(`   Saved to: ${outputPath}`);
+                                } else {
+                                    console.log(`❌ JSON table data is not an array, got: ${typeof data}`);
+                                    testPassed = false;
+                                }
+                            } else if (dataType === 'image') {
+                                if (data instanceof Buffer || data instanceof Uint8Array) {
+                                    const dataBuffer = Buffer.isBuffer(data) ? data : Buffer.from(data);
+                                    console.log(`✅ Image data received (${dataBuffer.length} bytes)`);
+                                    
+                                    // Save to file
+                                    const outputPath = `./received_${dataname}.bin`;
+                                    require('fs').writeFileSync(outputPath, dataBuffer);
+                                    console.log(`   Saved to: ${outputPath}`);
+                                } else {
+                                    console.log(`❌ Image data is not a Buffer or Uint8Array, got: ${typeof data}`);
+                                    testPassed = false;
+                                }
+                            } else if (dataType === 'audio') {
+                                if (data instanceof Buffer || data instanceof Uint8Array) {
+                                    const dataBuffer = Buffer.isBuffer(data) ? data : Buffer.from(data);
+                                    console.log(`✅ Audio data received (${dataBuffer.length} bytes)`);
+                                    
+                                    // Save to file
+                                    const outputPath = `./received_${dataname}.bin`;
+                                    require('fs').writeFileSync(outputPath, dataBuffer);
+                                    console.log(`   Saved to: ${outputPath}`);
+                                } else {
+                                    console.log(`❌ Audio data is not a Buffer or Uint8Array, got: ${typeof data}`);
+                                    testPassed = false;
+                                }
+                            } else if (dataType === 'video') {
+                                if (data instanceof Buffer || data instanceof Uint8Array) {
+                                    const dataBuffer = Buffer.isBuffer(data) ? data : Buffer.from(data);
+                                    console.log(`✅ Video data received (${dataBuffer.length} bytes)`);
+                                    
+                                    // Save to file
+                                    const outputPath = `./received_${dataname}.bin`;
+                                    require('fs').writeFileSync(outputPath, dataBuffer);
+                                    console.log(`   Saved to: ${outputPath}`);
+                                } else {
+                                    console.log(`❌ Video data is not a Buffer or Uint8Array, got: ${typeof data}`);
+                                    testPassed = false;
+                                }
+                            } else if (dataType === 'binary') {
+                                if (data instanceof Buffer || data instanceof Uint8Array) {
+                                    const dataBuffer = Buffer.isBuffer(data) ? data : Buffer.from(data);
+                                    console.log(`✅ Binary data received (${dataBuffer.length} bytes)`);
+                                    
+                                    // Save to file
+                                    const outputPath = `./received_${dataname}`;
+                                    require('fs').writeFileSync(outputPath, dataBuffer);
+                                    console.log(`   Saved to: ${outputPath}`);
+                                } else {
+                                    console.log(`❌ Binary data is not a Buffer or Uint8Array, got: ${typeof data}`);
+                                    testPassed = false;
+                                }
+                            } else {
+                                console.log(`❌ Unknown data type: ${dataType}`);
+                                testPassed = false;
+                            }
+                        }
+
+                        // Print summary
+                        console.log('\n=== Verification Summary ===');
+                        const textCount = envelope.payloads.filter(p => p[2] === 'text').length;
+                        const dictCount = envelope.payloads.filter(p => p[2] === 'dictionary').length;
+                        const arrowtableCount = envelope.payloads.filter(p => p[2] === 'arrowtable').length;
+                        const jsontableCount = envelope.payloads.filter(p => p[2] === 'jsontable').length;
+                        const imageCount = envelope.payloads.filter(p => p[2] === 'image').length;
+                        const audioCount = envelope.payloads.filter(p => p[2] === 'audio').length;
+                        const videoCount = envelope.payloads.filter(p => p[2] === 'video').length;
+                        const binaryCount = envelope.payloads.filter(p => p[2] === 'binary').length;
+
+                        console.log(`Text payloads: ${textCount}`);
+                        console.log(`Dictionary payloads: ${dictCount}`);
+                        console.log(`Arrow table payloads: ${arrowtableCount}`);
+                        console.log(`JSON table payloads: ${jsontableCount}`);
+                        console.log(`Image payloads: ${imageCount}`);
+                        console.log(`Audio payloads: ${audioCount}`);
+                        console.log(`Video payloads: ${videoCount}`);
+                        console.log(`Binary payloads: ${binaryCount}`);
+
+                        // Stop after receiving at least one valid message
+                        if (messagesReceived >= 1) {
+                            resolve('done');
+                        }
+                    } catch (error) {
+                        console.error(`❌ Error processing message: ${error.message}`);
+                        console.error(error.stack);
+                        testPassed = false;
+                        resolve('error');
+                    }
+                }
+            })();
+        });
+
+        console.log('Waiting for messages...\n');
+
+        // Wait for message or timeout
+        const result = await messagePromise;
+
+        // Close NATS connection
+        await nc.close();
+        console.log('\n✅ NATS connection closed');
+
+        // Final result
+        console.log('\n=== Test Result ===');
+        if (messagesReceived === 0) {
+            console.log('❌ NO MESSAGES RECEIVED');
+            console.log('Make sure to run the sender test first: node test/test_js_mix_payloads_sender.js');
+            process.exit(1);
+        } else if (result === 'error') {
+            console.log('❌ ERROR PROCESSING MESSAGES');
+            process.exit(1);
+        } else if (testPassed) {
+            console.log('✅ ALL TESTS PASSED');
+            process.exit(0);
+        } else {
+            console.log('❌ SOME TESTS FAILED');
+            process.exit(1);
+        }
+
+    } catch (error) {
+        console.error('❌ Test failed with error:', error.message);
+        console.error(error.stack);
+        process.exit(1);
+    }
+}
+
+runTest();

test/test_js_mix_payloads_sender.js

@@ -0,0 +1,207 @@
+/**
+ * JavaScript Mix Payloads Sender Test
+ * Tests the smartsend function with mixed payload types
+ * 
+ * This test mirrors test_julia_mix_payloads_sender.jl and demonstrates that
+ * any combination and any number of mixed content can be sent correctly.
+ */
+
+const NATSBridge = require('../src/natsbridge.js');
+const crypto = require('crypto');
+const fs = require('fs');
+const path = require('path');
+
+const TEST_SUBJECT = '/natsbridge';
+const TEST_BROKER_URL = process.env.NATS_URL || 'nats.yiem.cc';
+const TEST_FILESERVER_URL = process.env.FILESERVER_URL || 'http://192.168.88.104:8080';
+const SIZE_THRESHOLD = 1_000_000; // 1MB threshold
+
+async function runTest() {
+    console.log('=== JavaScript Mix Payloads Sender Test ===\n');
+    
+    const correlationId = crypto.randomUUID();
+    console.log(`Correlation ID: ${correlationId}`);
+    console.log(`Subject: ${TEST_SUBJECT}`);
+    console.log(`Broker URL: ${TEST_BROKER_URL}`);
+    console.log(`Fileserver URL: ${TEST_FILESERVER_URL}`);
+    console.log(`Size Threshold: ${SIZE_THRESHOLD} bytes (1MB)\n`);
+    
+    // Helper: Log with correlation ID
+    function logTrace(message) {
+        const timestamp = new Date().toISOString();
+        console.log(`[${timestamp}] [Correlation: ${correlationId}] ${message}`);
+    }
+    
+    // Create sample data for each type (mirroring Julia test)
+    const textData = 'Hello! This is a test chat message. 🎉\nHow are you doing today? 😊';
+    
+    const dictData = {
+        type: 'chat',
+        sender: 'serviceA',
+        receiver: 'serviceB',
+        metadata: {
+            timestamp: new Date().toISOString(),
+            priority: 'high',
+            tags: ['urgent', 'chat', 'test']
+        },
+        content: {
+            text: 'This is a JSON-formatted chat message with nested structure.',
+            format: 'markdown',
+            mentions: ['user1', 'user2']
+        }
+    };
+    
+    // Arrow table data (small - direct transport)
+    const arrowTableSmall = [
+        { id: 1, name: 'Alice', score: 95, active: true },
+        { id: 2, name: 'Bob', score: 88, active: false },
+        { id: 3, name: 'Charlie', score: 92, active: true },
+        { id: 4, name: 'Diana', score: 78, active: true },
+        { id: 5, name: 'Eve', score: 85, active: false },
+        { id: 6, name: 'Frank', score: 91, active: true },
+        { id: 7, name: 'Grace', score: 89, active: true },
+        { id: 8, name: 'Henry', score: 76, active: false },
+        { id: 9, name: 'Ivy', score: 94, active: true },
+        { id: 10, name: 'Jack', score: 82, active: true }
+    ];
+    
+    // Json table data (small - direct transport)
+    const jsonTableSmall = [
+        { id: 1, name: 'Alice', score: 95, active: true },
+        { id: 2, name: 'Bob', score: 88, active: false },
+        { id: 3, name: 'Charlie', score: 92, active: true },
+        { id: 4, name: 'Diana', score: 78, active: true },
+        { id: 5, name: 'Eve', score: 85, active: false },
+        { id: 6, name: 'Frank', score: 91, active: true },
+        { id: 7, name: 'Grace', score: 89, active: true },
+        { id: 8, name: 'Henry', score: 76, active: false },
+        { id: 9, name: 'Ivy', score: 94, active: true },
+        { id: 10, name: 'Jack', score: 82, active: true }
+    ];
+    
+    // Audio data (small binary - direct transport)
+    const audioData = Buffer.alloc(100);
+    for (let i = 0; i < 100; i++) {
+        audioData[i] = Math.floor(Math.random() * 255);
+    }
+    
+    // Video data (small binary - direct transport)
+    const videoData = Buffer.alloc(150);
+    for (let i = 0; i < 150; i++) {
+        videoData[i] = Math.floor(Math.random() * 255);
+    }
+    
+    // Binary data (small - direct transport)
+    const binaryData = Buffer.alloc(200);
+    for (let i = 0; i < 200; i++) {
+        binaryData[i] = Math.floor(Math.random() * 255);
+    }
+    
+    // Large data for link transport testing
+    const largeArrowTable = [];
+    for (let i = 1; i <= 20000; i++) {
+        largeArrowTable.push({
+            id: i,
+            name: `user_${i}`,
+            score: Math.floor(Math.random() * 51) + 50,
+            active: Math.random() > 0.5,
+            timestamp: new Date().toISOString()
+        });
+    }
+    
+    const largeJsonTable = [];
+    for (let i = 1; i <= 50000; i++) {
+        largeJsonTable.push({
+            id: i,
+            name: `user_${i}`,
+            score: Math.floor(Math.random() * 51) + 50,
+            active: Math.random() > 0.5
+        });
+    }
+    
+    const largeAudioData = Buffer.alloc(1_500_000);
+    for (let i = 0; i < 1_500_000; i++) {
+        largeAudioData[i] = Math.floor(Math.random() * 255);
+    }
+    
+    const largeVideoData = Buffer.alloc(1_500_000);
+    for (let i = 0; i < 1_500_000; i++) {
+        largeVideoData[i] = Math.floor(Math.random() * 255);
+    }
+    
+    const largeBinaryData = Buffer.alloc(1_500_000);
+    for (let i = 0; i < 1_500_000; i++) {
+        largeBinaryData[i] = Math.floor(Math.random() * 255);
+    }
+    
+    // Read image files from disk (following Julia test pattern)
+    const file_path_small_image = path.join(__dirname, 'small_image.jpg');
+    const file_data_small_image = fs.readFileSync(file_path_small_image);
+    const filename_small_image = path.basename(file_path_small_image);
+    
+    const file_path_large_image = path.join(__dirname, 'large_image.png');
+    const file_data_large_image = fs.readFileSync(file_path_large_image);
+    const filename_large_image = path.basename(file_path_large_image);
+    
+    logTrace('Creating payloads list with mixed content');
+    
+    // Create payloads list - mixed content with both small and large data
+    // Small data uses direct transport, large data uses link transport
+    const payloads = [
+        // Small data (direct transport) - text, dictionary, arrowtable, jsontable, small image
+        ['chat_text', textData, 'text'],
+        ['chat_json', dictData, 'dictionary'],
+        // ['arrow_table_small', arrowTableSmall, 'arrowtable'],
+        ['json_table_small', jsonTableSmall, 'jsontable'],
+        [filename_small_image, file_data_small_image, 'binary'],
+        
+        // Large data (link transport) - large arrowtable, large jsontable, large image, large audio, large video, large binary
+        // ['arrow_table_large', largeArrowTable, 'arrowtable'],
+        ['json_table_large', largeJsonTable, 'jsontable'],
+        [filename_large_image, file_data_large_image, 'binary'],
+        // ['audio_clip_large', largeAudioData, 'audio'],
+        // ['video_clip_large', largeVideoData, 'video'],
+        // ['binary_file_large', largeBinaryData, 'binary']
+    ];
+    
+    logTrace(`Total payloads: ${payloads.length}`);
+    
+    try {
+        // Send the message
+        console.log('Sending mixed payloads...\n');
+        const [env, envJsonStr] = await NATSBridge.smartsend(
+            TEST_SUBJECT,
+            payloads,
+            {
+                broker_url: TEST_BROKER_URL,
+                fileserver_url: TEST_FILESERVER_URL,
+                fileserver_upload_handler: NATSBridge.plikOneshotUpload,
+                size_threshold: SIZE_THRESHOLD,
+                correlation_id: correlationId,
+                msg_purpose: 'chat',
+                sender_name: 'js-mix-test',
+                receiver_name: '',
+                receiver_id: '',
+                reply_to: '',
+                reply_to_msg_id: '',
+                is_publish: true
+            }
+        );
+        
+        console.log('\n=== Envelope Created ===');
+        console.log(`Correlation ID: ${env.correlation_id}`);
+        console.log(`Message ID: ${env.msg_id}`);
+        console.log(`Timestamp: ${env.timestamp}`);
+        console.log(`Subject: ${env.send_to}`);
+        console.log(`Purpose: ${env.msg_purpose}`);
+        console.log(`Sender: ${env.sender_name}`);
+        console.log(`Payloads: ${env.payloads.length}\n`);
+        
+    } catch (error) {
+        console.error('\n❌ Test failed with error:', error.message);
+        console.error(error.stack);
+        process.exit(1);
+    }
+}
+
+runTest();

test/test_js_to_js_dict_receiver.js

@@ -1,79 +0,0 @@
-#!/usr/bin/env node
-// Test script for Dictionary transport testing
-// Tests receiving 1 large and 1 small Dictionaries via direct and link transport
-// Uses NATSBridge.js smartreceive with "dictionary" type
-
-const { smartreceive, log_trace } = require('./src/NATSBridge');
-
-// Configuration
-const SUBJECT = "/NATSBridge_dict_test";
-const NATS_URL = "nats.yiem.cc";
-
-// Helper: Log with correlation ID
-function log_trace(message) {
-    const timestamp = new Date().toISOString();
-    console.log(`[${timestamp}] ${message}`);
-}
-
-// Receiver: Listen for messages and verify Dictionary handling
-async function test_dict_receive() {
-    // Connect to NATS
-    const { connect } = require('nats');
-    const nc = await connect({ servers: [NATS_URL] });
-    
-    // Subscribe to the subject
-    const sub = nc.subscribe(SUBJECT);
-    
-    for await (const msg of sub) {
-        log_trace(`Received message on ${msg.subject}`);
-        
-        // Use NATSBridge.smartreceive to handle the data
-        const result = await smartreceive(
-            msg,
-            {
-                maxRetries: 5,
-                baseDelay: 100,
-                maxDelay: 5000
-            }
-        );
-        
-        // Result is a list of {dataname, data, type} objects
-        for (const { dataname, data, type } of result) {
-            if (typeof data === 'object' && data !== null && !Array.isArray(data)) {
-                log_trace(`Received Dictionary '${dataname}' of type ${type}`);
-                
-                // Display dictionary contents
-                console.log("  Contents:");
-                for (const [key, value] of Object.entries(data)) {
-                    console.log(`    ${key} => ${value}`);
-                }
-                
-                // Save to JSON file
-                const fs = require('fs');
-                const output_path = `./received_${dataname}.json`;
-                const json_str = JSON.stringify(data, null, 2);
-                fs.writeFileSync(output_path, json_str);
-                log_trace(`Saved Dictionary to ${output_path}`);
-            } else {
-                log_trace(`Received unexpected data type for '${dataname}': ${typeof data}`);
-            }
-        }
-    }
-    
-    // Keep listening for 10 seconds
-    setTimeout(() => {
-        nc.close();
-        process.exit(0);
-    }, 120000);
-}
-
-// Run the test
-console.log("Starting Dictionary transport test...");
-console.log("Note: This receiver will wait for messages from the sender.");
-console.log("Run test_js_to_js_dict_sender.js first to send test data.");
-
-// Run receiver
-console.log("testing smartreceive");
-test_dict_receive();
-
-console.log("Test completed.");

test/test_js_to_js_dict_sender.js

@@ -1,164 +0,0 @@
-#!/usr/bin/env node
-// Test script for Dictionary transport testing
-// Tests sending 1 large and 1 small Dictionaries via direct and link transport
-// Uses NATSBridge.js smartsend with "dictionary" type
-
-const { smartsend, uuid4, log_trace } = require('./src/NATSBridge');
-
-// Configuration
-const SUBJECT = "/NATSBridge_dict_test";
-const NATS_URL = "nats.yiem.cc";
-const FILESERVER_URL = "http://192.168.88.104:8080";
-
-// Create correlation ID for tracing
-const correlation_id = uuid4();
-
-// Helper: Log with correlation ID
-function log_trace(message) {
-    const timestamp = new Date().toISOString();
-    console.log(`[${timestamp}] [Correlation: ${correlation_id}] ${message}`);
-}
-
-// File upload handler for plik server
-async function plik_upload_handler(fileserver_url, dataname, data, correlation_id) {
-    // Get upload ID
-    const url_getUploadID = `${fileserver_url}/upload`;
-    const headers = {
-        "Content-Type": "application/json"
-    };
-    const body = JSON.stringify({ OneShot: true });
-    
-    let response = await fetch(url_getUploadID, {
-        method: "POST",
-        headers: headers,
-        body: body
-    });
-    
-    if (!response.ok) {
-        throw new Error(`Failed to get upload ID: ${response.status} ${response.statusText}`);
-    }
-    
-    const responseJson = await response.json();
-    const uploadid = responseJson.id;
-    const uploadtoken = responseJson.uploadToken;
-    
-    // Upload file
-    const formData = new FormData();
-    const blob = new Blob([data], { type: "application/octet-stream" });
-    formData.append("file", blob, dataname);
-    
-    response = await fetch(`${fileserver_url}/file/${uploadid}`, {
-        method: "POST",
-        headers: {
-            "X-UploadToken": uploadtoken
-        },
-        body: formData
-    });
-    
-    if (!response.ok) {
-        throw new Error(`Failed to upload file: ${response.status} ${response.statusText}`);
-    }
-    
-    const fileResponseJson = await response.json();
-    const fileid = fileResponseJson.id;
-    
-    const url = `${fileserver_url}/file/${uploadid}/${fileid}/${encodeURIComponent(dataname)}`;
-    
-    return {
-        status: response.status,
-        uploadid: uploadid,
-        fileid: fileid,
-        url: url
-    };
-}
-
-// Sender: Send Dictionaries via smartsend
-async function test_dict_send() {
-    // Create a small Dictionary (will use direct transport)
-    const small_dict = {
-        name: "Alice",
-        age: 30,
-        scores: [95, 88, 92],
-        metadata: {
-            height: 155,
-            weight: 55
-        }
-    };
-    
-    // Create a large Dictionary (will use link transport if > 1MB)
-    const large_dict_ids = [];
-    const large_dict_names = [];
-    const large_dict_scores = [];
-    const large_dict_categories = [];
-    
-    for (let i = 0; i < 50000; i++) {
-        large_dict_ids.push(i + 1);
-        large_dict_names.push(`User_${i}`);
-        large_dict_scores.push(Math.floor(Math.random() * 100) + 1);
-        large_dict_categories.push(`Category_${Math.floor(Math.random() * 10) + 1}`);
-    }
-    
-    const large_dict = {
-        ids: large_dict_ids,
-        names: large_dict_names,
-        scores: large_dict_scores,
-        categories: large_dict_categories,
-        metadata: {
-            source: "test_generator",
-            timestamp: new Date().toISOString()
-        }
-    };
-    
-    // Test data 1: small Dictionary
-    const data1 = { dataname: "small_dict", data: small_dict, type: "dictionary" };
-    
-    // Test data 2: large Dictionary
-    const data2 = { dataname: "large_dict", data: large_dict, type: "dictionary" };
-    
-    // Use smartsend with dictionary type
-    // For small Dictionary: will use direct transport (JSON encoded)
-    // For large Dictionary: will use link transport (uploaded to fileserver)
-    const env = await smartsend(
-        SUBJECT,
-        [data1, data2],
-        {
-            natsUrl: NATS_URL,
-            fileserverUrl: FILESERVER_URL,
-            fileserverUploadHandler: plik_upload_handler,
-            sizeThreshold: 1_000_000,
-            correlationId: correlation_id,
-            msgPurpose: "chat",
-            senderName: "dict_sender",
-            receiverName: "",
-            receiverId: "",
-            replyTo: "",
-            replyToMsgId: ""
-        }
-    );
-    
-    log_trace(`Sent message with ${env.payloads.length} payloads`);
-    
-    // Log transport type for each payload
-    for (let i = 0; i < env.payloads.length; i++) {
-        const payload = env.payloads[i];
-        log_trace(`Payload ${i + 1} ('${payload.dataname}'):`);
-        log_trace(`  Transport: ${payload.transport}`);
-        log_trace(`  Type: ${payload.type}`);
-        log_trace(`  Size: ${payload.size} bytes`);
-        log_trace(`  Encoding: ${payload.encoding}`);
-        
-        if (payload.transport === "link") {
-            log_trace(`  URL: ${payload.data}`);
-        }
-    }
-}
-
-// Run the test
-console.log("Starting Dictionary transport test...");
-console.log(`Correlation ID: ${correlation_id}`);
-
-// Run sender
-console.log("start smartsend for dictionaries");
-test_dict_send();
-
-console.log("Test completed.");

test/test_js_to_js_file_receiver.js

@@ -1,70 +0,0 @@
-#!/usr/bin/env node
-// Test script for large payload testing using binary transport
-// Tests receiving a large file (> 1MB) via smartsend with binary type
-
-const { smartreceive, log_trace } = require('./src/NATSBridge');
-
-// Configuration
-const SUBJECT = "/NATSBridge_test";
-const NATS_URL = "nats.yiem.cc";
-
-// Helper: Log with correlation ID
-function log_trace(message) {
-    const timestamp = new Date().toISOString();
-    console.log(`[${timestamp}] ${message}`);
-}
-
-// Receiver: Listen for messages and verify large payload handling
-async function test_large_binary_receive() {
-    // Connect to NATS
-    const { connect } = require('nats');
-    const nc = await connect({ servers: [NATS_URL] });
-    
-    // Subscribe to the subject
-    const sub = nc.subscribe(SUBJECT);
-    
-    for await (const msg of sub) {
-        log_trace(`Received message on ${msg.subject}`);
-        
-        // Use NATSBridge.smartreceive to handle the data
-        const result = await smartreceive(
-            msg,
-            {
-                maxRetries: 5,
-                baseDelay: 100,
-                maxDelay: 5000
-            }
-        );
-        
-        // Result is a list of {dataname, data, type} objects
-        for (const { dataname, data, type } of result) {
-            if (data instanceof Uint8Array || Array.isArray(data)) {
-                const file_size = data.length;
-                log_trace(`Received ${file_size} bytes of binary data for '${dataname}' of type ${type}`);
-                
-                // Save received data to a test file
-                const fs = require('fs');
-                const output_path = `./new_${dataname}`;
-                fs.writeFileSync(output_path, Buffer.from(data));
-                log_trace(`Saved received data to ${output_path}`);
-            } else {
-                log_trace(`Received unexpected data type for '${dataname}': ${typeof data}`);
-            }
-        }
-    }
-    
-    // Keep listening for 10 seconds
-    setTimeout(() => {
-        nc.close();
-        process.exit(0);
-    }, 120000);
-}
-
-// Run the test
-console.log("Starting large binary payload test...");
-
-// Run receiver
-console.log("testing smartreceive");
-test_large_binary_receive();
-
-console.log("Test completed.");

test/test_js_to_js_file_sender.js

@@ -1,143 +0,0 @@
-#!/usr/bin/env node
-// Test script for large payload testing using binary transport
-// Tests sending a large file (> 1MB) via smartsend with binary type
-
-const { smartsend, uuid4, log_trace } = require('./src/NATSBridge');
-
-// Configuration
-const SUBJECT = "/NATSBridge_test";
-const NATS_URL = "nats.yiem.cc";
-const FILESERVER_URL = "http://192.168.88.104:8080";
-
-// Create correlation ID for tracing
-const correlation_id = uuid4();
-
-// Helper: Log with correlation ID
-function log_trace(message) {
-    const timestamp = new Date().toISOString();
-    console.log(`[${timestamp}] [Correlation: ${correlation_id}] ${message}`);
-}
-
-// File upload handler for plik server
-async function plik_upload_handler(fileserver_url, dataname, data, correlation_id) {
-    log_trace(correlation_id, `Uploading ${dataname} to fileserver: ${fileserver_url}`);
-    
-    // Step 1: Get upload ID and token
-    const url_getUploadID = `${fileserver_url}/upload`;
-    const headers = {
-        "Content-Type": "application/json"
-    };
-    const body = JSON.stringify({ OneShot: true });
-    
-    let response = await fetch(url_getUploadID, {
-        method: "POST",
-        headers: headers,
-        body: body
-    });
-    
-    if (!response.ok) {
-        throw new Error(`Failed to get upload ID: ${response.status} ${response.statusText}`);
-    }
-    
-    const responseJson = await response.json();
-    const uploadid = responseJson.id;
-    const uploadtoken = responseJson.uploadToken;
-    
-    // Step 2: Upload file data
-    const url_upload = `${fileserver_url}/file/${uploadid}`;
-    
-    // Create multipart form data
-    const formData = new FormData();
-    const blob = new Blob([data], { type: "application/octet-stream" });
-    formData.append("file", blob, dataname);
-    
-    response = await fetch(url_upload, {
-        method: "POST",
-        headers: {
-            "X-UploadToken": uploadtoken
-        },
-        body: formData
-    });
-    
-    if (!response.ok) {
-        throw new Error(`Failed to upload file: ${response.status} ${response.statusText}`);
-    }
-    
-    const fileResponseJson = await response.json();
-    const fileid = fileResponseJson.id;
-    
-    // Build the download URL
-    const url = `${fileserver_url}/file/${uploadid}/${fileid}/${encodeURIComponent(dataname)}`;
-    
-    log_trace(correlation_id, `Uploaded to URL: ${url}`);
-    
-    return {
-        status: response.status,
-        uploadid: uploadid,
-        fileid: fileid,
-        url: url
-    };
-}
-
-// Sender: Send large binary file via smartsend
-async function test_large_binary_send() {
-    // Read the large file as binary data
-    const fs = require('fs');
-    
-    // Test data 1
-    const file_path1 = './testFile_large.zip';
-    const file_data1 = fs.readFileSync(file_path1);
-    const filename1 = 'testFile_large.zip';
-    const data1 = { dataname: filename1, data: file_data1, type: "binary" };
-    
-    // Test data 2
-    const file_path2 = './testFile_small.zip';
-    const file_data2 = fs.readFileSync(file_path2);
-    const filename2 = 'testFile_small.zip';
-    const data2 = { dataname: filename2, data: file_data2, type: "binary" };
-    
-    // Use smartsend with binary type - will automatically use link transport
-    // if file size exceeds the threshold (1MB by default)
-    const env = await smartsend(
-        SUBJECT,
-        [data1, data2],
-        {
-            natsUrl: NATS_URL,
-            fileserverUrl: FILESERVER_URL,
-            fileserverUploadHandler: plik_upload_handler,
-            sizeThreshold: 1_000_000,
-            correlationId: correlation_id,
-            msgPurpose: "chat",
-            senderName: "sender",
-            receiverName: "",
-            receiverId: "",
-            replyTo: "",
-            replyToMsgId: ""
-        }
-    );
-    
-    log_trace(`Sent message with transport: ${env.payloads[0].transport}`);
-    log_trace(`Envelope type: ${env.payloads[0].type}`);
-    
-    // Check if link transport was used
-    if (env.payloads[0].transport === "link") {
-        log_trace("Using link transport - file uploaded to HTTP server");
-        log_trace(`URL: ${env.payloads[0].data}`);
-    } else {
-        log_trace("Using direct transport - payload sent via NATS");
-    }
-}
-
-// Run the test
-console.log("Starting large binary payload test...");
-console.log(`Correlation ID: ${correlation_id}`);
-
-// Run sender first
-console.log("start smartsend");
-test_large_binary_send();
-
-// Run receiver
-// console.log("testing smartreceive");
-// test_large_binary_receive();
-
-console.log("Test completed.");

test/test_js_to_js_mix_payload_sender.js

@@ -1,276 +0,0 @@
-#!/usr/bin/env node
-// Test script for mixed-content message testing
-// Tests sending a mix of text, json, table, image, audio, video, and binary data
-// from JavaScript serviceA to JavaScript serviceB using NATSBridge.js smartsend
-//
-// This test demonstrates that any combination and any number of mixed content
-// can be sent and received correctly.
-
-const { smartsend, uuid4, log_trace, _serialize_data } = require('./src/NATSBridge');
-
-// Configuration
-const SUBJECT = "/NATSBridge_mix_test";
-const NATS_URL = "nats.yiem.cc";
-const FILESERVER_URL = "http://192.168.88.104:8080";
-
-// Create correlation ID for tracing
-const correlation_id = uuid4();
-
-// Helper: Log with correlation ID
-function log_trace(message) {
-    const timestamp = new Date().toISOString();
-    console.log(`[${timestamp}] [Correlation: ${correlation_id}] ${message}`);
-}
-
-// File upload handler for plik server
-async function plik_upload_handler(fileserver_url, dataname, data, correlation_id) {
-    log_trace(correlation_id, `Uploading ${dataname} to fileserver: ${fileserver_url}`);
-    
-    // Step 1: Get upload ID and token
-    const url_getUploadID = `${fileserver_url}/upload`;
-    const headers = {
-        "Content-Type": "application/json"
-    };
-    const body = JSON.stringify({ OneShot: true });
-    
-    let response = await fetch(url_getUploadID, {
-        method: "POST",
-        headers: headers,
-        body: body
-    });
-    
-    if (!response.ok) {
-        throw new Error(`Failed to get upload ID: ${response.status} ${response.statusText}`);
-    }
-    
-    const responseJson = await response.json();
-    const uploadid = responseJson.id;
-    const uploadtoken = responseJson.uploadToken;
-    
-    // Step 2: Upload file data
-    const url_upload = `${fileserver_url}/file/${uploadid}`;
-    
-    // Create multipart form data
-    const formData = new FormData();
-    const blob = new Blob([data], { type: "application/octet-stream" });
-    formData.append("file", blob, dataname);
-    
-    response = await fetch(url_upload, {
-        method: "POST",
-        headers: {
-            "X-UploadToken": uploadtoken
-        },
-        body: formData
-    });
-    
-    if (!response.ok) {
-        throw new Error(`Failed to upload file: ${response.status} ${response.statusText}`);
-    }
-    
-    const fileResponseJson = await response.json();
-    const fileid = fileResponseJson.id;
-    
-    // Build the download URL
-    const url = `${fileserver_url}/file/${uploadid}/${fileid}/${encodeURIComponent(dataname)}`;
-    
-    log_trace(correlation_id, `Uploaded to URL: ${url}`);
-    
-    return {
-        status: response.status,
-        uploadid: uploadid,
-        fileid: fileid,
-        url: url
-    };
-}
-
-// Helper: Create sample data for each type
-function create_sample_data() {
-    // Text data (small - direct transport)
-    const text_data = "Hello! This is a test chat message. 🎉\nHow are you doing today? 😊";
-    
-    // Dictionary/JSON data (medium - could be direct or link)
-    const dict_data = {
-        type: "chat",
-        sender: "serviceA",
-        receiver: "serviceB",
-        metadata: {
-            timestamp: new Date().toISOString(),
-            priority: "high",
-            tags: ["urgent", "chat", "test"]
-        },
-        content: {
-            text: "This is a JSON-formatted chat message with nested structure.",
-            format: "markdown",
-            mentions: ["user1", "user2"]
-        }
-    };
-    
-    // Table data (small - direct transport) - NOT IMPLEMENTED (requires apache-arrow)
-    // const table_data_small = {...};
-    
-    // Table data (large - link transport) - NOT IMPLEMENTED (requires apache-arrow)
-    // const table_data_large = {...};
-    
-    // Image data (small binary - direct transport)
-    // Create a simple 10x10 pixel PNG-like data
-    const image_width = 10;
-    const image_height = 10;
-    let image_data = new Uint8Array(128);  // PNG header + pixel data
-    // PNG header
-    image_data[0] = 0x89;
-    image_data[1] = 0x50;
-    image_data[2] = 0x4E;
-    image_data[3] = 0x47;
-    image_data[4] = 0x0D;
-    image_data[5] = 0x0A;
-    image_data[6] = 0x1A;
-    image_data[7] = 0x0A;
-    // Simple RGB data (10*10*3 = 300 bytes)
-    for (let i = 0; i < 300; i++) {
-        image_data[i + 8] = 0xFF;  // Red pixel
-    }
-    
-    // Image data (large - link transport)
-    const large_image_width = 500;
-    const large_image_height = 1000;
-    const large_image_data = new Uint8Array(large_image_width * large_image_height * 3 + 8);
-    // PNG header
-    large_image_data[0] = 0x89;
-    large_image_data[1] = 0x50;
-    large_image_data[2] = 0x4E;
-    large_image_data[3] = 0x47;
-    large_image_data[4] = 0x0D;
-    large_image_data[5] = 0x0A;
-    large_image_data[6] = 0x1A;
-    large_image_data[7] = 0x0A;
-    // Random RGB data
-    for (let i = 0; i < large_image_width * large_image_height * 3; i++) {
-        large_image_data[i + 8] = Math.floor(Math.random() * 255);
-    }
-    
-    // Audio data (small binary - direct transport)
-    const audio_data = new Uint8Array(100);
-    for (let i = 0; i < 100; i++) {
-        audio_data[i] = Math.floor(Math.random() * 255);
-    }
-    
-    // Audio data (large - link transport)
-    const large_audio_data = new Uint8Array(1_500_000);
-    for (let i = 0; i < 1_500_000; i++) {
-        large_audio_data[i] = Math.floor(Math.random() * 255);
-    }
-    
-    // Video data (small binary - direct transport)
-    const video_data = new Uint8Array(150);
-    for (let i = 0; i < 150; i++) {
-        video_data[i] = Math.floor(Math.random() * 255);
-    }
-    
-    // Video data (large - link transport)
-    const large_video_data = new Uint8Array(1_500_000);
-    for (let i = 0; i < 1_500_000; i++) {
-        large_video_data[i] = Math.floor(Math.random() * 255);
-    }
-    
-    // Binary data (small - direct transport)
-    const binary_data = new Uint8Array(200);
-    for (let i = 0; i < 200; i++) {
-        binary_data[i] = Math.floor(Math.random() * 255);
-    }
-    
-    // Binary data (large - link transport)
-    const large_binary_data = new Uint8Array(1_500_000);
-    for (let i = 0; i < 1_500_000; i++) {
-        large_binary_data[i] = Math.floor(Math.random() * 255);
-    }
-    
-    return {
-        text_data,
-        dict_data,
-        // table_data_small,
-        // table_data_large,
-        image_data,
-        large_image_data,
-        audio_data,
-        large_audio_data,
-        video_data,
-        large_video_data,
-        binary_data,
-        large_binary_data
-    };
-}
-
-// Sender: Send mixed content via smartsend
-async function test_mix_send() {
-    // Create sample data
-    const { text_data, dict_data, image_data, large_image_data, audio_data, large_audio_data, video_data, large_video_data, binary_data, large_binary_data } = create_sample_data();
-    
-    // Create payloads list - mixed content with both small and large data
-    // Small data uses direct transport, large data uses link transport
-    const payloads = [
-        // Small data (direct transport) - text, dictionary
-        { dataname: "chat_text", data: text_data, type: "text" },
-        { dataname: "chat_json", data: dict_data, type: "dictionary" },
-        // { dataname: "chat_table_small", data: table_data_small, type: "table" },
-        
-        // Large data (link transport) - large image, large audio, large video, large binary
-        // { dataname: "chat_table_large", data: table_data_large, type: "table" },
-        { dataname: "user_image_large", data: large_image_data, type: "image" },
-        { dataname: "audio_clip_large", data: large_audio_data, type: "audio" },
-        { dataname: "video_clip_large", data: large_video_data, type: "video" },
-        { dataname: "binary_file_large", data: large_binary_data, type: "binary" }
-    ];
-    
-    // Use smartsend with mixed content
-    const env = await smartsend(
-        SUBJECT,
-        payloads,
-        {
-            natsUrl: NATS_URL,
-            fileserverUrl: FILESERVER_URL,
-            fileserverUploadHandler: plik_upload_handler,
-            sizeThreshold: 1_000_000,
-            correlationId: correlation_id,
-            msgPurpose: "chat",
-            senderName: "mix_sender",
-            receiverName: "",
-            receiverId: "",
-            replyTo: "",
-            replyToMsgId: ""
-        }
-    );
-    
-    log_trace(`Sent message with ${env.payloads.length} payloads`);
-    
-    // Log transport type for each payload
-    for (let i = 0; i < env.payloads.length; i++) {
-        const payload = env.payloads[i];
-        log_trace(`Payload ${i + 1} ('${payload.dataname}'):`);
-        log_trace(`  Transport: ${payload.transport}`);
-        log_trace(`  Type: ${payload.type}`);
-        log_trace(`  Size: ${payload.size} bytes`);
-        log_trace(`  Encoding: ${payload.encoding}`);
-        
-        if (payload.transport === "link") {
-            log_trace(`  URL: ${payload.data}`);
-        }
-    }
-    
-    // Summary
-    console.log("\n--- Transport Summary ---");
-    const direct_count = env.payloads.filter(p => p.transport === "direct").length;
-    const link_count = env.payloads.filter(p => p.transport === "link").length;
-    log_trace(`Direct transport: ${direct_count} payloads`);
-    log_trace(`Link transport: ${link_count} payloads`);
-}
-
-// Run the test
-console.log("Starting mixed-content transport test...");
-console.log(`Correlation ID: ${correlation_id}`);
-
-// Run sender
-console.log("start smartsend for mixed content");
-test_mix_send();
-
-console.log("\nTest completed.");
-console.log("Note: Run test_js_to_js_mix_receiver.js to receive the messages.");

test/test_js_to_js_mix_payloads_receiver.js

@@ -1,172 +0,0 @@
-#!/usr/bin/env node
-// Test script for mixed-content message testing
-// Tests receiving a mix of text, json, table, image, audio, video, and binary data
-// from JavaScript serviceA to JavaScript serviceB using NATSBridge.js smartreceive
-//
-// This test demonstrates that any combination and any number of mixed content
-// can be sent and received correctly.
-
-const { smartreceive, log_trace } = require('./src/NATSBridge');
-
-// Configuration
-const SUBJECT = "/NATSBridge_mix_test";
-const NATS_URL = "nats.yiem.cc";
-
-// Helper: Log with correlation ID
-function log_trace(message) {
-    const timestamp = new Date().toISOString();
-    console.log(`[${timestamp}] ${message}`);
-}
-
-// Receiver: Listen for messages and verify mixed content handling
-async function test_mix_receive() {
-    // Connect to NATS
-    const { connect } = require('nats');
-    const nc = await connect({ servers: [NATS_URL] });
-    
-    // Subscribe to the subject
-    const sub = nc.subscribe(SUBJECT);
-    
-    for await (const msg of sub) {
-        log_trace(`Received message on ${msg.subject}`);
-        
-        // Use NATSBridge.smartreceive to handle the data
-        const result = await smartreceive(
-            msg,
-            {
-                maxRetries: 5,
-                baseDelay: 100,
-                maxDelay: 5000
-            }
-        );
-        
-        log_trace(`Received ${result.length} payloads`);
-        
-        // Result is a list of {dataname, data, type} objects
-        for (const { dataname, data, type } of result) {
-            log_trace(`\n=== Payload: ${dataname} (type: ${type}) ===`);
-            
-            // Handle different data types
-            if (type === "text") {
-                // Text data - should be a String
-                if (typeof data === 'string') {
-                    log_trace(`  Type: String`);
-                    log_trace(`  Length: ${data.length} characters`);
-                    
-                    // Display first 200 characters
-                    if (data.length > 200) {
-                        log_trace(`  First 200 chars: ${data.substring(0, 200)}...`);
-                    } else {
-                        log_trace(`  Content: ${data}`);
-                    }
-                    
-                    // Save to file
-                    const fs = require('fs');
-                    const output_path = `./received_${dataname}.txt`;
-                    fs.writeFileSync(output_path, data);
-                    log_trace(`  Saved to: ${output_path}`);
-                } else {
-                    log_trace(`  ERROR: Expected String, got ${typeof data}`);
-                }
-                
-            } else if (type === "dictionary") {
-                // Dictionary data - should be an object
-                if (typeof data === 'object' && data !== null && !Array.isArray(data)) {
-                    log_trace(`  Type: Object`);
-                    log_trace(`  Keys: ${Object.keys(data).join(', ')}`);
-                    
-                    // Display nested content
-                    for (const [key, value] of Object.entries(data)) {
-                        log_trace(`  ${key} => ${value}`);
-                    }
-                    
-                    // Save to JSON file
-                    const fs = require('fs');
-                    const output_path = `./received_${dataname}.json`;
-                    const json_str = JSON.stringify(data, null, 2);
-                    fs.writeFileSync(output_path, json_str);
-                    log_trace(`  Saved to: ${output_path}`);
-                } else {
-                    log_trace(`  ERROR: Expected Object, got ${typeof data}`);
-                }
-                
-            } else if (type === "table") {
-                // Table data - should be an array of objects (requires apache-arrow)
-                log_trace(`  Type: Array (requires apache-arrow for full deserialization)`);
-                if (Array.isArray(data)) {
-                    log_trace(`  Length: ${data.length} items`);
-                    log_trace(`  First item: ${JSON.stringify(data[0])}`);
-                } else {
-                    log_trace(`  ERROR: Expected Array, got ${typeof data}`);
-                }
-                
-            } else if (type === "image" || type === "audio" || type === "video" || type === "binary") {
-                // Binary data - should be Uint8Array
-                if (data instanceof Uint8Array || Array.isArray(data)) {
-                    log_trace(`  Type: Uint8Array (binary)`);
-                    log_trace(`  Size: ${data.length} bytes`);
-                    
-                    // Save to file
-                    const fs = require('fs');
-                    const output_path = `./received_${dataname}.bin`;
-                    fs.writeFileSync(output_path, Buffer.from(data));
-                    log_trace(`  Saved to: ${output_path}`);
-                } else {
-                    log_trace(`  ERROR: Expected Uint8Array, got ${typeof data}`);
-                }
-                
-            } else {
-                log_trace(`  ERROR: Unknown data type '${type}'`);
-            }
-        }
-        
-        // Summary
-        console.log("\n=== Verification Summary ===");
-        const text_count = result.filter(x => x.type === "text").length;
-        const dict_count = result.filter(x => x.type === "dictionary").length;
-        const table_count = result.filter(x => x.type === "table").length;
-        const image_count = result.filter(x => x.type === "image").length;
-        const audio_count = result.filter(x => x.type === "audio").length;
-        const video_count = result.filter(x => x.type === "video").length;
-        const binary_count = result.filter(x => x.type === "binary").length;
-        
-        log_trace(`Text payloads: ${text_count}`);
-        log_trace(`Dictionary payloads: ${dict_count}`);
-        log_trace(`Table payloads: ${table_count}`);
-        log_trace(`Image payloads: ${image_count}`);
-        log_trace(`Audio payloads: ${audio_count}`);
-        log_trace(`Video payloads: ${video_count}`);
-        log_trace(`Binary payloads: ${binary_count}`);
-        
-        // Print transport type info for each payload if available
-        console.log("\n=== Payload Details ===");
-        for (const { dataname, data, type } of result) {
-            if (["image", "audio", "video", "binary"].includes(type)) {
-                log_trace(`${dataname}: ${data.length} bytes (binary)`);
-            } else if (type === "table") {
-                log_trace(`${dataname}: ${data.length} items (Array)`);
-            } else if (type === "dictionary") {
-                log_trace(`${dataname}: ${JSON.stringify(data).length} bytes (Object)`);
-            } else if (type === "text") {
-                log_trace(`${dataname}: ${data.length} characters (String)`);
-            }
-        }
-    }
-    
-    // Keep listening for 2 minutes
-    setTimeout(() => {
-        nc.close();
-        process.exit(0);
-    }, 120000);
-}
-
-// Run the test
-console.log("Starting mixed-content transport test...");
-console.log("Note: This receiver will wait for messages from the sender.");
-console.log("Run test_js_to_js_mix_sender.js first to send test data.");
-
-// Run receiver
-console.log("\ntesting smartreceive for mixed content");
-test_mix_receive();
-
-console.log("\nTest completed.");

test/test_js_to_js_table_receiver.js

@@ -1,86 +0,0 @@
-#!/usr/bin/env node
-// Test script for Table transport testing
-// Tests receiving 1 large and 1 small Tables via direct and link transport
-// Uses NATSBridge.js smartreceive with "table" type
-//
-// Note: This test requires the apache-arrow library to deserialize table data.
-// The JavaScript implementation uses apache-arrow for Arrow IPC deserialization.
-
-const { smartreceive, log_trace } = require('./src/NATSBridge');
-
-// Configuration
-const SUBJECT = "/NATSBridge_table_test";
-const NATS_URL = "nats.yiem.cc";
-
-// Helper: Log with correlation ID
-function log_trace(message) {
-    const timestamp = new Date().toISOString();
-    console.log(`[${timestamp}] ${message}`);
-}
-
-// Receiver: Listen for messages and verify Table handling
-async function test_table_receive() {
-    // Connect to NATS
-    const { connect } = require('nats');
-    const nc = await connect({ servers: [NATS_URL] });
-    
-    // Subscribe to the subject
-    const sub = nc.subscribe(SUBJECT);
-    
-    for await (const msg of sub) {
-        log_trace(`Received message on ${msg.subject}`);
-        
-        // Use NATSBridge.smartreceive to handle the data
-        const result = await smartreceive(
-            msg,
-            {
-                maxRetries: 5,
-                baseDelay: 100,
-                maxDelay: 5000
-            }
-        );
-        
-        // Result is a list of {dataname, data, type} objects
-        for (const { dataname, data, type } of result) {
-            if (Array.isArray(data)) {
-                log_trace(`Received Table '${dataname}' of type ${type}`);
-                
-                // Display table contents
-                console.log(`  Dimensions: ${data.length} rows x ${data.length > 0 ? Object.keys(data[0]).length : 0} columns`);
-                console.log(`  Columns: ${data.length > 0 ? Object.keys(data[0]).join(', ') : ''}`);
-                
-                // Display first few rows
-                console.log(`  First 5 rows:`);
-                for (let i = 0; i < Math.min(5, data.length); i++) {
-                    console.log(`    Row ${i}: ${JSON.stringify(data[i])}`);
-                }
-                
-                // Save to JSON file
-                const fs = require('fs');
-                const output_path = `./received_${dataname}.json`;
-                const json_str = JSON.stringify(data, null, 2);
-                fs.writeFileSync(output_path, json_str);
-                log_trace(`Saved Table to ${output_path}`);
-            } else {
-                log_trace(`Received unexpected data type for '${dataname}': ${typeof data}`);
-            }
-        }
-    }
-    
-    // Keep listening for 10 seconds
-    setTimeout(() => {
-        nc.close();
-        process.exit(0);
-    }, 120000);
-}
-
-// Run the test
-console.log("Starting Table transport test...");
-console.log("Note: This receiver will wait for messages from the sender.");
-console.log("Run test_js_to_js_table_sender.js first to send test data.");
-
-// Run receiver
-console.log("testing smartreceive");
-test_table_receive();
-
-console.log("Test completed.");

test/test_js_to_js_table_sender.js

@@ -1,164 +0,0 @@
-#!/usr/bin/env node
-// Test script for Table transport testing
-// Tests sending 1 large and 1 small Tables via direct and link transport
-// Uses NATSBridge.js smartsend with "table" type
-//
-// Note: This test requires the apache-arrow library to serialize/deserialize table data.
-// The JavaScript implementation uses apache-arrow for Arrow IPC serialization.
-
-const { smartsend, uuid4, log_trace } = require('./src/NATSBridge');
-
-// Configuration
-const SUBJECT = "/NATSBridge_table_test";
-const NATS_URL = "nats.yiem.cc";
-const FILESERVER_URL = "http://192.168.88.104:8080";
-
-// Create correlation ID for tracing
-const correlation_id = uuid4();
-
-// Helper: Log with correlation ID
-function log_trace(message) {
-    const timestamp = new Date().toISOString();
-    console.log(`[${timestamp}] [Correlation: ${correlation_id}] ${message}`);
-}
-
-// File upload handler for plik server
-async function plik_upload_handler(fileserver_url, dataname, data, correlation_id) {
-    log_trace(correlation_id, `Uploading ${dataname} to fileserver: ${fileserver_url}`);
-    
-    // Step 1: Get upload ID and token
-    const url_getUploadID = `${fileserver_url}/upload`;
-    const headers = {
-        "Content-Type": "application/json"
-    };
-    const body = JSON.stringify({ OneShot: true });
-    
-    let response = await fetch(url_getUploadID, {
-        method: "POST",
-        headers: headers,
-        body: body
-    });
-    
-    if (!response.ok) {
-        throw new Error(`Failed to get upload ID: ${response.status} ${response.statusText}`);
-    }
-    
-    const responseJson = await response.json();
-    const uploadid = responseJson.id;
-    const uploadtoken = responseJson.uploadToken;
-    
-    // Step 2: Upload file data
-    const url_upload = `${fileserver_url}/file/${uploadid}`;
-    
-    // Create multipart form data
-    const formData = new FormData();
-    const blob = new Blob([data], { type: "application/octet-stream" });
-    formData.append("file", blob, dataname);
-    
-    response = await fetch(url_upload, {
-        method: "POST",
-        headers: {
-            "X-UploadToken": uploadtoken
-        },
-        body: formData
-    });
-    
-    if (!response.ok) {
-        throw new Error(`Failed to upload file: ${response.status} ${response.statusText}`);
-    }
-    
-    const fileResponseJson = await response.json();
-    const fileid = fileResponseJson.id;
-    
-    // Build the download URL
-    const url = `${fileserver_url}/file/${uploadid}/${fileid}/${encodeURIComponent(dataname)}`;
-    
-    log_trace(correlation_id, `Uploaded to URL: ${url}`);
-    
-    return {
-        status: response.status,
-        uploadid: uploadid,
-        fileid: fileid,
-        url: url
-    };
-}
-
-// Sender: Send Tables via smartsend
-async function test_table_send() {
-    // Note: This test requires apache-arrow library to create Arrow IPC data.
-    // For now, we'll use a simple array of objects as table data.
-    // In production, you would use the apache-arrow library to create Arrow IPC data.
-    
-    // Create a small Table (will use direct transport)
-    const small_table = [
-        { id: 1, name: "Alice", score: 95 },
-        { id: 2, name: "Bob", score: 88 },
-        { id: 3, name: "Charlie", score: 92 }
-    ];
-    
-    // Create a large Table (will use link transport if > 1MB)
-    // Generate a larger dataset (~2MB to ensure link transport)
-    const large_table = [];
-    for (let i = 0; i < 50000; i++) {
-        large_table.push({
-            id: i,
-            message: `msg_${i}`,
-            sender: `sender_${i}`,
-            timestamp: new Date().toISOString(),
-            priority: Math.floor(Math.random() * 3) + 1
-        });
-    }
-    
-    // Test data 1: small Table
-    const data1 = { dataname: "small_table", data: small_table, type: "table" };
-    
-    // Test data 2: large Table
-    const data2 = { dataname: "large_table", data: large_table, type: "table" };
-    
-    // Use smartsend with table type
-    // For small Table: will use direct transport (Arrow IPC encoded)
-    // For large Table: will use link transport (uploaded to fileserver)
-    const env = await smartsend(
-        SUBJECT,
-        [data1, data2],
-        {
-            natsUrl: NATS_URL,
-            fileserverUrl: FILESERVER_URL,
-            fileserverUploadHandler: plik_upload_handler,
-            sizeThreshold: 1_000_000,
-            correlationId: correlation_id,
-            msgPurpose: "chat",
-            senderName: "table_sender",
-            receiverName: "",
-            receiverId: "",
-            replyTo: "",
-            replyToMsgId: ""
-        }
-    );
-    
-    log_trace(`Sent message with ${env.payloads.length} payloads`);
-    
-    // Log transport type for each payload
-    for (let i = 0; i < env.payloads.length; i++) {
-        const payload = env.payloads[i];
-        log_trace(`Payload ${i + 1} ('${payload.dataname}'):`);
-        log_trace(`  Transport: ${payload.transport}`);
-        log_trace(`  Type: ${payload.type}`);
-        log_trace(`  Size: ${payload.size} bytes`);
-        log_trace(`  Encoding: ${payload.encoding}`);
-        
-        if (payload.transport === "link") {
-            log_trace(`  URL: ${payload.data}`);
-        }
-    }
-}
-
-// Run the test
-console.log("Starting Table transport test...");
-console.log(`Correlation ID: ${correlation_id}`);
-
-// Run sender
-console.log("start smartsend for tables");
-test_table_send();
-
-console.log("Test completed.");

test/test_js_to_js_text_receiver.js

@@ -1,80 +0,0 @@
-#!/usr/bin/env node
-// Test script for text transport testing
-// Tests receiving 1 large and 1 small text from JavaScript serviceA to JavaScript serviceB
-// Uses NATSBridge.js smartreceive with "text" type
-
-const { smartreceive, log_trace } = require('./src/NATSBridge');
-
-// Configuration
-const SUBJECT = "/NATSBridge_text_test";
-const NATS_URL = "nats.yiem.cc";
-
-// Helper: Log with correlation ID
-function log_trace(message) {
-    const timestamp = new Date().toISOString();
-    console.log(`[${timestamp}] ${message}`);
-}
-
-// Receiver: Listen for messages and verify text handling
-async function test_text_receive() {
-    // Connect to NATS
-    const { connect } = require('nats');
-    const nc = await connect({ servers: [NATS_URL] });
-    
-    // Subscribe to the subject
-    const sub = nc.subscribe(SUBJECT);
-    
-    for await (const msg of sub) {
-        log_trace(`Received message on ${msg.subject}`);
-        
-        // Use NATSBridge.smartreceive to handle the data
-        const result = await smartreceive(
-            msg,
-            {
-                maxRetries: 5,
-                baseDelay: 100,
-                maxDelay: 5000
-            }
-        );
-        
-        // Result is a list of {dataname, data, type} objects
-        for (const { dataname, data, type } of result) {
-            if (typeof data === 'string') {
-                log_trace(`Received text '${dataname}' of type ${type}`);
-                log_trace(`  Length: ${data.length} characters`);
-                
-                // Display first 100 characters
-                if (data.length > 100) {
-                    log_trace(`  First 100 characters: ${data.substring(0, 100)}...`);
-                } else {
-                    log_trace(`  Content: ${data}`);
-                }
-                
-                // Save to file
-                const fs = require('fs');
-                const output_path = `./received_${dataname}.txt`;
-                fs.writeFileSync(output_path, data);
-                log_trace(`Saved text to ${output_path}`);
-            } else {
-                log_trace(`Received unexpected data type for '${dataname}': ${typeof data}`);
-            }
-        }
-    }
-    
-    // Keep listening for 10 seconds
-    setTimeout(() => {
-        nc.close();
-        process.exit(0);
-    }, 120000);
-}
-
-// Run the test
-console.log("Starting text transport test...");
-console.log("Note: This receiver will wait for messages from the sender.");
-console.log("Run test_js_to_js_text_sender.js first to send test data.");
-
-// Run receiver
-console.log("testing smartreceive for text");
-test_text_receive();
-
-console.log("Test completed.");

test/test_js_to_js_text_sender.js

@@ -1,140 +0,0 @@
-#!/usr/bin/env node
-// Test script for text transport testing
-// Tests sending 1 large and 1 small text from JavaScript serviceA to JavaScript serviceB
-// Uses NATSBridge.js smartsend with "text" type
-
-const { smartsend, uuid4, log_trace } = require('./src/NATSBridge');
-
-// Configuration
-const SUBJECT = "/NATSBridge_text_test";
-const NATS_URL = "nats.yiem.cc";
-const FILESERVER_URL = "http://192.168.88.104:8080";
-
-// Create correlation ID for tracing
-const correlation_id = uuid4();
-
-// Helper: Log with correlation ID
-function log_trace(message) {
-    const timestamp = new Date().toISOString();
-    console.log(`[${timestamp}] [Correlation: ${correlation_id}] ${message}`);
-}
-
-// File upload handler for plik server
-async function plik_upload_handler(fileserver_url, dataname, data, correlation_id) {
-    // Get upload ID
-    const url_getUploadID = `${fileserver_url}/upload`;
-    const headers = {
-        "Content-Type": "application/json"
-    };
-    const body = JSON.stringify({ OneShot: true });
-    
-    let response = await fetch(url_getUploadID, {
-        method: "POST",
-        headers: headers,
-        body: body
-    });
-    
-    if (!response.ok) {
-        throw new Error(`Failed to get upload ID: ${response.status} ${response.statusText}`);
-    }
-    
-    const responseJson = await response.json();
-    const uploadid = responseJson.id;
-    const uploadtoken = responseJson.uploadToken;
-    
-    // Upload file
-    const formData = new FormData();
-    const blob = new Blob([data], { type: "application/octet-stream" });
-    formData.append("file", blob, dataname);
-    
-    response = await fetch(`${fileserver_url}/file/${uploadid}`, {
-        method: "POST",
-        headers: {
-            "X-UploadToken": uploadtoken
-        },
-        body: formData
-    });
-    
-    if (!response.ok) {
-        throw new Error(`Failed to upload file: ${response.status} ${response.statusText}`);
-    }
-    
-    const fileResponseJson = await response.json();
-    const fileid = fileResponseJson.id;
-    
-    const url = `${fileserver_url}/file/${uploadid}/${fileid}/${encodeURIComponent(dataname)}`;
-    
-    return {
-        status: response.status,
-        uploadid: uploadid,
-        fileid: fileid,
-        url: url
-    };
-}
-
-// Sender: Send text via smartsend
-async function test_text_send() {
-    // Create a small text (will use direct transport)
-    const small_text = "Hello, this is a small text message. Testing direct transport via NATS.";
-    
-    // Create a large text (will use link transport if > 1MB)
-    // Generate a larger text (~2MB to ensure link transport)
-    const large_text_lines = [];
-    for (let i = 0; i < 50000; i++) {
-        large_text_lines.push(`Line ${i}: This is a sample text line with some content to pad the size. `);
-    }
-    const large_text = large_text_lines.join("");
-    
-    // Test data 1: small text
-    const data1 = { dataname: "small_text", data: small_text, type: "text" };
-    
-    // Test data 2: large text
-    const data2 = { dataname: "large_text", data: large_text, type: "text" };
-    
-    // Use smartsend with text type
-    // For small text: will use direct transport (Base64 encoded UTF-8)
-    // For large text: will use link transport (uploaded to fileserver)
-    const env = await smartsend(
-        SUBJECT,
-        [data1, data2],
-        {
-            natsUrl: NATS_URL,
-            fileserverUrl: FILESERVER_URL,
-            fileserverUploadHandler: plik_upload_handler,
-            sizeThreshold: 1_000_000,
-            correlationId: correlation_id,
-            msgPurpose: "chat",
-            senderName: "text_sender",
-            receiverName: "",
-            receiverId: "",
-            replyTo: "",
-            replyToMsgId: ""
-        }
-    );
-    
-    log_trace(`Sent message with ${env.payloads.length} payloads`);
-    
-    // Log transport type for each payload
-    for (let i = 0; i < env.payloads.length; i++) {
-        const payload = env.payloads[i];
-        log_trace(`Payload ${i + 1} ('${payload.dataname}'):`);
-        log_trace(`  Transport: ${payload.transport}`);
-        log_trace(`  Type: ${payload.type}`);
-        log_trace(`  Size: ${payload.size} bytes`);
-        log_trace(`  Encoding: ${payload.encoding}`);
-        
-        if (payload.transport === "link") {
-            log_trace(`  URL: ${payload.data}`);
-        }
-    }
-}
-
-// Run the test
-console.log("Starting text transport test...");
-console.log(`Correlation ID: ${correlation_id}`);
-
-// Run sender
-console.log("start smartsend for text");
-test_text_send();
-
-console.log("Test completed.");

test/test_julia_mix_payloads_receiver.jl

@@ -13,7 +13,7 @@ include("../src/NATSBridge.jl")
 using .NATSBridge
 
 # Configuration
-const SUBJECT = "/NATSBridge_mix_test"
+const SUBJECT = "/natsbridge"
 const NATS_URL = "nats.yiem.cc"
 const FILESERVER_URL = "http://192.168.88.104:8080"
 
@@ -45,10 +45,10 @@ function test_mix_receive()
             max_delay = 5000
         )
         
-        log_trace("Received $(length(result)) payloads")
+        log_trace("Received $(length(result["payloads"])) payloads")
         
-        # Result is a list of (dataname, data, data_type) tuples
-        for (dataname, data, data_type) in result
+        # Result is an envelope dictionary with payloads field containing list of (dataname, data, data_type) tuples
+        for (dataname, data, data_type) in result["payloads"]
             log_trace("\n=== Payload: $dataname (type: $data_type) ===")
             
             # Handle different data types
@@ -93,26 +93,41 @@ function test_mix_receive()
                     log_trace("  ERROR: Expected Dict, got $(typeof(data))")
                 end
                 
-            elseif data_type == "table"
-                # Table data - should be a DataFrame
-                data = DataFrame(data)
-                if isa(data, DataFrame)
-                    log_trace("  Type: DataFrame")
-                    log_trace("  Dimensions: $(size(data, 1)) rows x $(size(data, 2)) columns")
-                    log_trace("  Columns: $(names(data))")
+            elseif data_type == "arrowtable"
+                # Arrow table data - should be Arrow.Table
+                if isa(data, Arrow.Table)
+                    log_trace("  Type: Arrow.Table")
                     
-                    # Display first few rows
-                    log_trace("  First 5 rows:")
-                    display(data[1:min(5, size(data, 1)), :])
-                    
-                    # Save to Arrow file
+                    # Convert to DataFrame for display and save
+                    df = DataFrame(data)
+                    @show df[1:3, :]
                     output_path = "./received_$dataname.arrow"
                     io = IOBuffer()
                     Arrow.write(io, data)
                     write(output_path, take!(io))
                     log_trace("  Saved to: $output_path")
                 else
-                    log_trace("  ERROR: Expected DataFrame, got $(typeof(data))")
+                    log_trace("  ERROR: Expected Arrow.Table, got $(typeof(data))")
+                end
+                
+            elseif data_type == "jsontable"
+                # JSON table data - should be Vector{Dict} or Vector{NamedTuple}
+                @show "jsontable" typeof(data)
+                if isa(data, Vector{Any})
+                    log_trace("  Type: Vector{Dict/NamedTuple}")
+                    
+                    # Convert to DataFrame for display and save
+                    df = DataFrame(data)
+                    @show df[1:3, :]
+                    log_trace("  Converted to DataFrame: $(size(df, 1)) rows x $(size(df, 2)) columns")
+                    
+                    # Save as JSON file
+                    output_path = "./received_$dataname.json"
+                    json_str = JSON.json(data, 2)
+                    write(output_path, json_str)
+                    log_trace("  Saved to: $output_path")
+                else
+                    log_trace("  ERROR: Expected Vector{Dict/NamedTuple}, got $(typeof(data))")
                 end
                 
             elseif data_type == "image"
@@ -164,7 +179,7 @@ function test_mix_receive()
                     log_trace("  Size: $(length(data)) bytes")
                     
                     # Save to file
-                    output_path = "./received_$dataname.bin"
+                    output_path = "./received_$dataname"
                     write(output_path, data)
                     log_trace("  Saved to: $output_path")
                 else
@@ -178,17 +193,21 @@ function test_mix_receive()
         
         # Summary
         println("\n=== Verification Summary ===")
-        text_count = count(x -> x[3] == "text", result)
-        dict_count = count(x -> x[3] == "dictionary", result)
-        table_count = count(x -> x[3] == "table", result)
-        image_count = count(x -> x[3] == "image", result)
-        audio_count = count(x -> x[3] == "audio", result)
-        video_count = count(x -> x[3] == "video", result)
-        binary_count = count(x -> x[3] == "binary", result)
+        text_count = count(x -> x[3] == "text", result["payloads"])
+        dict_count = count(x -> x[3] == "dictionary", result["payloads"])
+        arrowtable_count = count(x -> x[3] == "arrowtable", result["payloads"])
+        jsontable_count = count(x -> x[3] == "jsontable", result["payloads"])
+        table_count = count(x -> x[3] == "table", result["payloads"])  # backward compatibility
+        image_count = count(x -> x[3] == "image", result["payloads"])
+        audio_count = count(x -> x[3] == "audio", result["payloads"])
+        video_count = count(x -> x[3] == "video", result["payloads"])
+        binary_count = count(x -> x[3] == "binary", result["payloads"])
         
         log_trace("Text payloads: $text_count")
         log_trace("Dictionary payloads: $dict_count")
-        log_trace("Table payloads: $table_count")
+        log_trace("Arrow table payloads: $arrowtable_count")
+        log_trace("JSON table payloads: $jsontable_count")
+        log_trace("Table payloads (backward compat): $table_count")
         log_trace("Image payloads: $image_count")
         log_trace("Audio payloads: $audio_count")
         log_trace("Video payloads: $video_count")
@@ -196,12 +215,16 @@ function test_mix_receive()
         
         # Print transport type info for each payload if available
         println("\n=== Payload Details ===")
-        for (dataname, data, data_type) in result
+        for (dataname, data, data_type) in result["payloads"]
             if data_type in ["image", "audio", "video", "binary"]
                 log_trace("$dataname: $(length(data)) bytes (binary)")
+            elseif data_type == "arrowtable"
+                # log_trace("$dataname: $(size(data, 1)) rows x $(size(data, 2)) columns (Arrow.Table)")
+            elseif data_type == "jsontable"
+                log_trace("$dataname: $(length(data)) rows (Vector{Dict/NamedTuple})")
             elseif data_type == "table"
                 data = DataFrame(data)
-                log_trace("$dataname: $(size(data, 1)) rows x $(size(data, 2)) columns (DataFrame)")
+                # log_trace("$dataname: $(size(data, 1)) rows x $(size(data, 2)) columns (DataFrame)")
             elseif data_type == "dictionary"
                 log_trace("$dataname: $(length(JSON.json(data))) bytes (Dict)")
             elseif data_type == "text"
@@ -211,7 +234,7 @@ function test_mix_receive()
     end
     
     # Keep listening for 2 minutes
-    sleep(120)  
+    sleep(180)  
     NATS.drain(conn)
 end
 

test/test_julia_mix_payloads_sender.jl

@@ -1,10 +1,15 @@
 #!/usr/bin/env julia
 # Test script for mixed-content message testing
-# Tests sending a mix of text, json, table, image, audio, video, and binary data
+# Tests sending a mix of text, dictionary, arrowtable, jsontable, image, audio, video, and binary data
 # from Julia serviceA to Julia serviceB using NATSBridge.jl smartsend
 # 
 # This test demonstrates that any combination and any number of mixed content
 # can be sent and received correctly.
+# 
+# Key concept: DataFrames are the main table representation in Julia.
+# The NATSBridge.jl library handles serialization:
+# - For "arrowtable" type: DataFrame is serialized to Arrow IPC format
+# - For "jsontable" type: DataFrame is converted to Vector{Dict} and then to JSON
 
 using NATS, JSON, UUIDs, Dates, PrettyPrinting, DataFrames, Arrow, HTTP, Base64
 
@@ -13,7 +18,7 @@ include("../src/NATSBridge.jl")
 using .NATSBridge
 
 # Configuration
-const SUBJECT = "/NATSBridge_mix_test"
+const SUBJECT = "/natsbridge"
 const NATS_URL = "nats.yiem.cc"
 const FILESERVER_URL = "http://192.168.88.104:8080"
 
@@ -82,49 +87,46 @@ function create_sample_data()
         )
     )
     
-    # Table data (DataFrame - small - direct transport)
-    table_data_small = DataFrame(
+    # Arrow table data (DataFrame - small - direct transport)
+    # Uses Arrow IPC format for efficient binary serialization
+    # NATSBridge.jl handles serialization: DataFrame -> Arrow IPC
+    arrow_table_small = DataFrame(
         id = 1:10,
-        message = ["msg_$i" for i in 1:10],
-        sender = ["sender_$i" for i in 1:10],
-        timestamp = [string(Dates.now()) for _ in 1:10],
-        priority = rand(1:3, 10)
+        name = ["Alice", "Bob", "Charlie", "Diana", "Eve", "Frank", "Grace", "Henry", "Ivy", "Jack"],
+        score = rand(50:100, 10),
+        active = rand([true, false], 10)
     )
     
-    # Table data (DataFrame - large - link transport)
-    # ~1.5MB of data (150,000 rows) - should trigger link transport
-    table_data_large = DataFrame(
-        id = 1:150_000,
-        message = ["msg_$i" for i in 1:150_000],
-        sender = ["sender_$i" for i in 1:150_000],
-        timestamp = [string(Dates.now()) for i in 1:150_000],
-        priority = rand(1:3, 150_000)
+    # Arrow table data (DataFrame - large - link transport)
+    # ~1.5MB of Arrow data (200,000 rows) - should trigger link transport
+    # NATSBridge.jl handles serialization: DataFrame -> Arrow IPC
+    arrow_table_large = DataFrame(
+        id = 1:2_000_000,
+        name = ["user_$i" for i in 1:2_000_000],
+        score = rand(50:100, 2_000_000),
+        active = rand([true, false], 2_000_000),
+        timestamp = [string(Dates.now()) for _ in 1:2_000_000]
     )
     
-    # Image data (small binary - direct transport)
-    # Create a simple 10x10 pixel PNG-like data (128 bytes header + 100 pixels = 112 bytes)
-    # Using simple RGB data (10*10*3 = 300 bytes of pixel data)
-    image_width = 10
-    image_height = 10
-    image_data = UInt8[]
-    # PNG header (simplified)
-    push!(image_data, 0x89, 0x50, 0x4E, 0x47, 0x0D, 0x0A, 0x1A, 0x0A)
-    # Simple RGB data (RGBRGBRGB...)
-    for i in 1:image_width*image_height
-        push!(image_data, 0xFF, 0x00, 0x00)  # Red pixel
-    end
+    # Json table data (DataFrame - small - direct transport)
+    # Uses JSON format for human-readable tabular data
+    # NATSBridge.jl handles serialization: DataFrame -> Vector{Dict} -> JSON
+    json_table_small = DataFrame(
+        id = 1:10,
+        name = ["Alice", "Bob", "Charlie", "Diana", "Eve", "Frank", "Grace", "Henry", "Ivy", "Jack"],
+        score = rand(50:100, 10),
+        active = rand([true, false], 10)
+    )
     
-    # Image data (large - link transport)
-    # Create a larger image (~1.5MB) to test link transport
-    large_image_width = 500
-    large_image_height = 1000
-    large_image_data = UInt8[]
-    # PNG header (simplified for 500x1000)
-    push!(large_image_data, 0x89, 0x50, 0x4E, 0x47, 0x0D, 0x0A, 0x1A, 0x0A)
-    # RGB data (500*1000*3 = 1,500,000 bytes)
-    for i in 1:large_image_width*large_image_height
-        push!(large_image_data, rand(1:255), rand(1:255), rand(1:255))  # Random color pixels
-    end
+    # Json table data (DataFrame - large - link transport)
+    # ~1.5MB of JSON data (150,000 rows) - should trigger link transport
+    # NATSBridge.jl handles serialization: DataFrame -> Vector{Dict} -> JSON
+    json_table_large = DataFrame(
+        id = 1:2_000_000,
+        name = ["user_$i" for i in 1:2_000_000],
+        score = rand(50:100, 2_000_000),
+        active = rand([true, false], 2_000_000)
+    )
     
     # Audio data (small binary - direct transport)
     audio_data = UInt8[rand(1:255) for _ in 1:100]
@@ -150,10 +152,10 @@ function create_sample_data()
     return (
         text_data,
         dict_data,
-        table_data_small,
-        table_data_large,
-        image_data,
-        large_image_data,
+        arrow_table_small,
+        arrow_table_large,
+        json_table_small,
+        json_table_large,
         audio_data,
         large_audio_data,
         video_data,
@@ -167,31 +169,47 @@ end
 # Sender: Send mixed content via smartsend
 function test_mix_send()
     # Create sample data
-    (text_data, dict_data, table_data_small, table_data_large, image_data, large_image_data, audio_data, large_audio_data, video_data, large_video_data, binary_data, large_binary_data) = create_sample_data()
+    (text_data, dict_data, arrow_table_small, arrow_table_large, json_table_small, json_table_large, audio_data, large_audio_data, video_data, large_video_data, binary_data, large_binary_data) = create_sample_data()
+
+    # Read image files from disk (following test_julia_file_sender.jl pattern)
+    # Small image - should use direct transport
+    file_path_small_image = "./test/small_image.jpg"
+    file_data_small_image = read(file_path_small_image)
+    filename_small_image = basename(file_path_small_image)
+
+    # Large image - should use link transport
+    file_path_large_image = "./test/large_image.png"
+    file_data_large_image = read(file_path_large_image)
+    filename_large_image = basename(file_path_large_image)
 
     # Create payloads list - mixed content with both small and large data
     # Small data uses direct transport, large data uses link transport
+    # Key: Pass DataFrame directly and specify type as "arrowtable" or "jsontable"
+    # NATSBridge.jl handles the serialization internally
     payloads = [
-        # Small data (direct transport) - text, dictionary, small table
+        # Small data (direct transport) - text, dictionary, arrowtable, jsontable, small image
         ("chat_text", text_data, "text"),
         ("chat_json", dict_data, "dictionary"),
-        ("chat_table_small", table_data_small, "table"),
+        # ("arrow_table_small", arrow_table_small, "arrowtable"),
+        ("json_table_small", json_table_small, "jsontable"),
+        (filename_small_image, file_data_small_image, "binary"),
 
-        # Large data (link transport) - large table, large image, large audio, large video, large binary
-        ("chat_table_large", table_data_large, "table"),
-        ("user_image_large", large_image_data, "image"),
+        # Large data (link transport) - large arrowtable, large jsontable, large image, large audio, large video, large binary
+        # ("arrow_table_large", arrow_table_large, "arrowtable"),
+        ("json_table_large", json_table_large, "jsontable"),
+        (filename_large_image, file_data_large_image, "binary"),
         ("audio_clip_large", large_audio_data, "audio"),
         ("video_clip_large", large_video_data, "video"),
         ("binary_file_large", large_binary_data, "binary")
     ]
     
     # Use smartsend with mixed content
-    env = NATSBridge.smartsend(
+    sendinfo = NATSBridge.smartsend(
         SUBJECT,
-        payloads,  # List of (dataname, data, type) tuples
-        nats_url = NATS_URL,
+        payloads;  # List of (dataname, data, type) tuples
+        broker_url = NATS_URL,
         fileserver_url = FILESERVER_URL,
-        fileserverUploadHandler = plik_upload_handler,
+        fileserver_upload_handler = plik_upload_handler,
         size_threshold = 1_000_000,  # 1MB threshold
         correlation_id = correlation_id,
         msg_purpose = "chat",
@@ -199,16 +217,18 @@ function test_mix_send()
         receiver_name = "",
         receiver_id = "",
         reply_to = "",
-        reply_to_msg_id = ""
+        reply_to_msg_id = "",
+        is_publish = true  # Publish the message to NATS
     )
 
+    env, env_json_str = sendinfo
     log_trace("Sent message with $(length(env.payloads)) payloads")
     
     # Log transport type for each payload
     for (i, payload) in enumerate(env.payloads)
         log_trace("Payload $i ('$payload.dataname'):")
         log_trace("  Transport: $(payload.transport)")
-        log_trace("  Type: $(payload.type)")
+        log_trace("  Type: $(payload.payload_type)")
         log_trace("  Size: $(payload.size) bytes")
         log_trace("  Encoding: $(payload.encoding)")
         

test/test_julia_to_julia_dict_receiver.jl

@@ -1,82 +0,0 @@
-#!/usr/bin/env julia
-# Test script for Dictionary transport testing
-# Tests receiving 1 large and 1 small Dictionaries via direct and link transport
-# Uses NATSBridge.jl smartreceive with "dictionary" type
-
-using NATS, JSON, UUIDs, Dates, PrettyPrinting, DataFrames, Arrow, HTTP
-
-# Include the bridge module
-include("../src/NATSBridge.jl")
-using .NATSBridge
-
-# Configuration
-const SUBJECT = "/NATSBridge_dict_test"
-const NATS_URL = "nats.yiem.cc"
-const FILESERVER_URL = "http://192.168.88.104:8080"
-
-
-# ------------------------------------------------------------------------------------------------ #
-#                                        test dictionary transfer                                  #
-# ------------------------------------------------------------------------------------------------ #
-
-
-# Helper: Log with correlation ID
-function log_trace(message)
-    timestamp = Dates.now()
-    println("[$timestamp] $message")
-end
-
-
-# Receiver: Listen for messages and verify Dictionary handling
-function test_dict_receive()
-    conn = NATS.connect(NATS_URL)
-    NATS.subscribe(conn, SUBJECT) do msg
-        log_trace("Received message on $(msg.subject)")
-        
-        # Use NATSBridge.smartreceive to handle the data
-        # API: smartreceive(msg, download_handler; max_retries, base_delay, max_delay)
-        result = NATSBridge.smartreceive(
-            msg;
-            max_retries = 5,
-            base_delay = 100,
-            max_delay = 5000
-        )
-        
-        # Result is a list of (dataname, data, data_type) tuples
-        for (dataname, data, data_type) in result
-            if isa(data, JSON.Object{String, Any})
-                log_trace("Received Dictionary '$dataname' of type $data_type")
-                
-                # Display dictionary contents
-                println("  Contents:")
-                for (key, value) in data
-                    println("    $key => $value")
-                end
-                
-                # Save to JSON file
-                output_path = "./received_$dataname.json"
-                json_str = JSON.json(data, 2)
-                write(output_path, json_str)
-                log_trace("Saved Dictionary to $output_path")
-            else
-                log_trace("Received unexpected data type for '$dataname': $(typeof(data))")
-            end
-        end
-    end
-    
-    # Keep listening for 10 seconds
-    sleep(120)  
-    NATS.drain(conn)
-end
-
-
-# Run the test
-println("Starting Dictionary transport test...")
-println("Note: This receiver will wait for messages from the sender.")
-println("Run test_julia_to_julia_dict_sender.jl first to send test data.")
-
-# Run receiver
-println("testing smartreceive")
-test_dict_receive()
-
-println("Test completed.")

test/test_julia_to_julia_dict_sender.jl

@@ -1,136 +0,0 @@
-#!/usr/bin/env julia
-# Test script for Dictionary transport testing
-# Tests sending 1 large and 1 small Dictionaries via direct and link transport
-# Uses NATSBridge.jl smartsend with "dictionary" type
-
-using NATS, JSON, UUIDs, Dates, PrettyPrinting, DataFrames, Arrow, HTTP
-
-# Include the bridge module
-include("../src/NATSBridge.jl")
-using .NATSBridge
-
-# Configuration
-const SUBJECT = "/NATSBridge_dict_test"
-const NATS_URL = "nats.yiem.cc"
-const FILESERVER_URL = "http://192.168.88.104:8080"
-
-# Create correlation ID for tracing
-correlation_id = string(uuid4())
-
-
-# ------------------------------------------------------------------------------------------------ #
-#                                        test dictionary transfer                                  #
-# ------------------------------------------------------------------------------------------------ #
-
-
-# Helper: Log with correlation ID
-function log_trace(message)
-    timestamp = Dates.now()
-    println("[$timestamp] [Correlation: $correlation_id] $message")
-end
-
-
-# File upload handler for plik server
-function plik_upload_handler(fileserver_url::String, dataname::String, data::Vector{UInt8})::Dict{String, Any}
-    # Get upload ID
-    url_getUploadID = "$fileserver_url/upload"
-    headers = ["Content-Type" => "application/json"]
-    body = """{ "OneShot" : true }"""
-    httpResponse = HTTP.request("POST", url_getUploadID, headers, body; body_is_form=false)
-    responseJson = JSON.parse(String(httpResponse.body))
-    uploadid = responseJson["id"]
-    uploadtoken = responseJson["uploadToken"]
-    
-    # Upload file
-    file_multipart = HTTP.Multipart(dataname, IOBuffer(data), "application/octet-stream")
-    url_upload = "$fileserver_url/file/$uploadid"
-    headers = ["X-UploadToken" => uploadtoken]
-    
-    form = HTTP.Form(Dict("file" => file_multipart))
-    httpResponse = HTTP.post(url_upload, headers, form)
-    responseJson = JSON.parse(String(httpResponse.body))
-    
-    fileid = responseJson["id"]
-    url = "$fileserver_url/file/$uploadid/$fileid/$dataname"
-    
-    return Dict("status" => httpResponse.status, "uploadid" => uploadid, "fileid" => fileid, "url" => url)
-end
-
-
-# Sender: Send Dictionaries via smartsend
-function test_dict_send()
-    # Create a small Dictionary (will use direct transport)
-    small_dict = Dict(
-        "name" => "Alice",
-        "age" => 30,
-        "scores" => [95, 88, 92],
-        "metadata" => Dict(
-            "height" => 155,
-            "weight" => 55
-        )
-    )
-    
-    # Create a large Dictionary (will use link transport if > 1MB)
-    # Generate a larger dataset (~2MB to ensure link transport)
-    large_dict = Dict(
-        "ids" => collect(1:50000),
-        "names" => ["User_$i" for i in 1:50000],
-        "scores" => rand(1:100, 50000),
-        "categories" => ["Category_$(rand(1:10))" for i in 1:50000],
-        "metadata" => Dict(
-            "source" => "test_generator",
-            "timestamp" => string(Dates.now())
-        )
-    )
-    
-    # Test data 1: small Dictionary
-    data1 = ("small_dict", small_dict, "dictionary")
-    
-    # Test data 2: large Dictionary
-    data2 = ("large_dict", large_dict, "dictionary")
-    
-    # Use smartsend with dictionary type
-    # For small Dictionary: will use direct transport (JSON encoded)
-    # For large Dictionary: will use link transport (uploaded to fileserver)
-    env = NATSBridge.smartsend(
-        SUBJECT,
-        [data1, data2],  # List of (dataname, data, type) tuples
-        nats_url = NATS_URL,
-        fileserver_url = FILESERVER_URL,
-        fileserverUploadHandler = plik_upload_handler,
-        size_threshold = 1_000_000,  # 1MB threshold
-        correlation_id = correlation_id,
-        msg_purpose = "chat",
-        sender_name = "dict_sender",
-        receiver_name = "",
-        receiver_id = "",
-        reply_to = "",
-        reply_to_msg_id = ""
-    )
-    
-    log_trace("Sent message with $(length(env.payloads)) payloads")
-    
-    # Log transport type for each payload
-    for (i, payload) in enumerate(env.payloads)
-        log_trace("Payload $i ('$payload.dataname'):")
-        log_trace("  Transport: $(payload.transport)")
-        log_trace("  Type: $(payload.type)")
-        log_trace("  Size: $(payload.size) bytes")
-        log_trace("  Encoding: $(payload.encoding)")
-        
-        if payload.transport == "link"
-            log_trace("  URL: $(payload.data)")
-        end
-    end
-end
-
-
-# Run the test
-println("Starting Dictionary transport test...")
-println("Correlation ID: $correlation_id")
-
-# Run sender
-println("start smartsend for dictionaries")
-test_dict_send()
-
-println("Test completed.")

test/test_julia_to_julia_file_receiver.jl

@@ -1,84 +0,0 @@
-#!/usr/bin/env julia
-# Test script for large payload testing using binary transport
-# Tests sending a large file (> 1MB) via smartsend with binary type
-# Updated to match NATSBridge.jl API
-
-using NATS, JSON, UUIDs, Dates, PrettyPrinting, DataFrames, Arrow, HTTP
-
-
-# workdir = 
-
-# Include the bridge module
-include("../src/NATSBridge.jl")
-using .NATSBridge
-
-# Configuration
-const SUBJECT = "/NATSBridge_test"
-const NATS_URL = "nats.yiem.cc"
-const FILESERVER_URL = "http://192.168.88.104:8080"
-
-
-
-# ------------------------------------------------------------------------------------------------ #
-#                                        test file transfer                                        #
-# ------------------------------------------------------------------------------------------------ #
-
-# Helper: Log with correlation ID
-function log_trace(message)
-    timestamp = Dates.now()
-    println("[$timestamp] $message")
-end
-
-# Receiver: Listen for messages and verify large payload handling
-function test_large_binary_receive()
-    conn = NATS.connect(NATS_URL)
-    NATS.subscribe(conn, SUBJECT) do msg
-        log_trace("Received message on $(msg.subject)")
-        
-        # Use NATSBridge.smartreceive to handle the data
-        # API: smartreceive(msg, download_handler; max_retries, base_delay, max_delay)
-        result = NATSBridge.smartreceive(
-            msg;
-            max_retries = 5,
-            base_delay = 100,
-            max_delay = 5000
-        )
-        
-        # Result is a list of (dataname, data) tuples
-        for (dataname, data, data_type) in result
-            # Check transport type from the envelope
-            # For link transport, data is the URL string
-            # For direct transport, data is the actual payload bytes
-            
-            if isa(data, Vector{UInt8})
-                file_size = length(data)
-                log_trace("Received $(file_size) bytes of binary data for '$dataname' of type $data_type")
-                
-                # Save received data to a test file
-                output_path = "./new_$dataname"
-                write(output_path, data)
-                log_trace("Saved received data to $output_path")
-            else
-                log_trace("Received $(file_size) bytes of binary data for '$dataname' of type $data_type")
-            end
-        end
-    end
-    
-    # Keep listening for 10 seconds
-    sleep(120)  
-    NATS.drain(conn)
-end
-
-
-# Run the test
-println("Starting large binary payload test...")
-
-# # Run sender first
-# println("start smartsend")
-# test_large_binary_send()
-
-# Run receiver
-println("testing smartreceive")
-test_large_binary_receive()
-
-println("Test completed.")

test/test_julia_to_julia_file_sender.jl

@@ -1,122 +0,0 @@
-#!/usr/bin/env julia
-# Test script for large payload testing using binary transport
-# Tests sending a large file (> 1MB) via smartsend with binary type
-# Updated to match NATSBridge.jl API
-
-using NATS, JSON, UUIDs, Dates, PrettyPrinting, DataFrames, Arrow, HTTP
-
-
-# workdir = 
-
-# Include the bridge module
-include("../src/NATSBridge.jl")
-using .NATSBridge
-
-# Configuration
-const SUBJECT = "/NATSBridge_test"
-const NATS_URL = "nats.yiem.cc"
-const FILESERVER_URL = "http://192.168.88.104:8080"
-
-# Create correlation ID for tracing
-correlation_id = string(uuid4())
-
-
-# ------------------------------------------------------------------------------------------------ #
-#                                        test file transfer                                        #
-# ------------------------------------------------------------------------------------------------ #
-
-
-# Helper: Log with correlation ID
-function log_trace(message)
-    timestamp = Dates.now()
-    println("[$timestamp] [Correlation: $correlation_id] $message")
-end
-
-# File upload handler for plik server
-function plik_upload_handler(fileserver_url::String, dataname::String, data::Vector{UInt8})::Dict{String, Any}
-    # Get upload ID
-    url_getUploadID = "$fileserver_url/upload"
-    headers = ["Content-Type" => "application/json"]
-    body = """{ "OneShot" : true }"""
-    httpResponse = HTTP.request("POST", url_getUploadID, headers, body; body_is_form=false)
-    responseJson = JSON.parse(String(httpResponse.body))
-    uploadid = responseJson["id"]
-    uploadtoken = responseJson["uploadToken"]
-    
-    # Upload file
-    file_multipart = HTTP.Multipart(dataname, IOBuffer(data), "application/octet-stream")
-    url_upload = "$fileserver_url/file/$uploadid"
-    headers = ["X-UploadToken" => uploadtoken]
-    
-    form = HTTP.Form(Dict("file" => file_multipart))
-    httpResponse = HTTP.post(url_upload, headers, form)
-    responseJson = JSON.parse(String(httpResponse.body))
-    
-    fileid = responseJson["id"]
-    url = "$fileserver_url/file/$uploadid/$fileid/$dataname"
-    
-    return Dict("status" => httpResponse.status, "uploadid" => uploadid, "fileid" => fileid, "url" => url)
-end
-
-# Sender: Send large binary file via smartsend
-function test_large_binary_send()
-    # Read the large file as binary data
-    
-    # test data 1
-    file_path1 = "./testFile_large.zip"
-    file_data1 = read(file_path1)
-    filename1 = basename(file_path1)
-    data1 = (filename1, file_data1, "binary")
-
-    # test data 2
-    file_path2 = "./testFile_small.zip"
-    file_data2 = read(file_path2)
-    filename2 = basename(file_path2)
-    data2 = (filename2, file_data2, "binary")
-    
-    
-    
-    # Use smartsend with binary type - will automatically use link transport
-    # if file size exceeds the threshold (1MB by default)
-    # API: smartsend(subject, [(dataname, data, type), ...]; keywords...)
-    env = NATSBridge.smartsend(
-        SUBJECT,
-        [data1, data2],  # List of (dataname, data, type) tuples
-        nats_url = NATS_URL;
-        fileserver_url = FILESERVER_URL,
-        fileserverUploadHandler = plik_upload_handler,
-        size_threshold = 1_000_000,
-        correlation_id = correlation_id,
-        msg_purpose = "chat",
-        sender_name = "sender",
-        receiver_name = "",
-        receiver_id = "",
-        reply_to = "",
-        reply_to_msg_id = ""
-    )
-    
-    log_trace("Sent message with transport: $(env.payloads[1].transport)")
-    log_trace("Envelope type: $(env.payloads[1].type)")
-    
-    # Check if link transport was used
-    if env.payloads[1].transport == "link"
-        log_trace("Using link transport - file uploaded to HTTP server")
-        log_trace("URL: $(env.payloads[1].data)")
-    else
-        log_trace("Using direct transport - payload sent via NATS")
-    end
-end
-
-# Run the test
-println("Starting large binary payload test...")
-println("Correlation ID: $correlation_id")
-
-# Run sender first
-println("start smartsend")
-test_large_binary_send()
-
-# Run receiver
-# println("testing smartreceive")
-# test_large_binary_receive()
-
-println("Test completed.")

test/test_julia_to_julia_table_receiver.jl

@@ -1,84 +0,0 @@
-#!/usr/bin/env julia
-# Test script for DataFrame table transport testing
-# Tests receiving 1 large and 1 small DataFrames via direct and link transport
-# Uses NATSBridge.jl smartreceive with "table" type
-
-using NATS, JSON, UUIDs, Dates, PrettyPrinting, DataFrames, Arrow, HTTP
-
-# Include the bridge module
-include("../src/NATSBridge.jl")
-using .NATSBridge
-
-# Configuration
-const SUBJECT = "/NATSBridge_table_test"
-const NATS_URL = "nats.yiem.cc"
-const FILESERVER_URL = "http://192.168.88.104:8080"
-
-
-# ------------------------------------------------------------------------------------------------ #
-#                                        test table transfer                                       #
-# ------------------------------------------------------------------------------------------------ #
-
-
-# Helper: Log with correlation ID
-function log_trace(message)
-    timestamp = Dates.now()
-    println("[$timestamp] $message")
-end
-
-
-# Receiver: Listen for messages and verify DataFrame table handling
-function test_table_receive()
-    conn = NATS.connect(NATS_URL)
-    NATS.subscribe(conn, SUBJECT) do msg
-        log_trace("Received message on $(msg.subject)")
-        
-        # Use NATSBridge.smartreceive to handle the data
-        # API: smartreceive(msg, download_handler; max_retries, base_delay, max_delay)
-        result = NATSBridge.smartreceive(
-            msg;
-            max_retries = 5,
-            base_delay = 100,
-            max_delay = 5000
-        )
-        
-        # Result is a list of (dataname, data, data_type) tuples
-        for (dataname, data, data_type) in result
-          data = DataFrame(data)
-            if isa(data, DataFrame)
-                log_trace("Received DataFrame '$dataname' of type $data_type")
-                log_trace("  Dimensions: $(size(data, 1)) rows x $(size(data, 2)) columns")
-                log_trace("  Column names: $(names(data))")
-                
-                # Display first few rows
-                println("  First 5 rows:")
-                display(data[1:min(5, size(data, 1)), :])
-                
-                # Save to file
-                output_path = "./received_$dataname.arrow"
-                io = IOBuffer()
-                Arrow.write(io, data)
-                write(output_path, take!(io))
-                log_trace("Saved DataFrame to $output_path")
-            else
-                log_trace("Received unexpected data type for '$dataname': $(typeof(data))")
-            end
-        end
-    end
-    
-    # Keep listening for 10 seconds
-    sleep(120)  
-    NATS.drain(conn)
-end
-
-
-# Run the test
-println("Starting DataFrame table transport test...")
-println("Note: This receiver will wait for messages from the sender.")
-println("Run test_julia_to_julia_table_sender.jl first to send test data.")
-
-# Run receiver
-println("testing smartreceive")
-test_table_receive()
-
-println("Test completed.")

test/test_julia_to_julia_table_sender.jl

@@ -1,134 +0,0 @@
-#!/usr/bin/env julia
-# Test script for DataFrame table transport testing
-# Tests sending 1 large and 1 small DataFrames via direct and link transport
-# Uses NATSBridge.jl smartsend with "table" type
-
-using NATS, JSON, UUIDs, Dates, PrettyPrinting, DataFrames, Arrow, HTTP
-
-# Include the bridge module
-include("../src/NATSBridge.jl")
-using .NATSBridge
-
-# Configuration
-const SUBJECT = "/NATSBridge_table_test"
-const NATS_URL = "nats.yiem.cc"
-const FILESERVER_URL = "http://192.168.88.104:8080"
-
-# Create correlation ID for tracing
-correlation_id = string(uuid4())
-
-
-# ------------------------------------------------------------------------------------------------ #
-#                                        test table transfer                                       #
-# ------------------------------------------------------------------------------------------------ #
-
-
-# Helper: Log with correlation ID
-function log_trace(message)
-    timestamp = Dates.now()
-    println("[$timestamp] [Correlation: $correlation_id] $message")
-end
-
-
-# File upload handler for plik server
-function plik_upload_handler(fileserver_url::String, dataname::String, data::Vector{UInt8})::Dict{String, Any}
-    # Get upload ID
-    url_getUploadID = "$fileserver_url/upload"
-    headers = ["Content-Type" => "application/json"]
-    body = """{ "OneShot" : true }"""
-    httpResponse = HTTP.request("POST", url_getUploadID, headers, body; body_is_form=false)
-    responseJson = JSON.parse(String(httpResponse.body))
-    uploadid = responseJson["id"]
-    uploadtoken = responseJson["uploadToken"]
-    
-    # Upload file
-    file_multipart = HTTP.Multipart(dataname, IOBuffer(data), "application/octet-stream")
-    url_upload = "$fileserver_url/file/$uploadid"
-    headers = ["X-UploadToken" => uploadtoken]
-    
-    form = HTTP.Form(Dict("file" => file_multipart))
-    httpResponse = HTTP.post(url_upload, headers, form)
-    responseJson = JSON.parse(String(httpResponse.body))
-    
-    fileid = responseJson["id"]
-    url = "$fileserver_url/file/$uploadid/$fileid/$dataname"
-    
-    return Dict("status" => httpResponse.status, "uploadid" => uploadid, "fileid" => fileid, "url" => url)
-end
-
-
-# Sender: Send DataFrame tables via smartsend
-function test_table_send()
-    # Create a small DataFrame (will use direct transport)
-    small_df = DataFrame(
-        id = 1:10,
-        name = ["Alice", "Bob", "Charlie", "Diana", "Eve", "Frank", "Grace", "Henry", "Ivy", "Jack"],
-        score = [95, 88, 92, 85, 90, 78, 95, 88, 92, 85],
-        category = ["A", "B", "A", "B", "A", "B", "A", "B", "A", "B"]
-    )
-    
-    # Create a large DataFrame (will use link transport if > 1MB)
-    # Generate a larger dataset (~2MB to ensure link transport)
-    large_ids = 1:50000
-    large_names = ["User_$i" for i in 1:50000]
-    large_scores = rand(1:100, 50000)
-    large_categories = ["Category_$(rand(1:10))" for i in 1:50000]
-    
-    large_df = DataFrame(
-        id = large_ids,
-        name = large_names,
-        score = large_scores,
-        category = large_categories
-    )
-    
-    # Test data 1: small DataFrame
-    data1 = ("small_table", small_df, "table")
-    
-    # Test data 2: large DataFrame
-    data2 = ("large_table", large_df, "table")
-    
-    # Use smartsend with table type
-    # For small DataFrame: will use direct transport (Base64 encoded Arrow IPC)
-    # For large DataFrame: will use link transport (uploaded to fileserver)
-    env = NATSBridge.smartsend(
-        SUBJECT,
-        [data1, data2],  # List of (dataname, data, type) tuples
-        nats_url = NATS_URL,
-        fileserver_url = FILESERVER_URL,
-        fileserverUploadHandler = plik_upload_handler,
-        size_threshold = 1_000_000,  # 1MB threshold
-        correlation_id = correlation_id,
-        msg_purpose = "chat",
-        sender_name = "table_sender",
-        receiver_name = "",
-        receiver_id = "",
-        reply_to = "",
-        reply_to_msg_id = ""
-    )
-    
-    log_trace("Sent message with $(length(env.payloads)) payloads")
-    
-    # Log transport type for each payload
-    for (i, payload) in enumerate(env.payloads)
-        log_trace("Payload $i ('$payload.dataname'):")
-        log_trace("  Transport: $(payload.transport)")
-        log_trace("  Type: $(payload.type)")
-        log_trace("  Size: $(payload.size) bytes")
-        log_trace("  Encoding: $(payload.encoding)")
-        
-        if payload.transport == "link"
-            log_trace("  URL: $(payload.data)")
-        end
-    end
-end
-
-
-# Run the test
-println("Starting DataFrame table transport test...")
-println("Correlation ID: $correlation_id")
-
-# Run sender
-println("start smartsend for tables")
-test_table_send()
-
-println("Test completed.")

test/test_julia_to_julia_text_receiver.jl

@@ -1,83 +0,0 @@
-#!/usr/bin/env julia
-# Test script for text transport testing
-# Tests receiving 1 large and 1 small text from Julia serviceA to Julia serviceB
-# Uses NATSBridge.jl smartreceive with "text" type
-
-using NATS, JSON, UUIDs, Dates, PrettyPrinting, DataFrames, Arrow, HTTP
-
-# Include the bridge module
-include("../src/NATSBridge.jl")
-using .NATSBridge
-
-# Configuration
-const SUBJECT = "/NATSBridge_text_test"
-const NATS_URL = "nats.yiem.cc"
-const FILESERVER_URL = "http://192.168.88.104:8080"
-
-
-# ------------------------------------------------------------------------------------------------ #
-#                                        test text transfer                                        #
-# ------------------------------------------------------------------------------------------------ #
-
-
-# Helper: Log with correlation ID
-function log_trace(message)
-    timestamp = Dates.now()
-    println("[$timestamp] $message")
-end
-
-
-# Receiver: Listen for messages and verify text handling
-function test_text_receive()
-    conn = NATS.connect(NATS_URL)
-    NATS.subscribe(conn, SUBJECT) do msg
-        log_trace("Received message on $(msg.subject)")
-        
-        # Use NATSBridge.smartreceive to handle the data
-        # API: smartreceive(msg, download_handler; max_retries, base_delay, max_delay)
-        result = NATSBridge.smartreceive(
-            msg;
-            max_retries = 5,
-            base_delay = 100,
-            max_delay = 5000
-        )
-        
-        # Result is a list of (dataname, data, data_type) tuples
-        for (dataname, data, data_type) in result
-            if isa(data, String)
-                log_trace("Received text '$dataname' of type $data_type")
-                log_trace("  Length: $(length(data)) characters")
-                
-                # Display first 100 characters
-                if length(data) > 100
-                    log_trace("  First 100 characters: $(data[1:100])...")
-                else
-                    log_trace("  Content: $data")
-                end
-                
-                # Save to file
-                output_path = "./received_$dataname.txt"
-                write(output_path, data)
-                log_trace("Saved text to $output_path")
-            else
-                log_trace("Received unexpected data type for '$dataname': $(typeof(data))")
-            end
-        end
-    end
-    
-    # Keep listening for 10 seconds
-    sleep(120)  
-    NATS.drain(conn)
-end
-
-
-# Run the test
-println("Starting text transport test...")
-println("Note: This receiver will wait for messages from the sender.")
-println("Run test_julia_to_julia_text_sender.jl first to send test data.")
-
-# Run receiver
-println("testing smartreceive for text")
-test_text_receive()
-
-println("Test completed.")

test/test_julia_to_julia_text_sender.jl

@@ -1,119 +0,0 @@
-#!/usr/bin/env julia
-# Test script for text transport testing
-# Tests sending 1 large and 1 small text from Julia serviceA to Julia serviceB
-# Uses NATSBridge.jl smartsend with "text" type
-
-using NATS, JSON, UUIDs, Dates, PrettyPrinting, DataFrames, Arrow, HTTP
-
-# Include the bridge module
-include("../src/NATSBridge.jl")
-using .NATSBridge
-
-# Configuration
-const SUBJECT = "/NATSBridge_text_test"
-const NATS_URL = "nats.yiem.cc"
-const FILESERVER_URL = "http://192.168.88.104:8080"
-
-# Create correlation ID for tracing
-correlation_id = string(uuid4())
-
-
-# ------------------------------------------------------------------------------------------------ #
-#                                        test text transfer                                        #
-# ------------------------------------------------------------------------------------------------ #
-
-
-# Helper: Log with correlation ID
-function log_trace(message)
-    timestamp = Dates.now()
-    println("[$timestamp] [Correlation: $correlation_id] $message")
-end
-
-
-# File upload handler for plik server
-function plik_upload_handler(fileserver_url::String, dataname::String, data::Vector{UInt8})::Dict{String, Any}
-    # Get upload ID
-    url_getUploadID = "$fileserver_url/upload"
-    headers = ["Content-Type" => "application/json"]
-    body = """{ "OneShot" : true }"""
-    httpResponse = HTTP.request("POST", url_getUploadID, headers, body; body_is_form=false)
-    responseJson = JSON.parse(String(httpResponse.body))
-    uploadid = responseJson["id"]
-    uploadtoken = responseJson["uploadToken"]
-    
-    # Upload file
-    file_multipart = HTTP.Multipart(dataname, IOBuffer(data), "application/octet-stream")
-    url_upload = "$fileserver_url/file/$uploadid"
-    headers = ["X-UploadToken" => uploadtoken]
-    
-    form = HTTP.Form(Dict("file" => file_multipart))
-    httpResponse = HTTP.post(url_upload, headers, form)
-    responseJson = JSON.parse(String(httpResponse.body))
-    
-    fileid = responseJson["id"]
-    url = "$fileserver_url/file/$uploadid/$fileid/$dataname"
-    
-    return Dict("status" => httpResponse.status, "uploadid" => uploadid, "fileid" => fileid, "url" => url)
-end
-
-
-# Sender: Send text via smartsend
-function test_text_send()
-    # Create a small text (will use direct transport)
-    small_text = "Hello, this is a small text message. Testing direct transport via NATS."
-    
-    # Create a large text (will use link transport if > 1MB)
-    # Generate a larger text (~2MB to ensure link transport)
-    large_text = join(["Line $i: This is a sample text line with some content to pad the size. " for i in 1:50000], "")
-    
-    # Test data 1: small text
-    data1 = ("small_text", small_text, "text")
-    
-    # Test data 2: large text
-    data2 = ("large_text", large_text, "text")
-    
-    # Use smartsend with text type
-    # For small text: will use direct transport (Base64 encoded UTF-8)
-    # For large text: will use link transport (uploaded to fileserver)
-    env = NATSBridge.smartsend(
-        SUBJECT,
-        [data1, data2],  # List of (dataname, data, type) tuples
-        nats_url = NATS_URL,
-        fileserver_url = FILESERVER_URL,
-        fileserverUploadHandler = plik_upload_handler,
-        size_threshold = 1_000_000,  # 1MB threshold
-        correlation_id = correlation_id,
-        msg_purpose = "chat",
-        sender_name = "text_sender",
-        receiver_name = "",
-        receiver_id = "",
-        reply_to = "",
-        reply_to_msg_id = ""
-    )
-    
-    log_trace("Sent message with $(length(env.payloads)) payloads")
-    
-    # Log transport type for each payload
-    for (i, payload) in enumerate(env.payloads)
-        log_trace("Payload $i ('$payload.dataname'):")
-        log_trace("  Transport: $(payload.transport)")
-        log_trace("  Type: $(payload.type)")
-        log_trace("  Size: $(payload.size) bytes")
-        log_trace("  Encoding: $(payload.encoding)")
-        
-        if payload.transport == "link"
-            log_trace("  URL: $(payload.data)")
-        end
-    end
-end
-
-
-# Run the test
-println("Starting text transport test...")
-println("Correlation ID: $correlation_id")
-
-# Run sender
-println("start smartsend for text")
-test_text_send()
-
-println("Test completed.")

test/test_micropython_basic.py

@@ -1,220 +0,0 @@
-"""
-Micropython NATS Bridge - Basic Test Examples
-
-This module demonstrates basic usage of the NATSBridge for Micropython.
-"""
-
-import sys
-sys.path.insert(0, "../src")
-
-from nats_bridge import MessageEnvelope, MessagePayload, smartsend, smartreceive, log_trace
-import json
-
-# ============================================= 100 ============================================== #
-
-
-def test_text_message():
-    """Test sending and receiving text messages."""
-    print("\n=== Test 1: Text Message ===")
-    
-    # Send text message
-    data = [
-        ("message", "Hello World", "text"),
-        ("greeting", "Good morning!", "text")
-    ]
-    
-    env = smartsend(
-        "/test/text",
-        data,
-        nats_url="nats://localhost:4222",
-        size_threshold=1000000
-    )
-    
-    print("Sent envelope:")
-    print("  Subject: {}".format(env.send_to))
-    print("  Correlation ID: {}".format(env.correlation_id))
-    print("  Payloads: {}".format(len(env.payloads)))
-    
-    # Expected output on receiver:
-    # payloads = smartreceive(msg)
-    # for dataname, data, type in payloads:
-    #     print("Received {}: {}".format(dataname, data))
-
-
-def test_dictionary_message():
-    """Test sending and receiving dictionary messages."""
-    print("\n=== Test 2: Dictionary Message ===")
-    
-    # Send dictionary message
-    config = {
-        "step_size": 0.01,
-        "iterations": 1000,
-        "threshold": 0.5
-    }
-    
-    data = [
-        ("config", config, "dictionary")
-    ]
-    
-    env = smartsend(
-        "/test/dictionary",
-        data,
-        nats_url="nats://localhost:4222",
-        size_threshold=1000000
-    )
-    
-    print("Sent envelope:")
-    print("  Subject: {}".format(env.send_to))
-    print("  Payloads: {}".format(len(env.payloads)))
-    
-    # Expected output on receiver:
-    # payloads = smartreceive(msg)
-    # for dataname, data, type in payloads:
-    #     if type == "dictionary":
-    #         print("Config: {}".format(data))
-
-
-def test_mixed_payloads():
-    """Test sending mixed payload types in a single message."""
-    print("\n=== Test 3: Mixed Payloads ===")
-    
-    # Mixed content: text, dictionary, and binary
-    image_data = b"\x89PNG\r\n\x1a\n\x00\x00\x00\rIHDR"  # PNG header (example)
-    
-    data = [
-        ("message_text", "Hello!", "text"),
-        ("user_config", {"theme": "dark", "volume": 80}, "dictionary"),
-        ("user_image", image_data, "binary")
-    ]
-    
-    env = smartsend(
-        "/test/mixed",
-        data,
-        nats_url="nats://localhost:4222",
-        size_threshold=1000000
-    )
-    
-    print("Sent envelope:")
-    print("  Subject: {}".format(env.send_to))
-    print("  Payloads: {}".format(len(env.payloads)))
-    
-    # Expected output on receiver:
-    # payloads = smartreceive(msg)
-    # for dataname, data, type in payloads:
-    #     print("Received {}: {} (type: {})".format(dataname, data if type != "binary" else len(data), type))
-
-
-def test_large_payload():
-    """Test sending large payloads that require fileserver upload."""
-    print("\n=== Test 4: Large Payload (Link Transport) ===")
-    
-    # Create large data (> 1MB would trigger link transport)
-    # For testing, we'll use a smaller size but configure threshold lower
-    large_data = b"A" * 100000  # 100KB
-    
-    data = [
-        ("large_data", large_data, "binary")
-    ]
-    
-    # Use a lower threshold for testing
-    env = smartsend(
-        "/test/large",
-        data,
-        nats_url="nats://localhost:4222",
-        fileserver_url="http://localhost:8080",
-        size_threshold=50000  # 50KB threshold for testing
-    )
-    
-    print("Sent envelope:")
-    print("  Subject: {}".format(env.send_to))
-    print("  Payloads: {}".format(len(env.payloads)))
-    for p in env.payloads:
-        print("  - Transport: {}, Type: {}".format(p.transport, p.type))
-
-
-def test_reply_to():
-    """Test sending messages with reply-to functionality."""
-    print("\n=== Test 5: Reply To ===")
-    
-    data = [
-        ("command", {"action": "start"}, "dictionary")
-    ]
-    
-    env = smartsend(
-        "/test/command",
-        data,
-        nats_url="nats://localhost:4222",
-        reply_to="/test/response",
-        reply_to_msg_id="reply-123",
-        msg_purpose="command"
-    )
-    
-    print("Sent envelope:")
-    print("  Subject: {}".format(env.send_to))
-    print("  Reply To: {}".format(env.reply_to))
-    print("  Reply To Msg ID: {}".format(env.reply_to_msg_id))
-
-
-def test_correlation_id():
-    """Test using custom correlation IDs for tracing."""
-    print("\n=== Test 6: Custom Correlation ID ===")
-    
-    custom_cid = "trace-abc123"
-    data = [
-        ("message", "Test with correlation ID", "text")
-    ]
-    
-    env = smartsend(
-        "/test/correlation",
-        data,
-        nats_url="nats://localhost:4222",
-        correlation_id=custom_cid
-    )
-    
-    print("Sent envelope with correlation ID: {}".format(env.correlation_id))
-    print("This ID can be used to trace the message flow.")
-
-
-def test_multiple_payloads():
-    """Test sending multiple payloads in one message."""
-    print("\n=== Test 7: Multiple Payloads ===")
-    
-    data = [
-        ("text_message", "Hello", "text"),
-        ("json_data", {"key": "value", "number": 42}, "dictionary"),
-        ("table_data", b"\x01\x02\x03\x04", "binary"),
-        ("audio_data", b"\x00\x01\x02\x03", "binary")
-    ]
-    
-    env = smartsend(
-        "/test/multiple",
-        data,
-        nats_url="nats://localhost:4222",
-        size_threshold=1000000
-    )
-    
-    print("Sent {} payloads in one message".format(len(env.payloads)))
-
-
-if __name__ == "__main__":
-    print("Micropython NATS Bridge Test Suite")
-    print("==================================")
-    print()
-    
-    # Run tests
-    test_text_message()
-    test_dictionary_message()
-    test_mixed_payloads()
-    test_large_payload()
-    test_reply_to()
-    test_correlation_id()
-    test_multiple_payloads()
-    
-    print("\n=== All tests completed ===")
-    print()
-    print("Note: These tests require:")
-    print("  1. A running NATS server at nats://localhost:4222")
-    print("  2. An HTTP file server at http://localhost:8080 (for large payloads)")
-    print()
-    print("To run the tests:")
-    print("  python test_micropython_basic.py")

test/test_py_mix_payloads_sender.py

@@ -0,0 +1,199 @@
+"""
+Python Mix Payloads Sender Test
+Tests the smartsend function with mixed payload types
+"""
+
+import asyncio
+import sys
+import os
+import base64
+
+# Add parent directory to path
+sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
+
+from natsbridge import smartsend, DEFAULT_BROKER_URL, DEFAULT_FILESERVER_URL
+
+TEST_SUBJECT = '/test/mix'
+TEST_BROKER_URL = os.environ.get('NATS_URL', 'nats://localhost:4222')
+TEST_FILESERVER_URL = os.environ.get('FILESERVER_URL', 'http://localhost:8080')
+
+
+async def run_test():
+    print('=== Python Mix Payloads Sender Test ===\n')
+    
+    correlation_id = 'py-mix-test-' + str(asyncio.get_event_loop().time() * 1000000)
+    print(f'Correlation ID: {correlation_id}')
+    print(f'Subject: {TEST_SUBJECT}')
+    print(f'Broker URL: {TEST_BROKER_URL}\n')
+    
+    # Test data - mixed payload types
+    text_data = 'Hello, NATSBridge!'
+    dict_data = {'key1': 'value1', 'key2': 42, 'nested': {'a': 1, 'b': 2}}
+    image_data = bytes([0x89, 0x50, 0x4E, 0x47, 0x0D, 0x0A, 0x1A, 0x0A])  # PNG header
+    
+    # Table data
+    try:
+        import pandas as pd
+        table_data = pd.DataFrame({
+            'id': [1, 2, 3],
+            'name': ['Alice', 'Bob', 'Charlie'],
+            'age': [30, 25, 35]
+        })
+        table_available = True
+    except ImportError:
+        table_available = False
+        table_data = None
+    
+    test_data = [
+        ('message', text_data, 'text'),
+        ('config', dict_data, 'dictionary'),
+        ('image', image_data, 'image')
+    ]
+    
+    if table_available:
+        test_data.append(('users', table_data, 'table'))
+    
+    try:
+        # Send the message
+        print('Sending mixed payloads...')
+        env, env_json_str = await smartsend(
+            TEST_SUBJECT,
+            test_data,
+            broker_url=TEST_BROKER_URL,
+            fileserver_url=TEST_FILESERVER_URL,
+            correlation_id=correlation_id,
+            msg_purpose='test',
+            sender_name='py-mix-test',
+            is_publish=False
+        )
+        
+        print('\n=== Envelope Created ===')
+        print(f'Correlation ID: {env["correlation_id"]}')
+        print(f'Message ID: {env["msg_id"]}')
+        print(f'Timestamp: {env["timestamp"]}')
+        print(f'Subject: {env["send_to"]}')
+        print(f'Purpose: {env["msg_purpose"]}')
+        print(f'Sender: {env["sender_name"]}')
+        print(f'Payloads: {len(env["payloads"])}\n')
+        
+        # Validate envelope structure
+        print('=== Validation ===')
+        passed = True
+        
+        expected_count = 4 if table_available else 3
+        if len(env['payloads']) != expected_count:
+            print(f'❌ Expected {expected_count} payloads, got {len(env["payloads"])}')
+            passed = False
+        else:
+            print('✅ Correct number of payloads')
+        
+        # Test each payload
+        expected_datanames = ['message', 'config', 'image']
+        expected_types = ['text', 'dictionary', 'image']
+        expected_data = [text_data, dict_data, image_data]
+        
+        if table_available:
+            expected_datanames.append('users')
+            expected_types.append('table')
+        
+        for i in range(len(env['payloads'])):
+            payload = env['payloads'][i]
+            
+            if payload['dataname'] != expected_datanames[i]:
+                print(f"❌ Payload {i + 1}: Expected dataname '{expected_datanames[i]}', got '{payload['dataname']}'")
+                passed = False
+            else:
+                print(f'✅ Payload {i + 1}: Correct dataname')
+            
+            if payload['payload_type'] != expected_types[i]:
+                print(f"❌ Payload {i + 1}: Expected type '{expected_types[i]}', got '{payload['payload_type']}'")
+                passed = False
+            else:
+                print(f'✅ Payload {i + 1}: Correct type')
+            
+            if payload['transport'] != 'direct':
+                print(f"❌ Payload {i + 1}: Expected transport 'direct', got '{payload['transport']}'")
+                passed = False
+            else:
+                print(f'✅ Payload {i + 1}: Correct transport')
+            
+            if payload['encoding'] != 'base64':
+                print(f"❌ Payload {i + 1}: Expected encoding 'base64', got '{payload['encoding']}'")
+                passed = False
+            else:
+                print(f'✅ Payload {i + 1}: Correct encoding')
+            
+            # Verify data integrity based on type
+            decoded_data = base64.b64decode(payload['data'])
+            
+            if expected_types[i] == 'text':
+                decoded_text = decoded_data.decode('utf8')
+                if decoded_text != expected_data[i]:
+                    print(f'❌ Payload {i + 1}: Data integrity mismatch')
+                    passed = False
+                else:
+                    print(f'✅ Payload {i + 1}: Data integrity verified')
+            elif expected_types[i] == 'dictionary':
+                import json
+                decoded_dict = json.loads(decoded_data.decode('utf8'))
+                if json.dumps(decoded_dict, sort_keys=True) != json.dumps(expected_data[i], sort_keys=True):
+                    print(f'❌ Payload {i + 1}: Data integrity mismatch')
+                    passed = False
+                else:
+                    print(f'✅ Payload {i + 1}: Data integrity verified')
+            elif expected_types[i] == 'image':
+                if decoded_data != expected_data[i]:
+                    print(f'❌ Payload {i + 1}: Data integrity mismatch')
+                    passed = False
+                else:
+                    print(f'✅ Payload {i + 1}: Data integrity verified')
+            elif expected_types[i] == 'table':
+                if len(decoded_data) > 0:
+                    print(f'✅ Payload {i + 1}: Arrow IPC data present ({len(decoded_data)} bytes)')
+                else:
+                    print(f'❌ Payload {i + 1}: Arrow IPC data is empty')
+                    passed = False
+            
+            print(f'   Size: {payload["size"]} bytes\n')
+        
+        # Test with chat-like payload (text + image + audio)
+        print('=== Chat-like Payload Test ===')
+        chat_data = [
+            ('text', 'Hello!', 'text'),
+            ('image', bytes([0xFF, 0xD8, 0xFF, 0xE0]), 'image'),
+            ('audio', bytes([0x46, 0x4C, 0x41, 0x43]), 'audio')
+        ]
+        
+        chat_env, _ = await smartsend(
+            TEST_SUBJECT,
+            chat_data,
+            broker_url=TEST_BROKER_URL,
+            fileserver_url=TEST_FILESERVER_URL,
+            correlation_id='chat-' + correlation_id,
+            is_publish=False
+        )
+        
+        if len(chat_env['payloads']) == 3:
+            print('✅ Chat-like payloads handled correctly')
+        else:
+            print('❌ Chat-like payloads handling failed')
+            passed = False
+        
+        # Final result
+        print('\n=== Test Result ===')
+        if passed:
+            print('✅ ALL TESTS PASSED')
+            sys.exit(0)
+        else:
+            print('❌ SOME TESTS FAILED')
+            sys.exit(1)
+            
+    except Exception as e:
+        print(f'❌ Test failed with error: {e}')
+        import traceback
+        traceback.print_exc()
+        sys.exit(1)
+
+
+if __name__ == '__main__':
+    asyncio.run(run_test())

tutorial_julia.md

@@ -1,634 +0,0 @@
-# NATSBridge.jl Tutorial
-
-A comprehensive tutorial for learning how to use NATSBridge.jl for bi-directional communication between Julia and JavaScript services using NATS.
-
-## Table of Contents
-
-1. [What is NATSBridge.jl?](#what-is-natsbridgejl)
-2. [Key Concepts](#key-concepts)
-3. [Installation](#installation)
-4. [Basic Usage](#basic-usage)
-5. [Payload Types](#payload-types)
-6. [Transport Strategies](#transport-strategies)
-7. [Advanced Features](#advanced-features)
-8. [Complete Examples](#complete-examples)
-
----
-
-## What is NATSBridge.jl?
-
-NATSBridge.jl is a Julia module that provides a high-level API for sending and receiving data across network boundaries using NATS as the message bus. It implements the **Claim-Check pattern** for handling large payloads efficiently.
-
-### Core Features
-
-- **Bi-directional communication**: Julia ↔ JavaScript
-- **Smart transport selection**: Automatic direct vs link transport based on payload size
-- **Multi-payload support**: Send multiple payloads of different types in a single message
-- **Claim-check pattern**: Upload large files to HTTP server, send only URLs via NATS
-- **Type-aware serialization**: Different serialization strategies for different data types
-
----
-
-## Key Concepts
-
-### 1. msgEnvelope_v1 (Message Envelope)
-
-The `msgEnvelope_v1` structure provides a comprehensive message format for bidirectional communication:
-
-```julia
-struct msgEnvelope_v1
-  correlationId::String       # Unique identifier to track messages
-  msgId::String               # This message id
-  timestamp::String           # Message published timestamp
-  
-  sendTo::String              # Topic/subject the sender sends to
-  msgPurpose::String          # Purpose (ACK | NACK | updateStatus | shutdown | chat)
-  senderName::String          # Sender name (e.g., "agent-wine-web-frontend")
-  senderId::String            # Sender id (uuid4)
-  receiverName::String        # Message receiver name (e.g., "agent-backend")
-  receiverId::String          # Message receiver id (uuid4 or nothing for broadcast)
-  replyTo::String             # Topic to reply to
-  replyToMsgId::String        # Message id this message is replying to
-  brokerURL::String           # NATS server address
-  
-  metadata::Dict{String, Any}
-  payloads::AbstractArray{msgPayload_v1}  # Multiple payloads stored here
-end
-```
-
-### 2. msgPayload_v1 (Payload Structure)
-
-The `msgPayload_v1` structure provides flexible payload handling:
-
-```julia
-struct msgPayload_v1
-  id::String                    # Id of this payload (e.g., "uuid4")
-  dataname::String              # Name of this payload (e.g., "login_image")
-  type::String                  # "text | dictionary | table | image | audio | video | binary"
-  transport::String             # "direct | link"
-  encoding::String              # "none | json | base64 | arrow-ipc"
-  size::Integer                 # Data size in bytes
-  data::Any                     # Payload data in case of direct transport or a URL in case of link
-  metadata::Dict{String, Any}   # Dict("checksum" => "sha256_hash", ...)
-end
-```
-
-### 3. Standard API Format
-
-The system uses a **standardized list-of-tuples format** for all payload operations:
-
-```julia
-# Input format for smartsend (always a list of tuples with type info)
-[(dataname1, data1, type1), (dataname2, data2, type2), ...]
-
-# Output format for smartreceive (always returns a list of tuples)
-[(dataname1, data1, type1), (dataname2, data2, type2), ...]
-```
-
-**Important**: Even when sending a single payload, you must wrap it in a list.
-
----
-
-## Installation
-
-```julia
-using Pkg
-Pkg.add("NATS")
-Pkg.add("JSON")
-Pkg.add("Arrow")
-Pkg.add("HTTP")
-Pkg.add("UUIDs")
-Pkg.add("Dates")
-Pkg.add("Base64")
-Pkg.add("PrettyPrinting")
-Pkg.add("DataFrames")
-```
-
-Then include the NATSBridge module:
-
-```julia
-include("NATSBridge.jl")
-using .NATSBridge
-```
-
----
-
-## Basic Usage
-
-### Sending Data (smartsend)
-
-```julia
-using NATSBridge
-
-# Send a simple dictionary
-data = Dict("key" => "value")
-env = NATSBridge.smartsend("my.subject", [("dataname1", data, "dictionary")])
-```
-
-### Receiving Data (smartreceive)
-
-```julia
-using NATSBridge
-
-# Subscribe to a NATS subject
-NATS.subscribe("my.subject") do msg
-    # Process the message
-    result = NATSBridge.smartreceive(
-        msg,
-        max_retries = 5,
-        base_delay = 100,
-        max_delay = 5000
-    )
-    
-    # result is a list of (dataname, data, type) tuples
-    for (dataname, data, type) in result
-        println("Received $dataname of type $type")
-        println("Data: $data")
-    end
-end
-```
-
----
-
-## Payload Types
-
-NATSBridge.jl supports the following payload types:
-
-| Type | Description | Serialization |
-|------|-------------|---------------|
-| `text` | Plain text | UTF-8 encoding |
-| `dictionary` | JSON-serializable data (Dict, NamedTuple) | JSON |
-| `table` | Tabular data (DataFrame, array of structs) | Apache Arrow IPC |
-| `image` | Image data (Bitmap, PNG/JPG bytes) | Binary |
-| `audio` | Audio data (WAV, MP3 bytes) | Binary |
-| `video` | Video data (MP4, AVI bytes) | Binary |
-| `binary` | Generic binary data | Binary |
-
----
-
-## Transport Strategies
-
-NATSBridge.jl automatically selects the appropriate transport strategy based on payload size:
-
-### Direct Transport (< 1MB)
-
-Small payloads are encoded as Base64 and sent directly over NATS.
-
-```julia
-# Small data (< 1MB) - uses direct transport
-small_data = rand(1000)  # ~8KB
-env = NATSBridge.smartsend("small", [("data", small_data, "table")])
-```
-
-### Link Transport (≥ 1MB)
-
-Large payloads are uploaded to an HTTP file server, and only the URL is sent via NATS.
-
-```julia
-# Large data (≥ 1MB) - uses link transport
-large_data = rand(10_000_000)  # ~80MB
-env = NATSBridge.smartsend("large", [("data", large_data, "table")])
-```
-
----
-
-## Complete Examples
-
-### Example 1: Text Message
-
-**Sender:**
-```julia
-using NATSBridge
-using UUIDs
-
-const SUBJECT = "/NATSBridge_text_test"
-const NATS_URL = "nats://localhost:4222"
-const FILESERVER_URL = "http://localhost:8080"
-
-function plik_upload_handler(fileserver_url::String, dataname::String, data::Vector{UInt8})::Dict{String, Any}
-    url_getUploadID = "$fileserver_url/upload"
-    headers = ["Content-Type" => "application/json"]
-    body = """{ "OneShot" : true }"""
-    httpResponse = HTTP.request("POST", url_getUploadID, headers, body; body_is_form=false)
-    responseJson = JSON.parse(String(httpResponse.body))
-    uploadid = responseJson["id"]
-    uploadtoken = responseJson["uploadToken"]
-    
-    file_multipart = HTTP.Multipart(dataname, IOBuffer(data), "application/octet-stream")
-    url_upload = "$fileserver_url/file/$uploadid"
-    headers = ["X-UploadToken" => uploadtoken]
-    
-    form = HTTP.Form(Dict("file" => file_multipart))
-    httpResponse = HTTP.post(url_upload, headers, form)
-    responseJson = JSON.parse(String(httpResponse.body))
-    
-    fileid = responseJson["id"]
-    url = "$fileserver_url/file/$uploadid/$fileid/$dataname"
-    
-    return Dict("status" => httpResponse.status, "uploadid" => uploadid, "fileid" => fileid, "url" => url)
-end
-
-function test_text_send()
-    small_text = "Hello, this is a small text message."
-    large_text = join(["Line $i: " for i in 1:50000], "")
-    
-    data1 = ("small_text", small_text, "text")
-    data2 = ("large_text", large_text, "text")
-    
-    env = NATSBridge.smartsend(
-        SUBJECT,
-        [data1, data2],
-        nats_url = NATS_URL,
-        fileserver_url = FILESERVER_URL,
-        fileserverUploadHandler = plik_upload_handler,
-        size_threshold = 1_000_000,
-        correlation_id = string(uuid4()),
-        msg_purpose = "chat",
-        sender_name = "text_sender"
-    )
-end
-```
-
-**Receiver:**
-```julia
-using NATSBridge
-
-const SUBJECT = "/NATSBridge_text_test"
-const NATS_URL = "nats://localhost:4222"
-
-function test_text_receive()
-    conn = NATS.connect(NATS_URL)
-    NATS.subscribe(conn, SUBJECT) do msg
-        result = NATSBridge.smartreceive(
-            msg,
-            max_retries = 5,
-            base_delay = 100,
-            max_delay = 5000
-        )
-        
-        for (dataname, data, data_type) in result
-            if data_type == "text"
-                println("Received text: $data")
-                write("./received_$dataname.txt", data)
-            end
-        end
-    end
-    sleep(120)
-    NATS.drain(conn)
-end
-```
-
-### Example 2: Dictionary (JSON) Message
-
-**Sender:**
-```julia
-using NATSBridge
-using UUIDs
-
-const SUBJECT = "/NATSBridge_dict_test"
-const NATS_URL = "nats://localhost:4222"
-const FILESERVER_URL = "http://localhost:8080"
-
-function plik_upload_handler(fileserver_url::String, dataname::String, data::Vector{UInt8})::Dict{String, Any}
-    url_getUploadID = "$fileserver_url/upload"
-    headers = ["Content-Type" => "application/json"]
-    body = """{ "OneShot" : true }"""
-    httpResponse = HTTP.request("POST", url_getUploadID, headers, body; body_is_form=false)
-    responseJson = JSON.parse(String(httpResponse.body))
-    uploadid = responseJson["id"]
-    uploadtoken = responseJson["uploadToken"]
-    
-    file_multipart = HTTP.Multipart(dataname, IOBuffer(data), "application/octet-stream")
-    url_upload = "$fileserver_url/file/$uploadid"
-    headers = ["X-UploadToken" => uploadtoken]
-    
-    form = HTTP.Form(Dict("file" => file_multipart))
-    httpResponse = HTTP.post(url_upload, headers, form)
-    responseJson = JSON.parse(String(httpResponse.body))
-    
-    fileid = responseJson["id"]
-    url = "$fileserver_url/file/$uploadid/$fileid/$dataname"
-    
-    return Dict("status" => httpResponse.status, "uploadid" => uploadid, "fileid" => fileid, "url" => url)
-end
-
-function test_dict_send()
-    small_dict = Dict("name" => "Alice", "age" => 30)
-    large_dict = Dict("ids" => collect(1:50000), "names" => ["User_$i" for i in 1:50000])
-    
-    data1 = ("small_dict", small_dict, "dictionary")
-    data2 = ("large_dict", large_dict, "dictionary")
-    
-    env = NATSBridge.smartsend(
-        SUBJECT,
-        [data1, data2],
-        nats_url = NATS_URL,
-        fileserver_url = FILESERVER_URL,
-        fileserverUploadHandler = plik_upload_handler,
-        size_threshold = 1_000_000,
-        correlation_id = string(uuid4()),
-        msg_purpose = "chat"
-    )
-end
-```
-
-**Receiver:**
-```julia
-using NATSBridge
-
-const SUBJECT = "/NATSBridge_dict_test"
-const NATS_URL = "nats://localhost:4222"
-
-function test_dict_receive()
-    conn = NATS.connect(NATS_URL)
-    NATS.subscribe(conn, SUBJECT) do msg
-        result = NATSBridge.smartreceive(
-            msg,
-            max_retries = 5,
-            base_delay = 100,
-            max_delay = 5000
-        )
-        
-        for (dataname, data, data_type) in result
-            if data_type == "dictionary"
-                println("Received dictionary: $data")
-                write("./received_$dataname.json", JSON.json(data, 2))
-            end
-        end
-    end
-    sleep(120)
-    NATS.drain(conn)
-end
-```
-
-### Example 3: DataFrame (Table) Message
-
-**Sender:**
-```julia
-using NATSBridge
-using DataFrames
-using UUIDs
-
-const SUBJECT = "/NATSBridge_table_test"
-const NATS_URL = "nats://localhost:4222"
-const FILESERVER_URL = "http://localhost:8080"
-
-function plik_upload_handler(fileserver_url::String, dataname::String, data::Vector{UInt8})::Dict{String, Any}
-    url_getUploadID = "$fileserver_url/upload"
-    headers = ["Content-Type" => "application/json"]
-    body = """{ "OneShot" : true }"""
-    httpResponse = HTTP.request("POST", url_getUploadID, headers, body; body_is_form=false)
-    responseJson = JSON.parse(String(httpResponse.body))
-    uploadid = responseJson["id"]
-    uploadtoken = responseJson["uploadToken"]
-    
-    file_multipart = HTTP.Multipart(dataname, IOBuffer(data), "application/octet-stream")
-    url_upload = "$fileserver_url/file/$uploadid"
-    headers = ["X-UploadToken" => uploadtoken]
-    
-    form = HTTP.Form(Dict("file" => file_multipart))
-    httpResponse = HTTP.post(url_upload, headers, form)
-    responseJson = JSON.parse(String(httpResponse.body))
-    
-    fileid = responseJson["id"]
-    url = "$fileserver_url/file/$uploadid/$fileid/$dataname"
-    
-    return Dict("status" => httpResponse.status, "uploadid" => uploadid, "fileid" => fileid, "url" => url)
-end
-
-function test_table_send()
-    small_df = DataFrame(id = 1:10, name = ["Alice", "Bob", "Charlie"], score = [95, 88, 92])
-    large_df = DataFrame(id = 1:50000, name = ["User_$i" for i in 1:50000], score = rand(1:100, 50000))
-    
-    data1 = ("small_table", small_df, "table")
-    data2 = ("large_table", large_df, "table")
-    
-    env = NATSBridge.smartsend(
-        SUBJECT,
-        [data1, data2],
-        nats_url = NATS_URL,
-        fileserver_url = FILESERVER_URL,
-        fileserverUploadHandler = plik_upload_handler,
-        size_threshold = 1_000_000,
-        correlation_id = string(uuid4()),
-        msg_purpose = "chat"
-    )
-end
-```
-
-**Receiver:**
-```julia
-using NATSBridge
-using DataFrames
-
-const SUBJECT = "/NATSBridge_table_test"
-const NATS_URL = "nats://localhost:4222"
-
-function test_table_receive()
-    conn = NATS.connect(NATS_URL)
-    NATS.subscribe(conn, SUBJECT) do msg
-        result = NATSBridge.smartreceive(
-            msg,
-            max_retries = 5,
-            base_delay = 100,
-            max_delay = 5000
-        )
-        
-        for (dataname, data, data_type) in result
-            if data_type == "table"
-                data = DataFrame(data)
-                println("Received DataFrame with $(size(data, 1)) rows")
-                display(data[1:min(5, size(data, 1)), :])
-            end
-        end
-    end
-    sleep(120)
-    NATS.drain(conn)
-end
-```
-
-### Example 4: Mixed Content (Chat with Text, Image, Audio)
-
-**Sender:**
-```julia
-using NATSBridge
-using DataFrames
-using UUIDs
-
-const SUBJECT = "/NATSBridge_mix_test"
-const NATS_URL = "nats://localhost:4222"
-const FILESERVER_URL = "http://localhost:8080"
-
-function plik_upload_handler(fileserver_url::String, dataname::String, data::Vector{UInt8})::Dict{String, Any}
-    url_getUploadID = "$fileserver_url/upload"
-    headers = ["Content-Type" => "application/json"]
-    body = """{ "OneShot" : true }"""
-    httpResponse = HTTP.request("POST", url_getUploadID, headers, body; body_is_form=false)
-    responseJson = JSON.parse(String(httpResponse.body))
-    uploadid = responseJson["id"]
-    uploadtoken = responseJson["uploadToken"]
-    
-    file_multipart = HTTP.Multipart(dataname, IOBuffer(data), "application/octet-stream")
-    url_upload = "$fileserver_url/file/$uploadid"
-    headers = ["X-UploadToken" => uploadtoken]
-    
-    form = HTTP.Form(Dict("file" => file_multipart))
-    httpResponse = HTTP.post(url_upload, headers, form)
-    responseJson = JSON.parse(String(httpResponse.body))
-    
-    fileid = responseJson["id"]
-    url = "$fileserver_url/file/$uploadid/$fileid/$dataname"
-    
-    return Dict("status" => httpResponse.status, "uploadid" => uploadid, "fileid" => fileid, "url" => url)
-end
-
-function test_mix_send()
-    # Text data
-    text_data = "Hello! This is a test chat message. 🎉"
-    
-    # Dictionary data
-    dict_data = Dict("type" => "chat", "sender" => "serviceA")
-    
-    # Small table data
-    table_data_small = DataFrame(id = 1:10, name = ["msg_$i" for i in 1:10])
-    
-    # Large table data (link transport)
-    table_data_large = DataFrame(id = 1:150_000, name = ["msg_$i" for i in 1:150_000])
-    
-    # Small image data (direct transport)
-    image_data = UInt8[rand(1:255) for _ in 1:100]
-    
-    # Large image data (link transport)
-    large_image_data = UInt8[rand(1:255) for _ in 1:1_500_000]
-    
-    # Small audio data (direct transport)
-    audio_data = UInt8[rand(1:255) for _ in 1:100]
-    
-    # Large audio data (link transport)
-    large_audio_data = UInt8[rand(1:255) for _ in 1:1_500_000]
-    
-    # Small video data (direct transport)
-    video_data = UInt8[rand(1:255) for _ in 1:150]
-    
-    # Large video data (link transport)
-    large_video_data = UInt8[rand(1:255) for _ in 1:1_500_000]
-    
-    # Small binary data (direct transport)
-    binary_data = UInt8[rand(1:255) for _ in 1:200]
-    
-    # Large binary data (link transport)
-    large_binary_data = UInt8[rand(1:255) for _ in 1:1_500_000]
-    
-    # Create payloads list - mixed content
-    payloads = [
-        # Small data (direct transport)
-        ("chat_text", text_data, "text"),
-        ("chat_json", dict_data, "dictionary"),
-        ("chat_table_small", table_data_small, "table"),
-        
-        # Large data (link transport)
-        ("chat_table_large", table_data_large, "table"),
-        ("user_image_large", large_image_data, "image"),
-        ("audio_clip_large", large_audio_data, "audio"),
-        ("video_clip_large", large_video_data, "video"),
-        ("binary_file_large", large_binary_data, "binary")
-    ]
-    
-    env = NATSBridge.smartsend(
-        SUBJECT,
-        payloads,
-        nats_url = NATS_URL,
-        fileserver_url = FILESERVER_URL,
-        fileserverUploadHandler = plik_upload_handler,
-        size_threshold = 1_000_000,
-        correlation_id = string(uuid4()),
-        msg_purpose = "chat",
-        sender_name = "mix_sender"
-    )
-end
-```
-
-**Receiver:**
-```julia
-using NATSBridge
-using DataFrames
-
-const SUBJECT = "/NATSBridge_mix_test"
-const NATS_URL = "nats://localhost:4222"
-
-function test_mix_receive()
-    conn = NATS.connect(NATS_URL)
-    NATS.subscribe(conn, SUBJECT) do msg
-        result = NATSBridge.smartreceive(
-            msg,
-            max_retries = 5,
-            base_delay = 100,
-            max_delay = 5000
-        )
-        
-        println("Received $(length(result)) payloads")
-        
-        for (dataname, data, data_type) in result
-            println("\n=== Payload: $dataname (type: $data_type) ===")
-            
-            if data_type == "text"
-                println("  Type: String")
-                println("  Length: $(length(data)) characters")
-                
-            elseif data_type == "dictionary"
-                println("  Type: JSON Object")
-                println("  Keys: $(keys(data))")
-                
-            elseif data_type == "table"
-                data = DataFrame(data)
-                println("  Type: DataFrame")
-                println("  Dimensions: $(size(data, 1)) rows x $(size(data, 2)) columns")
-                
-            elseif data_type == "image"
-                println("  Type: Vector{UInt8}")
-                println("  Size: $(length(data)) bytes")
-                write("./received_$dataname.bin", data)
-                
-            elseif data_type == "audio"
-                println("  Type: Vector{UInt8}")
-                println("  Size: $(length(data)) bytes")
-                write("./received_$dataname.bin", data)
-                
-            elseif data_type == "video"
-                println("  Type: Vector{UInt8}")
-                println("  Size: $(length(data)) bytes")
-                write("./received_$dataname.bin", data)
-                
-            elseif data_type == "binary"
-                println("  Type: Vector{UInt8}")
-                println("  Size: $(length(data)) bytes")
-                write("./received_$dataname.bin", data)
-            end
-        end
-    end
-    sleep(120)
-    NATS.drain(conn)
-end
-```
-
----
-
-## Best Practices
-
-1. **Always wrap payloads in a list** - Even for single payloads: `[("dataname", data, "type")]`
-2. **Use appropriate transport** - Let NATSBridge handle size-based routing (default 1MB threshold)
-3. **Customize size threshold** - Use `size_threshold` parameter to adjust the direct/link split
-4. **Provide fileserver handler** - Implement `fileserverUploadHandler` for link transport
-5. **Include correlation IDs** - Track messages across distributed systems
-6. **Handle errors** - Implement proper error handling for network failures
-7. **Close connections** - Ensure NATS connections are properly closed using `NATS.drain()`
-
----
-
-## Conclusion
-
-NATSBridge.jl provides a powerful abstraction for bi-directional communication between Julia and JavaScript services. By understanding the key concepts and following the best practices, you can build robust, scalable applications that leverage the full power of NATS messaging.
-
-For more information, see:
-- [`docs/architecture.md`](./architecture.md) - Detailed architecture documentation
-- [`docs/implementation.md`](./implementation.md) - Implementation details

walkthrough_julia.md

@@ -1,939 +0,0 @@
-# NATSBridge.jl Walkthrough: Building a Chat System
-
-A step-by-step guided walkthrough for building a real-time chat system using NATSBridge.jl with mixed content support (text, images, audio, video, and files).
-
-## Prerequisites
-
-- Julia 1.7+
-- NATS server running
-- HTTP file server (Plik) running
-
-## Step 1: Understanding the Chat System Architecture
-
-### System Components
-
-```
-┌─────────────────────────────────────────────────────────────────────────────┐
-│                              Chat System                                   │
-├─────────────────────────────────────────────────────────────────────────────┤
-│                                                                            │
-│  ┌──────────────┐        NATS         ┌──────────────┐                     │
-│  │   Julia      │◄───────┬───────►   │   JavaScript │                     │
-│  │  Service     │        │          │   Client     │                     │
-│  │              │        │          │              │                     │
-│  │ - Text       │        │          │ - Text       │                     │
-│  │ - Images     │        │          │ - Images     │                     │
-│  │ - Audio      │        ▼          │ - Audio      │                     │
-│  │ - Video      │  NATSBridge.jl    │ - Files      │                     │
-│  │ - Files      │        │          │ - Tables     │                     │
-│  └──────────────┘        │          └──────────────┘                     │
-│                          │                                                 │
-│                  ┌───────┴───────┐                                         │
-│                  │   NATS      │                                         │
-│                  │   Server    │                                         │
-│                  └─────────────┘                                         │
-│                                                                            │
-└─────────────────────────────────────────────────────────────────────────────┘
-
-For large payloads (> 1MB):
-┌─────────────────────────────────────────────────────────────────────────────┐
-│                           File Server (Plik)                               │
-│                                                                            │
-│  Julia Service ──► Upload ──► File Server ──► Download ◄── JavaScript Client│
-│                                                                            │
-└─────────────────────────────────────────────────────────────────────────────┘
-```
-
-### Message Format
-
-Each chat message is an envelope containing multiple payloads:
-
-```json
-{
-  "correlationId": "uuid4",
-  "msgId": "uuid4",
-  "timestamp": "2024-01-15T10:30:00Z",
-  "sendTo": "/chat/room1",
-  "msgPurpose": "chat",
-  "senderName": "user-1",
-  "senderId": "uuid4",
-  "receiverName": "user-2",
-  "receiverId": "uuid4",
-  "brokerURL": "nats://localhost:4222",
-  "payloads": [
-    {
-      "id": "uuid4",
-      "dataname": "message_text",
-      "type": "text",
-      "transport": "direct",
-      "encoding": "base64",
-      "size": 256,
-      "data": "SGVsbG8gV29ybGQh",
-      "metadata": {}
-    },
-    {
-      "id": "uuid4",
-      "dataname": "user_image",
-      "type": "image",
-      "transport": "link",
-      "encoding": "none",
-      "size": 15433,
-      "data": "http://localhost:8080/file/UPLOAD_ID/FILE_ID/image.jpg",
-      "metadata": {}
-    }
-  ]
-}
-```
-
-## Step 2: Setting Up the Environment
-
-### 1. Start NATS Server
-
-```bash
-# Using Docker
-docker run -d -p 4222:4222 -p 8222:8222 --name nats-server nats:latest
-
-# Or download from https://github.com/nats-io/nats-server/releases
-./nats-server
-```
-
-### 2. Start HTTP File Server (Plik)
-
-```bash
-# Using Docker
-docker run -d -p 8080:8080 --name plik plik/plik:latest
-
-# Or download from https://github.com/arnaud-lb/plik/releases
-./plikd -d
-```
-
-### 3. Install Julia Dependencies
-
-```julia
-using Pkg
-Pkg.add("NATS")
-Pkg.add("JSON")
-Pkg.add("Arrow")
-Pkg.add("HTTP")
-Pkg.add("UUIDs")
-Pkg.add("Dates")
-Pkg.add("Base64")
-Pkg.add("PrettyPrinting")
-Pkg.add("DataFrames")
-```
-
-## Step 3: Basic Text-Only Chat
-
-### Sender (User 1)
-
-```julia
-using NATS
-using JSON
-using UUIDs
-using Dates
-using PrettyPrinting
-using DataFrames
-using Arrow
-using HTTP
-using Base64
-
-# Include the bridge module
-include("NATSBridge.jl")
-using .NATSBridge
-
-# Configuration
-const NATS_URL = "nats://localhost:4222"
-const FILESERVER_URL = "http://localhost:8080"
-const SUBJECT = "/chat/room1"
-
-# File upload handler for plik server
-function plik_upload_handler(fileserver_url::String, dataname::String, data::Vector{UInt8})::Dict{String, Any}
-    url_getUploadID = "$fileserver_url/upload"
-    headers = ["Content-Type" => "application/json"]
-    body = """{ "OneShot" : true }"""
-    httpResponse = HTTP.request("POST", url_getUploadID, headers, body; body_is_form=false)
-    responseJson = JSON.parse(String(httpResponse.body))
-    uploadid = responseJson["id"]
-    uploadtoken = responseJson["uploadToken"]
-    
-    file_multipart = HTTP.Multipart(dataname, IOBuffer(data), "application/octet-stream")
-    url_upload = "$fileserver_url/file/$uploadid"
-    headers = ["X-UploadToken" => uploadtoken]
-    
-    form = HTTP.Form(Dict("file" => file_multipart))
-    httpResponse = HTTP.post(url_upload, headers, form)
-    responseJson = JSON.parse(String(httpResponse.body))
-    
-    fileid = responseJson["id"]
-    url = "$fileserver_url/file/$uploadid/$fileid/$dataname"
-    
-    return Dict("status" => httpResponse.status, "uploadid" => uploadid, "fileid" => fileid, "url" => url)
-end
-
-# Send a simple text message
-function send_text_message()
-    message_text = "Hello, how are you today?"
-    
-    env = NATSBridge.smartsend(
-        SUBJECT,
-        [("message", message_text, "text")],
-        nats_url = NATS_URL,
-        fileserver_url = FILESERVER_URL,
-        fileserverUploadHandler = plik_upload_handler,
-        size_threshold = 1_000_000,
-        correlation_id = string(uuid4()),
-        msg_purpose = "chat",
-        sender_name = "user-1"
-    )
-    
-    println("Sent text message with correlation ID: $(env.correlationId)")
-end
-
-send_text_message()
-```
-
-### Receiver (User 2)
-
-```julia
-using NATS
-using JSON
-using UUIDs
-using Dates
-using PrettyPrinting
-using DataFrames
-using Arrow
-using HTTP
-using Base64
-
-# Include the bridge module
-include("NATSBridge.jl")
-using .NATSBridge
-
-# Configuration
-const NATS_URL = "nats://localhost:4222"
-const SUBJECT = "/chat/room1"
-
-# Message handler
-function message_handler(msg::NATS.Msg)
-    payloads = NATSBridge.smartreceive(
-        msg,
-        max_retries = 5,
-        base_delay = 100,
-        max_delay = 5000
-    )
-    
-    # Extract the text message
-    for (dataname, data, data_type) in payloads
-        if data_type == "text"
-            println("Received message: $data")
-            # Save to file
-            write("./received_$dataname.txt", data)
-        end
-    end
-end
-
-# Subscribe to the chat room
-NATS.subscribe(SUBJECT) do msg
-    message_handler(msg)
-end
-
-# Keep the program running
-while true
-    sleep(1)
-end
-```
-
-## Step 4: Adding Image Support
-
-### Sending an Image
-
-```julia
-using NATS
-using JSON
-using UUIDs
-using Dates
-using PrettyPrinting
-using DataFrames
-using Arrow
-using HTTP
-using Base64
-
-include("NATSBridge.jl")
-using .NATSBridge
-
-const NATS_URL = "nats://localhost:4222"
-const FILESERVER_URL = "http://localhost:8080"
-const SUBJECT = "/chat/room1"
-
-function plik_upload_handler(fileserver_url::String, dataname::String, data::Vector{UInt8})::Dict{String, Any}
-    url_getUploadID = "$fileserver_url/upload"
-    headers = ["Content-Type" => "application/json"]
-    body = """{ "OneShot" : true }"""
-    httpResponse = HTTP.request("POST", url_getUploadID, headers, body; body_is_form=false)
-    responseJson = JSON.parse(String(httpResponse.body))
-    uploadid = responseJson["id"]
-    uploadtoken = responseJson["uploadToken"]
-    
-    file_multipart = HTTP.Multipart(dataname, IOBuffer(data), "application/octet-stream")
-    url_upload = "$fileserver_url/file/$uploadid"
-    headers = ["X-UploadToken" => uploadtoken]
-    
-    form = HTTP.Form(Dict("file" => file_multipart))
-    httpResponse = HTTP.post(url_upload, headers, form)
-    responseJson = JSON.parse(String(httpResponse.body))
-    
-    fileid = responseJson["id"]
-    url = "$fileserver_url/file/$uploadid/$fileid/$dataname"
-    
-    return Dict("status" => httpResponse.status, "uploadid" => uploadid, "fileid" => fileid, "url" => url)
-end
-
-function send_image()
-    # Read image file
-    image_data = read("screenshot.png", Vector{UInt8})
-    
-    # Send with text message
-    env = NATSBridge.smartsend(
-        SUBJECT,
-        [
-            ("text", "Check out this screenshot!", "text"),
-            ("screenshot", image_data, "image")
-        ],
-        nats_url = NATS_URL,
-        fileserver_url = FILESERVER_URL,
-        fileserverUploadHandler = plik_upload_handler,
-        size_threshold = 1_000_000,
-        correlation_id = string(uuid4()),
-        msg_purpose = "chat",
-        sender_name = "user-1"
-    )
-    
-    println("Sent image with correlation ID: $(env.correlationId)")
-end
-
-send_image()
-```
-
-### Receiving an Image
-
-```julia
-using NATS
-using JSON
-using UUIDs
-using Dates
-using PrettyPrinting
-using DataFrames
-using Arrow
-using HTTP
-using Base64
-
-include("NATSBridge.jl")
-using .NATSBridge
-
-const NATS_URL = "nats://localhost:4222"
-const SUBJECT = "/chat/room1"
-
-function message_handler(msg::NATS.Msg)
-    payloads = NATSBridge.smartreceive(
-        msg,
-        max_retries = 5,
-        base_delay = 100,
-        max_delay = 5000
-    )
-    
-    for (dataname, data, data_type) in payloads
-        if data_type == "text"
-            println("Text: $data")
-        elseif data_type == "image"
-            # Save image to file
-            filename = "received_$dataname.bin"
-            write(filename, data)
-            println("Saved image: $filename")
-        end
-    end
-end
-
-NATS.subscribe(SUBJECT) do msg
-    message_handler(msg)
-end
-```
-
-## Step 5: Handling Large Files with Link Transport
-
-### Automatic Transport Selection
-
-```julia
-using NATS
-using JSON
-using UUIDs
-using Dates
-using PrettyPrinting
-using DataFrames
-using Arrow
-using HTTP
-using Base64
-
-include("NATSBridge.jl")
-using .NATSBridge
-
-const NATS_URL = "nats://localhost:4222"
-const FILESERVER_URL = "http://localhost:8080"
-const SUBJECT = "/chat/room1"
-
-function plik_upload_handler(fileserver_url::String, dataname::String, data::Vector{UInt8})::Dict{String, Any}
-    url_getUploadID = "$fileserver_url/upload"
-    headers = ["Content-Type" => "application/json"]
-    body = """{ "OneShot" : true }"""
-    httpResponse = HTTP.request("POST", url_getUploadID, headers, body; body_is_form=false)
-    responseJson = JSON.parse(String(httpResponse.body))
-    uploadid = responseJson["id"]
-    uploadtoken = responseJson["uploadToken"]
-    
-    file_multipart = HTTP.Multipart(dataname, IOBuffer(data), "application/octet-stream")
-    url_upload = "$fileserver_url/file/$uploadid"
-    headers = ["X-UploadToken" => uploadtoken]
-    
-    form = HTTP.Form(Dict("file" => file_multipart))
-    httpResponse = HTTP.post(url_upload, headers, form)
-    responseJson = JSON.parse(String(httpResponse.body))
-    
-    fileid = responseJson["id"]
-    url = "$fileserver_url/file/$uploadid/$fileid/$dataname"
-    
-    return Dict("status" => httpResponse.status, "uploadid" => uploadid, "fileid" => fileid, "url" => url)
-end
-
-function send_large_file()
-    # Create a large file (> 1MB triggers link transport)
-    large_data = rand(10_000_000)  # ~80MB
-    
-    env = NATSBridge.smartsend(
-        SUBJECT,
-        [("large_file", large_data, "binary")],
-        nats_url = NATS_URL,
-        fileserver_url = FILESERVER_URL,
-        fileserverUploadHandler = plik_upload_handler,
-        size_threshold = 1_000_000,
-        correlation_id = string(uuid4()),
-        msg_purpose = "chat",
-        sender_name = "user-1"
-    )
-    
-    println("Uploaded large file to: $(env.payloads[1].data)")
-    println("Correlation ID: $(env.correlationId)")
-end
-
-send_large_file()
-```
-
-## Step 6: Audio and Video Support
-
-### Sending Audio
-
-```julia
-using NATS
-using JSON
-using UUIDs
-using Dates
-using PrettyPrinting
-using DataFrames
-using Arrow
-using HTTP
-using Base64
-
-include("NATSBridge.jl")
-using .NATSBridge
-
-const NATS_URL = "nats://localhost:4222"
-const FILESERVER_URL = "http://localhost:8080"
-const SUBJECT = "/chat/room1"
-
-function plik_upload_handler(fileserver_url::String, dataname::String, data::Vector{UInt8})::Dict{String, Any}
-    url_getUploadID = "$fileserver_url/upload"
-    headers = ["Content-Type" => "application/json"]
-    body = """{ "OneShot" : true }"""
-    httpResponse = HTTP.request("POST", url_getUploadID, headers, body; body_is_form=false)
-    responseJson = JSON.parse(String(httpResponse.body))
-    uploadid = responseJson["id"]
-    uploadtoken = responseJson["uploadToken"]
-    
-    file_multipart = HTTP.Multipart(dataname, IOBuffer(data), "application/octet-stream")
-    url_upload = "$fileserver_url/file/$uploadid"
-    headers = ["X-UploadToken" => uploadtoken]
-    
-    form = HTTP.Form(Dict("file" => file_multipart))
-    httpResponse = HTTP.post(url_upload, headers, form)
-    responseJson = JSON.parse(String(httpResponse.body))
-    
-    fileid = responseJson["id"]
-    url = "$fileserver_url/file/$uploadid/$fileid/$dataname"
-    
-    return Dict("status" => httpResponse.status, "uploadid" => uploadid, "fileid" => fileid, "url" => url)
-end
-
-function send_audio()
-    # Read audio file (WAV, MP3, etc.)
-    audio_data = read("voice_message.mp3", Vector{UInt8})
-    
-    env = NATSBridge.smartsend(
-        SUBJECT,
-        [("voice_message", audio_data, "audio")],
-        nats_url = NATS_URL,
-        fileserver_url = FILESERVER_URL,
-        fileserverUploadHandler = plik_upload_handler,
-        size_threshold = 1_000_000,
-        correlation_id = string(uuid4()),
-        msg_purpose = "chat",
-        sender_name = "user-1"
-    )
-    
-    println("Sent audio message: $(env.correlationId)")
-end
-
-send_audio()
-```
-
-### Sending Video
-
-```julia
-using NATS
-using JSON
-using UUIDs
-using Dates
-using PrettyPrinting
-using DataFrames
-using Arrow
-using HTTP
-using Base64
-
-include("NATSBridge.jl")
-using .NATSBridge
-
-const NATS_URL = "nats://localhost:4222"
-const FILESERVER_URL = "http://localhost:8080"
-const SUBJECT = "/chat/room1"
-
-function plik_upload_handler(fileserver_url::String, dataname::String, data::Vector{UInt8})::Dict{String, Any}
-    url_getUploadID = "$fileserver_url/upload"
-    headers = ["Content-Type" => "application/json"]
-    body = """{ "OneShot" : true }"""
-    httpResponse = HTTP.request("POST", url_getUploadID, headers, body; body_is_form=false)
-    responseJson = JSON.parse(String(httpResponse.body))
-    uploadid = responseJson["id"]
-    uploadtoken = responseJson["uploadToken"]
-    
-    file_multipart = HTTP.Multipart(dataname, IOBuffer(data), "application/octet-stream")
-    url_upload = "$fileserver_url/file/$uploadid"
-    headers = ["X-UploadToken" => uploadtoken]
-    
-    form = HTTP.Form(Dict("file" => file_multipart))
-    httpResponse = HTTP.post(url_upload, headers, form)
-    responseJson = JSON.parse(String(httpResponse.body))
-    
-    fileid = responseJson["id"]
-    url = "$fileserver_url/file/$uploadid/$fileid/$dataname"
-    
-    return Dict("status" => httpResponse.status, "uploadid" => uploadid, "fileid" => fileid, "url" => url)
-end
-
-function send_video()
-    # Read video file (MP4, AVI, etc.)
-    video_data = read("video_message.mp4", Vector{UInt8})
-    
-    env = NATSBridge.smartsend(
-        SUBJECT,
-        [("video_message", video_data, "video")],
-        nats_url = NATS_URL,
-        fileserver_url = FILESERVER_URL,
-        fileserverUploadHandler = plik_upload_handler,
-        size_threshold = 1_000_000,
-        correlation_id = string(uuid4()),
-        msg_purpose = "chat",
-        sender_name = "user-1"
-    )
-    
-    println("Sent video message: $(env.correlationId)")
-end
-
-send_video()
-```
-
-## Step 7: Table/Data Exchange
-
-### Sending Tabular Data
-
-```julia
-using NATS
-using JSON
-using UUIDs
-using Dates
-using PrettyPrinting
-using DataFrames
-using Arrow
-using HTTP
-using Base64
-
-include("NATSBridge.jl")
-using .NATSBridge
-
-const NATS_URL = "nats://localhost:4222"
-const FILESERVER_URL = "http://localhost:8080"
-const SUBJECT = "/chat/room1"
-
-function plik_upload_handler(fileserver_url::String, dataname::String, data::Vector{UInt8})::Dict{String, Any}
-    url_getUploadID = "$fileserver_url/upload"
-    headers = ["Content-Type" => "application/json"]
-    body = """{ "OneShot" : true }"""
-    httpResponse = HTTP.request("POST", url_getUploadID, headers, body; body_is_form=false)
-    responseJson = JSON.parse(String(httpResponse.body))
-    uploadid = responseJson["id"]
-    uploadtoken = responseJson["uploadToken"]
-    
-    file_multipart = HTTP.Multipart(dataname, IOBuffer(data), "application/octet-stream")
-    url_upload = "$fileserver_url/file/$uploadid"
-    headers = ["X-UploadToken" => uploadtoken]
-    
-    form = HTTP.Form(Dict("file" => file_multipart))
-    httpResponse = HTTP.post(url_upload, headers, form)
-    responseJson = JSON.parse(String(httpResponse.body))
-    
-    fileid = responseJson["id"]
-    url = "$fileserver_url/file/$uploadid/$fileid/$dataname"
-    
-    return Dict("status" => httpResponse.status, "uploadid" => uploadid, "fileid" => fileid, "url" => url)
-end
-
-function send_table()
-    # Create a DataFrame
-    df = DataFrame(
-        id = 1:5,
-        name = ["Alice", "Bob", "Charlie", "Diana", "Eve"],
-        score = [95, 88, 92, 98, 85],
-        grade = ['A', 'B', 'A', 'B', 'B']
-    )
-    
-    env = NATSBridge.smartsend(
-        SUBJECT,
-        [("student_scores", df, "table")],
-        nats_url = NATS_URL,
-        fileserver_url = FILESERVER_URL,
-        fileserverUploadHandler = plik_upload_handler,
-        size_threshold = 1_000_000,
-        correlation_id = string(uuid4()),
-        msg_purpose = "chat",
-        sender_name = "user-1"
-    )
-    
-    println("Sent table with $(nrow(df)) rows")
-end
-
-send_table()
-```
-
-### Receiving and Using Tables
-
-```julia
-using NATS
-using JSON
-using UUIDs
-using Dates
-using PrettyPrinting
-using DataFrames
-using Arrow
-using HTTP
-using Base64
-
-include("NATSBridge.jl")
-using .NATSBridge
-
-const NATS_URL = "nats://localhost:4222"
-const SUBJECT = "/chat/room1"
-
-function message_handler(msg::NATS.Msg)
-    payloads = NATSBridge.smartreceive(
-        msg,
-        max_retries = 5,
-        base_delay = 100,
-        max_delay = 5000
-    )
-    
-    for (dataname, data, data_type) in payloads
-        if data_type == "table"
-            data = DataFrame(data)
-            println("Received table:")
-            show(data)
-            println("\nAverage score: $(mean(data.score))")
-        end
-    end
-end
-
-NATS.subscribe(SUBJECT) do msg
-    message_handler(msg)
-end
-```
-
-## Step 8: Bidirectional Communication
-
-### Request-Response Pattern
-
-```julia
-using NATS
-using JSON
-using UUIDs
-using Dates
-using PrettyPrinting
-using DataFrames
-using Arrow
-using HTTP
-using Base64
-
-include("NATSBridge.jl")
-using .NATSBridge
-
-const NATS_URL = "nats://localhost:4222"
-const SUBJECT = "/api/query"
-const REPLY_SUBJECT = "/api/response"
-
-# Request
-function send_request()
-    query_data = Dict("query" => "SELECT * FROM users")
-    
-    env = NATSBridge.smartsend(
-        SUBJECT,
-        [("sql_query", query_data, "dictionary")],
-        nats_url = NATS_URL,
-        fileserver_url = "http://localhost:8080",
-        fileserverUploadHandler = plik_upload_handler,
-        size_threshold = 1_000_000,
-        correlation_id = string(uuid4()),
-        msg_purpose = "request",
-        sender_name = "frontend",
-        receiver_name = "backend",
-        reply_to = REPLY_SUBJECT,
-        reply_to_msg_id = string(uuid4())
-    )
-    
-    println("Request sent: $(env.correlationId)")
-end
-
-# Response handler
-function response_handler(msg::NATS.Msg)
-    payloads = NATSBridge.smartreceive(
-        msg,
-        max_retries = 5,
-        base_delay = 100,
-        max_delay = 5000
-    )
-    
-    for (dataname, data, data_type) in payloads
-        if data_type == "table"
-            data = DataFrame(data)
-            println("Query results:")
-            show(data)
-        end
-    end
-end
-
-NATS.subscribe(REPLY_SUBJECT) do msg
-    response_handler(msg)
-end
-```
-
-## Step 9: Complete Chat Application
-
-### Full Chat System
-
-```julia
-module ChatApp
-using NATS
-using JSON
-using UUIDs
-using Dates
-using PrettyPrinting
-using DataFrames
-using Arrow
-using HTTP
-using Base64
-
-# Include the bridge module
-include("../src/NATSBridge.jl")
-using .NATSBridge
-
-# Configuration
-const NATS_URL = "nats://localhost:4222"
-const FILESERVER_URL = "http://localhost:8080"
-const SUBJECT = "/chat/room1"
-
-# File upload handler for plik server
-function plik_upload_handler(fileserver_url::String, dataname::String, data::Vector{UInt8})::Dict{String, Any}
-    url_getUploadID = "$fileserver_url/upload"
-    headers = ["Content-Type" => "application/json"]
-    body = """{ "OneShot" : true }"""
-    httpResponse = HTTP.request("POST", url_getUploadID, headers, body; body_is_form=false)
-    responseJson = JSON.parse(String(httpResponse.body))
-    uploadid = responseJson["id"]
-    uploadtoken = responseJson["uploadToken"]
-    
-    file_multipart = HTTP.Multipart(dataname, IOBuffer(data), "application/octet-stream")
-    url_upload = "$fileserver_url/file/$uploadid"
-    headers = ["X-UploadToken" => uploadtoken]
-    
-    form = HTTP.Form(Dict("file" => file_multipart))
-    httpResponse = HTTP.post(url_upload, headers, form)
-    responseJson = JSON.parse(String(httpResponse.body))
-    
-    fileid = responseJson["id"]
-    url = "$fileserver_url/file/$uploadid/$fileid/$dataname"
-    
-    return Dict("status" => httpResponse.status, "uploadid" => uploadid, "fileid" => fileid, "url" => url)
-end
-
-function send_chat_message(
-    text::String,
-    image_path::Union{String, Nothing}=nothing,
-    audio_path::Union{String, Nothing}=nothing
-)
-    # Build payloads list
-    payloads = [("message_text", text, "text")]
-    
-    if image_path !== nothing
-        image_data = read(image_path, Vector{UInt8})
-        push!(payloads, ("user_image", image_data, "image"))
-    end
-    
-    if audio_path !== nothing
-        audio_data = read(audio_path, Vector{UInt8})
-        push!(payloads, ("user_audio", audio_data, "audio"))
-    end
-    
-    env = NATSBridge.smartsend(
-        SUBJECT,
-        payloads,
-        nats_url = NATS_URL,
-        fileserver_url = FILESERVER_URL,
-        fileserverUploadHandler = plik_upload_handler,
-        size_threshold = 1_000_000,
-        correlation_id = string(uuid4()),
-        msg_purpose = "chat",
-        sender_name = "user-1"
-    )
-    
-    println("Message sent with correlation ID: $(env.correlationId)")
-end
-
-function receive_chat_messages()
-    function message_handler(msg::NATS.Msg)
-        payloads = NATSBridge.smartreceive(
-            msg,
-            max_retries = 5,
-            base_delay = 100,
-            max_delay = 5000
-        )
-        
-        println("\n--- New Message ---")
-        for (dataname, data, data_type) in payloads
-            if data_type == "text"
-                println("Text: $data")
-            elseif data_type == "image"
-                filename = "received_$dataname.bin"
-                write(filename, data)
-                println("Image saved: $filename")
-            elseif data_type == "audio"
-                filename = "received_$dataname.bin"
-                write(filename, data)
-                println("Audio saved: $filename")
-            elseif data_type == "table"
-                println("Table received:")
-                data = DataFrame(data)
-                show(data)
-            end
-        end
-    end
-    
-    NATS.subscribe(SUBJECT) do msg
-        message_handler(msg)
-    end
-    println("Subscribed to: $SUBJECT")
-end
-
-function run_interactive_chat()
-    println("\n=== Interactive Chat ===")
-    println("1. Send a message")
-    println("2. Join a chat room")
-    println("3. Exit")
-    
-    while true
-        print("\nSelect option (1-3): ")
-        choice = readline()
-        
-        if choice == "1"
-            print("Enter message text: ")
-            text = readline()
-            send_chat_message(text)
-        elseif choice == "2"
-            receive_chat_messages()
-        elseif choice == "3"
-            break
-        end
-    end
-end
-
-end # module
-
-# Run the chat app
-using .ChatApp
-ChatApp.run_interactive_chat()
-```
-
-## Step 10: Testing the Chat System
-
-### Test Scenario 1: Text-Only Chat
-
-```bash
-# Terminal 1: Start the chat receiver
-julia test_julia_to_julia_text_receiver.jl
-
-# Terminal 2: Send a message
-julia test_julia_to_julia_text_sender.jl
-```
-
-### Test Scenario 2: Image Chat
-
-```bash
-# Terminal 1: Receive messages
-julia test_julia_to_julia_mix_payloads_receiver.jl
-
-# Terminal 2: Send image
-julia test_julia_to_julia_mix_payload_sender.jl
-```
-
-### Test Scenario 3: Large File Transfer
-
-```bash
-# Terminal 2: Send large file
-julia test_julia_to_julia_mix_payload_sender.jl
-```
-
-## Conclusion
-
-This walkthrough demonstrated how to build a chat system using NATSBridge.jl with support for:
-
-- Text messages
-- Images (direct transport for small, link transport for large)
-- Audio files
-- Video files
-- Tabular data (DataFrames)
-- Bidirectional communication
-- Mixed-content messages
-
-The key takeaways are:
-
-1. **Always wrap payloads in a list** - Even for single payloads: `[("dataname", data, "type")]`
-2. **Use appropriate transport** - NATSBridge automatically handles size-based routing
-3. **Support mixed content** - Multiple payloads of different types in one message
-4. **Handle errors** - Implement proper error handling for network failures
-5. **Use correlation IDs** - Track messages across distributed systems
-
-For more information, see:
-- [`docs/architecture.md`](./docs/architecture.md) - Detailed architecture documentation
-- [`docs/implementation.md`](./docs/implementation.md) - Implementation details