add natsbridge_csr.js

Reviewed-on: #9

.gitignore

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

AI_prompt.txt

@@ -13,3 +13,91 @@ Role: Principal Systems Architect & Lead Software Engineer.Objective: Implement
 
 
 Create a walkthrough for Julia service-A service sending a mix-content chat message to Julia service-B. the chat message must includes 
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+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.
+
+
+
+
+
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+
+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.
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+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 To ensure accuracy, the Julia src directory will serve as the ground truth, as the documentation may be outdated.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 To ensure accuracy,  NATSBridge.jl will serve as the ground truth, as the documentation may be outdated.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.
+
+
+
+
+
+
+
+
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+
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+

Project.toml

@@ -1,6 +1,6 @@
 name = "NATSBridge"
 uuid = "f2724d33-f338-4a57-b9f8-1be882570d10"
-version = "0.4.2"
+version = "0.5.4"
 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/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

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/tutorial.md

@@ -1,604 +0,0 @@
-# NATSBridge Tutorial
-
-A step-by-step guide to get started with NATSBridge - a high-performance, bi-directional data bridge for **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)
-7. [Cross-Platform Communication](#cross-platform-communication)
-
----
-
-## Overview
-
-NATSBridge enables seamless communication between Julia, JavaScript, and Python/Micropython applications 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
-
-### 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 |
-
----
-
-## Prerequisites
-
-Before you begin, ensure you have:
-
-1. **NATS Server** running (or accessible)
-2. **HTTP File Server** (optional, for large payloads > 1MB)
-3. **One of the supported platforms**: Julia, JavaScript (Node.js), or Python/Micropython
-
----
-
-## Installation
-
-### Julia
-
-```julia
-using Pkg
-Pkg.add("NATS")
-Pkg.add("Arrow")
-Pkg.add("JSON3")
-Pkg.add("HTTP")
-Pkg.add("UUIDs")
-Pkg.add("Dates")
-```
-
-### JavaScript
-
-```bash
-npm install nats.js apache-arrow uuid base64-url
-```
-
-### Python/Micropython
-
-1. Copy `src/nats_bridge.py` to your device
-2. Install dependencies:
-
-**For Python (desktop):**
-```bash
-pip install nats-py
-```
-
-**For Micropython:**
-- `urequests` for HTTP requests
-- `base64` for base64 encoding (built-in)
-- `json` for JSON handling (built-in)
-
----
-
-## 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
-
-# Use Python's built-in server
-python3 -m http.server 8080 --directory /tmp/fileserver
-```
-
-### Step 3: Send Your First Message
-
-#### Python/Micropython
-
-```python
-from nats_bridge import smartsend
-
-# Send a text message
-data = [("message", "Hello World", "text")]
-env = smartsend("/chat/room1", data, nats_url="nats://localhost:4222")
-print("Message sent!")
-```
-
-#### JavaScript
-
-```javascript
-const { smartsend } = require('./src/NATSBridge');
-
-// Send a text message
-await smartsend("/chat/room1", [
-    { dataname: "message", data: "Hello World", type: "text" }
-], { natsUrl: "nats://localhost:4222" });
-
-console.log("Message sent!");
-```
-
-#### Julia
-
-```julia
-using NATSBridge
-
-# Send a text message
-data = [("message", "Hello World", "text")]
-env = smartsend("/chat/room1", data, nats_url="nats://localhost:4222")
-println("Message sent!")
-```
-
-### Step 4: Receive Messages
-
-#### Python/Micropython
-
-```python
-from nats_bridge import smartreceive
-
-# Receive and process message
-envelope = smartreceive(msg)
-for dataname, data, type in envelope["payloads"]:
-    print(f"Received {dataname}: {data}")
-```
-
-#### JavaScript
-
-```javascript
-const { smartreceive } = require('./src/NATSBridge');
-
-// Receive and process message
-const envelope = await smartreceive(msg);
-for (const payload of envelope.payloads) {
-    console.log(`Received ${payload.dataname}: ${payload.data}`);
-}
-```
-
-#### Julia
-
-```julia
-using NATSBridge
-
-# Receive and process message
-envelope = smartreceive(msg, fileserverDownloadHandler)
-for (dataname, data, type) in envelope["payloads"]
-    println("Received $dataname: $data")
-end
-```
-
----
-
-## Basic Examples
-
-### Example 1: Sending a Dictionary
-
-#### Python/Micropython
-
-```python
-from nats_bridge import smartsend
-
-# Create configuration dictionary
-config = {
-    "wifi_ssid": "MyNetwork",
-    "wifi_password": "password123",
-    "update_interval": 60
-}
-
-# Send as dictionary type
-data = [("config", config, "dictionary")]
-env = smartsend("/device/config", data, nats_url="nats://localhost:4222")
-```
-
-#### JavaScript
-
-```javascript
-const { smartsend } = require('./src/NATSBridge');
-
-const config = {
-    wifi_ssid: "MyNetwork",
-    wifi_password: "password123",
-    update_interval: 60
-};
-
-await smartsend("/device/config", [
-    { dataname: "config", data: config, type: "dictionary" }
-]);
-```
-
-#### Julia
-
-```julia
-using NATSBridge
-
-config = Dict(
-    "wifi_ssid" => "MyNetwork",
-    "wifi_password" => "password123",
-    "update_interval" => 60
-)
-
-data = [("config", config, "dictionary")]
-smartsend("/device/config", data)
-```
-
-### Example 2: Sending Binary Data (Image)
-
-#### Python/Micropython
-
-```python
-from nats_bridge import smartsend
-
-# Read image file
-with open("image.png", "rb") as f:
-    image_data = f.read()
-
-# Send as binary type
-data = [("user_image", image_data, "binary")]
-env = smartsend("/chat/image", data, nats_url="nats://localhost:4222")
-```
-
-#### JavaScript
-
-```javascript
-const { smartsend } = require('./src/NATSBridge');
-
-// Read image file (Node.js)
-const fs = require('fs');
-const image_data = fs.readFileSync('image.png');
-
-await smartsend("/chat/image", [
-    { dataname: "user_image", data: image_data, type: "binary" }
-]);
-```
-
-#### Julia
-
-```julia
-using NATSBridge
-
-# Read image file
-image_data = read("image.png")
-
-data = [("user_image", image_data, "binary")]
-smartsend("/chat/image", data)
-```
-
-### Example 3: Request-Response Pattern
-
-#### Python/Micropython (Requester)
-
-```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"
-)
-```
-
-#### JavaScript (Responder)
-
-```javascript
-const { smartreceive, smartsend } = require('./src/NATSBridge');
-
-// Subscribe to command topic
-const sub = nc.subscribe("/device/command");
-
-for await (const msg of sub) {
-    const envelope = await smartreceive(msg);
-    
-    // Process command
-    for (const payload of envelope.payloads) {
-        if (payload.dataname === "command") {
-            const command = payload.data;
-            
-            if (command.action === "read_sensor") {
-                // Read sensor and send response
-                const response = {
-                    sensor_id: "sensor-001",
-                    value: 42.5,
-                    timestamp: new Date().toISOString()
-                };
-                
-                await smartsend("/device/response", [
-                    { dataname: "sensor_data", data: response, type: "dictionary" }
-                ], {
-                    reply_to: envelope.replyTo,
-                    reply_to_msg_id: envelope.msgId
-                });
-            }
-        }
-    }
-}
-```
-
----
-
-## Advanced Usage
-
-### Example 4: Large Payloads (File Server)
-
-For payloads larger than 1MB, NATSBridge automatically uses the file server:
-
-#### Python/Micropython
-
-```python
-from nats_bridge import smartsend
-import os
-
-# Create large data (> 1MB)
-large_data = os.urandom(2_000_000)  # 2MB of random data
-
-# Send with file server URL
-env = smartsend(
-    "/data/large",
-    [("large_file", large_data, "binary")],
-    nats_url="nats://localhost:4222",
-    fileserver_url="http://localhost:8080",
-    size_threshold=1_000_000
-)
-
-# The envelope will contain the download URL
-print(f"File uploaded to: {env.payloads[0].data}")
-```
-
-#### JavaScript
-
-```javascript
-const { smartsend } = require('./src/NATSBridge');
-
-// Create large data (> 1MB)
-const largeData = new ArrayBuffer(2_000_000);
-const view = new Uint8Array(largeData);
-view.fill(42);  // Fill with some data
-
-await smartsend("/data/large", [
-    { dataname: "large_file", data: largeData, type: "binary" }
-], {
-    fileserverUrl: "http://localhost:8080",
-    sizeThreshold: 1_000_000
-});
-```
-
-#### Julia
-
-```julia
-using NATSBridge
-
-# Create large data (> 1MB)
-large_data = rand(UInt8, 2_000_000)
-
-env = smartsend(
-    "/data/large",
-    [("large_file", large_data, "binary")],
-    fileserver_url="http://localhost:8080"
-)
-
-# The envelope will contain the download URL
-println("File uploaded to: $(env.payloads[1].data)")
-```
-
-### Example 5: Mixed Content (Chat with Text + Image)
-
-NATSBridge supports sending multiple payloads with different types in a single message:
-
-#### Python/Micropython
-
-```python
-from nats_bridge import smartsend
-
-# Read image file
-with open("avatar.png", "rb") as f:
-    image_data = f.read()
-
-# Send mixed content
-data = [
-    ("message_text", "Hello with image!", "text"),
-    ("user_avatar", image_data, "image")
-]
-
-env = smartsend("/chat/mixed", data, nats_url="nats://localhost:4222")
-```
-
-#### JavaScript
-
-```javascript
-const { smartsend } = require('./src/NATSBridge');
-
-const fs = require('fs');
-
-await smartsend("/chat/mixed", [
-    {
-        dataname: "message_text",
-        data: "Hello with image!",
-        type: "text"
-    },
-    {
-        dataname: "user_avatar",
-        data: fs.readFileSync("avatar.png"),
-        type: "image"
-    }
-]);
-```
-
-#### Julia
-
-```julia
-using NATSBridge
-
-image_data = read("avatar.png")
-
-data = [
-    ("message_text", "Hello with image!", "text"),
-    ("user_avatar", image_data, "image")
-]
-
-smartsend("/chat/mixed", data)
-```
-
-### Example 6: Table Data (Arrow IPC)
-
-For tabular data, NATSBridge uses Apache Arrow IPC format:
-
-#### Python/Micropython
-
-```python
-from nats_bridge import smartsend
-import pandas as pd
-
-# Create DataFrame
-df = pd.DataFrame({
-    "id": [1, 2, 3],
-    "name": ["Alice", "Bob", "Charlie"],
-    "score": [95, 88, 92]
-})
-
-# Send as table type
-data = [("students", df, "table")]
-env = smartsend("/data/students", data, nats_url="nats://localhost:4222")
-```
-
-#### 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, "table")]
-smartsend("/data/students", data)
-```
-
----
-
-## Cross-Platform Communication
-
-NATSBridge enables seamless communication between different platforms:
-
-### Julia ↔ JavaScript
-
-#### Julia Sender
-
-```julia
-using NATSBridge
-
-# Send dictionary from Julia to JavaScript
-config = Dict("step_size" => 0.01, "iterations" => 1000)
-data = [("config", config, "dictionary")]
-smartsend("/analysis/config", data, nats_url="nats://localhost:4222")
-```
-
-#### JavaScript Receiver
-
-```javascript
-const { smartreceive } = require('./src/NATSBridge');
-
-// Receive dictionary from Julia
-const envelope = await smartreceive(msg);
-for (const payload of envelope.payloads) {
-    if (payload.type === "dictionary") {
-        console.log("Received config:", payload.data);
-        // payload.data = { step_size: 0.01, iterations: 1000 }
-    }
-}
-```
-
-### JavaScript ↔ Python
-
-#### JavaScript Sender
-
-```javascript
-const { smartsend } = require('./src/NATSBridge');
-
-await smartsend("/data/transfer", [
-    { dataname: "message", data: "Hello from JS!", type: "text" }
-]);
-```
-
-#### Python Receiver
-
-```python
-from nats_bridge import smartreceive
-
-envelope = smartreceive(msg)
-for dataname, data, type in envelope["payloads"]:
-    if type == "text":
-        print(f"Received from JS: {data}")
-```
-
-### Python ↔ Julia
-
-#### Python Sender
-
-```python
-from nats_bridge import smartsend
-
-data = [("message", "Hello from Python!", "text")]
-smartsend("/chat/python", data)
-```
-
-#### Julia Receiver
-
-```julia
-using NATSBridge
-
-envelope = smartreceive(msg, fileserverDownloadHandler)
-for (dataname, data, type) in envelope["payloads"]
-    if type == "text"
-        println("Received from Python: $data")
-    end
-end
-```
-
----
-
-## Next Steps
-
-1. **Explore the test directory** for more examples
-2. **Check the documentation** for advanced configuration options
-3. **Join the community** to share your use cases
-
----
-
-## 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 (bytes/Vector{UInt8})
-
----
-
-## License
-
-MIT

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

@@ -1,709 +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<Object>} - Envelope dictionary with metadata and payloads field containing 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}`);
-        }
-    }
-    
-    // Replace payloads array with the processed list of {dataname, data, type} tuples
-    json_data.payloads = payloads_list;
-    
-    return json_data;
-}
-
-// 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

@@ -1,295 +0,0 @@
-# NATSBridge
-
-A high-performance, bi-directional data bridge for **Julia**, **JavaScript**, and **Python/Micropython** using NATS (Core & JetStream), implementing the Claim-Check pattern for large payloads.
-
-## Overview
-
-NATSBridge enables seamless communication between Julia, JavaScript, and Python/Micropython applications 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
-
-## Features
-
-- ✅ Bi-directional NATS communication across Julia ↔ JavaScript ↔ Python/Micropython
-- ✅ 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 |
-
-## Implementation Guides
-
-### [Julia Implementation](../tutorial_julia.md)
-
-See the [Julia tutorial](../tutorial_julia.md) for getting started with Julia.
-
-### [JavaScript Implementation](#javascript-implementation)
-
-See [`NATSBridge.js`](NATSBridge.js) for the JavaScript implementation.
-
-### [Python/Micropython Implementation](#pythonmicropython-implementation)
-
-See [`nats_bridge.py`](nats_bridge.py) for the Python/Micropython implementation.
-
-## Installation
-
-### Julia
-
-```julia
-using Pkg
-Pkg.add("NATS")
-Pkg.add("Arrow")
-Pkg.add("JSON3")
-Pkg.add("HTTP")
-Pkg.add("UUIDs")
-Pkg.add("Dates")
-```
-
-### JavaScript
-
-```bash
-npm install nats.js apache-arrow uuid base64-url
-```
-
-### Python/Micropython
-
-1. Copy `nats_bridge.py` to your device
-2. Ensure you have the following dependencies:
-   - `urequests` for HTTP requests (Micropython)
-   - `requests` for HTTP requests (Python)
-   - `base64` for base64 encoding
-   - `json` for JSON handling
-   - `socket` for networking (Micropython)
-
-## Usage
-
-### Basic Text Message
-
-#### Python/Micropython
-
-```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))
-```
-
-#### Julia
-
-```julia
-using NATSBridge
-
-# Sender
-data = [("message", "Hello World", "text")]
-env = smartsend("/chat/room1", data, nats_url="nats://localhost:4222")
-
-# Receiver
-envelope = smartreceive(msg, fileserverDownloadHandler)
-# envelope["payloads"] = [("message", "Hello World", "text"), ...]
-```
-
-#### JavaScript
-
-```javascript
-const { smartsend, smartreceive } = require('./src/NATSBridge');
-
-// Sender
-await smartsend("/chat/room1", [
-    { dataname: "message", data: "Hello World", type: "text" }
-], { natsUrl: "nats://localhost:4222" });
-
-// Receiver
-const envelope = await smartreceive(msg);
-// envelope.payloads = [{ dataname: "message", data: "Hello World", type: "text" }, ...]
-```
-
-### Sending JSON Configuration
-
-#### Python/Micropython
-
-```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/Micropython
-
-```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/Micropython
-
-```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/Micropython
-
-```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`](../examples/micropython_example.py) for more detailed examples.
-
-## Testing
-
-Run the test suite:
-
-```bash
-# Python/Micropython
-python test/test_micropython_basic.py
-
-# JavaScript
-node test/test_js_to_js_text_sender.js
-node test/test_js_to_js_text_receiver.js
-
-# Julia
-julia test/test_julia_to_julia_text_sender.jl
-julia test/test_julia_to_julia_text_receiver.jl
-```
-
-## Requirements
-
-- **Julia**: NATS server (nats.io), HTTP file server (optional)
-- **JavaScript**: NATS server (nats.io), HTTP file server (optional)
-- **Python/Micropython**: NATS server (nats.io), HTTP file server (optional)
-
-## License
-
-MIT

src/nats_bridge.py

@@ -1,667 +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:
-        dict: Envelope dictionary with metadata and 'payloads' field containing 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))
-    
-    # Replace payloads field with the processed list of (dataname, data, type) tuples
-    json_data["payloads"] = payloads_list
-    
-    return json_data
-
-
-# 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

@@ -1,80 +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 ${msg.subject}`);
-        
-        // Use NATSBridge.smartreceive to handle the data
-        const result = await smartreceive(
-            msg,
-            {
-                maxRetries: 5,
-                baseDelay: 100,
-                maxDelay: 5000
-            }
-        );
-        
-        // Result is an envelope dictionary with payloads field
-        // Access payloads with result.payloads
-        for (const { dataname, data, type } of result.payloads) {
-            if (typeof data === 'object' && data !== null && !Array.isArray(data)) {
-                log_trace(`Received Dictionary '${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

@@ -1,71 +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 an envelope dictionary with payloads field
-        // Access payloads with result.payloads
-        for (const { dataname, data, type } of result.payloads) {
-            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

@@ -1,173 +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.payloads.length} payloads`);
-        
-        // Result is an envelope dictionary with payloads field
-        // Access payloads with result.payloads
-        for (const { dataname, data, type } of result.payloads) {
-            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.payloads.filter(x => x.type === "text").length;
-        const dict_count = result.payloads.filter(x => x.type === "dictionary").length;
-        const table_count = result.payloads.filter(x => x.type === "table").length;
-        const image_count = result.payloads.filter(x => x.type === "image").length;
-        const audio_count = result.payloads.filter(x => x.type === "audio").length;
-        const video_count = result.payloads.filter(x => x.type === "video").length;
-        const binary_count = result.payloads.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: ${binary_count}`);
-        
-        // Print transport type info for each payload if available
-        console.log("\n=== Payload Details ===");
-        for (const { dataname, data, type } of result.payloads) {
-            if (["image", "audio", "video", "binary"].includes(type)) {
-                log_trace(`${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

@@ -1,87 +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 ${msg.subject}`);
-        
-        // Use NATSBridge.smartreceive to handle the data
-        const result = await smartreceive(
-            msg,
-            {
-                maxRetries: 5,
-                baseDelay: 100,
-                maxDelay: 5000
-            }
-        );
-        
-        // Result is an envelope dictionary with payloads field
-        // Access payloads with result.payloads
-        for (const { dataname, data, type } of result.payloads) {
-            if (Array.isArray(data)) {
-                log_trace(`Received Table '${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

@@ -1,81 +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 ${msg.subject}`);
-        
-        // Use NATSBridge.smartreceive to handle the data
-        const result = await smartreceive(
-            msg,
-            {
-                maxRetries: 5,
-                baseDelay: 100,
-                maxDelay: 5000
-            }
-        );
-        
-        // Result is an envelope dictionary with payloads field
-        // Access payloads with result.payloads
-        for (const { dataname, data, type } of result.payloads) {
-            if (typeof data === 'string') {
-                log_trace(`Received text '${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"
 
@@ -93,26 +93,41 @@ function test_mix_receive()
                     log_trace("  ERROR: Expected Dict, got $(typeof(data))")
                 end
                 
-            elseif data_type == "table"
+            elseif data_type == "arrowtable"
-                # Table data - should be a DataFrame
+                # Arrow table data - should be Arrow.Table
-                data = DataFrame(data)
+                if isa(data, Arrow.Table)
-                if isa(data, DataFrame)
+                    log_trace("  Type: Arrow.Table")
-                    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
+                    # Convert to DataFrame for display and save
-                    log_trace("  First 5 rows:")
+                    df = DataFrame(data)
-                    display(data[1:min(5, size(data, 1)), :])
+                    @show df[1:3, :]
-                    
-                    # 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))")
+                    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
@@ -180,7 +195,9 @@ function test_mix_receive()
         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"])
+        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"])
@@ -188,7 +205,9 @@ function test_mix_receive()
         
         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: $video_count")
@@ -199,9 +218,13 @@ function test_mix_receive()
         for (dataname, data, data_type) in result["payloads"]
             if data_type in ["image", "audio", "video", "binary"]
                 log_trace("$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: $(length(data)) rows (Vector{Dict/NamedTuple})")
             elseif data_type == "table"
-              data = DataFrame(data)
+                data = DataFrame(data)
-                log_trace("$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)
+    # Arrow table data (DataFrame - small - direct transport)
-    table_data_small = DataFrame(
+    # Uses Arrow IPC format for efficient binary serialization
+    # NATSBridge.jl handles serialization: DataFrame -> Arrow IPC
+    arrow_table_small = DataFrame(
         id = 1:10,
-        message = ["msg_$i" for i in 1:10],
+        name = ["Alice", "Bob", "Charlie", "Diana", "Eve", "Frank", "Grace", "Henry", "Ivy", "Jack"],
-        sender = ["sender_$i" for i in 1:10],
+        score = rand(50:100, 10),
-        timestamp = [string(Dates.now()) for _ in 1:10],
+        active = rand([true, false], 10)
-        priority = rand(1:3, 10)
     )
     
-    # Table data (DataFrame - large - link transport)
+    # Arrow table data (DataFrame - large - link transport)
-    # ~1.5MB of data (150,000 rows) - should trigger link transport
+    # ~1.5MB of Arrow data (200,000 rows) - should trigger link transport
-    table_data_large = DataFrame(
+    # NATSBridge.jl handles serialization: DataFrame -> Arrow IPC
-        id = 1:150_000,
+    arrow_table_large = DataFrame(
-        message = ["msg_$i" for i in 1:150_000],
+        id = 1:2_000_000,
-        sender = ["sender_$i" for i in 1:150_000],
+        name = ["user_$i" for i in 1:2_000_000],
-        timestamp = [string(Dates.now()) for i in 1:150_000],
+        score = rand(50:100, 2_000_000),
-        priority = rand(1:3, 150_000)
+        active = rand([true, false], 2_000_000),
+        timestamp = [string(Dates.now()) for _ in 1:2_000_000]
     )
     
-    # Image data (small binary - direct transport)
+    # Json table data (DataFrame - small - direct transport)
-    # Create a simple 10x10 pixel PNG-like data (128 bytes header + 100 pixels = 112 bytes)
+    # Uses JSON format for human-readable tabular data
-    # Using simple RGB data (10*10*3 = 300 bytes of pixel data)
+    # NATSBridge.jl handles serialization: DataFrame -> Vector{Dict} -> JSON
-    image_width = 10
+    json_table_small = DataFrame(
-    image_height = 10
+        id = 1:10,
-    image_data = UInt8[]
+        name = ["Alice", "Bob", "Charlie", "Diana", "Eve", "Frank", "Grace", "Henry", "Ivy", "Jack"],
-    # PNG header (simplified)
+        score = rand(50:100, 10),
-    push!(image_data, 0x89, 0x50, 0x4E, 0x47, 0x0D, 0x0A, 0x1A, 0x0A)
+        active = rand([true, false], 10)
-    # Simple RGB data (RGBRGBRGB...)
+    )
-    for i in 1:image_width*image_height
-        push!(image_data, 0xFF, 0x00, 0x00)  # Red pixel
-    end
     
-    # Image data (large - link transport)
+    # Json table data (DataFrame - large - link transport)
-    # Create a larger image (~1.5MB) to test link transport
+    # ~1.5MB of JSON data (150,000 rows) - should trigger link transport
-    large_image_width = 500
+    # NATSBridge.jl handles serialization: DataFrame -> Vector{Dict} -> JSON
-    large_image_height = 1000
+    json_table_large = DataFrame(
-    large_image_data = UInt8[]
+        id = 1:2_000_000,
-    # PNG header (simplified for 500x1000)
+        name = ["user_$i" for i in 1:2_000_000],
-    push!(large_image_data, 0x89, 0x50, 0x4E, 0x47, 0x0D, 0x0A, 0x1A, 0x0A)
+        score = rand(50:100, 2_000_000),
-    # RGB data (500*1000*3 = 1,500,000 bytes)
+        active = rand([true, false], 2_000_000)
-    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
     
     # 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,
+        arrow_table_small,
-        table_data_large,
+        arrow_table_large,
-        image_data,
+        json_table_small,
-        large_image_data,
+        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
+        # Large data (link transport) - large arrowtable, large jsontable, large image, large audio, large video, large binary
-        ("chat_table_large", table_data_large, "table"),
+        # ("arrow_table_large", arrow_table_large, "arrowtable"),
-        ("user_image_large", large_image_data, "image"),
+        ("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,
+        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 $(msg.subject)")
-        
-        # Use NATSBridge.smartreceive to handle the data
-        # API: smartreceive(msg, download_handler; max_retries, base_delay, max_delay)
-        result = NATSBridge.smartreceive(
-            msg;
-            max_retries = 5,
-            base_delay = 100,
-            max_delay = 5000
-        )
-        
-        # Result is an envelope dictionary with payloads field containing list of (dataname, data, data_type) tuples
-        for (dataname, data, data_type) in result["payloads"]
-            if isa(data, JSON.Object{String, Any})
-                log_trace("Received Dictionary '$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 an envelope dictionary with payloads field containing list of (dataname, data, data_type) tuples
-        for (dataname, data, data_type) in result["payloads"]
-            # 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 $(msg.subject)")
-        
-        # Use NATSBridge.smartreceive to handle the data
-        # API: smartreceive(msg, download_handler; max_retries, base_delay, max_delay)
-        result = NATSBridge.smartreceive(
-            msg;
-            max_retries = 5,
-            base_delay = 100,
-            max_delay = 5000
-        )
-        
-        # Result is an envelope dictionary with payloads field containing list of (dataname, data, data_type) tuples
-        for (dataname, data, data_type) in result["payloads"]
-          data = DataFrame(data)
-            if isa(data, DataFrame)
-                log_trace("Received DataFrame '$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 $(msg.subject)")
-        
-        # Use NATSBridge.smartreceive to handle the data
-        # API: smartreceive(msg, download_handler; max_retries, base_delay, max_delay)
-        result = NATSBridge.smartreceive(
-            msg;
-            max_retries = 5,
-            base_delay = 100,
-            max_delay = 5000
-        )
-        
-        # Result is an envelope dictionary with payloads field containing list of (dataname, data, data_type) tuples
-        for (dataname, data, data_type) in result["payloads"]
-            if isa(data, String)
-                log_trace("Received text '$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

@@ -1,207 +0,0 @@
-#!/usr/bin/env python3
-"""
-Basic functionality test for nats_bridge.py
-Tests the core classes and functions without NATS connection
-"""
-
-import sys
-import os
-
-# Add src to path for import
-sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', 'src'))
-
-from nats_bridge import (
-    MessagePayload,
-    MessageEnvelope,
-    smartsend,
-    smartreceive,
-    log_trace,
-    generate_uuid,
-    get_timestamp,
-    _serialize_data,
-    _deserialize_data
-)
-import json
-
-
-def test_message_payload():
-    """Test MessagePayload class"""
-    print("\n=== Testing MessagePayload ===")
-    
-    # Test direct transport with text
-    payload1 = MessagePayload(
-        data="Hello World",
-        msg_type="text",
-        id="test-id-1",
-        dataname="message",
-        transport="direct",
-        encoding="base64",
-        size=11
-    )
-    
-    assert payload1.id == "test-id-1"
-    assert payload1.dataname == "message"
-    assert payload1.type == "text"
-    assert payload1.transport == "direct"
-    assert payload1.encoding == "base64"
-    assert payload1.size == 11
-    print("  [PASS] MessagePayload with text data")
-    
-    # Test link transport with URL
-    payload2 = MessagePayload(
-        data="http://example.com/file.txt",
-        msg_type="binary",
-        id="test-id-2",
-        dataname="file",
-        transport="link",
-        encoding="none",
-        size=1000
-    )
-    
-    assert payload2.transport == "link"
-    assert payload2.data == "http://example.com/file.txt"
-    print("  [PASS] MessagePayload with link transport")
-    
-    # Test to_dict method
-    payload_dict = payload1.to_dict()
-    assert "id" in payload_dict
-    assert "dataname" in payload_dict
-    assert "type" in payload_dict
-    assert "transport" in payload_dict
-    assert "data" in payload_dict
-    print("  [PASS] MessagePayload.to_dict() method")
-
-
-def test_message_envelope():
-    """Test MessageEnvelope class"""
-    print("\n=== Testing MessageEnvelope ===")
-    
-    # Create payloads
-    payload1 = MessagePayload("Hello", "text", id="p1", dataname="msg1")
-    payload2 = MessagePayload("http://example.com/file", "binary", id="p2", dataname="file", transport="link")
-    
-    # Create envelope
-    env = MessageEnvelope(
-        send_to="/test/subject",
-        payloads=[payload1, payload2],
-        correlation_id="test-correlation-id",
-        msg_id="test-msg-id",
-        msg_purpose="chat",
-        sender_name="test_sender",
-        receiver_name="test_receiver",
-        reply_to="/test/reply"
-    )
-    
-    assert env.send_to == "/test/subject"
-    assert env.correlation_id == "test-correlation-id"
-    assert env.msg_id == "test-msg-id"
-    assert env.msg_purpose == "chat"
-    assert len(env.payloads) == 2
-    print("  [PASS] MessageEnvelope creation")
-    
-    # Test to_json method
-    json_str = env.to_json()
-    json_data = json.loads(json_str)
-    assert json_data["sendTo"] == "/test/subject"
-    assert json_data["correlationId"] == "test-correlation-id"
-    assert json_data["msgPurpose"] == "chat"
-    assert len(json_data["payloads"]) == 2
-    print("  [PASS] MessageEnvelope.to_json() method")
-
-
-def test_serialize_data():
-    """Test _serialize_data function"""
-    print("\n=== Testing _serialize_data ===")
-    
-    # Test text serialization
-    text_bytes = _serialize_data("Hello", "text")
-    assert isinstance(text_bytes, bytes)
-    assert text_bytes == b"Hello"
-    print("  [PASS] Text serialization")
-    
-    # Test dictionary serialization
-    dict_data = {"key": "value", "number": 42}
-    dict_bytes = _serialize_data(dict_data, "dictionary")
-    assert isinstance(dict_bytes, bytes)
-    parsed = json.loads(dict_bytes.decode('utf-8'))
-    assert parsed["key"] == "value"
-    print("  [PASS] Dictionary serialization")
-    
-    # Test binary serialization
-    binary_data = b"\x00\x01\x02"
-    binary_bytes = _serialize_data(binary_data, "binary")
-    assert binary_bytes == b"\x00\x01\x02"
-    print("  [PASS] Binary serialization")
-    
-    # Test image serialization
-    image_data = bytes([1, 2, 3, 4, 5])
-    image_bytes = _serialize_data(image_data, "image")
-    assert image_bytes == image_data
-    print("  [PASS] Image serialization")
-
-
-def test_deserialize_data():
-    """Test _deserialize_data function"""
-    print("\n=== Testing _deserialize_data ===")
-    
-    # Test text deserialization
-    text_bytes = b"Hello"
-    text_data = _deserialize_data(text_bytes, "text", "test-correlation-id")
-    assert text_data == "Hello"
-    print("  [PASS] Text deserialization")
-    
-    # Test dictionary deserialization
-    dict_bytes = b'{"key": "value"}'
-    dict_data = _deserialize_data(dict_bytes, "dictionary", "test-correlation-id")
-    assert dict_data == {"key": "value"}
-    print("  [PASS] Dictionary deserialization")
-    
-    # Test binary deserialization
-    binary_data = b"\x00\x01\x02"
-    binary_result = _deserialize_data(binary_data, "binary", "test-correlation-id")
-    assert binary_result == b"\x00\x01\x02"
-    print("  [PASS] Binary deserialization")
-
-
-def test_utilities():
-    """Test utility functions"""
-    print("\n=== Testing Utility Functions ===")
-    
-    # Test generate_uuid
-    uuid1 = generate_uuid()
-    uuid2 = generate_uuid()
-    assert uuid1 != uuid2
-    print(f"  [PASS] generate_uuid() - generated: {uuid1}")
-    
-    # Test get_timestamp
-    timestamp = get_timestamp()
-    assert "T" in timestamp
-    print(f"  [PASS] get_timestamp() - generated: {timestamp}")
-
-
-def main():
-    """Run all tests"""
-    print("=" * 60)
-    print("NATSBridge Python/Micropython - Basic Functionality Tests")
-    print("=" * 60)
-    
-    try:
-        test_message_payload()
-        test_message_envelope()
-        test_serialize_data()
-        test_deserialize_data()
-        test_utilities()
-        
-        print("\n" + "=" * 60)
-        print("ALL TESTS PASSED!")
-        print("=" * 60)
-        
-    except Exception as e:
-        print(f"\n[FAIL] Test failed with error: {e}")
-        import traceback
-        traceback.print_exc()
-        sys.exit(1)
-
-
-if __name__ == "__main__":
-    main()

test/test_micropython_dict_receiver.py

@@ -1,70 +0,0 @@
-#!/usr/bin/env python3
-"""
-Test script for dictionary transport testing - Receiver
-Tests receiving dictionary messages via NATS using nats_bridge.py smartreceive
-"""
-
-import sys
-import os
-import json
-
-# Add src to path for import
-sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', 'src'))
-
-from nats_bridge import smartreceive, log_trace
-import nats
-import asyncio
-
-# Configuration
-SUBJECT = "/NATSBridge_dict_test"
-NATS_URL = "nats://nats.yiem.cc:4222"
-
-
-async def main():
-    log_trace("", f"Starting dictionary transport receiver test...")
-    log_trace("", f"Note: This receiver will wait for messages from the sender.")
-    log_trace("", f"Run test_micropython_dict_sender.py first to send test data.")
-    
-    # Connect to NATS
-    nc = await nats.connect(NATS_URL)
-    log_trace("", f"Connected to NATS at {NATS_URL}")
-    
-    # Subscribe to the subject
-    async def message_handler(msg):
-        log_trace("", f"Received message on {msg.subject}")
-        
-        # Use smartreceive to handle the data
-        result = smartreceive(msg.data)
-        
-        # Result is an envelope dictionary with payloads field containing list of (dataname, data, data_type) tuples
-        for dataname, data, data_type in result["payloads"]:
-            if isinstance(data, dict):
-                log_trace(result.get("correlationId", ""), f"Received dictionary '{dataname}' of type {data_type}")
-                log_trace(result.get("correlationId", ""), f"  Keys: {list(data.keys())}")
-                
-                # Display first few items for small dicts
-                if isinstance(data, dict) and len(data) <= 10:
-                    log_trace(result.get("correlationId", ""), f"  Content: {json.dumps(data, indent=2)}")
-                else:
-                    # For large dicts, show summary
-                    log_trace(result.get("correlationId", ""), f"  Summary: {json.dumps(data, default=str)[:200]}...")
-                
-                # Save to file
-                output_path = f"./received_{dataname}.json"
-                with open(output_path, 'w') as f:
-                    json.dump(data, f, indent=2)
-                log_trace(result.get("correlationId", ""), f"Saved dictionary to {output_path}")
-            else:
-                log_trace(result.get("correlationId", ""), f"Received unexpected data type for '{dataname}': {type(data)}")
-    
-    sid = await nc.subscribe(SUBJECT, cb=message_handler)
-    log_trace("", f"Subscribed to {SUBJECT} with subscription ID: {sid}")
-    
-    # Keep listening for 120 seconds
-    await asyncio.sleep(120)
-    await nc.close()
-    log_trace("", "Test completed.")
-
-
-if __name__ == "__main__":
-    asyncio.run(main())

test/test_micropython_dict_sender.py

@@ -1,99 +0,0 @@
-#!/usr/bin/env python3
-"""
-Test script for dictionary transport testing - Micropython
-Tests sending dictionary messages via NATS using nats_bridge.py smartsend
-"""
-
-import sys
-import os
-
-# Add src to path for import
-sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', 'src'))
-
-from nats_bridge import smartsend, log_trace
-import uuid
-
-# Configuration
-SUBJECT = "/NATSBridge_dict_test"
-NATS_URL = "nats://nats.yiem.cc:4222"
-FILESERVER_URL = "http://192.168.88.104:8080"
-SIZE_THRESHOLD = 1_000_000  # 1MB
-
-# Create correlation ID for tracing
-correlation_id = str(uuid.uuid4())
-
-
-def main():
-    # Create a small dictionary (will use direct transport)
-    small_dict = {
-        "name": "test",
-        "value": 42,
-        "enabled": True,
-        "metadata": {
-            "version": "1.0.0",
-            "timestamp": "2026-02-22T12:00:00Z"
-        }
-    }
-    
-    # Create a large dictionary (will use link transport if > 1MB)
-    # Generate a larger dictionary (~2MB to ensure link transport)
-    large_dict = {
-        "id": str(uuid.uuid4()),
-        "items": [
-            {
-                "index": i,
-                "name": f"item_{i}",
-                "value": i * 1.5,
-                "data": "x" * 10000  # Large string per item
-            }
-            for i in range(200)
-        ],
-        "metadata": {
-            "count": 200,
-            "created": "2026-02-22T12:00:00Z"
-        }
-    }
-    
-    # Test data 1: small dictionary
-    data1 = ("small_dict", small_dict, "dictionary")
-    
-    # Test data 2: large dictionary
-    data2 = ("large_dict", large_dict, "dictionary")
-    
-    log_trace(correlation_id, f"Starting smartsend for subject: {SUBJECT}")
-    log_trace(correlation_id, f"Correlation ID: {correlation_id}")
-    
-    # Use smartsend with dictionary type
-    env = smartsend(
-        SUBJECT,
-        [data1, data2],  # List of (dataname, data, type) tuples
-        nats_url=NATS_URL,
-        fileserver_url=FILESERVER_URL,
-        size_threshold=SIZE_THRESHOLD,
-        correlation_id=correlation_id,
-        msg_purpose="chat",
-        sender_name="dict_sender",
-        receiver_name="",
-        receiver_id="",
-        reply_to="",
-        reply_to_msg_id=""
-    )
-    
-    log_trace(correlation_id, f"Sent message with {len(env.payloads)} payloads")
-    
-    # Log transport type for each payload
-    for i, payload in enumerate(env.payloads):
-        log_trace(correlation_id, f"Payload {i+1} ('{payload.dataname}'):")
-        log_trace(correlation_id, f"  Transport: {payload.transport}")
-        log_trace(correlation_id, f"  Type: {payload.type}")
-        log_trace(correlation_id, f"  Size: {payload.size} bytes")
-        log_trace(correlation_id, f"  Encoding: {payload.encoding}")
-        
-        if payload.transport == "link":
-            log_trace(correlation_id, f"  URL: {payload.data}")
-    
-    print(f"Test completed. Correlation ID: {correlation_id}")
-
-
-if __name__ == "__main__":
-    main()

test/test_micropython_file_receiver.py

@@ -1,65 +0,0 @@
-#!/usr/bin/env python3
-"""
-Test script for file transport testing - Receiver
-Tests receiving binary files via NATS using nats_bridge.py smartreceive
-"""
-
-import sys
-import os
-
-# Add src to path for import
-sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', 'src'))
-
-from nats_bridge import smartreceive, log_trace
-import nats
-import asyncio
-
-# Configuration
-SUBJECT = "/NATSBridge_file_test"
-NATS_URL = "nats://nats.yiem.cc:4222"
-
-
-async def main():
-    log_trace("", f"Starting file transport receiver test...")
-    log_trace("", f"Note: This receiver will wait for messages from the sender.")
-    log_trace("", f"Run test_micropython_file_sender.py first to send test data.")
-    
-    # Connect to NATS
-    nc = await nats.connect(NATS_URL)
-    log_trace("", f"Connected to NATS at {NATS_URL}")
-    
-    # Subscribe to the subject
-    async def message_handler(msg):
-        log_trace("", f"Received message on {msg.subject}")
-        
-        # Use smartreceive to handle the data
-        result = smartreceive(msg.data)
-        
-        # Result is an envelope dictionary with payloads field containing list of (dataname, data, data_type) tuples
-        for dataname, data, data_type in result["payloads"]:
-            if isinstance(data, bytes):
-                log_trace(result.get("correlationId", ""), f"Received binary '{dataname}' of type {data_type}")
-                log_trace(result.get("correlationId", ""), f"  Size: {len(data)} bytes")
-                
-                # Display first 100 bytes as hex
-                log_trace(result.get("correlationId", ""), f"  First 100 bytes (hex): {data[:100].hex()}")
-                
-                # Save to file
-                output_path = f"./received_{dataname}.bin"
-                with open(output_path, 'wb') as f:
-                    f.write(data)
-                log_trace(result.get("correlationId", ""), f"Saved binary to {output_path}")
-            else:
-                log_trace(result.get("correlationId", ""), f"Received unexpected data type for '{dataname}': {type(data)}")
-    
-    sid = await nc.subscribe(SUBJECT, cb=message_handler)
-    log_trace("", f"Subscribed to {SUBJECT} with subscription ID: {sid}")
-    
-    # Keep listening for 120 seconds
-    await asyncio.sleep(120)
-    await nc.close()
-    log_trace("", "Test completed.")
-
-
-if __name__ == "__main__":
-    asyncio.run(main())

test/test_micropython_file_sender.py

@@ -1,79 +0,0 @@
-#!/usr/bin/env python3
-"""
-Test script for file transport testing - Micropython
-Tests sending binary files via NATS using nats_bridge.py smartsend
-"""
-
-import sys
-import os
-
-# Add src to path for import
-sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', 'src'))
-
-from nats_bridge import smartsend, log_trace
-import uuid
-
-# Configuration
-SUBJECT = "/NATSBridge_file_test"
-NATS_URL = "nats://nats.yiem.cc:4222"
-FILESERVER_URL = "http://192.168.88.104:8080"
-SIZE_THRESHOLD = 1_000_000  # 1MB
-
-# Create correlation ID for tracing
-correlation_id = str(uuid.uuid4())
-
-
-def main():
-    # Create small binary data (will use direct transport)
-    small_binary = b"This is small binary data for testing direct transport."
-    small_binary += b"\x00" * 100  # Add some null bytes
-    
-    # Create large binary data (will use link transport if > 1MB)
-    # Generate a larger binary (~2MB to ensure link transport)
-    large_binary = bytes([
-        (i * 7) % 256 for i in range(2_000_000)
-    ])
-    
-    # Test data 1: small binary (direct transport)
-    data1 = ("small_binary", small_binary, "binary")
-    
-    # Test data 2: large binary (link transport)
-    data2 = ("large_binary", large_binary, "binary")
-    
-    log_trace(correlation_id, f"Starting smartsend for subject: {SUBJECT}")
-    log_trace(correlation_id, f"Correlation ID: {correlation_id}")
-    
-    # Use smartsend with binary type
-    env = smartsend(
-        SUBJECT,
-        [data1, data2],  # List of (dataname, data, type) tuples
-        nats_url=NATS_URL,
-        fileserver_url=FILESERVER_URL,
-        size_threshold=SIZE_THRESHOLD,
-        correlation_id=correlation_id,
-        msg_purpose="chat",
-        sender_name="file_sender",
-        receiver_name="",
-        receiver_id="",
-        reply_to="",
-        reply_to_msg_id=""
-    )
-    
-    log_trace(correlation_id, f"Sent message with {len(env.payloads)} payloads")
-    
-    # Log transport type for each payload
-    for i, payload in enumerate(env.payloads):
-        log_trace(correlation_id, f"Payload {i+1} ('{payload.dataname}'):")
-        log_trace(correlation_id, f"  Transport: {payload.transport}")
-        log_trace(correlation_id, f"  Type: {payload.type}")
-        log_trace(correlation_id, f"  Size: {payload.size} bytes")
-        log_trace(correlation_id, f"  Encoding: {payload.encoding}")
-        
-        if payload.transport == "link":
-            log_trace(correlation_id, f"  URL: {payload.data}")
-    
-    print(f"Test completed. Correlation ID: {correlation_id}")
-
-
-if __name__ == "__main__":
-    main()

test/test_micropython_mixed_receiver.py

@@ -1,97 +0,0 @@
-#!/usr/bin/env python3
-"""
-Test script for mixed payload testing - Receiver
-Tests receiving mixed payload types via NATS using nats_bridge.py smartreceive
-"""
-
-import sys
-import os
-import json
-
-# Add src to path for import
-sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', 'src'))
-
-from nats_bridge import smartreceive, log_trace
-import nats
-import asyncio
-
-# Configuration
-SUBJECT = "/NATSBridge_mixed_test"
-NATS_URL = "nats://nats.yiem.cc:4222"
-
-
-async def main():
-    log_trace("", f"Starting mixed payload receiver test...")
-    log_trace("", f"Note: This receiver will wait for messages from the sender.")
-    log_trace("", f"Run test_micropython_mixed_sender.py first to send test data.")
-    
-    # Connect to NATS
-    nc = await nats.connect(NATS_URL)
-    log_trace("", f"Connected to NATS at {NATS_URL}")
-    
-    # Subscribe to the subject
-    async def message_handler(msg):
-        log_trace("", f"Received message on {msg.subject}")
-        
-        # Use smartreceive to handle the data
-        result = smartreceive(msg.data)
-        
-        log_trace(result.get("correlationId", ""), f"Received envelope with {len(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(result.get("correlationId", ""), f"\n--- Payload: {dataname} (type: {data_type}) ---")
-            
-            if isinstance(data, str):
-                log_trace(result.get("correlationId", ""), f"  Type: text/string")
-                log_trace(result.get("correlationId", ""), f"  Length: {len(data)} characters")
-                if len(data) <= 100:
-                    log_trace(result.get("correlationId", ""), f"  Content: {data}")
-                else:
-                    log_trace(result.get("correlationId", ""), f"  First 100 chars: {data[:100]}...")
-                # Save to file
-                output_path = f"./received_{dataname}.txt"
-                with open(output_path, 'w') as f:
-                    f.write(data)
-                log_trace(result.get("correlationId", ""), f"  Saved to: {output_path}")
-                
-            elif isinstance(data, dict):
-                log_trace(result.get("correlationId", ""), f"  Type: dictionary")
-                log_trace(result.get("correlationId", ""), f"  Keys: {list(data.keys())}")
-                log_trace(result.get("correlationId", ""), f"  Content: {json.dumps(data, indent=2)}")
-                # Save to file
-                output_path = f"./received_{dataname}.json"
-                with open(output_path, 'w') as f:
-                    json.dump(data, f, indent=2)
-                log_trace(result.get("correlationId", ""), f"  Saved to: {output_path}")
-                
-            elif isinstance(data, bytes):
-                log_trace(result.get("correlationId", ""), f"  Type: binary")
-                log_trace(result.get("correlationId", ""), f"  Size: {len(data)} bytes")
-                log_trace(result.get("correlationId", ""), f"  First 100 bytes (hex): {data[:100].hex()}")
-                # Save to file
-                output_path = f"./received_{dataname}.bin"
-                with open(output_path, 'wb') as f:
-                    f.write(data)
-                log_trace(result.get("correlationId", ""), f"  Saved to: {output_path}")
-            else:
-                log_trace(result.get("correlationId", ""), f"  Received unexpected data type: {type(data)}")
-        
-        # Log envelope metadata
-        log_trace(result.get("correlationId", ""), f"\n--- Envelope Metadata ---")
-        log_trace(result.get("correlationId", ""), f"  Correlation ID: {result.get('correlationId', 'N/A')}")
-        log_trace(result.get("correlationId", ""), f"  Message ID: {result.get('msgId', 'N/A')}")
-        log_trace(result.get("correlationId", ""), f"  Sender: {result.get('senderName', 'N/A')}")
-        log_trace(result.get("correlationId", ""), f"  Purpose: {result.get('msgPurpose', 'N/A')}")
-    
-    sid = await nc.subscribe(SUBJECT, cb=message_handler)
-    log_trace("", f"Subscribed to {SUBJECT} with subscription ID: {sid}")
-    
-    # Keep listening for 120 seconds
-    await asyncio.sleep(120)
-    await nc.close()
-    log_trace("", "Test completed.")
-
-
-if __name__ == "__main__":
-    asyncio.run(main())

test/test_micropython_mixed_sender.py

@@ -1,93 +0,0 @@
-#!/usr/bin/env python3
-"""
-Test script for mixed payload testing - Micropython
-Tests sending mixed payload types via NATS using nats_bridge.py smartsend
-"""
-
-import sys
-import os
-
-# Add src to path for import
-sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', 'src'))
-
-from nats_bridge import smartsend, log_trace
-import uuid
-
-# Configuration
-SUBJECT = "/NATSBridge_mixed_test"
-NATS_URL = "nats://nats.yiem.cc:4222"
-FILESERVER_URL = "http://192.168.88.104:8080"
-SIZE_THRESHOLD = 1_000_000  # 1MB
-
-# Create correlation ID for tracing
-correlation_id = str(uuid.uuid4())
-
-
-def main():
-    # Create payloads for mixed content test
-    
-    # 1. Small text (direct transport)
-    text_data = "Hello, this is a text message for testing mixed payloads!"
-    
-    # 2. Small dictionary (direct transport)
-    dict_data = {
-        "status": "ok",
-        "code": 200,
-        "message": "Test successful",
-        "items": [1, 2, 3]
-    }
-    
-    # 3. Small binary (direct transport)
-    binary_data = b"\x00\x01\x02\x03\x04\x05" + b"\xff" * 100
-    
-    # 4. Large text (link transport - will use fileserver)
-    large_text = "\n".join([
-        f"Line {i}: This is a large text payload for link transport testing. " * 50
-        for i in range(100)
-    ])
-    
-    # Test data list - mixed payload types
-    data = [
-        ("message_text", text_data, "text"),
-        ("config_dict", dict_data, "dictionary"),
-        ("small_binary", binary_data, "binary"),
-        ("large_text", large_text, "text"),
-    ]
-    
-    log_trace(correlation_id, f"Starting smartsend for subject: {SUBJECT}")
-    log_trace(correlation_id, f"Correlation ID: {correlation_id}")
-    
-    # Use smartsend with mixed types
-    env = smartsend(
-        SUBJECT,
-        data,  # List of (dataname, data, type) tuples
-        nats_url=NATS_URL,
-        fileserver_url=FILESERVER_URL,
-        size_threshold=SIZE_THRESHOLD,
-        correlation_id=correlation_id,
-        msg_purpose="chat",
-        sender_name="mixed_sender",
-        receiver_name="",
-        receiver_id="",
-        reply_to="",
-        reply_to_msg_id=""
-    )
-    
-    log_trace(correlation_id, f"Sent message with {len(env.payloads)} payloads")
-    
-    # Log transport type for each payload
-    for i, payload in enumerate(env.payloads):
-        log_trace(correlation_id, f"Payload {i+1} ('{payload.dataname}'):")
-        log_trace(correlation_id, f"  Transport: {payload.transport}")
-        log_trace(correlation_id, f"  Type: {payload.type}")
-        log_trace(correlation_id, f"  Size: {payload.size} bytes")
-        log_trace(correlation_id, f"  Encoding: {payload.encoding}")
-        
-        if payload.transport == "link":
-            log_trace(correlation_id, f"  URL: {payload.data}")
-    
-    print(f"Test completed. Correlation ID: {correlation_id}")
-
-
-if __name__ == "__main__":
-    main()

test/test_micropython_text_receiver.py

@@ -1,69 +0,0 @@
-#!/usr/bin/env python3
-"""
-Test script for text transport testing - Receiver
-Tests receiving text messages via NATS using nats_bridge.py smartreceive
-"""
-
-import sys
-import os
-import json
-
-# Add src to path for import
-sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', 'src'))
-
-from nats_bridge import smartreceive, log_trace
-import nats
-import asyncio
-
-# Configuration
-SUBJECT = "/NATSBridge_text_test"
-NATS_URL = "nats://nats.yiem.cc:4222"
-
-
-async def main():
-    log_trace("", f"Starting text transport receiver test...")
-    log_trace("", f"Note: This receiver will wait for messages from the sender.")
-    log_trace("", f"Run test_micropython_text_sender.py first to send test data.")
-    
-    # Connect to NATS
-    nc = await nats.connect(NATS_URL)
-    log_trace("", f"Connected to NATS at {NATS_URL}")
-    
-    # Subscribe to the subject
-    async def message_handler(msg):
-        log_trace("", f"Received message on {msg.subject}")
-        
-        # Use smartreceive to handle the data
-        result = smartreceive(msg.data)
-        
-        # Result is an envelope dictionary with payloads field containing list of (dataname, data, data_type) tuples
-        for dataname, data, data_type in result["payloads"]:
-            if isinstance(data, str):
-                log_trace(result.get("correlationId", ""), f"Received text '{dataname}' of type {data_type}")
-                log_trace(result.get("correlationId", ""), f"  Length: {len(data)} characters")
-                
-                # Display first 100 characters
-                if len(data) > 100:
-                    log_trace(result.get("correlationId", ""), f"  First 100 characters: {data[:100]}...")
-                else:
-                    log_trace(result.get("correlationId", ""), f"  Content: {data}")
-                
-                # Save to file
-                output_path = f"./received_{dataname}.txt"
-                with open(output_path, 'w') as f:
-                    f.write(data)
-                log_trace(result.get("correlationId", ""), f"Saved text to {output_path}")
-            else:
-                log_trace(result.get("correlationId", ""), f"Received unexpected data type for '{dataname}': {type(data)}")
-    
-    sid = await nc.subscribe(SUBJECT, cb=message_handler)
-    log_trace("", f"Subscribed to {SUBJECT} with subscription ID: {sid}")
-    
-    # Keep listening for 120 seconds
-    await asyncio.sleep(120)
-    await nc.close()
-    log_trace("", "Test completed.")
-
-
-if __name__ == "__main__":
-    asyncio.run(main())

test/test_micropython_text_sender.py

@@ -1,81 +0,0 @@
-#!/usr/bin/env python3
-"""
-Test script for text transport testing - Micropython
-Tests sending text messages via NATS using nats_bridge.py smartsend
-"""
-
-import sys
-import os
-
-# Add src to path for import
-sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', 'src'))
-
-from nats_bridge import smartsend, log_trace
-import uuid
-
-# Configuration
-SUBJECT = "/NATSBridge_text_test"
-NATS_URL = "nats://nats.yiem.cc:4222"
-FILESERVER_URL = "http://192.168.88.104:8080"
-SIZE_THRESHOLD = 1_000_000  # 1MB
-
-# Create correlation ID for tracing
-correlation_id = str(uuid.uuid4())
-
-
-def main():
-    # 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 = "\n".join([
-        f"Line {i}: This is a sample text line with some content to pad the size. " * 100 
-        for i in range(500)
-    ])
-    
-    # Test data 1: small text
-    data1 = ("small_text", small_text, "text")
-    
-    # Test data 2: large text
-    data2 = ("large_text", large_text, "text")
-    
-    log_trace(correlation_id, f"Starting smartsend for subject: {SUBJECT}")
-    log_trace(correlation_id, f"Correlation ID: {correlation_id}")
-    
-    # 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 = smartsend(
-        SUBJECT,
-        [data1, data2],  # List of (dataname, data, type) tuples
-        nats_url=NATS_URL,
-        fileserver_url=FILESERVER_URL,
-        size_threshold=SIZE_THRESHOLD,
-        correlation_id=correlation_id,
-        msg_purpose="chat",
-        sender_name="text_sender",
-        receiver_name="",
-        receiver_id="",
-        reply_to="",
-        reply_to_msg_id=""
-    )
-    
-    log_trace(correlation_id, f"Sent message with {len(env.payloads)} payloads")
-    
-    # Log transport type for each payload
-    for i, payload in enumerate(env.payloads):
-        log_trace(correlation_id, f"Payload {i+1} ('{payload.dataname}'):")
-        log_trace(correlation_id, f"  Transport: {payload.transport}")
-        log_trace(correlation_id, f"  Type: {payload.type}")
-        log_trace(correlation_id, f"  Size: {payload.size} bytes")
-        log_trace(correlation_id, f"  Encoding: {payload.encoding}")
-        
-        if payload.transport == "link":
-            log_trace(correlation_id, f"  URL: {payload.data}")
-    
-    print(f"Test completed. Correlation ID: {correlation_id}")
-
-
-if __name__ == "__main__":
-    main()

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())