update

Reviewed-on: #44

Manifest.toml

@@ -2,7 +2,7 @@
 
 julia_version = "1.12.6"
 manifest_format = "2.0"
-project_hash = "0db36d4fb31037ba05065476e6aebaf4cd0e1e8c"
+project_hash = "aa163e2bf572632825162936e107be18384fd40f"
 
 [[deps.Accessors]]
 deps = ["CompositionsBase", "ConstructionBase", "Dates", "InverseFunctions", "MacroTools"]
@@ -44,6 +44,12 @@ git-tree-sha1 = "d57bd3762d308bded22c3b82d033bff85f6195c6"
 uuid = "ec485272-7323-5ecc-a04f-4719b315124d"
 version = "0.4.0"
 
+[[deps.Arrow]]
+deps = ["ArrowTypes", "BitIntegers", "CodecLz4", "CodecZstd", "ConcurrentUtilities", "DataAPI", "Dates", "EnumX", "Mmap", "PooledArrays", "SentinelArrays", "StringViews", "Tables", "TimeZones", "TranscodingStreams", "UUIDs"]
+git-tree-sha1 = "4a69a3eadc1f7da78d950d1ef270c3a62c1f7e01"
+uuid = "69666777-d1a9-59fb-9406-91d4454c9d45"
+version = "2.8.1"
+
 [[deps.ArrowTypes]]
 deps = ["Sockets", "UUIDs"]
 git-tree-sha1 = "404265cd8128a2515a81d5eae16de90fdef05101"
@@ -58,6 +64,12 @@ version = "1.11.0"
 uuid = "2a0f44e3-6c83-55bd-87e4-b1978d98bd5f"
 version = "1.11.0"
 
+[[deps.BitIntegers]]
+deps = ["Random"]
+git-tree-sha1 = "091d591a060e43df1dd35faab3ca284925c48e46"
+uuid = "c3b6d118-76ef-56ca-8cc7-ebb389d030a1"
+version = "0.3.7"
+
 [[deps.BufferedStreams]]
 git-tree-sha1 = "6863c5b7fc997eadcabdbaf6c5f201dc30032643"
 uuid = "e1450e63-4bb3-523b-b2a4-4ffa8c0fd77d"
@@ -90,12 +102,24 @@ git-tree-sha1 = "40956acdbef3d8c7cc38cba42b56034af8f8581a"
 uuid = "6c391c72-fb7b-5838-ba82-7cfb1bcfecbf"
 version = "0.3.4"
 
+[[deps.CodecLz4]]
+deps = ["Lz4_jll", "TranscodingStreams"]
+git-tree-sha1 = "d58afcd2833601636b48ee8cbeb2edcb086522c2"
+uuid = "5ba52731-8f18-5e0d-9241-30f10d1ec561"
+version = "0.4.6"
+
 [[deps.CodecZlib]]
 deps = ["TranscodingStreams", "Zlib_jll"]
 git-tree-sha1 = "962834c22b66e32aa10f7611c08c8ca4e20749a9"
 uuid = "944b1d66-785c-5afd-91f1-9de20f533193"
 version = "0.7.8"
 
+[[deps.CodecZstd]]
+deps = ["TranscodingStreams", "Zstd_jll"]
+git-tree-sha1 = "da54a6cd93c54950c15adf1d336cfd7d71f51a56"
+uuid = "6b39b394-51ab-5f42-8807-6242bab2b4c2"
+version = "0.8.7"
+
 [[deps.CommonSolve]]
 git-tree-sha1 = "cf963add2340ad9960e5eb22844e61ad8f931fe1"
 uuid = "38540f10-b2f7-11e9-35d8-d573e4eb0ff2"
@@ -130,6 +154,12 @@ weakdeps = ["InverseFunctions"]
     [deps.CompositionsBase.extensions]
     CompositionsBaseInverseFunctionsExt = "InverseFunctions"
 
+[[deps.ConcurrentUtilities]]
+deps = ["Serialization", "Sockets"]
+git-tree-sha1 = "3c9be947934c38475bafe822c6d61aaed17f0738"
+uuid = "f0e56b4a-5159-44fe-b623-3e5288b988bb"
+version = "2.6.0"
+
 [[deps.ConstructionBase]]
 git-tree-sha1 = "b4b092499347b18a015186eae3042f72267106cb"
 uuid = "187b0558-2788-49d3-abe0-74a17ed4e7c9"
@@ -531,6 +561,12 @@ git-tree-sha1 = "1d4c737ab26f51ceed52ab2019c09b7660eb7440"
 uuid = "6f1432cf-f94c-5a45-995e-cdbf5db27b0b"
 version = "3.8.0"
 
+[[deps.Lz4_jll]]
+deps = ["Artifacts", "JLLWrappers", "Libdl"]
+git-tree-sha1 = "191686b1ac1ea9c89fc52e996ad15d1d241d1e33"
+uuid = "5ced341a-0733-55b8-9ab6-a4889d929147"
+version = "1.10.1+0"
+
 [[deps.MacroTools]]
 git-tree-sha1 = "1e0228a030642014fe5cfe68c2c0a818f9e3f522"
 uuid = "1914dd2f-81c6-5fcd-8719-6d5c9610ff09"
@@ -938,6 +974,11 @@ git-tree-sha1 = "8a90c1d77c3277a5d43b83927b3cbe2c70a37484"
 uuid = "892a3eda-7b42-436c-8928-eab12a02cf0e"
 version = "0.4.7"
 
+[[deps.StringViews]]
+git-tree-sha1 = "f2dcb92855b31ad92fe8f079d4f75ac57c93e4b8"
+uuid = "354b36f9-a18e-4713-926e-db85100087ba"
+version = "1.3.7"
+
 [[deps.StructTypes]]
 deps = ["Dates", "UUIDs"]
 git-tree-sha1 = "159331b30e94d7b11379037feeb9b690950cace8"
@@ -1080,6 +1121,14 @@ git-tree-sha1 = "011b0a7331b41c25524b64dc42afc9683ee89026"
 uuid = "a9144af2-ca23-56d9-984f-0d03f7b5ccf8"
 version = "1.0.21+0"
 
+[[deps.msghandler]]
+deps = ["Arrow", "Base64", "DataFrames", "Dates", "GeneralUtils", "HTTP", "JSON", "NATS", "PrettyPrinting", "Revise", "UUIDs"]
+git-tree-sha1 = "e82a79cf6602541ea25409aded57b2ace4a7c29f"
+repo-rev = "main"
+repo-url = "https://git.yiem.cc/ton/msghandler"
+uuid = "f2724d33-f338-4a57-b9f8-1be882570d10"
+version = "1.2.1"
+
 [[deps.nghttp2_jll]]
 deps = ["Artifacts", "Libdl"]
 uuid = "8e850ede-7688-5339-a07c-302acd2aaf8d"

Project.toml

@@ -22,6 +22,7 @@ SQLLLM = "2ebc79c7-cc10-4a3a-9665-d2e1d61e63d3"
 Serialization = "9e88b42a-f829-5b0c-bbe9-9e923198166b"
 URIs = "5c2747f8-b7ea-4ff2-ba2e-563bfd36b1d4"
 UUIDs = "cf7118a7-6976-5b1a-9a39-7adc72f591a4"
+msghandler = "f2724d33-f338-4a57-b9f8-1be882570d10"
 
 [compat]
 Base64 = "1.11.0"
@@ -33,3 +34,4 @@ JSON = "1.6.1"
 LLMMCTS = "0.1.5"
 NATS = "0.1.0"
 SQLLLM = "0.2.8"
+msghandler = "1.2.1"

README.md

@@ -6,7 +6,7 @@ Julia framework for building agents with tool use.
 
 1. Install dependencies: `]add JSON, DataStructures, UUIDs, Dates, ...`
 2. Create a `yiemAgent` with `loadTools("src/tools")`
-3. Call `run_agent(agent, "message")` then `take_response(agent)`
+3. Call `runAgent(agent, "message")` then `takeResponse(agent)`
 
 ## Architecture
 
@@ -16,7 +16,7 @@ src/
 ├── type.jl               # Core types (messages, tools, agent state)
 ├── utils.jl              # Message formatting, validation
 ├── agentCore.jl          # Agent loop, tool execution pipeline
-├── api.jl                # Public API (run_agent, take_response, etc.)
+├── api.jl                # Public API (runAgent, takeResponse, etc.)
 └── tools/
     ├── registry.jl       # Tool registry (loadTools, registerTool, listTools)
     ├── getWeather.jl     # Weather lookup tool

etc.jl

@@ -1,2 +1,5 @@
-# ── executeToolCalls() Julia pseudo code ──────────────────────────
-# Full call stack from runLoop → executeToolCalls → prepare → execute → finalize → emit
+check my understand:
+1) if LLM didn't use tool calls, assistantMessage get pushed into agent._state.messages and 
+it will be the latest message in agent._state.messages. then _agentLoop() can pick it as 
+the output to outputChannel
+2) if LLM use tool calls but toolResultBatch.terminate is false, assistantMessageToolCall

etc.md

@@ -0,0 +1,8 @@
+check my understanding
+1) if LLM didn't use tool calls, assistantMessage get pushed into agent._state.messages and it will be the latest message in agent._state.messages. then _agentLoop() can pick it as the output to outputChannel
+2) if LLM use tool calls, assistantMessageToolCall get pushed into agent._state.messages. then toolResult get pushed into agent._state.messages. if toolResultBatch.terminate is false then _processMessage() loop continue
+3) if LLM use tool calls, assistantMessageToolCall get pushed into agent._state.messages. then toolResult get pushed into agent._state.messages. if toolResultBatch.terminate is true then final_response message get pushed into agent._state.messages. _processMessage() loop exit. then _agentLoop() can pick it as the output to outputChannel
+
+Is my understanding correct?
+
+

src/YiemAgent.jl

@@ -1,7 +1,6 @@
 module YiemAgent
 
-  # export agent
-
+  export register_all_tools
 
   """ Order by dependencies of each file. The 1st included file must not depend on any other
   files and each file can only depend on the file included before it. 
@@ -13,9 +12,23 @@ module YiemAgent
   include("utils.jl")
   using .utils
 
-  include("tools/registry.jl")
+  include("tools/getWeather.jl")
+  include("tools/getTime.jl")
+  include("tools/searchWine.jl")
+  include("tools/writeTool.jl")
+
+  include("toolRegistry.jl")
   using .toolRegistry
 
+  function register_all_tools(store::toolRegistry.toolStore)
+      registerTool(store, getWeatherTool())
+      registerTool(store, getTimeTool())
+      registerTool(store, searchWineTool())
+      registerTool(store, writeToolTool())
+      registerTool(store, listTool(store))
+      return store.tools
+  end
+
   # include("llmfunction.jl")
   # using .llmfunction
 

src/api.jl

@@ -5,12 +5,11 @@ export prompt
 using JSON, DataStructures, Dates, UUIDs, HTTP, Random, PrettyPrinting, Serialization,
       DataFrames
 using GeneralUtils
-using ..type, ..utils
+using ..type, ..utils, ..agentCore, ..toolRegistry
 
 # ---------------------------------------------- 100 --------------------------------------------- #
 
 
-
 """
 Send a message to the agent's input channel.
 
@@ -25,16 +24,16 @@ The agent processes messages from `inputChannel` in the background task.
 - The same `agent` instance for chaining
 
 # Notes
-- Use `take_response(agent)` to receive the agent's response after sending a message.
-- Use `follow_up(agent, msg)` to send messages while the agent is still processing.
+- Use `takeResponse(agent)` to receive the agent's response after sending a message.
+- Use `followUp(agent, msg)` to send messages while the agent is still processing.
 
 # Examples
 ```jldoctest
-julia> run_agent(agent, "Hello!")
+julia> runAgent(agent, "Hello!")
 yiemAgent(...)
 ```
 """
-function run_agent(agent::yiemAgent, msg)
+function runAgent(agent::yiemAgent, msg)
   put!(agent.inputChannel, msg)
   return agent
 end
@@ -51,15 +50,15 @@ Blocks until the agent sends a response.
 - An `assistantMessage` instance representing the agent's response
 
 # Notes
-- Use `run_agent(agent, msg)` to send a message before calling this function.
+- Use `runAgent(agent, msg)` to send a message before calling this function.
 
 # Examples
 ```jldoctest
-julia> response = take_response(agent)
+julia> response = takeResponse(agent)
 assistantMessage(...)
 ```
 """
-function take_response(agent::yiemAgent)
+function takeResponse(agent::yiemAgent)
   return take!(agent.outputChannel)
 end
 
@@ -77,17 +76,17 @@ and before any tool call results are sent.
 - The same `agent` instance for chaining
 
 # Notes
-- Use `run_agent(agent, msg)` for the primary message and `follow_up(agent, msg)` for additional
+- Use `runAgent(agent, msg)` for the primary message and `followUp(agent, msg)` for additional
   messages while the agent is processing.
 - Follow-up messages are buffered in a separate channel (capacity 32 by default).
 
 # Examples
 ```jldoctest
-julia> follow_up(agent, "Also consider red wines")
+julia> followUp(agent, "Also consider red wines")
 yiemAgent(...)
 ```
 """
-function follow_up(agent::yiemAgent, msg)
+function followUp(agent::yiemAgent, msg)
   put!(agent.followUpChannel, msg)
   return agent
 end
@@ -105,19 +104,19 @@ then closes all channels (`inputChannel`, `outputChannel`, `followUpChannel`).
 - `nothing`
 
 # Notes
-- After calling `stop_agent`, the agent is no longer usable. A new agent must be created
+- After calling `stopAgent`, the agent is no longer usable. A new agent must be created
   for further interaction.
 - If the background task throws a `TaskFailedException`, it is rethrown.
 
 # Examples
 ```jldoctest
-julia> stop_agent(agent)
+julia> stopAgent(agent)
 ```
 """
-function stop_agent(agent::yiemAgent)
+function stopAgent(agent::yiemAgent)
   put!(agent.inputChannel, :shutdown)
   try
-    fetch(agent._agent_loop)
+    fetch(agent._agentLoop)
   catch e
     if e isa TaskFailedException
       rethrow(e)

src/toolRegistry.jl

@@ -0,0 +1,179 @@
+module toolRegistry
+
+export toolStore, registerTool, getTools, clearTools, listTool
+
+using Dates
+using JSON, DataStructures
+using ..type
+
+"""
+Per-agent isolated tool storage.
+
+Each agent gets its own `toolStore` so tool registration is independent —
+`registerTool(store, tool)` only affects that agent's tool set.
+
+# Fields
+- `tools::OrderedDict{String, agentTool}` — keyed by name for O(1) lookup + ordered iteration
+- `name::String` — identifier for debugging/logs
+"""
+struct toolStore
+    tools::OrderedDict{String, agentTool}
+    name::String
+end
+
+"""
+    toolStore(; name="default") -> toolStore
+
+Create a new empty tool store.
+
+# Keyword Arguments
+- `name::String`: Display name for logging (default: `"default"`)
+
+# Example
+```julia
+julia> store = toolStore(name="agent1")
+toolStore(OrderedDict{String, agentTool}(), "agent1")
+```
+"""
+function toolStore(; name::String="default")::toolStore
+    toolStore(OrderedDict{String, agentTool}(), name)
+end
+
+"""
+    listTool(store::toolStore) -> agentTool
+
+Return an `agentTool` definition for listing registered tools.
+
+Each call produces a **new** tool object that captures (closes over)
+`store`. `register_all_tools` auto-registers one so the LLM can discover tools
+at runtime.
+
+# Arguments
+- `store`: The tool store whose tools will be listed when the tool runs
+
+# Example
+```julia
+julia> store = toolStore(name="agent1");
+
+julia> register_all_tools(store)  # auto-registers listTools
+[toolRegistry:agent1] Loaded tool: getWeather (Weather Lookup)
+[toolRegistry:agent1] Registered tool: listTools
+
+julia> tools = getTools(store)
+OrderedDict{String, agentTool} with 4 entries:
+  "getWeather" => agentTool(...)
+  "getTime" => agentTool(...)
+  "writeTool" => agentTool(...)
+  "listTools" => agentTool(...)
+```
+"""
+function listTool(store::toolStore)::agentTool
+    return agentTool(
+        name = "listTools",
+        label = "List Tools",
+        description = "List all available tools with their names, labels, and descriptions. Use this before creating a new tool to check for name collisions.",
+        inputSchema = Dict{String,Any}(
+            "type" => "object",
+            "properties" => Dict{String,Any}(),
+            "required" => Any[]
+        ),
+        execute = (toolCallId, args, signal, onPartialResult) -> begin
+            tools = getTools(store)
+            if isempty(tools)
+                result_text = "No tools registered."
+            else
+                lines = String["- $(t.name): $(t.label) — $(t.description)" for (k, t) in tools]
+                result_text = "Available tools:\n" * join(lines, "\n")
+            end
+            return agentToolResult(
+                [textContent(result_text)],
+                Dict{Any,Any}("count" => length(tools)),
+                nothing, false
+            )
+        end,
+        prepareArguments = nothing,
+        validateRequiredArgs = nothing,
+        parallelToolExecute = false
+    )
+end
+
+# Note: register_all_tools is defined in YiemAgent.jl where tool functions are in scope
+
+"""
+    registerTool(store::toolStore, tool::agentTool) -> OrderedDict{String, agentTool}
+
+Add `tool` to `store`, overwriting any existing tool with the same name.
+
+# Arguments
+- `store`: Tool store to modify
+- `tool`: The `agentTool` to register
+
+# Returns
+- The same `store.tools` dict (modified in place)
+
+# Example
+```julia
+julia> store = toolStore(name="agent1");
+
+julia> registerTool(store, listTool(store))
+[toolRegistry:agent1] Registered tool: listTools
+OrderedDict{String, agentTool} with 1 entry:
+  "listTools" => agentTool(...)
+```
+"""
+function registerTool(store::toolStore, tool::agentTool)::OrderedDict{String, agentTool}
+    store.tools[tool.name] = tool
+    println("[$(store.name)] Registered tool: $(tool.name)")
+    return store.tools
+end
+
+"""
+Return the tools registered in `store`.
+
+The returned dict is the **same object** stored inside `store` — mutations
+to it (e.g. via `registerTool`) are visible through subsequent calls.
+
+# Arguments
+- `store`: Tool store to query
+
+# Returns
+- `OrderedDict{String, agentTool}`: Tools keyed by name, in registration order
+
+# Example
+```julia
+julia> tools = getTools(store)
+OrderedDict{String, agentTool} with 2 entries:
+  "getWeather" => agentTool(...)
+  "getTime" => agentTool(...)
+```
+"""
+function getTools(store::toolStore)::OrderedDict{String, agentTool}
+    return store.tools
+end
+
+"""
+Remove all tools from `store`.
+
+# Arguments
+- `store`: Tool store to clear
+
+# Returns
+- `nothing`
+
+# Example
+```julia
+julia> clearTools(store)
+[toolRegistry:agent1] Registry cleared
+nothing
+
+julia> getTools(store)
+OrderedDict{String, agentTool} with 0 entries
+```
+"""
+function clearTools(store::toolStore)::Nothing
+    empty!(store.tools)
+    println("[$(store.name)] Registry cleared")
+    return nothing
+end
+
+end # module

src/tools/README.md

@@ -1,525 +0,0 @@
-# Tools
-
-Tools allow the agent to perform actions and fetch data. Each tool defines a **schema** (what arguments it accepts) and an **execution function** (what it does).
-
-## Tool Anatomy
-
-Each tool has 3 main parts:
-
-### 1. Schema (`inputSchema`)
-
-JSON Schema (MCP format) describing the tool's arguments. The `"required"` array lists mandatory fields:
-
-```julia
-inputSchema = Dict{String,Any}(
-    "type" => "object",
-    "properties" => Dict(
-        "city" => Dict("type" => "string", "description" => "City name"),
-        "units" => Dict("type" => "string", "enum" => ["celsius", "fahrenheit"], "default" => "celsius")
-    ),
-    "required" => ["city"]
-)
-```
-
-### 2. Execution Function (`execute`)
-
-A function with the signature:
-
-```julia
-execute(toolCallId::String, args::Dict{String,Any}, signal::Union{Nothing,abortSignal}, onPartialResult::Function)::agentToolResult
-```
-
-- **`toolCallId`** — unique ID for this invocation (from the LLM's tool call)
-- **`args`** — validated arguments provided by the LLM
-- **`signal`** — abort signal for cancellable operations
-- **`onPartialResult`** — callback for streaming progress updates
-- **Returns** — `agentToolResult` with content, details, usage, and termination flag
-
-```julia
-function executeTool(toolCallId::String, args::Dict{String,Any}, signal::Union{Nothing,abortSignal}, onPartialResult::Function)::agentToolResult
-    # Optional: stream progress updates
-    onPartialResult(Dict("status" => "Fetching data..."))
-    
-    # Do work
-    result = "Weather in $(args["city"]): Sunny, 22°C"
-    
-    # Return result
-    return agentToolResult(
-        [textContent(result)],
-        Dict{Any,Any}(),  # details
-        nothing,           # usage
-        false              # terminate (true to stop agent loop)
-    )
-end
-```
-
-### 3. Tool Definition (`getTool()`)
-
-Returns an `agentTool` struct:
-
-| Field | Type | Description |
-|---|---|---|
-| `name` | `String` | Unique identifier (e.g. `"getWeather"`) |
-| `label` | `String` | Human-readable name (e.g. `"Weather Lookup"`) |
-| `description` | `String` | What the tool does (shown to the LLM) |
-| `inputSchema` | `Any` | JSON Schema (MCP format) |
-| `execute` | `Function` | The execution function |
-| `prepareArguments` | `Union{Function,Nothing}` | Optional argument transform before validation |
-| `validateRequiredArgs` | `Union{Function,Nothing}` | Optional custom validation |
-| `parallelToolExecute` | `Bool` | Run this tool in parallel with others |
-
-## Argument Validation
-
-Validation happens **before** tool execution, in the `prepareToolCall` phase. Invalid calls return an error immediately without invoking `execute`, `beforeToolCall`, or logging `toolExecutionStart`.
-
-### Default: JSON Schema Required Fields
-
-Set `validateRequiredArgs = nothing` to use the default validator, which checks that all fields in `inputSchema["required"]` are present:
-
-```julia
-# src/tools/getWeather.jl — uses default validation
-function getTool()::agentTool
-    return agentTool(
-        name = "getWeather",
-        # ...
-        validateRequiredArgs = nothing,  # uses default
-    )
-end
-```
-
-### Custom Validation Hook
-
-Override `validateRequiredArgs` when you need:
-- **Cross-field constraints** (e.g. "at least one of X or Y")
-- **Format validation** (e.g. regex patterns, date parsing)
-- **Domain rules** (e.g. value ranges, business logic)
-
-The hook signature takes only `args`:
-
-```julia
-function validateRequiredArgs(args::Dict{String,Any})::Union{Nothing,String}
-    tz = get(args, "timezone", nothing)
-    city = get(args, "city", "")
-    
-    if !haskey(args, "timezone") && isempty(city)
-        return "Missing required argument: provide at least one of 'timezone' or 'city'"
-    end
-    
-    if tz !== nothing
-        tz_str = string(tz)
-        if !occursin(r"^[A-Za-z]+\/[A-Za-z]+(/[A-Za-z]+)*$", tz_str)
-            return "Invalid timezone format: '$tz_str'. Use IANA format, e.g. 'America/New_York'"
-        end
-    end
-    
-    return nothing
-end
-```
-
-Return `nothing` to pass, or an error `String` to fail. The error is fed back to the LLM so it can retry with corrected arguments.
-
-## Tool Discovery and Lifecycle
-
-The agent iterates through tools via a **discover → execute → loop** cycle. Here is the complete flow from the framework author's perspective:
-
-### The Agent Loop
-
-```julia
-# agentCore.jl:175 - _process_message()
-while true
-    # 1. Drain messages from inputChannel
-    while isready(agent.inputChannel)
-        raw_msg = take!(agent.inputChannel)
-        user_msg = OpenAiToUserMessage(raw_msg)
-        push!(agent._state.messages, user_msg)
-    end
-
-    # 2. Format messages for LLM
-    ctx = agent.prepareContext(agent._state)
-    formatted = agent.formatMsgForLLM(ctx)
-
-    # 3. Call LLM
-    response = agent.llmCall(formatted)
-
-    # 4. Check if LLM used tool calls
-    if has_tool_calls(response.content)
-        # 5. Execute tools, feed results back to LLM, loop
-    else
-        # 6. No tool calls — return final response
-        break
-    end
-end
-```
-
-### Step 1: Tool Discovery
-
-Tools are discovered from `agent._state.tools`, which is a `Vector{agentTool}` populated during agent creation:
-
-```julia
-# Loading tools
-tools = loadTools("src/tools")  # returns Vector{agentTool}
-
-# Passing to agent
-agent = yiemAgent(
-    systemPrompt = "...",
-    tools = tools,  # ← tools stored in agent._state.tools
-    llmCall = my_llm_call,
-    agentEventSink = my_event_sink,
-)
-```
-
-When the LLM response contains tool calls, the agent builds an `agentContext` with those tools:
-
-```julia
-context = agentContext(
-    agent._state.systemPrompt,
-    agent._state.messages,
-    agent._state.tools,  # ← tools available for discovery
-)
-```
-
-### Step 2: Extract Tool Calls from LLM Response
-
-The agent inspects the `response.content` blocks for `tool_calls`:
-
-```julia
-# agentCore.jl:217-245
-tool_call_list = agentToolCall[]
-
-for content_block in response.content
-    if content_block isa Dict
-        if get(content_block, :type, "") == "tool_calls"
-            # OpenAI format: {"type": "tool_calls", "tool_calls": [...]}
-            for tc_data in get(content_block, :tool_calls, [])
-                tc = agentToolCall(
-                    type = "function",
-                    id = get(tc_data, :id, string(uuid4())),
-                    name = get(tc_data, :function, Dict())[:name],
-                    arguments = get(tc_data, :function, Dict())[:arguments],
-                )
-                push!(tool_call_list, tc)
-            end
-        elseif get(content_block, :type, "") == "tool_call"
-            # Alternative format: single tool_call block
-            tc = agentToolCall(
-                type = "function",
-                id = get(content_block, :id, string(uuid4())),
-                name = get(content_block, :name, ""),
-                arguments = get(content_block, :arguments, Dict()),
-            )
-            push!(tool_call_list, tc)
-        end
-    end
-end
-```
-
-### Step 3: Execute Each Tool Call
-
-For each tool call, the agent runs through the **prepare → execute → finalize** pipeline:
-
-```julia
-# agentCore.jl:247-302
-if has_tool_calls && length(tool_call_list) > 0
-    context = agentContext(agent._state.systemPrompt, agent._state.messages, agent._state.tools)
-    config = agentLoopConfig(agent._state.tools, agent.beforeToolCall, agent.afterToolCall, execution_mode)
-    signal = nothing
-    emit = agent.agentEventSink
-
-    # Execute all tool calls (sequential or parallel)
-    batch = executeToolCalls(context, response, tool_call_list, config, signal, emit)
-
-    # Save results to conversation history
-    for tool_result in batch.messages
-        push!(agent._state.messages, tool_result)
-    end
-
-    # If any tool requested termination, break the loop
-    if batch.terminate
-        final_response = build_final_response(batch)
-        break
-    end
-    # Otherwise, loop back to step 2 (format + call LLM again)
-end
-```
-
-### Step 4: The Per-Call Pipeline
-
-Each tool call goes through three phases:
-
-```
-┌─────────────────────────────────────────────────────────────────┐
-│ PREPARE  →  prepareToolCall()                                  │
-│                                                                 │
-│   1. Find tool by name in context.tools                         │
-│   2. Transform args via tool.prepareArguments (if defined)      │
-│   3. Validate via tool.validateRequiredArgs (or default)        │
-│   4. Run beforeToolCall hook (if defined)                       │
-│   └── on any failure → return immediateOutcome (skip execution) │
-│   └── success → return preparedToolCall                         │
-├─────────────────────────────────────────────────────────────────┤
-│ EXECUTE  →  executePreparedToolCall()                           │
-│                                                                 │
-│   1. emit toolExecutionStart event                              │
-│   2. call tool.execute(toolCallId, args, signal, onPartialResult)│
-│   3. wait for all pending update events                         │
-│   └── on error → return executedOutcome(isError=true)           │
-│   └── success → return executedOutcome(isError=false)           │
-├─────────────────────────────────────────────────────────────────┤
-│ FINALIZE  →  finalizeExecutedToolCall()                         │
-│                                                                 │
-│   1. Run afterToolCall hook (if defined)                        │
-│      - can mutate content, details, usage, terminate, isError   │
-│   2. emit toolExecutionEnd event                                │
-│   3. createToolResultMessage → adds to conversation history     │
-│   └── return finalizedOutcome                                   │
-└─────────────────────────────────────────────────────────────────┘
-```
-
-### Step 5: Feed Results Back to LLM
-
-Tool results are added to `agent._state.messages` as `toolResultMessage` objects. On the next loop iteration, `formatMsgForLLM()` converts them to OpenAI format and the LLM receives the results:
-
-```
-Conversation history after tool execution:
-  [system] "You are a helpful assistant."
-  [user] "What's the weather in Tokyo?"
-  [assistant] (tool_calls: getWeather(city="Tokyo"))
-  [tool] tool_call_id="call_1", tool_name="getWeather", content="Weather in Tokyo: Sunny, 22°C"
-```
-
-The LLM then decides: call another tool, or return a final text answer.
-
-## Execution Modes
-
-### Sequential
-
-Tools execute one at a time in order. Required when:
-- Tools have implicit dependencies
-- Tools share state (e.g. writing to the same file)
-- Tools have `parallelToolExecute = false`
-
-Set globally via `agentLoopConfig.toolExecution = "sequential"`, or per-tool via `parallelToolExecute = false`.
-
-### Parallel
-
-Tools execute concurrently when all are independent. Reduces wall-clock time. Set `parallelToolExecute = true` on individual tools, or set `agentLoopConfig.toolExecution = "parallel"`.
-
-## Streaming Partial Results
-
-For long-running tools (API calls, file uploads, training), use `onPartialResult` to stream progress:
-
-```julia
-function executeTool(toolCallId::String, args::Dict{String,Any}, signal::Union{Nothing,abortSignal}, onPartialResult::Function)::agentToolResult
-    onPartialResult(Dict("status" => "Step 1: Fetching data..."))
-    sleep(1)
-    
-    onPartialResult(Dict("status" => "Step 2: Processing..."))
-    sleep(1)
-    
-    return agentToolResult(
-        [textContent("Done!")],
-        Dict{Any,Any}(), nothing, false
-    )
-end
-```
-
-UI listeners and the TUI consume these events in real time via `toolExecutionUpdate`.
-
-## Loading Tools
-
-### Auto-load from Directory
-
-```julia
-using .toolRegistry
-
-tools = loadTools("src/tools")  # scans for *.jl files with getTool()
-```
-
-Files are loaded alphabetically for deterministic registration order.
-
-### Manual Registration
-
-```julia
-tool = getTool()  # from your tool module
-registerTool(tool)
-```
-
-## Complete Lifecycle Example
-
-```julia
-# ─── USER SENDS MESSAGE ───────────────────────────────────────────
-run_agent(agent, "What's the weather in Tokyo?")
-
-# ─── LOOP ITERATION 1 ─────────────────────────────────────────────
-# Agent formats messages and calls LLM
-formatted = agent.formatMsgForLLM(agent.prepareContext(agent._state))
-response = agent.llmCall(formatted)
-# LLM returns: {"content": [{"type": "tool_calls", "tool_calls": [{"name": "getWeather", "arguments": {"city": "Tokyo"}}]}]}
-
-# Agent extracts tool call, builds context
-context = agentContext(systemPrompt, messages, agent._state.tools)
-tool_call_list = [agentToolCall("call_1", "getWeather", Dict("city" => "Tokyo"))]
-
-# PREPARE: find tool, validate args
-tool = find(t -> t.name == "getWeather", context.tools)  # found!
-validateRequiredArgs(Dict("city" => "Tokyo"), tool.inputSchema)  # passes
-beforeToolCall_hook(agentMsgCtx, nothing)  # nil, skipped
-
-# EXECUTE: call tool.execute()
-result = tool.execute("call_1", Dict("city" => "Tokyo"), nothing, onPartialResult)
-# Returns: agentToolResult([textContent("Weather in Tokyo: Sunny, 22°C")], Dict(), nothing, false)
-
-# FINALIZE: afterToolCall hook, emit events
-finalized = finalizedOutcome(tc, result, false)
-emit(toolExecEndEvent("call_1", "getWeather", result, false))
-msg = createToolResultMessage(finalized)  # toolResultMessage for conversation history
-
-# Add result to conversation
-push!(agent._state.messages, msg)
-# Messages now: [user: "What's the weather?", assistant: {tool_calls: getWeather}, tool: "Sunny, 22°C"]
-
-# ─── LOOP ITERATION 2 ─────────────────────────────────────────────
-# LLM called again with tool result included
-formatted = agent.formatMsgForLLM(agent.prepareContext(agent._state))
-response = agent.llmCall(formatted)
-# LLM returns: {"content": [{"type": "text", "text": "The weather in Tokyo is sunny, 22°C."}]}
-
-# No tool calls detected → break loop, return final response
-return assistantMessage(content=[textContent("The weather in Tokyo is sunny, 22°C.")], ...)
-
-# ─── USER RECEIVES RESPONSE ───────────────────────────────────────
-response = take_response(agent)
-println(response.content)
-# => "[textContent(\"The weather in Tokyo is sunny, 22°C.\")]"
-```
-
-## Self-Modifying Tools
-
-The framework includes tools that allow the agent to create new tools at runtime.
-
-### `writeTool` — Create New Tool Files
-
-`writeTool` is a **file writer**, not a code generator. The LLM provides the tool logic as `executeCode` (the actual Julia code), and `writeTool` wraps it in the required boilerplate.
-
-**How it works:**
-
-The LLM constructs `writeTool` with:
-- **`executeCode`** — the actual tool logic (Julia code body, NOT wrapped in a function)
-- **`name`, `label`, `description`** — tool metadata
-- **`inputSchema`** — parameter schema in MCP format
-- **`validateCode`, `prepareCode`** (optional) — custom validation/preparation logic
-
-`writeTool` produces `src/tools/<name>.jl` by:
-1. Converting the `inputSchema` Dict into a Julia `Dict{String,Any}(...)` string literal
-2. Indenting `executeCode` with 4 spaces
-3. Wrapping it inside a `function executeTool(...)::agentToolResult ... end` template
-4. Appending the `getTool()` definition that returns an `agentTool` struct
-5. Writing the combined string to disk
-
-**Workflow:**
-
-```
-LLM decides: "Need a searchWine tool. I'll provide the logic."
-
-LLM calls writeTool:
-  name: "searchWine"
-  executeCode: "query = args[\"query\"]\nresult = search(query)\nreturn ..."
-
-writeTool wraps it → src/tools/searchWine.jl:
-  function executeTool(...)::agentToolResult
-      query = args["query"]          ← LLM code (indented 4 spaces)
-      result = search(query)
-      return agentToolResult(...)
-  end
-
-  function getTool()::agentTool
-      return agentTool(name="searchWine", ...)
-  end
-
-Restart → loadTools("src/tools") loads searchWine.jl
-```
-
-**Example specification:**
-
-```julia
-Dict(
-    "name" => "searchWine",
-    "label" => "Wine Search",
-    "description" => "Search a wine database by name, region, or variety",
-    "inputSchema" => Dict(
-        "type" => "object",
-        "properties" => Dict(
-            "query" => Dict("type" => "string", "description" => "Search query"),
-            "maxResults" => Dict("type" => "integer", "default" => 10)
-        ),
-        "required" => ["query"]
-    ),
-    "executeCode" => """
-        query = args["query"]
-        max_results = get(args, "maxResults", 10)
-        # Perform search logic here
-        result = "Found 3 wines matching: $query"
-        return agentToolResult([textContent(result)], Dict{Any,Any}(), nothing, false)
-    """,
-    "parallel" => false
-)
-```
-
-**Optional hooks:**
-
-| Field | Description |
-|---|---|
-| `validateCode` | Custom validation Julia code (runs before execute). Return `nothing` to pass, or an error `String` to fail. |
-| `prepareCode` | Argument preparation code (runs before validation). Return modified args dict. |
-
-### `listTools` — Discover Available Tools
-
-Returns all registered tools. Primarily useful for **collision detection** before creating a new tool via `writeTool` — the LLM checks existing names before picking a unique one.
-
-```julia
-# Result from listTools:
-# Available tools:
-# - getWeather: Weather Lookup — Fetch current weather and forecast for a given city.
-# - getTime: Time Lookup — Get current local time for a timezone or city.
-# - writeTool: Create Tool — Generate new tool files...
-# - listTools: List Tools — List all available tools with their names and labels...
-```
-
-### Complete Self-Tooling Example
-
-```
-User: "I need to search for wines. Do you have a tool for that?"
-
-# ─── LOOP: Agent realizes no wine search tool exists ─────────────────
-
-# LLM generates the tool logic and calls writeTool to write it to disk
-
-[Tool Call] writeTool(name="searchWine", label="Wine Search",
-    description="Search a wine database by name, region, or variety",
-    inputSchema={...},
-    executeCode="query = args[\"query\"]\nresult = \"Found wines...\"\nreturn agentToolResult([textContent(result)], ...)")
-
-# writeTool generates src/tools/searchWine.jl
-
-# ─── SYSTEM RESTARTS ─────────────────────────────────────────────────
-
-# loadTools("src/tools") loads searchWine.jl alongside all other tools
-
-# ─── Agent calls the new tool ─────────────────────────────────────────
-
-[Tool Call] searchWine(query="cabernet", maxResults=5)
-# Result: "Found 5 cabernet wines..."
-
-# ─── Final response ──────────────────────────────────────────────────
-
-"The search found 5 cabernet wines: ..."
-```
-
-## Available Tools
-
-| Tool | Description | Validation |
-|---|---|---|
-| `getWeather` | Fetch weather for a city | Default (JSON Schema required) |
-| `getTime` | Get current time for a timezone or city | Custom (cross-field + format) |
-| `writeTool` | Create a new Julia tool module at runtime | Built-in (name + schema validation) |
-| `listTools` | List all available tools with descriptions | None (no arguments) |

src/tools/getTime.jl

@@ -1,3 +1,6 @@
+using .type
+using Dates
+
 """
 Validate required arguments for the getTime tool.
 
@@ -13,7 +16,7 @@ Demonstrates custom validation beyond simple required-field checking:
 - `nothing` if validation passes
 - `String` error message if validation fails
 """
-function validateRequiredArgs(args::Dict{String,Any})::Union{Nothing,String}
+function getTimeValidateRequiredArgs(args::Dict{String,Any})::Union{Nothing,String}
     tz = get(args, "timezone", nothing)
     city = get(args, "city", "")
     
@@ -41,7 +44,8 @@ Execute the getTime tool.
 
 Returns mock time data for the given timezone or city.
 """
-function executeTool(toolCallId::String, args::Dict{String,Any}, signal::Union{Nothing,abortSignal}, onPartialResult::Function)::agentToolResult
+function getTimeExecute(toolCallId::String, args::Dict{String,Any}, signal::Union{Nothing,abortSignal},
+  onPartialResult, llmCall=nothing)
     tz = get(args, "timezone", nothing)
     city = get(args, "city", "")
     if tz !== nothing
@@ -58,7 +62,7 @@ end
 """
 Define and return the getTime agentTool.
 """
-function getTool()::agentTool
+function getTimeTool()::agentTool
     return agentTool(
         name = "getTime",
         label = "Time Lookup",
@@ -71,9 +75,9 @@ function getTool()::agentTool
             ),
             "required" => []
         ),
-        execute = executeTool,
+        execute = getTimeExecute,
         prepareArguments = nothing,
-        validateRequiredArgs = validateRequiredArgs,
+        validateRequiredArgs = getTimeValidateRequiredArgs,
         parallelToolExecute = false
     )
 end

src/tools/getWeather.jl

@@ -1,23 +1,33 @@
+using msghandler
+using .type
+
 """
 Execute the getWeather tool.
 
 Returns mock weather data for the given city and temperature units.
 """
-function executeTool(toolCallId::String, args::Dict{String,Any}, signal::Union{Nothing,abortSignal}, onPartialResult::Function)::agentToolResult
-    city = get(args, "city", "")
-    units = get(args, "units", "celsius")
-    temp = units == "fahrenheit" ? "72" : "22"
-    unit_symbol = units == "celsius" ? "°C" : "°F"
-    return agentToolResult(
-        [textContent("Weather in $(city): Sunny, $(temp)$(unit_symbol)")],
-        Dict{Any,Any}(), nothing, false
-      )
+function getWeatherExecute(toolCallId::String, args::Dict{String,Any}, signal::Union{Nothing,abortSignal},
+  agentEventSink, llmCall=nothing)
+
+  agentEventSink("Getting weather...")
+
+  city = get(args, "city", "")
+  units = get(args, "units", "celsius")
+  temp = units == "fahrenheit" ? "72" : "22"
+  unit_symbol = units == "celsius" ? "°C" : "°F"
+  
+  return agentToolResult(
+      [textContent("Weather in $(city): Sunny, $(temp)$(unit_symbol)")],
+      Dict{Any,Any}(), 
+      nothing, 
+      false
+    )
 end
 
 """
 Define and return the getWeather agentTool.
 """
-function getTool()::agentTool
+function getWeatherTool()::agentTool
     return agentTool(
         name = "getWeather",
         label = "Weather Lookup",
@@ -30,7 +40,7 @@ function getTool()::agentTool
             ),
             "required" => ["city"]
         ),
-        execute = executeTool,
+        execute = getWeatherExecute,
         prepareArguments = nothing,
         validateRequiredArgs = nothing,
         parallelToolExecute = false

src/tools/registry.jl

@@ -1,196 +0,0 @@
-module toolRegistry
-
-export loadTools, registerTool, getTools, clearTools
-
-using Dates
-using JSON, DataStructures
-using ..type
-
-# Global registry — populated at runtime by loadTools() or registerTool()
-const _registry = Vector{agentTool}()
-
-# Module references — kept alive to prevent GC of tool code that closures depend on
-const _tool_modules = Vector{Module}()
-
-# Auto-register the built-in listTools tool
-function __init__()
-    registerTool(_listTool())
-end
-
-"""
-List tool definition — lets the agent query available tools for collision detection
-when creating new tools via writeTool.
-"""
-function _listTool()::agentTool
-    return agentTool(
-        name = "listTools",
-        label = "List Tools",
-        description = "List all available tools with their names, labels, and descriptions. Use this before creating a new tool to check for name collisions.",
-        inputSchema = Dict{String,Any}(
-            "type" => "object",
-            "properties" => Dict{String,Any}(),
-            "required" => Any[]
-        ),
-        execute = (toolCallId, args, signal, onPartialResult) -> begin
-            tools = getTools()
-            if isempty(tools)
-                result_text = "No tools registered."
-            else
-                lines = String["- $(t.name): $(t.label) — $(t.description)" for t in tools]
-                result_text = "Available tools:\n" * join(lines, "\n")
-            end
-            return agentToolResult(
-                [textContent(result_text)],
-                Dict{Any,Any}("count" => length(tools)),
-                nothing, false
-            )
-        end,
-        prepareArguments = nothing,
-        validateRequiredArgs = nothing,
-        parallelToolExecute = false
-    )
-end
-
-"""
-Load all tool modules from a directory.
-
-Scans `dir` for `.jl` files. Each file must define a function named
-`getTool()::agentTool`.  Files are sorted alphabetically so tool
-registration order is deterministic.
-
-Each `.jl` file is loaded into its own **submodule** so that all functions
-defined in the file (`validateRequiredArgs`, `prepareArguments`, `executeTool`,
-and any helper functions) are namespaced and never collide with other tools.
-
-# Tool file format
-Each `.jl` file defines one function `getTool()` that returns an `agentTool`.
-Inside the file you can freely define as many helper functions as you need —
-they will all be scoped under the tool's submodule.
-
-```julia
-# src/tools/getWeather.jl
-
-# These are namespaced — no collision with getTime.validateRequiredArgs, etc.
-function validateRequiredArgs(args::Dict{String,Any})::Union{Nothing,String}
-    ...
-end
-
-function getTool()::agentTool
-    return agentTool(
-        name = "getWeather",
-        ...
-    )
-end
-```
-
-# Arguments
-- `dir::String`: Directory path to scan for `.jl` tool files
-
-# Returns
-- `Vector{agentTool}`: All loaded tools
-
-# Errors
-- Throws `ArgumentError` if a tool file does not define a `getTool` function
-"""
-function loadTools(dir::String)::OrderedDict{String, agentTool}
-    if !isdir(dir)
-        throw(ArgumentError("Tool directory does not exist: $dir"))
-    end
-
-    tools = OrderedDict{String, agentTool}()
-    jl_files = filter(f -> endswith(f, ".jl") && !occursin(r"(?i)registry", f), readdir(dir))
-    sort!(jl_files)
-
-    for filename in jl_files
-        filepath = joinpath(dir, filename)
-
-        # Derive a unique module name from the filename only (not full path).
-        # e.g. "getWeather.jl" -> "_tool_getWeather"
-        mod_name = Symbol("_tool_", replace(rstrip(filename, '.'), ".jl" => ""))
-
-        # Build the complete module as a string and eval the parsed code.
-        # Julia does not allow `module ... end` inside eval(quote ...),
-        # and constructing the module AST by hand is fragile.
-        # Instead, we generate the full module source as a string,
-        # parse it, and eval the resulting expression.
-        # Also import Dates, UUIDs, DataStructures, JSON — common dependencies
-        # that tool files use (and that the ..type module transitively uses).
-        file_content = read(filepath, String)
-        module_code = """
-        module $(mod_name)
-        using ..type
-        using Dates, UUIDs, DataStructures, JSON
-        $(file_content)
-        end
-        """
-        mod = eval(Meta.parse(module_code))
-
-        # Call getTool() via Core.eval in the submodule's scope.
-        # This evaluates getTool() entirely within the new module's world,
-        # completely avoiding world-age issues — no invokelatest needed.
-        # Note: all uses of `tool` must be inside the `try` block because
-        # Julia 1.12's SSA form doesn't track `tool` as definitely assigned
-        # after a `try-catch` where it's only assigned inside `try`.
-        try
-            tool = Core.eval(mod, :(getTool()))
-            if !(tool isa agentTool)
-                throw(ArgumentError(
-                    "getTool() in $(filepath) did not return an agentTool instance, got: $(typeof(tool))"
-                ))
-            end
-            # Keep module reference alive — closures in the agentTool (execute,
-            # validateRequiredArgs, prepareArguments) may reference module-scoped
-            # functions. Without this, GC could collect the module.
-            push!(_tool_modules, mod)
-            push!(_registry, tool)
-            tools[tool.name] = tool
-            println("[toolRegistry] Loaded tool: $(tool.name) — $(tool.label)")
-        catch e
-            if e isa UndefVarError || occursin("getTool", sprint(showerror, e))
-                throw(ArgumentError(
-                    "Tool file $(filepath) does not define a `getTool()` function in module $(mod_name). " *
-                    "Each tool file must define: function getTool()::agentTool ... end"
-                ))
-            end
-            rethrow(e)
-        end
-    end
-
-    return tools
-end
-
-"""
-Register a single agentTool into the global registry.
-
-# Arguments
-- `tool::agentTool`: The tool to register
-
-# Returns
-- `Vector{agentTool}`: Updated registry
-"""
-function registerTool(tool::agentTool)::Vector{agentTool}
-    push!(_registry, tool)
-    println("[toolRegistry] Registered tool: $(tool.name)")
-    return _registry
-end
-
-"""
-Get all registered tools.
-
-# Returns
-- `Vector{agentTool}`: Copy of the registry
-"""
-function getTools()::Vector{agentTool}
-    return deepcopy(_registry)
-end
-
-"""
-Clear all registered tools from the global registry.
-"""
-function clearTools()::Nothing
-    empty!(_registry)
-    println("[toolRegistry] Registry cleared")
-    return nothing
-end
-
-end # module

src/tools/searchWine.jl

@@ -0,0 +1,397 @@
+using .type
+using LibPQ, DataFrames, JSON, DataStructures
+using Dates, Random, HTTP
+using GeneralUtils
+
+# ── Database config — update for your environment ───────────────────────
+const DB_CONFIG = Dict{String,Any}(
+    "host"     => "localhost",
+    "port"     => 5432,
+    "dbname"   => "winedb",
+    "user"     => "postgres",
+    "password" => "",
+)
+
+"""
+Execute the search_wine_database! tool.
+
+Uses the agent's LLM to generate SQL from the free-form text query,
+then executes it against the wine database and returns formatted results.
+"""
+function searchWineExecute(
+    toolCallId::String,
+    args::Dict{String,Any},
+    signal::Union{Nothing,abortSignal},
+    agentEventSink,
+    llmCall,
+)::agentToolResult
+  #WORKING
+    search_query = get(args, "searchQuery", "")::String
+
+    if isempty(search_query)
+        return agentToolResult(
+            [textContent("Please provide a search query for the wine database.")],
+            Dict{Any,Any}(), nothing, false
+        )
+    end
+
+    agentEventSink("searchWineExecute: query=$search_query")
+
+    # ── SQL generation prompt ───────────────────────────────────────────
+    systemmsg = """
+    # database_search_guidelines
+      - Keep SQL queries focused only on the provided information.
+      - Use wildcard character (%) to search more effectively.
+      - Do not create any table in the database.
+      - Text information in the database is usually stored in lower case.
+        If your search returns empty, try using lower case to search.
+      - Overly strict conditions usually yield empty results.
+      - Use ILIKE for case-insensitive text matching.
+      - Only output the SQL query — do not wrap it in backticks or add comments.
+
+    # situation
+      You are a wine store database assistant. You will be given a user's
+      natural language search query and the database table schema.
+
+    # objective
+      Generate a single SQL query to find wines matching the user's request.
+
+    # your responsibility includes
+      Fulfill the objective.
+
+    # you should respond with ONLY the SQL query string, ending with ';'
+    """
+
+    table_schema = """
+    CREATE TABLE wine (
+      wine_id uuid primary key default gen_random_uuid (),
+      wine_name varchar(128) not null,
+      winery varchar(128) not null,
+      vintage integer not null,
+      region varchar(128) not null,
+      country varchar(128) not null,
+      wine_type varchar(128) not null,
+      grape varchar(128) not null,
+      serving_temperature varchar(128) not null,
+      intensity integer,
+      sweetness integer,
+      tannin integer,
+      acidity integer,
+      fizziness integer,
+      tasting_notes text,
+      image_url jsonb,
+      manufacturer_sku text,
+      note text,
+      other_attributes jsonb,
+      created_time timestamptz default current_timestamp,
+      updated_time timestamptz default current_timestamp,
+      description text
+    );
+
+    CREATE TABLE retailer (
+      retailer_id uuid primary key default gen_random_uuid (),
+      retailer_name varchar(128) not null,
+      retailer_username varchar(128) not null,
+      retailer_password varchar(128) not null,
+      retailer_address text not null,
+      country varchar(128) not null,
+      contact_person varchar(128) not null,
+      telephone varchar(128) not null,
+      email varchar(128) not null,
+      note text,
+      other_attributes jsonb,
+      created_time timestamptz default current_timestamp,
+      updated_time timestamptz default current_timestamp,
+      description text
+    );
+
+    CREATE TABLE retailer_wine (
+      retailer_id uuid references retailer(retailer_id),
+      wine_id uuid references wine(wine_id),
+      constraint retailer_wine_id primary key (retailer_id, wine_id),
+      price NUMERIC(10, 2),
+      currency varchar(3) not null,
+      created_time timestamptz default current_timestamp,
+      updated_time timestamptz default current_timestamp
+    );
+    """
+
+    context = "<internal_context_for_assistant>\n<database_table_schema>\n$table_schema\n</database_table_schema>\n</internal_context_for_assistant>\n\n"
+    input = context * "User query: $search_query\n\nGenerate the SQL query:"
+
+    # ── Call LLM for SQL generation ────────────────────────────────────
+    max_attempts = 5
+    generated_sql = nothing
+
+    for attempt in 1:max_attempts
+        msg = Dict(
+            "messages" => [
+                Dict(
+                    "role" => "system",
+                    "content" => [Dict("type" => "text", "text" => systemmsg)],
+                ),
+                Dict(
+                    "role" => "user",
+                    "content" => [Dict("type" => "text", "text" => input)],
+                ),
+            ],
+            "temperature" => 0.7,
+        )
+
+        llm_response = llmCall(msg)
+
+        # Clean the response — extract SQL from potential markdown/code blocks
+        sql_text = _clean_sql_response(llm_response)
+
+        # Validate it looks like SQL
+        if _is_valid_sql(sql_text)
+            generated_sql = sql_text
+            agentEventSink("searchWine: generated SQL (attempt $attempt)\n$sql_text")
+            break
+        else
+            agentEventSink("searchWine: invalid SQL attempt $attempt: $sql_text")
+        end
+    end
+
+    if generated_sql === nothing
+        return agentToolResult(
+            [textContent("Failed to generate a valid SQL query for your search. Please try rephrasing.")],
+            Dict{Any,Any}("error" => "sql_generation_failed"), nothing, false
+        )
+    end
+
+    # ── Execute SQL ────────────────────────────────────────────────────
+    try
+        conn = LibPQ.Connection(DB_CONFIG)
+
+        # Ensure LIMIT to prevent large result sets
+        sanitized_sql = _ensure_limit(generated_sql)
+        agentEventSink("searchWine: executing\n$sanitized_sql")
+
+        result = LibPQ.execute(conn, sanitized_sql)
+        close(conn)
+
+        if !LibPQ.hasdata(result)
+            return agentToolResult(
+                [textContent("No wines found matching your search. Try loosening your criteria.")],
+                Dict{Any,Any}("count" => 0), nothing, false
+            )
+        end
+
+        df = DataFrame(result)
+        num_rows, num_cols = size(df)
+
+        if num_cols > 30
+            return agentToolResult(
+                [textContent("The result has more than 30 columns. Please be more specific in your search.")],
+                Dict{Any,Any}("error" => "too_many_columns"), nothing, false
+            )
+        end
+
+        # Randomly sample up to 2 rows for display if more than 2 results
+        display_df = df
+        if num_rows > 2
+            idx = sample(1:num_rows, min(2, num_rows), replace=false)
+            display_df = df[idx, :]
+        end
+
+        # Convert to vector of dicts
+        result_vec = GeneralUtils.dfToVectorDict(display_df)
+
+        # Fetch bottle images if available
+        for d in result_vec
+            image_url_json_str = get(d, "image_url", nothing)
+            if image_url_json_str !== nothing && !isempty(string(image_url_json_str))
+                try
+                    image_url_json_obj = JSON.parse(string(image_url_json_str))
+                    base_url = "http://192.168.88.106:8080/"
+                    if haskey(image_url_json_obj, "bottle")
+                        url = base_url * string(image_url_json_obj["bottle"])
+                        image_data = HTTP.get(url)
+                        image_base64_string = base64encode(image_data.body)
+                        d["image"] = image_base64_string
+                    end
+                catch
+                    # Skip image fetch on error
+                end
+            end
+        end
+
+        # Format results as readable text
+        result_str = _format_wine_results(display_df)
+
+        return agentToolResult(
+            [textContent(result_str)],
+            Dict{Any,Any}(
+                "count" => num_rows,
+                "displayed" => size(display_df, 1),
+            ),
+            nothing, false
+        )
+
+    catch e
+        errMsg = sprint(showerror, e)
+        return agentToolResult(
+            [textContent("Database error: $errMsg")],
+            Dict{Any,Any}("error" => errMsg), nothing, false
+        )
+    end
+end
+
+"""
+Extract a SQL query string from the LLM response, handling potential
+markdown code blocks, extra text, or JSON wrapping.
+"""
+function _clean_sql_response(response)::String
+    text = string(response)
+
+    # Try to extract from code block
+    if occursin("```", text)
+        extracted = GeneralUtils.extract_triple_backtick_text(text)
+        if !isempty(extracted)
+            text = extracted[1]
+            # Remove "sql\n" prefix if present
+            if startswith(text, "sql\n") || startswith(text, "SQL\n")
+                text = text[5:end]
+            end
+        end
+    end
+
+    # Remove JSON wrapping if present
+    text = strip(text)
+    if startswith(text, "{") && occursin("action_input", text)
+        # Parse as JSON and extract action_input
+        try
+            parsed = JSON.parse(text)
+            if parsed isa Dict
+                text = get(parsed, "action_input", text)
+            end
+        catch
+            # Keep original
+        end
+    end
+
+    # Extract SQL keywords to find the actual query
+    lines = split(strip(text), '\n')
+    sql_lines = String[]
+    for line in lines
+        stripped = strip(line)
+        if occursin(r"(?i)(SELECT|FROM|WHERE|JOIN|ORDER|LIMIT|INSERT|UPDATE|DELETE|CREATE|ALTER|DROP|WITH)", stripped)
+            # Take everything from this line to the end
+            push!(sql_lines, line)
+        elseif !isempty(sql_lines)
+            # Continue collecting if we already found SQL
+            push!(sql_lines, line)
+        end
+    end
+
+    result = join(sql_lines, "\n")
+
+    # Ensure it ends with semicolon
+    result = strip(result)
+    if !endswith(result, ";")
+        result *= ";"
+    end
+
+    return result
+end
+
+"""
+Check if a string looks like a valid SQL query.
+"""
+function _is_valid_sql(sql::String)::Bool
+    sql = strip(sql)
+    # Must start with a SQL keyword
+    has_sql_keyword = occursin(r"(?i)(SELECT|INSERT|UPDATE|DELETE|CREATE|ALTER|DROP|WITH)\s", sql) ||
+                      occursin(r"(?i)(SELECT|INSERT|UPDATE|DELETE|CREATE|ALTER|DROP|WITH)\s*;", sql)
+    # Must end with semicolon
+    has_semicolon = endswith(sql, ";")
+    # Must not be too short (reject single words)
+    reasonable_length = length(sql) > 10
+    return has_sql_keyword && has_semicolon && reasonable_length
+end
+
+"""
+Ensure the SQL query has a LIMIT clause to prevent loading excessive data.
+"""
+function _ensure_limit(sql::String)::String
+    sql = strip(sql)
+    if !occursin(r"(?i)LIMIT", sql)
+        # Remove existing semicolon, add LIMIT, re-add semicolon
+        if endswith(sql, ";")
+            sql = sql[1:end-1]
+        end
+        sql *= " ORDER BY RANDOM() LIMIT 2;"
+    end
+    return sql
+end
+
+"""
+Format wine database results as human-readable text.
+"""
+function _format_wine_results(df::DataFrame)::String
+    lines = String[]
+    num_rows = size(df, 1)
+
+    for i in 1:num_rows
+        row = df[i, :]
+        push!(lines, "$(i). $(get(row, :wine_name, "Unknown")) $(get(row, :vintage, ""))")
+
+        winery = get(row, :winery, "Unknown")
+        region = get(row, :region, "Unknown")
+        country = get(row, :country, "Unknown")
+        push!(lines, "   Winery: $winery")
+        push!(lines, "   Region: $region, $country")
+
+        grape = get(row, :grape, "Unknown")
+        wtype = get(row, :wine_type, "Unknown")
+        push!(lines, "   Grape: $grape")
+        push!(lines, "   Type: $wtype")
+
+        sweetness = get(row, :sweetness, "N/A")
+        intensity = get(row, :intensity, "N/A")
+        tannin_val = get(row, :tannin, "N/A")
+        acidity = get(row, :acidity, "N/A")
+        push!(lines, "   Profile: Sweetness: $sweetness, Intensity: $intensity, Tannin: $tannin_val, Acidity: $acidity")
+
+        tasting = get(row, :tasting_notes, nothing)
+        if tasting !== nothing && !isempty(string(tasting))
+            tn = string(tasting)
+            limit = min(200, length(tn))
+            push!(lines, "   Notes: $(tn[1:limit])$(length(tn) > limit ? "..." : "")")
+        end
+
+        price = get(row, :price, "N/A")
+        currency = get(row, :currency, "")
+        retailer = get(row, :retailer_name, "N/A")
+        push!(lines, "   Price: $price $currency at $retailer")
+        push!(lines, "")
+    end
+
+    return join(lines, "\n")
+end
+
+"""
+Define and return the searchWine agentTool.
+"""
+function searchWineTool()::agentTool
+    return agentTool(
+        name = "searchWine",
+        label = "Search Wine Database",
+        description = "Search the wine database for wines matching a free-text query. Uses the LLM to generate SQL and execute it against the database. Returns wine details including name, winery, vintage, tasting notes, and price.",
+        inputSchema = Dict{String,Any}(
+            "type" => "object",
+            "properties" => Dict(
+                "searchQuery" => Dict(
+                    "type" => "string",
+                    "description" => "Free-text description of the wine you're looking for, e.g., 'a light-bodied red wine from France under 50 dollars'",
+                ),
+            ),
+            "required" => ["searchQuery"],
+        ),
+        execute = searchWineExecute,
+        prepareArguments = nothing,
+        validateRequiredArgs = nothing,
+        parallelToolExecute = false,
+    )
+end

src/tools/writeTool.jl

@@ -1,3 +1,6 @@
+using .type
+using JSON
+
 """
 Tool that writes new Julia tool module files to disk.
 
@@ -5,15 +8,17 @@ The agent can use this tool when it encounters a task that no existing tool
 can handle. Provide the tool's name, label, description, inputSchema, and
 execute logic as Julia code. The tool is written to `src/tools/<name>.jl`.
 
-After calling this tool, restart the agent so `loadTools("src/tools")` picks
-up the new file. The new tool is immediately available.
+After calling this tool, add the new file to `YiemAgent.jl` with an `include()`
+statement (after `include("toolRegistry.jl")`), then restart the agent.
+The new tool must be registered in `register_all_tools()` in `toolRegistry.jl`.
 
 # Example
 
 1. Agent calls writeTool with a spec for a "searchWine" tool
 2. writeTool generates src/tools/searchWine.jl
-3. Restart agent — loadTools() picks up the new file
-4. Agent calls searchWine with args
+3. Developer adds `include("tools/searchWine.jl")` to YiemAgent.jl
+4. Developer adds `registerTool(store, searchWineTool())` to register_all_tools()
+5. Restart agent — new tool is available
 
 # How It Works
 
@@ -22,7 +27,7 @@ tool logic as `executeCode`, and writeTool wraps it in Julia boilerplate:
   - Converts `inputSchema` Dict into Julia `Dict{String,Any}(...)` string
   - Indents `executeCode` with 4 spaces
   - Wraps it inside `function executeTool(...)::agentToolResult ... end`
-  - Appends `getTool()` returning an `agentTool` struct
+  - Appends `writeToolTool()` returning an `agentTool` struct
   - Writes the combined string to `src/tools/<name>.jl`
 
 # Important Notes
@@ -103,7 +108,7 @@ end
 """
 Define and return the writeTool agentTool.
 """
-function getTool()::agentTool
+function writeToolTool()::agentTool
     return agentTool(
         name = "writeTool",
         label = "Create Tool",
@@ -125,7 +130,7 @@ function getTool()::agentTool
             ),
             "required" => ["name", "label", "description", "inputSchema", "executeCode"]
         ),
-        execute = (toolCallId::String, args::Dict{String,Any}, signal::Union{Nothing,abortSignal}, onPartialResult::Function) -> begin
+        execute = (toolCallId::String, args::Dict{String,Any}, signal::Union{Nothing,abortSignal}, onPartialResult, llmCall=nothing) -> begin
             tool_name = get(args, "name", "")::String
             tool_label = get(args, "label", tool_name)::String
             tool_description = get(args, "description", "")::String
@@ -248,13 +253,13 @@ function getTool()::agentTool
 
             tool_code = join(parts)
 
-            # Write the file — tool is loaded on next agent restart via loadTools()
+            # Write the file — tool must be included in YiemAgent.jl and registered in register_all_tools()
             write(filepath, tool_code)
 
             onPartialResult(Dict("status" => "Done"))
 
             return agentToolResult(
-                [textContent("Tool '$(tool_name)' written to $filepath. Restart the agent so loadTools() picks it up, then call listTools to verify.")],
+                [textContent("Tool '$(tool_name)' written to $filepath. Add include(\"tools/$(tool_name).jl\") to YiemAgent.jl and registerTool(store, $(tool_name)Tool()) to register_all_tools(), then restart the agent.")],
                 Dict{Any,Any}(
                     "file" => filepath,
                     "name" => tool_name,

src/type.jl

@@ -4,17 +4,17 @@
            messageContent, agentMessage, agent,
            # Model types
            modelCost, llmModel, llmUsage,
-           # Message content types
-           textContent, imageContent,
-           # Message types
-           userMessage, assistantMessage, toolResultMessage,
+            # Message content types
+            textContent, imageContent, reasoningContent,
+            # Message types
+            userMessage, assistantMessageToolCall, assistantMessage, toolResultMessage,
             # Tool types
              agentTool, validateRequiredArgs,
            # Context types
            agentContext, agentState, agentToolCall, prepareNextTurnContext,
            # Loop & execution types
-           agentLoopConfig, abortSignal, agentToolResult,
-           assistantMsgCtx, afterCtx,
+           agentLoopConfig, abortSignal, agentToolResult,beforeToolCallContext, 
+           beforeToolCallResult, afterToolCallContext,
            # Event types
            toolExecStartEvent, toolExecUpdateEvent, toolExecEndEvent,
            # Agent
@@ -23,7 +23,7 @@
            preparedToolCall, immediateOutcome, executedOutcome, finalizedOutcome,
            agentToolCallBatch,
            # Functions (defined elsewhere)
-           run_agent, take_response, follow_up, stop_agent
+           runAgent, takeResponse, followUp, stopAgent
 
 
 using Dates, UUIDs, DataStructures, JSON, NATS, Base.Threads
@@ -31,6 +31,13 @@ using GeneralUtils
 
 const Timestamp = DateTime
 
+struct agentToolCall               # A tool invocation from the LLM
+  type::String                              # Always "function"
+  id::String                                # Unique tool call identifier
+  name::String                              # Tool name
+  arguments::Dict{String, Any}              # Parsed tool arguments
+end
+
 # ------------------------------------------------------------------------------------------------ #
 #                                          LLM model info                                          #
 # ------------------------------------------------------------------------------------------------ #
@@ -75,6 +82,10 @@ struct imageContent <: messageContent         # Image message content
     mimeType::String                          # MIME type (e.g., "image/png")
 end
 
+struct reasoningContent <: messageContent    # LLM reasoning/thinking content
+    text::String                              # The reasoning text
+end
+
 
 # ------------------------------------------------------------------------------------------------ #
 #                                           Message types                                          #
@@ -108,6 +119,52 @@ function userMessage(; role="user", content=Vector{messageContent}(), timestamp=
     return userMessage(role, content, timestamp)
 end
 
+struct assistantMessageToolCall <: agentMessage   # Assistant message containing tool calls
+    role::String                            # Always "assistant"
+    toolCalls::Vector{agentToolCall}        # Tool calls to execute
+    content::Vector{messageContent}         # Reasoning/thinking content blocks
+    api::String                             # API name used (e.g., "openai")
+    provider::String                        # Provider name (e.g., "anthropic")
+    model::String                           # Model identifier
+    usage::llmUsage                         # Token usage for this message
+    stopReason::String                      # Why generation stopped (e.g., "tool_calls")
+    errorMessage::Union{String, Nothing}    # Error if generation failed
+    timestamp::Timestamp                    # When the message was received
+end
+
+"""
+Create a new assistant message containing tool calls.
+
+# Arguments
+- `role::String`: Always "assistant"
+- `toolCalls::Vector{agentToolCall}`: Tool calls to execute
+- `content::Vector{messageContent}`: Reasoning/thinking content blocks
+- `api::String`: API name used
+- `provider::String`: Provider name
+- `model::String`: Model identifier
+- `usage::llmUsage`: Token usage
+- `stopReason::String`: Why generation stopped
+- `errorMessage::Union{String, Nothing}`: Error if generation failed
+- `timestamp::Timestamp`: When the message was received
+
+# Returns
+- A new `assistantMessageToolCall` instance
+
+# Examples
+```julia
+julia> tc = agentToolCall("function", "call_1", "getWeather", Dict("city" => "Tokyo"))
+julia> msg = assistantMessageToolCall(toolCalls=[tc], stopReason="tool_calls")
+assistantMessageToolCall("assistant", [agentToolCall(...)], messageContent[], "", "", "", llmUsage(0, 0), "tool_calls", nothing, DateTime(...))
+```
+"""
+function assistantMessageToolCall(; role="assistant", toolCalls=agentToolCall[],
+    content=Vector{messageContent}(), api="", provider="", model=nothing, usage=llmUsage(0, 0),
+    stopReason="tool_calls", errorMessage=nothing, timestamp=now())
+    model_str = model isa AbstractString ? String(model) : ""
+    return assistantMessageToolCall(role, toolCalls, content, api, provider, model_str,
+                                     usage, stopReason, errorMessage, timestamp)
+end
+
 struct assistantMessage <: agentMessage     # Message from the AI assistant
     role::String                            # Always "assistant"
     content::Vector{messageContent}         # Text and/or image content
@@ -144,9 +201,10 @@ assistantMessage("assistant", [textContent("Hello!")], "", "", "gpt-4", ..., "en
 ```
 """
 function assistantMessage(; role="assistant", content=Vector{messageContent}(),
-    api="", provider="", model="", usage=llmUsage(0, 0), stopReason="end_turn",
+    api="", provider="", model=nothing, usage=llmUsage(0, 0), stopReason="end_turn",
     errorMessage=nothing, timestamp=now())
-    return assistantMessage(role, content, api, provider, model, usage, stopReason, errorMessage, timestamp)
+    model_str = model isa AbstractString ? String(model) : ""
+    return assistantMessage(role, content, api, provider, model_str, usage, stopReason, errorMessage, timestamp)
 end
 
 struct toolResultMessage <: agentMessage    # Result returned from a tool execution
@@ -263,7 +321,7 @@ struct agentTool                              # A tool available to the agent
     label::String                             # Human-readable tool name
     description::String                       # What the tool does
     inputSchema::Any                          # Tool parameters schema (JSON schema, MCP inputSchema format)
-    execute::Function                         # Tool execution function
+    execute                         # Tool execution function
     prepareArguments::Union{Function, Nothing}  # Optional argument preparation callback
     validateRequiredArgs::Union{Function, Nothing}  # Optional validation hook for required args
     parallelToolExecute::Bool  # Override: run tool calls sequentially or in parallel
@@ -273,7 +331,7 @@ end
 Keyword constructor for agentTool — allows `agentTool(name=..., label=..., ...)`.
 """
 function agentTool(; name::String, label::String, description::String, inputSchema::Any,
-                     execute::Function, prepareArguments::Union{Function, Nothing}=nothing,
+                     execute, prepareArguments::Union{Function, Nothing}=nothing,
                      validateRequiredArgs::Union{Function, Nothing}=nothing,
                      parallelToolExecute::Bool=false)
     return agentTool(name, label, description, inputSchema, execute,
@@ -291,7 +349,7 @@ Snapshot of the agent's conversation context.
 # Arguments
 - `systemPrompt::String`: System prompt for the agent
 - `messages::Vector{agentMessage}`: Conversation messages
-- `tools::Union{Dict{String, agentTool}, Nothing}`: Available tools keyed by name for O(1) lookup
+- `tools::Union{OrderedDict{String, agentTool}, Nothing}`: Available tools keyed by name for O(1) lookup
 
 # Returns
 - A new `agentContext` instance
@@ -299,7 +357,8 @@ Snapshot of the agent's conversation context.
 struct agentContext                           # Snapshot of the agent's conversation context
     systemPrompt::String                      # System prompt for the agent
     messages::Vector{agentMessage}            # Conversation messages
-    tools::Union{Dict{String, agentTool}, Nothing}  # Available tools keyed by name
+    tools::Union{OrderedDict{String, agentTool}, Nothing}  # Available tools keyed by name
+    llmCall::Union{Any, Nothing}              # LLM call function (for tools that need it)
 end
 
 
@@ -309,14 +368,13 @@ end
 
 mutable struct agentState                     # Mutable runtime state of an agent
     systemPrompt::String                      # System prompt for the agent
-    model::llmModel                           # LLM model to use
+    model::Union{llmModel, Nothing}                           # LLM model to use
     tools::OrderedDict{String, agentTool}     # Available tools keyed by name, insertion-ordered
 
     # messages history includes userMessage, assistantMessage, toolResultMessage. NO system prompt
     messages::Vector{agentMessage}            
     
     pendingToolCalls::Vector{String}          # Tool call IDs waiting for results
-    activeRun::Bool                             # is agent processing user message?
     errorMessage::Union{String, Nothing}      # Last error message
 end
 
@@ -341,29 +399,20 @@ julia> state = agentState(systemPrompt="You are a helpful assistant")
 agentState("You are a helpful assistant", OrderedDict{String, agentTool}(), agentMessage[], String[], nothing)
 """
 function agentState(
-    systemPrompt::String="",
-    model::llmModel=llmModel{String}("", "", "unknown", "unknown", "", false, String[], 
-                                    modelCost(0.0, 0.0, 0.0, 0.0), 0, 0),
-    tools::OrderedDict{String, agentTool}=OrderedDict{String, agentTool}(),
-    messages::Vector{agentMessage}=agentMessage[],
+  systemPrompt::String="",
+  model=llmModel("model_1", "unknown", "unknown", "", false, String[], 
+                  modelCost(0.0, 0.0, 0.0, 0.0), 0, 0),
+  tools::OrderedDict{String, agentTool}=OrderedDict{String, agentTool}(),
+  messages::Vector{agentMessage}=agentMessage[],
 )
-    agentState(
-      systemPrompt,
-      model,
-      deepcopy(tools),
-      deepcopy(messages),
-      Vector{String}(),
-      false,
-      nothing,
-    )
-end
-
-
-struct agentToolCall               # A tool invocation from the LLM
-    type::String                              # Always "function"
-    id::String                                # Unique tool call identifier
-    name::String                              # Tool name
-    arguments::Dict{String, Any}              # Parsed tool arguments
+  agentState(
+    systemPrompt,
+    model,
+    deepcopy(tools),
+    deepcopy(messages),
+    Vector{String}(),
+    nothing,
+  )
 end
 
 
@@ -395,16 +444,15 @@ end
 Configuration for the agent tool execution loop.
 
 # Arguments
-- `tools::OrderedDict{String, agentTool}`: Available tools keyed by name
 - `beforeToolCall::Union{Function, Nothing}`: Callback before tool execution
 - `afterToolCall::Union{Function, Nothing}`: Callback after tool execution
 - `toolExecution::String`: Execution mode — "sequential" or "parallel"
 """
 struct agentLoopConfig
-    tools::OrderedDict{String, agentTool}
     beforeToolCall::Union{Function, Nothing}
     afterToolCall::Union{Function, Nothing}
     toolExecution::String
+    llmCall::Union{Any, Nothing}               # LLM call function (for tools like searchWine)
 end
 
 """
@@ -437,31 +485,36 @@ end
 Context passed to the `beforeToolCall` hook.
 
 # Arguments
-- `message::assistantMessage`: The assistant message containing the tool call
+- `message::assistantMessageToolCall`: The assistant message containing the tool call
 - `toolCall::agentToolCall`: The tool call being prepared
 - `args::Dict{String,Any}`: Validated tool arguments
 - `context::agentContext`: Current conversation context
 """
-struct assistantMsgCtx
-    message::assistantMessage
+struct beforeToolCallContext
+    message::assistantMessageToolCall
     toolCall::agentToolCall
     args::Dict{String,Any}
     context::agentContext
 end
 
+struct beforeToolCallResult
+  block::Bool
+  reason::String
+end
+
 """
 Context passed to the `afterToolCall` hook.
 
 # Arguments
-- `message::assistantMessage`: The assistant message containing the tool call
+- `message::assistantMessageToolCall`: The assistant message containing the tool call
 - `toolCall::agentToolCall`: The tool call that was executed
 - `args::Dict{String,Any}`: Tool arguments
 - `result::agentToolResult`: The raw tool result
 - `isError::Bool`: Whether execution resulted in an error
 - `context::agentContext`: Current conversation context
 """
-struct afterCtx
-    message::assistantMessage
+struct afterToolCallContext
+    message::assistantMessageToolCall
     toolCall::agentToolCall
     args::Dict{String,Any}
     result::agentToolResult
@@ -521,138 +574,6 @@ end
 
 abstract type agent end 
 
-"""
-docstring
-"""
-mutable struct yiemAgent <: agent             # High-level agent wrapper
-  _state::agentState                          # Current state (prompt, model, messages, tools, etc.)
-  
-  # user sends prompt message to agent. if agent is idle, it process user message right away. 
-  # if agent is running, it process user message after  the current tool call finished.
-  inputChannel::Channel                        
-                                              
-  # Buffers messages the user sends while the agent is busy. Processed after all inputChannel 
-  # messages are handled and the agent is idle (not using a tool call).
-  followUpChannel::Channel                    
-
-  # agent sends response message to user after processing all user messages in inputChannel 
-  # and all followUp messages.
-  outputChannel::Channel                     
-                                              
-  _agent_loop::Union{Task, Nothing}                 # agent loop running in the background
-
-  # Preprocess/transform messages and context (modify, filter, prune, inject context from memory,  
-  # reorder, ...) for a single LLM call in _process_message()'s loop.
-  # returns new Vector{agentMessage}
-  prepareContext ::Union{Function, Nothing}   
-
-  # Convert prepareContext()'s new Vector{agentMessage} to LLM message format
-  formatMsgForLLM::Function    
-
-  # Actually invoke the LLM to get a completion response. The LLM response comes back as an 
-  # assistantMessage whose content is an array of content blocks. 
-  # Each block has a type — "text", "thinking", or "toolCall". 
-  # The code filters for type === "toolCall" blocks, then passes them to executeToolCalls().
-  llmCall::Function                           
-                                              
-  # Callback invoked before executing a tool call (ask for user permission/confirmation/abort, etc..)
-  beforeToolCall::Union{Function, Nothing}    
-
-  executeToolCalls::Function                  # execute tool calls ()
-  
-  # Callback invoked after executing a tool call to sanitize tools output so the output is ready 
-  # to be converted into toolResults message
-  afterToolCall::Union{Function, Nothing}     
-  # prepareNextTurn::Union{Function, Nothing}   # Callback to prepare the next conversation turn
-  # prepareNextTurnWithContext::Union{Function, Nothing}  # Same but receives context
-  sessionId::Union{String, Nothing}           # Optional session identifier
-  maxRetryDelayMs::Union{Int64, Nothing}      # Maximum delay between retries (ms)
-  parallelToolExecute::Bool                   # Default: false
-  agentEventSink::Function                    # agent emits its status via this function
-end
-
-"""
-Create a new yiemAgent instance with a background loop task.
-
-Spawns a background `@spawn` task that runs the agent loop, listening
-on `inputChannel` and `followUpChannel` channels concurrently.
-
-# Keyword Arguments
-- `systemPrompt::String`: System prompt for the agent
-- `model`: LLM model to use
-- `tools::OrderedDict{String, agentTool}`: Available tools keyed by name (default: empty)
-- `messages::Vector{agentMessage}`: Initial conversation messages (default: empty)
-- `formatMsgForLLM::Function`: Convert agent messages to LLM message format (default: `defaultformatMsgForLLM`)
-- `llmCall::Function`: Function to invoke the LLM (required)
-- `prepareContext::Union{Function, Nothing}`: Preprocess/transform messages before sending to LLM (default: `nothing`)
-- `beforeToolCall::Union{Function, Nothing}`: Callback invoked before executing a tool call (default: `nothing`)
-- `afterToolCall::Union{Function, Nothing}`: Callback invoked after executing a tool call (default: `nothing`)
-- `prepareNextTurn::Union{Function, Nothing}`: Callback to prepare the next conversation turn (default: `nothing`)
-- `prepareNextTurnWithContext::Union{Function, Nothing}`: Same but receives context (default: `nothing`)
-- `sessionId::Union{String, Nothing}`: Optional session identifier (default: `nothing`)
-- `maxRetryDelayMs::Union{Int64, Nothing}`: Maximum delay between retries in milliseconds (default: `nothing`)
-- `parallelToolExecute::Bool`: Run tool calls in parallel (default: `false`)
-- `agentEventSink::Function`: Callback to receive agent events
-
-# Returns
-- A new `yiemAgent` instance with an active background task
-
-# Examples
-```julia
-julia> tools = loadTools("src/tools")
-julia> agent = yiemAgent(systemPrompt="You are a helpful assistant", model=my_model, tools=tools, llmCall=...)
-yiemAgent(agentState(...), Channel(...), Channel(...), Channel(...), ..., ...)
-"""
-function yiemAgent(
-  ; systemPrompt::String="You are helpful assistant.",
-    model=nothing,
-    tools::OrderedDict{String, agentTool}=OrderedDict{String, agentTool}(),
-    messages::Vector{agentMessage}=agentMessage[],
-    prepareContext::Union{Function, Nothing}=nothing,
-    formatMsgForLLM::Function=defaultformatMsgForLLM,
-    llmCall::Function,
-    beforeToolCall::Union{Function, Nothing}=nothing,
-    afterToolCall::Union{Function, Nothing}=nothing,
-    # prepareNextTurn::Union{Function, Nothing}=nothing,
-    # prepareNextTurnWithContext::Union{Function, Nothing}=nothing,
-    sessionId::Union{String, Nothing}=nothing,
-    maxRetryDelayMs::Union{Int64, Nothing}=nothing,
-    parallelToolExecute::Bool=false,
-    agentEventSink::Function,
-  )
-  # Create channels: input (user -> agent), followUp (async queue), output (agent -> user)
-  inputChannel    = Channel(16)
-  followUp    = Channel(32)
-  outputChannel   = Channel(16)
-
-  # Create struct with a placeholder task, then spawn and replace it
-  agent = yiemAgent(
-    agentState(systemPrompt, model, tools, messages),
-    inputChannel,
-    followUp,
-    outputChannel,
-    nothing,  # placeholder — replaced below
-    prepareContext,
-    formatMsgForLLM,
-    llmCall,
-    beforeToolCall,
-    afterToolCall,
-    # prepareNextTurn,
-    # prepareNextTurnWithContext,
-    sessionId,
-    maxRetryDelayMs,
-    parallelToolExecute,
-    agentEventSink,
-  )
-
-  # Spawn the background loop and attach it
-  agent._agent_loop = @spawn _agent_loop(agent)
-
-  return agent
-end
-
-
-
 """
     preparedToolCall(tool, toolCall, args)
 

src/utils.jl

@@ -1,9 +1,11 @@
 module utils
 
-export clearhistory, availableWineToText, prepareContext, formatMsgForLLM, validateRequiredArgs, validateToolArguments, _userMessageToOpenAI, 
-        _assistantMessageToOpenAI, _toolResultMessageToOpenAI, _messageContentToBlocks
+export clearhistory, availableWineToText, prepareContext, formatMsgForLLM, validateRequiredArgs, 
+      validateToolArguments, _userMessageToOpenAI, 
+      _assistantMessageToOpenAI, _toolResultMessageToOpenAI, _messageContentToBlocks, _toolsToOpenAI,
+      beforeToolCall, afterToolCall, agentEventSink
 
-using UUIDs, Dates, DataStructures, HTTP, JSON
+using UUIDs, Dates, DataStructures, HTTP, JSON, NATS
 using GeneralUtils
 using ..type
 
@@ -73,7 +75,6 @@ function availableWineToText(vecd::Vector)::String
 end
 
 
-
 """
     prepareContext(state::agentState) -> agentContext
 
@@ -108,7 +109,7 @@ prepareContext(state).messages == deepcopy(state.messages)
 # end
 ```
 """
-function prepareContext(state::agentState)::agentContext
+function prepareContext(state::agentState, agentEventSink, llmCall=nothing)::agentContext
   
   #TODO filter tools from state.tools based on user intend in user message and tool description
   filteredTools = state.tools
@@ -119,7 +120,7 @@ function prepareContext(state::agentState)::agentContext
   #TODO add system prompt, adjust/modify and inject additional context into messages
   preparedMessages = deepcopy(state.messages) # messages that will be send to LLM
 
-  agentCtx = agentContext(preparedSystemPrompt, preparedMessages, filteredTools)
+  agentCtx = agentContext(preparedSystemPrompt, preparedMessages, filteredTools, llmCall)
 
   return agentCtx
 end
@@ -155,7 +156,7 @@ formatMsgForLLm(ctx) == Dict("messages" => [
 ])
 ```
 """
-function formatMsgForLLM(ctx::agentContext)::Dict{String, Any}
+function formatMsgForLLM(ctx::agentContext, agentEventSink)::Dict{String, Any}
 
   """ openai message format example
   msg = Dict(
@@ -183,19 +184,31 @@ function formatMsgForLLM(ctx::agentContext)::Dict{String, Any}
           Dict("type" => "text", "text" => "let me check."),
         ]
       ),
+    ],
+    "tools"=> [
       Dict(
-        "role" => "toolResult",
-        "content" => [
-          Dict("type" => "text", "text" => "name: Chateau Montelena ..."),
-        ]
-      ),
+        "type" => "function",
+        "function" => Dict(
+          "name" => "getWeather",
+          "description" => "Get current weather",
+          "parameters" => Dict(
+            "type" => "object",
+            "properties" => Dict(
+              "city" => Dict("type" => "string")
+            ),
+            "required" => ["city"]
+          )
+        )
+      )
     ],
     "temperature" => 0.7
   )
   """
 
+  openaiReadyMsg = Dict{String, Any}()
+  # openaiReadyMsg["model"] = "gemma-4-E4B-it-UD-Q4_K_XL"
   messages = Vector{Dict{String, Any}}()
-
+  agentEventSink("formatMsgForLLM 1")
   # System prompt as system message
   if !isempty(ctx.systemPrompt)
     push!(messages, Dict(
@@ -203,19 +216,113 @@ function formatMsgForLLM(ctx::agentContext)::Dict{String, Any}
       "content" => [Dict("type" => "text", "text" => ctx.systemPrompt)]
     ))
   end
-
+  agentEventSink("formatMsgForLLM 2")
   # Conversation messages
   for msg in ctx.messages
     if msg isa userMessage
       push!(messages, _userMessageToOpenAI(msg))
+    elseif msg isa assistantMessageToolCall
+      push!(messages, _assistantMessageToolCallToOpenAI(msg))
     elseif msg isa assistantMessage
       push!(messages, _assistantMessageToOpenAI(msg))
     elseif msg isa toolResultMessage
       push!(messages, _toolResultMessageToOpenAI(msg))
     end
   end
+  agentEventSink("formatMsgForLLM 3")
+  # Convert ctx.tools into OpenAI tools format
+  tools_array = _toolsToOpenAI(ctx.tools, agentEventSink)
+  agentEventSink("formatMsgForLLM 4")
+  openaiReadyMsg["messages"] = messages
+  openaiReadyMsg["temperature"] = 0.7
 
-  return Dict("messages" => messages)
+  if !isempty(tools_array)
+    openaiReadyMsg["tools"] = tools_array
+  end
+
+  return openaiReadyMsg
+end
+
+"""
+    beforeToolCall(context::beforeToolCallContext, signal::abortSignal) -> beforeToolCallResult
+
+Callback invoked before executing a tool call. Use this hook to inspect
+the tool call and decide whether to allow, block, or modify it.
+
+Common use cases:
+  - Request user approval via UI before running destructive tools.
+  - Validate business rules that cannot be expressed in the JSON schema.
+  - Check final context (e.g. session state, rate limits, permissions).
+
+# Arguments
+- `context::beforeToolCallContext`: Contains the assistant message, tool call,
+  validated arguments, and current conversation context.
+- `signal::abortSignal`: Signal that may be set to abort the operation.
+
+# Returns
+- `beforeToolCallResult(false, "N/A")` to allow the call to proceed.
+- `beforeToolCallResult(true, "Reason")` to block the call with a reason.
+- `nothing` is treated as allow (equivalent to `beforeToolCallResult(false, "N/A")`).
+
+# Example
+```julia
+function beforeToolCall(context::beforeToolCallContext, signal::abortSignal)
+    if context.toolCall.name == "deleteFile"
+        # Block file deletion unless explicitly approved
+        return beforeToolCallResult(true, "User must approve file deletion")
+    end
+    return beforeToolCallResult(false, "N/A")
+end
+```
+"""
+function beforeToolCall(context::beforeToolCallContext, signal::abortSignal
+  )::beforeToolCallResult
+  
+  # final context check
+
+  # seek user approval via UI
+
+  # other check
+  
+  return beforeToolCallResult(false, "N/A")
+end
+
+"""
+    afterToolCall(context::afterToolCallContext, signal::abortSignal) -> Union{agentToolResult, Nothing}
+
+Callback invoked after a tool call finishes executing (before and after errors).
+Use this hook to post-process the tool result before it is fed back to the LLM.
+
+Common use cases:
+  - Mask sensitive data (API keys, tokens) from result content.
+  - Normalize usage tracking data into a consistent format.
+  - Inspect the result and set `terminate: true` based on business logic
+    (e.g. "if deployment failed, stop the agent rather than retrying").
+  - Wrap error results in friendlier messages for the LLM to understand.
+
+# Arguments
+- `context::afterToolCallContext`: Contains the assistant message, tool call,
+  arguments, raw result, error status, and current conversation context.
+- `signal::abortSignal`: Signal that may be set to abort the operation.
+
+# Returns
+- `nothing` to pass the result through unchanged.
+- `agentToolResult(...)` to return a modified result (content, details, usage,
+  terminate flag can all be overridden).
+
+"""
+function afterToolCall(context::afterToolCallContext, signal::abortSignal
+  )::Union{agentToolResult, Nothing}
+
+  # modify context.result if needed and return agentToolResult
+  
+  return nothing
+end
+
+
+#TODO
+function agentEventSink(x)
+  
 end
 
 
@@ -231,6 +338,44 @@ end
 
 
 """
+Convert an assistantMessageToolCall to OpenAI message format.
+
+Produces a message with role="assistant", content=null, and a tool_calls array:
+{
+  "role": "assistant",
+  "content": null,
+  "tool_calls": [
+    {
+      "id": "call_1",
+      "type": "function",
+      "function": {
+        "name": "get_weather",
+        "arguments": "{\"location\": \"San Francisco, CA\"}"
+      }
+    }
+  ]
+}
+"""
+function _assistantMessageToolCallToOpenAI(msg::assistantMessageToolCall)::Dict{String, Any}
+  tool_calls = Dict{String, Any}[]
+  for tc in msg.toolCalls
+    push!(tool_calls, Dict(
+      "id" => tc.id,
+      "type" => tc.type,
+      "function" => Dict(
+        "name" => tc.name,
+        "arguments" => JSON.json(tc.arguments)
+      )
+    ))
+  end
+  return Dict(
+    "role" => "assistant",
+    "content" => nothing,
+    "tool_calls" => tool_calls
+  )
+end
+
+"""
 Convert an assistantMessage to OpenAI message format.
 """
 function _assistantMessageToOpenAI(msg::assistantMessage)::Dict{String, Any}
@@ -279,6 +424,40 @@ function _messageContentToBlocks(contents::Vector{messageContent})::Vector{Dict{
 end
 
 
+"""
+    _toolsToOpenAI(tools::Union{OrderedDict{String, agentTool}, Nothing}) -> Vector{Dict{String, Any}}
+
+Convert an OrderedDict of agentTool definitions into OpenAI function tool format.
+
+Returns an empty vector when `tools` is `nothing` or empty.
+
+# Examples
+```julia
+_toolsToOpenAI(nothing)  # => Dict{String, Any}[]
+_toolsToOpenAI(tools)    # => [Dict("type" => "function", "function" => Dict("name" => "getWeather", ...))]
+```
+"""
+function _toolsToOpenAI(tools::Union{OrderedDict{String, agentTool}, Nothing}, agentEventSink)::Vector{Dict{String, Any}}
+  tools_array = Vector{Dict{String, Any}}()
+  agentEventSink("_toolsToOpenAI 1")
+  agentEventSink(string(typeof(tools)))
+  if tools !== nothing
+    for (_, tool) in tools
+      push!(tools_array, Dict(
+        "type" => "function",
+        "function" => Dict(
+          "name" => tool.name,
+          "description" => tool.description,
+          "parameters" => tool.inputSchema
+        )
+      ))
+    end
+  end
+  agentEventSink("_toolsToOpenAI 2")
+  return tools_array
+end
+
+
 """
     validateRequiredArgs(args::Dict{String,Any}, inputSchema::Dict{String,Any}) -> Union{Nothing,String}
 

src_OLD/OLD_type.jl

@@ -1,375 +0,0 @@
-module type
-  
-export agent, sommelier, companion, virtualcustomer, agentcontext
-
-using Dates, UUIDs, DataStructures, JSON, NATS
-using GeneralUtils
-
-# ---------------------------------------------- 100 --------------------------------------------- #
-
-
-mutable struct agentcontext
-  text2textInstructLLM::Function
-  getTextEmbedding::Function
-  executeSQL::Function
-  similarSQLVectorDB::Function
-  insertSQLVectorDB::Function
-  similarSommelierDecision::Function
-  insertSommelierDecision::Function
-  find_related_tables_for_user_question::Function
-  pg_conn_str::String
-  agentconfig::AbstractDict
-end
-
-abstract type agent end
-
-mutable struct sommelier <: agent
-  name::String  # agent name
-  id::String    # agent id
-  retailername::String
-  retailerid::String
-  tools::Dict   
-  maxHistoryMsg::Integer  # e.g. 21th and earlier messages will get summarized
-  chathistory::Vector{Dict{String, Any}}
-  memory::Dict{String, Any}
-  context::agentcontext 
-  llmFormatName::String
-end
- 
-""" A sommelier agent.
-
-# Arguments
-  - `context::agentcontext`
-    Application context containing shared functions for LLM, SQL, and vector database operations.
-
-# Keyword Arguments
-  - `name::String`
-    Agent's name. Default: `"Assistant"`
-  - `id::String`
-    Agent's ID. Default: generated UUID string.
-  - `retailername::String`
-    Retailer name associated with the sommelier. Default: `"retailer_name"`
-  - `maxHistoryMsg::Integer`
-    Maximum history messages. Default: `20`
-  - `chathistory::Vector{Dict{String, String}}`
-    Chat history. Default: empty vector.
-  - `llmFormatName::String`
-    LLM format name. Default: `"granite3"`
-
-# Return
-  - `sommelier`: An instantiated sommelier agent.
-
-# Example
-```julia
-julia> using YiemAgent
-julia> context = agentcontext(
-           text2textInstructLLM,
-           getTextEmbedding,
-           executeSQL,
-           similarSQLVectorDB,
-           insertSQLVectorDB,
-           similarSommelierDecision,
-           insertSommelierDecision
-       )
-julia> agent = sommelier(context, name="WineExpert", id="123", retailername="MyWineShop")
-```
-"""
-function sommelier(
-  context::agentcontext,  # agent functions, db connect and other context
-  ;
-  name::String= "Assistant",
-  id::String= string(uuid4()),
-  retailername::String= "not specified",
-  retailerid::String= "not specified",
-  maxHistoryMsg::Integer= 20,
-  chathistory::Vector{Dict{String, Any}} = Vector{Dict{String, Any}}(),
-  llmFormatName::String= "granite3"
-  )
-
-  tools = Dict( # update input format
-      "chatbox"=> Dict(
-        "description" => "<askbox tool description>Useful for when you need to ask the user for more context. Do not ask the user their own question.</askbox tool description>",
-        "input" => """<input>Input is a text in JSON format.</input><input example>{\"Q1\": \"How are you doing?\", \"Q2\": \"How may I help you?\"}</input example>""",
-        "output" => "" ,
-      ),
-      "winestock"=> Dict(
-        "description" => "<winestock tool description>A handy tool for searching wine in your inventory that match the user preferences.</winestock tool description>",
-        "input" => """<input>Input is a JSON-formatted string that contains a detailed and precise search query.</input><input example>{\"wine type\": \"rose\", \"price\": \"max 35\", \"sweetness level\": \"sweet\", \"intensity level\": \"light bodied\", \"Tannin level\": \"low\", \"Acidity level\": \"low\"}</input example>""",
-        "output" => """<output>Output are wines that match the search query in JSON format.""",
-      ),
-    )
-
-  """ Memory
-
-    Chat history use openai format as follow:
-
-    image1_path = "test/large_image.png"                           ---
-    image1_bytes = read(image1_path)                                 | this part must be done
-    image1_base64_string = base64encode(image1_bytes)                | in frontend 
-    mime_type = "image/png"                                          | not in agent code
-    data1_uri = "data:<mime_type>;base64,<image1_base64_string>"   ---
-
-    chathistory= [
-      Dict(
-        "role" => "system",
-        "content" => [
-          Dict("type" => "text", "text" => "You are a helpful assistant"),
-        ]
-      ),
-      Dict(
-        "role" => "user",
-        "content" => [
-          Dict("type" => "text", "text" => "<internal_context_for_assistant> 
-                                            LLM context here...
-                                            </internal_context_for_assistant>
-                                            Do you know this wine? Just give me brief intro."
-          ),
-          Dict(
-            "type" => "image_url",
-            "image_url" => Dict("url" => data1_uri)
-          ),
-        ]
-      ),
-    ]
-  
-  shortmem = Dict(
-    "1"=> Dict("plan"=> "...", "action_name"=> "...", "action_input"=> "...", "action_result"=> "..."),
-    "2"=> Dict("plan"=> "...", "action_name"=> "...", "action_input"=> "...", "action_result"=> "..."),
-    ...
-    )
-  """
-  memory = Dict{String, Any}(
-            "shortmem"=> OrderedDict{String, Any}(),
-            "scratchpad"=> "",
-            "recap"=> OrderedDict{String, Any}(),
-          )
-
-  newAgent = sommelier(
-    name,
-    id,
-    retailername,
-    retailerid,
-    tools,
-    maxHistoryMsg,
-    chathistory,
-    memory,
-    context,
-    llmFormatName
-    )
-  systemmsg = 
-    """
-    # store_policy
-      - Generally speaking, the store inventory has some wines from France, the United States, Australia, Spain, and Italy, but you won't know exactly until you check your inventory.
-      - If you found wines in the store's database, they are in stock.
-      - You can only recommend wines that are currently in our inventory
-      - Before searching the database for wine, ensure you have at least the following information: 1) budget, 2) wine type, and 3) occasion. Additional details are always helpful. If the user is unsure, provide relevant information and gather insights to make reasonable inferences.
-      - Ask the user one question at a time.
-      - Once the user has selected their wine, if you haven't already, ask the user whether they need any further assistance. Do not offer any additional services.
-      - Only end the conversation when the user explicitly intends to do so. When ending, ensure a polite farewell and an invitation to return in the future.
-      - Spicy foods should be paired only with light red wines.
-      - We do not sell organic, sustainable, gluten-free, and sulfite-free wine. Inform the user imediately if they are looking for these types of wines. Do not sell our wines as such.
-      - Gift box, gift card, and custom messages are available. Inform the user to contact our sales team.
-
-    # store_guidelines
-      - Greeting the customer warmly by ask them how could you help. Do not ask any other questions during this greeting.
-      - Customer may provide images for you to look up.
-      - Encourage the customer to explore different options and try new things.
-      - If you are unable to locate the desired item in the database after 2 attempts, it may not be available in your inventory. In such cases, inform the user that the item is unavailable and suggest an alternative instead.
-      - Your store carries only wine.
-      - Vintage 0 means non-vintage.
-      - Start searching the database as broadly as possible within the given information boundary to maximize the chances of finding. Avoid unnecessary parameters unless specified by the user. Refine the search subsequently.
-      - User usually ask for something similar. This means you should use the search term based on the profile they like.
-
-    # situation
-      You are having conversation with a customer.
-
-    # your role
-      Your name is $(newAgent.name). You are a helpful sommelier for website-based $(newAgent.retailername)'s wine store.
-
-    # objective
-      - Establish a connection with the customer by talking to them politely and showing your enthusiasm for their wine preferences.
-      - Provide relevant information and guide them to select the best wines only from your store's inventory that align with their preferences.
-
-    # your responsibility includes
-      - According to the store's policy and guidelines, and make an informed decision about what available_actions you need to use to achieve the objective.
-      - Keep the conversation with the customer going smoothly
-
-    # your responsibility does NOT includes
-      - Requesting the user to place an order, make a purchase, or confirm the order. These are the job of our sales team at the store.
-      - Processing sales orders or engaging in any other sales-related activities. These are the job of our sales team at the store.
-      - Answering questions or offering additional services beyond those related to your store's wine recommendations such as discounts, quantity, rewards programs, promotions, delivery options, shipping, boxes, gift wrapping, packaging, personalized messages or something similar. These are the job of our sales team at the store.
-
-    # you should then respond to the user with interleaving plan, action_name, action_input in JSON format
-      1) "plan", Based on the current situation, state a complete action plan to complete the task and rationale. Be specific.
-      2) "action_name", (Typically corresponds to the execution of the first step in your plan) Can be one of the available_actions name
-      3) "action_input", The input to the action you are about to perform according to your plan.
-      After the action is executed you gets "action_result". It is the output from the action you selected.
-
-    # available actions
-      "CHAT_BOX", which you can use to talk with the user. The input is dialogue you want to chat with the user according to your plan.
-      "SEARCH_WINE_DATABASE", allows you to search information about wines you want in your inventory's database. The input is strictly supported search term including: retailer_name, wine price, winery, name, vintage, region, country, type of wine, grape varietal, tasting notes, occasion, food pairing, intensity, tannin, sweetness, and acidity.
-        Example query 1: "Dry, full-bodied red wine from Burgundy, France. Grape varietal could be Merlot or Syrah. price 100 to 1000 USD."
-        Example query 2: "Red or white wine, medium tannin, price under 700 USD"
-        Example query 3: "white wine from Tuscany, Italy or Bordeaux, France
-      "WINE_PRESENTATION_GUIDELINE", which you can use to check the store guidelines about how to present wines you have found to the user. The input is "nothing" keyword. The output is the guidelines that you can follow.
-      "END_CONVER_GUIDELINE", which you can use to check the store guidelines about how to end the conversation with the user. The input is "nothing" keyword. The output is the guidelines that you can follow.
-    """
-    
-  system_msg = Dict(
-      "role" => "system",
-      "content" => [
-        Dict("type" => "text", "text" => systemmsg),
-      ]
-    )
-
-  push!(newAgent.chathistory, system_msg)
-  
-  return newAgent
-end
- 
-
-mutable struct virtualcustomer <: agent
-  name::String  # agent name
-  id::String    # agent id
-  systemmsg::String # system message
-  tools::Dict   
-  maxHistoryMsg::Integer  # e.g. 21th and earlier messages will get summarized
-  chathistory::Vector{Dict{String, Any}}
-  memory::Dict{String, Any}
-  context  # NamedTuple of functions 
-  llmFormatName::String
-end
-
-function virtualcustomer(
-  context,  # NamedTuple of functions
-  ;
-  name::String= "Assistant",
-  id::String= string(uuid4()),
-  maxHistoryMsg::Integer= 20,
-  chathistory::Vector{Dict{String, String}} = Vector{Dict{String, String}}(),
-  llmFormatName::String= "granite3",
-  systemmsg::String=
-    """
-      Your name: $name
-      Your sex: Female
-      Your role: You are a helpful assistant.
-      You should follow the following guidelines:
-      - Focus on the latest conversation.
-      - Your like to be short and concise.
-
-      Let's begin!
-      """,
-  )
-
-  tools = Dict( # update input format
-      "chatbox"=> Dict(
-        "description" => "<askbox tool description>Useful for when you need to ask the user for more context. Do not ask the user their own question.</askbox tool description>",
-        "input" => """<input>Input is a text in JSON format.</input><input example>{\"Q1\": \"How are you doing?\", \"Q2\": \"How may I help you?\"}</input example>""",
-        "output" => "" ,
-      ),
-    )
-
-  """ Memory
-    Ref: Chat prompt format is openai
-    chathistory = [
-      Dict(
-        "role" => "system",
-        "content" => [
-          Dict("type" => "text", "text" => system_msg),
-        ]
-      ),
-      Dict(
-        "role" => "user",
-        "content" => [
-          Dict("type" => "text", "text" => "Do you know this wine? Just give me brief intro."),
-          Dict(
-            "type" => "image_url",
-            "image_url" => Dict("url" => data1_uri)
-          )
-        ]
-      )
-    ]
-  """
-  memory = Dict{String, Any}(
-            "shortmem"=> OrderedDict{String, Any}(
-            ),
-            "scratchpad"=> "",
-            "events"=> Vector{Dict{String, Any}}(),
-            "state"=> Dict{String, Any}(
-            ),
-            "recap"=> OrderedDict{String, Any}(),
-          )
-
-  newAgent = virtualcustomer(
-    name,
-    id,
-    systemmsg,
-    tools,
-    maxHistoryMsg,
-    chathistory,
-    memory,
-    context,
-    llmFormatName
-    )
-  
-  return newAgent
-end
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-end # module type

test/_extractToolCalls.jl

@@ -0,0 +1,642 @@
+using Test
+using YiemAgent
+using YiemAgent.agentCore
+using YiemAgent.type
+using JSON
+
+# Import the function from the private module scope
+import YiemAgent.agentCore: _extractToolCalls
+
+@testset "_extractToolCalls" begin
+
+    # ------------------------------------------------------------------ #
+    # Format 1: response["message"]["tool_calls"] (LMStudio.jl style)     #
+    # ------------------------------------------------------------------ #
+
+    @testset "single tool call via message format" begin
+        response = Dict{String,Any}(
+            "finish_reason" => "tool_calls",
+            "index" => 0,
+            "message" => Dict{String,Any}(
+                "role" => "assistant",
+                "content" => "",
+                "reasoning_content" => "Let me check the weather.",
+                "tool_calls" => Any[
+                    Dict{String,Any}(
+                        "type" => "function",
+                        "function" => Dict{String,Any}(
+                            "name" => "getWeather",
+                            "arguments" => "{\"city\":\"Bangkok, Thailand\"}",
+                        ),
+                        "id" => "tc_001",
+                    )
+                ],
+            ),
+        )
+        has_toolcalls, tc_list, assistant_msg = _extractToolCalls(response)
+        @test has_toolcalls == true
+        @test length(tc_list) == 1
+        @test tc_list[1].name == "getWeather"
+        @test tc_list[1].id == "tc_001"
+        @test tc_list[1].type == "function"
+        @test tc_list[1].arguments["city"] == "Bangkok, Thailand"
+        @test assistant_msg isa assistantMessage
+        @test assistant_msg.role == "assistant"
+        @test assistant_msg.stopReason == "tool_calls"
+        @test length(assistant_msg.content) == 1
+        @test assistant_msg.content[1] isa reasoningContent
+        @test assistant_msg.content[1].text == "Let me check the weather."
+    end
+
+    @testset "multiple tool calls via message format" begin
+        response = Dict{String,Any}(
+            "message" => Dict{String,Any}(
+                "role" => "assistant",
+                "content" => "",
+                "tool_calls" => Any[
+                    Dict{String,Any}(
+                        "type" => "function",
+                        "function" => Dict{String,Any}(
+                            "name" => "getWeather",
+                            "arguments" => "{\"city\":\"Tokyo, Japan\"}",
+                        ),
+                        "id" => "tc_001",
+                    ),
+                    Dict{String,Any}(
+                        "type" => "function",
+                        "function" => Dict{String,Any}(
+                            "name" => "getTime",
+                            "arguments" => "{\"timezone\":\"Asia/Tokyo\"}",
+                        ),
+                        "id" => "tc_002",
+                    ),
+                ],
+            ),
+        )
+        has_toolcalls, tc_list, assistant_msg = _extractToolCalls(response)
+        @test has_toolcalls == true
+        @test length(tc_list) == 2
+        @test tc_list[1].name == "getWeather"
+        @test tc_list[1].arguments["city"] == "Tokyo, Japan"
+        @test tc_list[2].name == "getTime"
+        @test tc_list[2].arguments["timezone"] == "Asia/Tokyo"
+        @test assistant_msg.role == "assistant"
+    end
+
+    @testset "tool call with empty arguments string" begin
+        response = Dict{String,Any}(
+            "message" => Dict{String,Any}(
+                "role" => "assistant",
+                "tool_calls" => Any[
+                    Dict{String,Any}(
+                        "type" => "function",
+                        "function" => Dict{String,Any}(
+                            "name" => "listTools",
+                            "arguments" => "{}",
+                        ),
+                        "id" => "tc_empty",
+                    ),
+                ],
+            ),
+        )
+        has_toolcalls, tc_list, assistant_msg = _extractToolCalls(response)
+        @test has_toolcalls == true
+        @test length(tc_list) == 1
+        @test tc_list[1].name == "listTools"
+        @test tc_list[1].arguments == Dict{String,Any}()
+        @test assistant_msg.stopReason == "end_turn"
+    end
+
+    @testset "tool call with missing id falls back to uuid" begin
+        response = Dict{String,Any}(
+            "message" => Dict{String,Any}(
+                "role" => "assistant",
+                "tool_calls" => Any[
+                    Dict{String,Any}(
+                        "type" => "function",
+                        "function" => Dict{String,Any}(
+                            "name" => "getTime",
+                            "arguments" => "{\"city\":\"NYC\"}",
+                        ),
+                    ),
+                ],
+            ),
+        )
+        has_toolcalls, tc_list, assistant_msg = _extractToolCalls(response)
+        @test has_toolcalls == true
+        @test length(tc_list) == 1
+        @test !isempty(tc_list[1].id)
+        @test tc_list[1].name == "getTime"
+    end
+
+    @testset "tool call with non-string arguments (pre-parsed dict)" begin
+        response = Dict{String,Any}(
+            "message" => Dict{String,Any}(
+                "role" => "assistant",
+                "tool_calls" => Any[
+                    Dict{String,Any}(
+                        "type" => "function",
+                        "function" => Dict{String,Any}(
+                            "name" => "getWeather",
+                            "arguments" => Dict{String,Any}("city" => "London", "units" => "fahrenheit"),
+                        ),
+                        "id" => "tc_parsed",
+                    ),
+                ],
+            ),
+        )
+        has_toolcalls, tc_list, assistant_msg = _extractToolCalls(response)
+        @test has_toolcalls == true
+        @test length(tc_list) == 1
+        @test tc_list[1].arguments["city"] == "London"
+        @test tc_list[1].arguments["units"] == "fahrenheit"
+    end
+
+    @testset "tool call with api/provider/model/usage metadata" begin
+        response = Dict{String,Any}(
+            "api" => "openai",
+            "provider" => "anthropic",
+            "model" => "claude-3-opus",
+            "message" => Dict{String,Any}(
+                "role" => "assistant",
+                "tool_calls" => Any[
+                    Dict{String,Any}(
+                        "type" => "function",
+                        "function" => Dict{String,Any}(
+                            "name" => "getTime",
+                            "arguments" => "{}",
+                        ),
+                        "id" => "tc_meta",
+                    ),
+                ],
+            ),
+        )
+        has_toolcalls, tc_list, assistant_msg = _extractToolCalls(response)
+        @test has_toolcalls == true
+        @test assistant_msg.api == "openai"
+        @test assistant_msg.provider == "anthropic"
+        @test assistant_msg.model == "claude-3-opus"
+    end
+
+    # --------------------------------------------------------------- #
+    # Format 2: response.content blocks (OpenAI API style)            #
+    # --------------------------------------------------------------- #
+
+    @testset "content blocks with tool_calls" begin
+        response = Dict{String,Any}(
+            "content" => Any[
+                Dict{String,Any}("type" => "text", "text" => "Let me check."),
+                Dict{String,Any}(
+                    "type" => "tool_calls",
+                    "tool_calls" => Any[
+                        Dict{String,Any}(
+                            "type" => "function",
+                            "function" => Dict{String,Any}(
+                                "name" => "getWeather",
+                                "arguments" => "{\"city\":\"Paris\"}",
+                            ),
+                            "id" => "tc_block_1",
+                        ),
+                    ],
+                ),
+            ],
+        )
+        has_toolcalls, tc_list, assistant_msg = _extractToolCalls(response)
+        @test has_toolcalls == true
+        @test length(tc_list) == 1
+        @test tc_list[1].name == "getWeather"
+        @test tc_list[1].arguments["city"] == "Paris"
+        # text block before tool_calls should be included in content
+        @test length(assistant_msg.content) == 1
+        @test assistant_msg.content[1].text == "Let me check."
+    end
+
+    @testset "content blocks with tool_call (single-call format)" begin
+        response = Dict{String,Any}(
+            "content" => Any[
+                Dict{String,Any}(
+                    "type" => "tool_call",
+                    "id" => "tc_single",
+                    "name" => "getTime",
+                    "arguments" => Dict{String,Any}("timezone" => "Europe/London"),
+                ),
+            ],
+        )
+        has_toolcalls, tc_list, assistant_msg = _extractToolCalls(response)
+        @test has_toolcalls == true
+        @test length(tc_list) == 1
+        @test tc_list[1].name == "getTime"
+        @test tc_list[1].id == "tc_single"
+        @test tc_list[1].arguments["timezone"] == "Europe/London"
+    end
+
+    @testset "content blocks with reasoning and text" begin
+        response = Dict{String,Any}(
+            "content" => Any[
+                Dict{String,Any}("type" => "reasoning", "text" => "Thinking..."),
+                Dict{String,Any}("type" => "text", "text" => "Here's the answer."),
+            ],
+        )
+        has_toolcalls, tc_list, assistant_msg = _extractToolCalls(response)
+        @test has_toolcalls == false
+        @test length(tc_list) == 0
+        @test length(assistant_msg.content) == 2
+        @test assistant_msg.content[1] isa reasoningContent
+        @test assistant_msg.content[1].text == "Thinking..."
+        @test assistant_msg.content[2] isa textContent
+        @test assistant_msg.content[2].text == "Here's the answer."
+    end
+
+    @testset "content blocks with text and tool_call (tool_call not in content)" begin
+        response = Dict{String,Any}(
+            "content" => Any[
+                Dict{String,Any}("type" => "text", "text" => "Sure, I'll check."),
+                Dict{String,Any}(
+                    "type" => "tool_call",
+                    "id" => "tc_mix",
+                    "name" => "getWeather",
+                    "arguments" => Dict{String,Any}("city" => "London"),
+                ),
+            ],
+        )
+        has_toolcalls, tc_list, assistant_msg = _extractToolCalls(response)
+        @test has_toolcalls == true
+        @test length(tc_list) == 1
+        @test tc_list[1].name == "getWeather"
+        # text block included, tool_call block excluded from content
+        @test length(assistant_msg.content) == 1
+        @test assistant_msg.content[1].text == "Sure, I'll check."
+    end
+
+    # ------------------------------------------------------------------ #
+    # assistantMessage construction                                       #
+    # ------------------------------------------------------------------ #
+
+    @testset "assistantMessage with error_message and errorMessage fallback" begin
+        response = Dict{String,Any}(
+            "error_message" => "rate limit",
+            "content" => Any[Dict{String,Any}("type" => "text", "text" => "fail")],
+        )
+        has_toolcalls, tc_list, assistant_msg = _extractToolCalls(response)
+        @test has_toolcalls == false
+        @test assistant_msg.errorMessage == "rate limit"
+    end
+
+    @testset "assistantMessage with usage tracking" begin
+        response = Dict{String,Any}(
+            "content" => Any[Dict{String,Any}("type" => "text", "text" => "hi")],
+            "usage" => llmUsage(100, 50),
+        )
+        has_toolcalls, tc_list, assistant_msg = _extractToolCalls(response)
+        @test assistant_msg.usage.inputTokens == 100
+        @test assistant_msg.usage.outputTokens == 50
+    end
+
+    @testset "assistantMessage with invalid usage defaults to zero" begin
+        response = Dict{String,Any}(
+            "content" => Any[Dict{String,Any}("type" => "text", "text" => "hi")],
+            "usage" => "invalid",
+        )
+        has_toolcalls, tc_list, assistant_msg = _extractToolCalls(response)
+        @test assistant_msg.usage.inputTokens == 0
+        @test assistant_msg.usage.outputTokens == 0
+    end
+
+    @testset "reasoning_content as textContent" begin
+        response = Dict{String,Any}(
+            "reasoning_content" => textContent("internal thought"),
+            "content" => Any[Dict{String,Any}("type" => "text", "text" => "output")],
+        )
+        has_toolcalls, tc_list, assistant_msg = _extractToolCalls(response)
+        @test length(assistant_msg.content) == 2
+        @test assistant_msg.content[1] isa reasoningContent
+        @test assistant_msg.content[1].text == "internal thought"
+        @test assistant_msg.content[2] isa textContent
+        @test assistant_msg.content[2].text == "output"
+    end
+
+    # ------------------------------------------------------------------ #
+    # No tool call cases                                                  #
+    # ------------------------------------------------------------------ #
+
+    @testset "no tool calls found" begin
+        response = Dict{String,Any}(
+            "content" => Any[
+                Dict{String,Any}("type" => "text", "text" => "Hello world."),
+            ],
+        )
+        has_toolcalls, tc_list, assistant_msg = _extractToolCalls(response)
+        @test has_toolcalls == false
+        @test length(tc_list) == 0
+        @test assistant_msg.stopReason == "end_turn"
+    end
+
+    @testset "empty message" begin
+        response = Dict{String,Any}()
+        has_toolcalls, tc_list, assistant_msg = _extractToolCalls(response)
+        @test has_toolcalls == false
+        @test length(tc_list) == 0
+        @test assistant_msg.role == "assistant"
+        @test assistant_msg.stopReason == "end_turn"
+        @test length(assistant_msg.content) == 0
+    end
+
+    @testset "message with empty tool_calls array" begin
+        response = Dict{String,Any}(
+            "message" => Dict{String,Any}(
+                "role" => "assistant",
+                "tool_calls" => Any[],
+            ),
+        )
+        has_toolcalls, tc_list, assistant_msg = _extractToolCalls(response)
+        @test has_toolcalls == false
+        @test length(tc_list) == 0
+        @test assistant_msg.role == "assistant"
+    end
+
+    @testset "message field is not a Dict" begin
+        response = Dict{String,Any}(
+            "message" => "not a dict",
+            "content" => Any[Dict{String,Any}("type" => "text", "text" => "fallback")],
+        )
+        has_toolcalls, tc_list, assistant_msg = _extractToolCalls(response)
+        @test has_toolcalls == false
+        @test length(tc_list) == 0
+        @test length(assistant_msg.content) == 1
+    end
+
+    @testset "Format 1 takes priority over Format 2" begin
+        response = Dict{String,Any}(
+            "message" => Dict{String,Any}(
+                "role" => "assistant",
+                "tool_calls" => Any[
+                    Dict{String,Any}(
+                        "type" => "function",
+                        "function" => Dict{String,Any}(
+                            "name" => "getWeather",
+                            "arguments" => "{\"city\":\"Format1\"}",
+                        ),
+                        "id" => "tc_fmt1",
+                    ),
+                ],
+            ),
+            "content" => Any[
+                Dict{String,Any}(
+                    "type" => "tool_call",
+                    "id" => "tc_fmt2",
+                    "name" => "getTime",
+                    "arguments" => Dict{String,Any}("city" => "Format2"),
+                ),
+            ],
+        )
+        has_toolcalls, tc_list, assistant_msg = _extractToolCalls(response)
+        @test has_toolcalls == true
+        @test length(tc_list) == 1
+        @test tc_list[1].name == "getWeather"
+    end
+
+    # ------------------------------------------------------------------ #
+    # Edge cases                                                          #
+    # ------------------------------------------------------------------ #
+
+    @testset "tool call with null arguments" begin
+        response = Dict{String,Any}(
+            "message" => Dict{String,Any}(
+                "role" => "assistant",
+                "tool_calls" => Any[
+                    Dict{String,Any}(
+                        "type" => "function",
+                        "function" => Dict{String,Any}(
+                            "name" => "getTime",
+                            "arguments" => nothing,
+                        ),
+                        "id" => "tc_null",
+                    ),
+                ],
+            ),
+        )
+        has_toolcalls, tc_list, assistant_msg = _extractToolCalls(response)
+        @test has_toolcalls == true
+        @test length(tc_list) == 1
+        @test tc_list[1].name == "getTime"
+    end
+
+    @testset "tool call with missing function key" begin
+        response = Dict{String,Any}(
+            "message" => Dict{String,Any}(
+                "role" => "assistant",
+                "tool_calls" => Any[
+                    Dict{String,Any}(
+                        "type" => "function",
+                        "id" => "tc_nofunc",
+                    ),
+                ],
+            ),
+        )
+        has_toolcalls, tc_list, assistant_msg = _extractToolCalls(response)
+        @test has_toolcalls == true
+        @test length(tc_list) == 1
+        @test tc_list[1].name == ""
+    end
+
+    @testset "tool call with missing name in function block" begin
+        response = Dict{String,Any}(
+            "message" => Dict{String,Any}(
+                "role" => "assistant",
+                "tool_calls" => Any[
+                    Dict{String,Any}(
+                        "type" => "function",
+                        "function" => Dict{String,Any}("arguments" => "{}"),
+                        "id" => "tc_noname",
+                    ),
+                ],
+            ),
+        )
+        has_toolcalls, tc_list, assistant_msg = _extractToolCalls(response)
+        @test has_toolcalls == true
+        @test length(tc_list) == 1
+        @test tc_list[1].name == ""
+    end
+
+    @testset "message format with JSON.Object (JSON.parse result)" begin
+        json_str = JSON.json(Dict(
+            "message" => Dict(
+                "role" => "assistant",
+                "tool_calls" => [
+                    Dict(
+                        "type" => "function",
+                        "function" => Dict("name" => "getWeather", "arguments" => "{\"city\":\"Test\"}"),
+                        "id" => "tc_jsonobj",
+                    ),
+                ],
+            ),
+        ))
+        parsed = JSON.parse(json_str)
+        has_toolcalls, tc_list, assistant_msg = _extractToolCalls(parsed)
+        @test has_toolcalls == true
+        @test length(tc_list) == 1
+        @test tc_list[1].name == "getWeather"
+        @test tc_list[1].arguments["city"] == "Test"
+    end
+
+    @testset "tool_calls block with mixed content types (text + tool_calls)" begin
+        response = Dict{String,Any}(
+            "content" => Any[
+                Dict{String,Any}("type" => "text", "text" => "I'll check both."),
+                Dict{String,Any}(
+                    "type" => "tool_calls",
+                    "tool_calls" => Any[
+                        Dict{String,Any}(
+                            "type" => "function",
+                            "function" => Dict{String,Any}(
+                                "name" => "getWeather",
+                                "arguments" => "{\"city\":\"London\"}",
+                            ),
+                            "id" => "tc_mix1",
+                        ),
+                        Dict{String,Any}(
+                            "type" => "function",
+                            "function" => Dict{String,Any}(
+                                "name" => "getTime",
+                                "arguments" => "{\"timezone\":\"UTC\"}",
+                            ),
+                            "id" => "tc_mix2",
+                        ),
+                    ],
+                ),
+            ],
+        )
+        has_toolcalls, tc_list, assistant_msg = _extractToolCalls(response)
+        @test has_toolcalls == true
+        @test length(tc_list) == 2
+        @test tc_list[1].name == "getWeather"
+        @test tc_list[2].name == "getTime"
+        @test length(assistant_msg.content) == 1
+        @test assistant_msg.content[1].text == "I'll check both."
+    end
+
+    @testset "tool_call block without arguments field" begin
+        response = Dict{String,Any}(
+            "content" => Any[
+                Dict{String,Any}(
+                    "type" => "tool_call",
+                    "id" => "tc_noargs",
+                    "name" => "getTime",
+                ),
+            ],
+        )
+        has_toolcalls, tc_list, assistant_msg = _extractToolCalls(response)
+        @test has_toolcalls == true
+        @test length(tc_list) == 1
+        @test tc_list[1].arguments == Dict{String,Any}()
+    end
+
+    @testset "tool_calls block with empty tool_calls array" begin
+        response = Dict{String,Any}(
+            "content" => Any[
+                Dict{String,Any}(
+                    "type" => "tool_calls",
+                    "tool_calls" => Any[],
+                ),
+            ],
+        )
+        has_toolcalls, tc_list, assistant_msg = _extractToolCalls(response)
+        @test has_toolcalls == false
+        @test length(tc_list) == 0
+    end
+
+    @testset "tool_calls block with non-AbstractDict elements" begin
+        response = Dict{String,Any}(
+            "content" => Any[
+                Dict{String,Any}(
+                    "type" => "tool_calls",
+                    "tool_calls" => Any["not a dict", 42, nothing],
+                ),
+            ],
+        )
+        has_toolcalls, tc_list, assistant_msg = _extractToolCalls(response)
+        @test has_toolcalls == false
+        @test length(tc_list) == 0
+    end
+
+    @testset "content field is not a Vector" begin
+        response = Dict{String,Any}(
+            "content" => "not a vector",
+        )
+        has_toolcalls, tc_list, assistant_msg = _extractToolCalls(response)
+        @test has_toolcalls == false
+        @test length(tc_list) == 0
+        @test length(assistant_msg.content) == 0
+    end
+
+    @testset "Dict-based response with all metadata fields" begin
+        response = Dict{String,Any}(
+            "api" => "openai",
+            "provider" => "anthropic",
+            "model" => "claude-3-sonnet",
+            "content" => Any[
+                Dict{String,Any}(
+                    "type" => "tool_call",
+                    "id" => "tc_meta",
+                    "name" => "getTime",
+                    "arguments" => Dict{String,Any}("city" => "Seoul"),
+                ),
+            ],
+        )
+        has_toolcalls, tc_list, assistant_msg = _extractToolCalls(response)
+        @test has_toolcalls == true
+        @test length(tc_list) == 1
+        @test tc_list[1].name == "getTime"
+        @test tc_list[1].arguments["city"] == "Seoul"
+        @test assistant_msg.api == "openai"
+        @test assistant_msg.provider == "anthropic"
+        @test assistant_msg.model == "claude-3-sonnet"
+    end
+
+    @testset "default role is assistant" begin
+        response = Dict{String,Any}(
+            "content" => Any[Dict{String,Any}("type" => "text", "text" => "no role specified")],
+        )
+        has_toolcalls, tc_list, assistant_msg = _extractToolCalls(response)
+        @test assistant_msg.role == "assistant"
+    end
+
+    @testset "tool call with custom role in message format" begin
+        response = Dict{String,Any}(
+            "message" => Dict{String,Any}(
+                "role" => "custom_role",
+                "tool_calls" => Any[
+                    Dict{String,Any}(
+                        "type" => "function",
+                        "function" => Dict{String,Any}(
+                            "name" => "getWeather",
+                            "arguments" => "{}",
+                        ),
+                        "id" => "tc_role",
+                    ),
+                ],
+            ),
+        )
+        has_toolcalls, tc_list, assistant_msg = _extractToolCalls(response)
+        @test assistant_msg.role == "custom_role"
+    end
+
+    @testset "image content block handling" begin
+        response = Dict{String,Any}(
+            "content" => Any[
+                Dict{String,Any}(
+                    "type" => "image_url",
+                    "image_url" => Dict("url" => "data:image/png;base64,abc123"),
+                ),
+                Dict{String,Any}("type" => "text", "text" => "What is this?"),
+            ],
+        )
+        has_toolcalls, tc_list, assistant_msg = _extractToolCalls(response)
+        @test has_toolcalls == false
+        @test length(assistant_msg.content) == 2
+        @test assistant_msg.content[1] isa textContent
+        @test assistant_msg.content[1].text == ""
+        @test assistant_msg.content[2].text == "What is this?"
+    end
+
+end

test/loadToolTest.jl

@@ -1,136 +0,0 @@
-using Test
-using YiemAgent
-using YiemAgent.toolRegistry
-using YiemAgent.type
-
-# Path to the real tools directory
-TOOLS_DIR = joinpath(@__DIR__, "..", "src", "tools")
-
-@testset "loadTools" begin
-
-    # ------------------------------------------------------------------ #
-    # 1. loadTools throws on non-existent directory                      #
-    # ------------------------------------------------------------------ #
-    @test_throws ArgumentError loadTools("/nonexistent/dir/that/does/not/exist")
-
-    # ------------------------------------------------------------------ #
-    # 2. loadTools throws if a .jl file does not define getTool()        #
-    #    Must run BEFORE any other loadTools call (getTool binding       #
-    #    persists in module scope after include()).                      #
-    # ------------------------------------------------------------------ #
-    bad_dir = mktempdir()
-    write(joinpath(bad_dir, "noTool.jl"), "x = 42\n")
-    @test_throws ArgumentError loadTools(bad_dir)
-
-    # ------------------------------------------------------------------ #
-    # 3. loadTools loads actual tool files from src/tools/               #
-    # ------------------------------------------------------------------ #
-    loaded = loadTools(TOOLS_DIR)
-    @test !isempty(loaded)
-    @test length(loaded) == 3
-
-    names = [k for k in keys(loaded)]
-    @test "getTime" in names
-    @test "getWeather" in names
-    @test "writeTool" in names
-
-    # ------------------------------------------------------------------ #
-    # 4. loadTools returns tools sorted alphabetically by filename       #
-    #    (getTime.jl < getWeather.jl < writeTool.jl)                      #
-    #    because 'T' < 'W' in ASCII                                       #
-    # ------------------------------------------------------------------ #
-    @test collect(keys(loaded))[1] == "getTime"
-    @test collect(keys(loaded))[2] == "getWeather"
-    @test collect(keys(loaded))[3] == "writeTool"
-
-    # ------------------------------------------------------------------ #
-    # 5. Verify loaded tool fields are correct                           #
-    # ------------------------------------------------------------------ #
-    # getTime
-    time_tool = loaded["getTime"]
-    @test time_tool.name == "getTime"
-    @test time_tool.label == "Time Lookup"
-    @test time_tool.validateRequiredArgs !== nothing
-    @test time_tool.parallelToolExecute == false
-    @test time_tool.inputSchema["required"] == Any[]
-
-    # getWeather
-    weather = loaded["getWeather"]
-    @test weather.name == "getWeather"
-    @test weather.label == "Weather Lookup"
-    @test weather.execute !== nothing
-    @test weather.parallelToolExecute == false
-    @test weather.inputSchema["required"] == ["city"]
-
-    # writeTool
-    wt = loaded["writeTool"]
-    @test wt.name == "writeTool"
-    @test wt.label == "Create Tool"
-    @test wt.execute !== nothing
-    @test "name" in wt.inputSchema["required"]
-    @test "executeCode" in wt.inputSchema["required"]
-
-    # ------------------------------------------------------------------ #
-    # 6. Tool execution returns valid results                            #
-    # ------------------------------------------------------------------ #
-    sig = nothing
-    op = x -> x  # no-op partial result callback
-
-    # execute getTime
-    result_t = time_tool.execute("call-1", Dict{String,Any}("city" => "Tokyo"), sig, op)
-    @test result_t isa agentToolResult
-    @test result_t.content[1] isa textContent
-    @test occursin("Tokyo", result_t.content[1].text)
-
-    # execute getTime with timezone
-    result_tz = time_tool.execute("call-2", Dict{String,Any}("timezone" => "America/New_York"), sig, op)
-    @test result_tz isa agentToolResult
-    @test occursin("America/New_York", result_tz.content[1].text)
-
-    # execute getWeather
-    result_w = weather.execute("call-3", Dict{String,Any}("city" => "Bangkok"), sig, op)
-    @test result_w isa agentToolResult
-    @test result_w.content[1] isa textContent
-    @test occursin("Bangkok", result_w.content[1].text)
-
-    # execute getWeather with units
-    result_w2 = weather.execute("call-4", Dict{String,Any}("city" => "London", "units" => "fahrenheit"), sig, op)
-    @test occursin("72°F", result_w2.content[1].text)
-
-    # ------------------------------------------------------------------ #
-    # 7. getTools / registerTool / clearTools                            #
-    # ------------------------------------------------------------------ #
-    registry_tools = getTools()
-    @test !isempty(registry_tools)
-    @test any(t -> t.name == "getTime", registry_tools)
-    @test any(t -> t.name == "getWeather", registry_tools)
-
-    clearTools()
-    @test isempty(getTools())
-
-    test_tool = agentTool(
-        name = "manualTool",
-        label = "Manual Tool",
-        description = "Registered manually",
-        inputSchema = Dict{String,Any}("type" => "object", "properties" => Dict{String,Any}(), "required" => Any[]),
-        execute = (toolCallId, args, signal, onPartialResult) ->
-            agentToolResult([textContent("manual")], Dict{Any,Any}(), nothing, false),
-        prepareArguments = nothing,
-        validateRequiredArgs = nothing,
-        parallelToolExecute = true
-    )
-    registerTool(test_tool)
-    reg = getTools()
-    @test any(t -> t.name == "manualTool", reg)
-    @test count(t -> t.name == "manualTool", reg) == 1
-    @test     reg[1].parallelToolExecute == true
-
-    # ------------------------------------------------------------------ #
-    # 8. getTools returns deep copy (mutations don't affect registry)    #
-    # ------------------------------------------------------------------ #
-    copy1 = getTools()
-    copy2 = getTools()
-    @test copy1 !== copy2
-    empty!(copy1)
-    @test !isempty(getTools())
-end

test/runtest.jl

@@ -1,401 +1,5 @@
-using JSON, Dates, UUIDs, PrettyPrinting, LibPQ, Base64, DataFrames, DataStructures, HTTP, Base64,
-      NATS, Base.Threads
-using YiemAgent, GeneralUtils, msghandler
-
-  function text2text_instruct_llm(sender_id::String, openai_msg::Dict{String, Any})
-    payloads = [("msg", openai_msg, "dictionary")]  # List of tuples
-    _, msg_envelope_json_str = msghandler.smartpack(
-          config["externalservice"]["servicesloadbalancer"]["nats"], 
-          payloads;
-          sender_id=sender_id,
-          msg_purpose="text2text",  
-          broker_url=config["nats_server_info"]["url"],
-          fileserver_url=config["externalservice"]["fileserver"]["url"])
-
-    reply = NATS.request(agent_conn, 
-                        config["externalservice"]["servicesloadbalancer"]["nats"], 
-                        msg_envelope_json_str, timeout=120)
-
-    incoming_env_json_str = String(reply.payload)
-    incoming_env = msghandler.smartunpack(incoming_env_json_str)
-    _llm_response = incoming_env["payloads"][1][2]
-    llm_response = _llm_response["choices"][1]["message"]["content"]
-    return llm_response
-  end
-
-  """ get a single text embedding from a LLM service
-  Example
-  text = ["hello"]
-  embedding = get_embedding(text)
-  """
-  function get_embedding(text::AbstractArray{String})
-    documents_dict = Dict("documents" => text)
-    payloads = [("documents", documents_dict, "dictionary")]
-    _, msg_envelope_json_str = msghandler.smartpack(
-      config["externalservice"]["servicesloadbalancer"]["nats"], 
-      payloads;   
-      msg_purpose="embedding",  
-      broker_url=config["nats_server_info"]["url"],
-      fileserver_url=config["externalservice"]["fileserver"]["url"])
-
-    reply = NATS.request(agent_conn, 
-                        config["externalservice"]["servicesloadbalancer"]["nats"], 
-                        msg_envelope_json_str, timeout=120)
-    incoming_env_json_str = String(reply.payload)
-    incoming_env = msghandler.smartunpack(incoming_env_json_str)
-    embedding_response = incoming_env["payloads"][1][2]
-
-    return embedding_response
-  end
-
-  """ sql = "SELECT * FROM wine;"
-  result = execute_sql_winedb(sql)
-  """
-  function execute_sql_winedb(sql::T) where {T<:AbstractString}
-    host_url, _port = split(config["externalservice"]["sommpanion_db"]["url"], ':')
-    port = parse(Int, _port)
-    dbname = "winedb"
-    user = config["externalservice"]["sommpanion_db"]["user"]
-    password = config["externalservice"]["sommpanion_db"]["password"]
-    db_connection = LibPQ.Connection("host=$host_url port=$port dbname=$dbname user=$user password=$password")
-    result = nothing
-    try
-      result = LibPQ.execute(db_connection, sql)  
-    catch e
-      LibPQ.close(db_connection)
-    end
-    
-    LibPQ.close(db_connection)
-    return result
-  end
-
-  """ find similar sql from vector database
-  sql = "SELECT * FROM wine;"
-  result, distance = similar_sql_vectordb(sql)
-  """
-  function similar_sql_vectordb(sql::T; maxdistance::Number=0.2) where {T<:AbstractString}
-    tablename = "sqlllm_decision_repository"
-    # get embedding of the query
-    df = find_similar_text_from_vectordb(sql, tablename, 
-          "function_input_embedding", execute_sql_vectordb)
-    # println(df[1, [:id, :function_output]])
-    row, col = size(df)
-    distance = row == 0 ? Inf : df[1, :distance]  
-    if row != 0 && distance < maxdistance
-      # if there is usable SQL, return it.
-      output_b64 = df[1, :function_output_base64]   # pick the closest match
-      output_str = String(base64decode(output_b64))
-      rowid = df[1, :id]
-      println("\n--| similar sql found. row id $rowid, distance $distance ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
-      pprintln(output_str)
-      return (result=output_str, distance=distance)
-    else
-      println("\n--| similar sql not found, max distance $maxdistance ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
-      return (result=nothing, distance=nothing)
-    end
-  end
-
-  """ insert query and sql into vector database
-  query = "get all wines from wine table"
-  sql = "SELECT * FROM wine;"
-  insert_sql_vectordb(query, sql)
-  """
-  function insert_sql_vectordb(query::T1, SQL::T2; maxdistance::Number=3
-    ) where {T1<:AbstractString, T2<:AbstractString}
-    
-    tablename = "sqlllm_decision_repository"
-    # get embedding of the query
-    # query = state[:thoughtHistory][:question]
-    df = find_similar_text_from_vectordb(query, tablename, 
-                                    "function_input_embedding", execute_sql_vectordb)
-    row, col = size(df)
-    distance = row == 0 ? Inf : df[1, :distance]
-    if row == 0 || distance > maxdistance # no close enough SQL stored in the database
-      _query_embedding = get_embedding([query])
-      _query_embedding = GeneralUtils.dictify(_query_embedding)
-      # println("\n--- _query_embedding() ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
-      # println(_query_embedding)
-      # println("---\n")
-      query_embedding = _query_embedding["data"][1]["embedding"]
-      query = replace(query, "'" => "")
-      sql_base64 = base64encode(SQL)
-      sql_ = replace(SQL, "'" => "")
-
-      sql = 
-        """
-        INSERT INTO $tablename (function_input, function_output, function_output_base64, function_input_embedding) VALUES ('$query', '$sql_', '$sql_base64', '$query_embedding');
-        """
-      # println("\n--| added new decision to vectorDB ", @__FILE__, ":", @__LINE__, " $(Dates.now())")
-      # println(sql)
-      _ = execute_sql_vectordb(sql)
-    end
-  end
-
-  """ execute sql against vectordb
-  sql = "SELECT * FROM wine;"
-  result = execute_sql_vectordb(sql)
-  """
-  function execute_sql_vectordb(sql::T) where {T<:AbstractString}
-    host_url, _port = split(config["externalservice"]["sommpanion_vectordb"]["url"], ':')
-    port = parse(Int, _port)
-    dbname = config["externalservice"]["sommpanion_vectordb"]["dbname"]
-    user = config["externalservice"]["sommpanion_vectordb"]["user"]
-    password = config["externalservice"]["sommpanion_vectordb"]["password"]
-    DBconnection = LibPQ.Connection("host=$host_url port=$port dbname=$dbname user=$user password=$password")
-    result = LibPQ.execute(DBconnection, sql)
-    close(DBconnection)
-    return result
-  end
-
-  """ search similar decision llm made from vectordb
-  """
-  function similar_sommelier_decision(recentevents::T1; maxdistance::Integer=3
-    )::Union{AbstractDict, Nothing} where {T1<:AbstractString}
-
-    tablename = "sommelier_decision_repository"
-    # find similar
-    df = find_similar_text_from_vectordb(recentevents, tablename, 
-                                    "function_input_embedding", execute_sql_vectordb)
-    row, col = size(df)
-    distance = row == 0 ? Inf : df[1, :distance]
-    if row != 0 && distance < maxdistance
-      # if there is usable decision, return it.
-      rowid = df[1, :id]
-      println("\n--| found similar decision. row id $rowid, distance $distance ", @__FILE__, " ", @__LINE__)
-      output_b64 = df[1, :function_output_base64]   # pick the closest match
-      _output_str = String(base64decode(output_b64))
-      output = copy(JSON.read(_output_str))
-      return output
-    else
-      println("\n--| similar decision not found, max distance $maxdistance ", @__FILE__, " ", @__LINE__)
-      return nothing
-    end
-  end
-
-  """ search similar text from vectordb
-  """
-  function find_similar_text_from_vectordb(text::T1, tablename::T2, embeddingColumnName::T3,
-    vectorDB::Function; limit::Integer=1
-    )::DataFrame where {T1<:AbstractString, T2<:AbstractString, T3<:AbstractString}
-    # get embedding from LLM service
-    _embedding = get_embedding([text])
-    _embedding = _embedding["data"][1]["embedding"]
-    _embedding = "$_embedding"
-
-    embedding = _embedding[4:end]
-
-    # check whether there is close enough vector already store in vectorDB. if no, add, else skip 
-    sql = """
-          SELECT *, $embeddingColumnName <-> '$embedding' as distance
-          FROM $tablename
-          ORDER BY distance LIMIT $limit;
-          """
-    response = vectorDB(sql)
-    df = DataFrame(response)
-
-    return df
-  end
-
-  """ insert decision llm made to vectordb
-  """
-  function insert_sommelier_decision(recentevents::T1, decision::T2; maxdistance::Integer=5
-    ) where {T1<:AbstractString, T2<:AbstractDict}
-    tablename = "sommelier_decision_repository"
-    # find similar
-    df = find_similar_text_from_vectordb(recentevents, tablename, 
-                                    "function_input_embedding", execute_sql_vectordb)
-    row, col = size(df)
-    distance = row == 0 ? Inf : df[1, :distance]
-    if row == 0 || distance > maxdistance # no close enough SQL stored in the database
-      _embedding = get_embedding([recentevents])[1]
-      recentevents_embedding = _embedding["data"][1]["embedding"]
-      recentevents = replace(recentevents, "'" => "")
-      decision_json = JSON.json(decision)
-      decision_base64 = base64encode(decision_json)
-      decision = replace(decision_json, "'" => "")
-      
-      sql = 
-      """
-      INSERT INTO $tablename (function_input, function_output, function_output_base64, function_input_embedding) VALUES ('$recentevents', '$decision', '$decision_base64', '$recentevents_embedding');
-      """
-      println("\n--| added new decision to vectorDB ", @__FILE__, " ", @__LINE__)
-      println(sql)
-      _ = execute_sql_vectordb(sql)
-    else
-      println("--| similar decision previously cached, distance $distance ", @__FILE__, " ", @__LINE__)
-    end
-  end
-
-config = JSON.parsefile("./appconfig.json")
-sessionId = "0"
-backend_session_topic = "sommpanion.testsubject"
-agent_ch = Channel(8)
-agent_conn  = NATS.connect(config["nats_server_info"]["url"])
-
-sub2 = NATS.subscribe(agent_conn, backend_session_topic) do msg
-  put!(agent_ch, msg)
-end
-
-agent_context = YiemAgent.agentcontext(
-    text2text_instruct_llm,
-    get_embedding,
-    execute_sql_winedb,
-    similar_sql_vectordb,
-    insert_sql_vectordb,
-    similar_sommelier_decision,
-    insert_sommelier_decision
-  )
-
-  # can't instantiate
-  agent = YiemAgent.sommelier(
-    agent_context;
-    name="Janie",
-    id=sessionId,  # agent instance id
-    retailername="Yiem Wine Ltd.",
-    llmFormatName=""
-  )
-
-
-image1_path = "test/large_image.png"
-image1_bytes = read(image1_path)
-image1_base64_string = base64encode(image1_bytes)
-mime_type = "image/png" 
-data1_uri = "data:$(mime_type);base64,$(image1_base64_string)"
-
-# 1. Read local file and encode to base64 string
-image2_path = "test/small_image.png"
-image2_bytes = read(image2_path)
-image2_base64_string = base64encode(image2_bytes)
-mime_type = "image/png" 
-data2_uri = "data:$(mime_type);base64,$(image2_base64_string)"
-
-# 3. Construct payload with the Data URI
-message = Dict(
-    "role" => "user",
-    "content" => [
-      Dict("type" => "text", "text" => "Do you know type of wine in the image?"),
-      Dict(
-        "type" => "image_url",
-        "image_url" => Dict("url" => data1_uri)
-      )
-    ]
-  )
-
-result = YiemAgent.conversation(agent; userinput=message)
-println("\n$result")
-
-
-
-
-
-
-
-
-
-# message = Dict(
-#     "role" => "user",
-#     "content" => [
-#       Dict("type" => "text", "text" => 
-#       "
-#       เป็นงานเลี้ยงทั่วไป
-#       "),
-#     ]
-#   )
-
-# result = YiemAgent.conversation(agent; userinput=message)
-# println("\n$result")
-
-
-
-
-
-
-
-
-
-# message = Dict(
-#     "role" => "user",
-#     "content" => [
-#       Dict("type" => "text", "text" => "no thanks. that's all"),
-#     ]
-#   )
-
-# result = YiemAgent.conversation(agent; userinput=message)
-# println("\n$result")
-
-
-
-
-
-
-# message = Dict(
-#     "role" => "user",
-#     "content" => [
-#       Dict("type" => "text", "text" => "What about this wine?"),
-#       Dict(
-#         "type" => "image_url",
-#         "image_url" => Dict("url" => data2_uri)
-#       )
-#     ]
-#   )
-
-# result = YiemAgent.conversation(agent; userinput=message)
-# println("\n$result")
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
+using Test
+using YiemAgent
 
+include("toolTest.jl")
+include("_extractToolCalls.jl")

test/toolTest.jl

@@ -0,0 +1,367 @@
+using Test
+using Dates
+using YiemAgent
+using YiemAgent.toolRegistry
+using YiemAgent.type
+using YiemAgent.agentCore
+
+@testset "register_all_tools with toolStore" begin
+
+    # ------------------------------------------------------------------ #
+    # 1. register_all_tools registers all static tools + listTools       #
+    # ------------------------------------------------------------------ #
+    store = toolStore(name="test1")
+    loaded = register_all_tools(store)
+    @test !isempty(loaded)
+    @test length(loaded) == 4  # getWeather + getTime + writeTool + listTools
+
+    names = [k for k in keys(loaded)]
+    @test "getTime" in names
+    @test "getWeather" in names
+    @test "writeTool" in names
+    @test "listTools" in names
+
+    # ------------------------------------------------------------------ #
+    # 2. register_all_tools returns tools in registration order          #
+    # ------------------------------------------------------------------ #
+    @test collect(keys(loaded))[1] == "getWeather"
+    @test collect(keys(loaded))[2] == "getTime"
+    @test collect(keys(loaded))[3] == "writeTool"
+    @test collect(keys(loaded))[4] == "listTools"
+
+    # ------------------------------------------------------------------ #
+    # 3. Verify loaded tool fields are correct                           #
+    # ------------------------------------------------------------------ #
+    # getTime
+    time_tool = loaded["getTime"]
+    @test time_tool.name == "getTime"
+    @test time_tool.label == "Time Lookup"
+    @test time_tool.validateRequiredArgs !== nothing
+    @test time_tool.parallelToolExecute == false
+    @test time_tool.inputSchema["required"] == Any[]
+
+    # getWeather
+    weather = loaded["getWeather"]
+    @test weather.name == "getWeather"
+    @test weather.label == "Weather Lookup"
+    @test weather.execute !== nothing
+    @test weather.parallelToolExecute == false
+    @test weather.inputSchema["required"] == ["city"]
+
+    # writeTool
+    wt = loaded["writeTool"]
+    @test wt.name == "writeTool"
+    @test wt.label == "Create Tool"
+    @test wt.execute !== nothing
+    @test "name" in wt.inputSchema["required"]
+    @test "executeCode" in wt.inputSchema["required"]
+
+    # ------------------------------------------------------------------ #
+    # 4. Tool execution returns valid results                            #
+    # ------------------------------------------------------------------ #
+    sig = nothing
+    op = x -> x  # no-op partial result callback
+
+    # execute getTime
+    result_t = time_tool.execute("call-1", Dict{String,Any}("city" => "Tokyo"), sig, op)
+    @test result_t isa agentToolResult
+    @test result_t.content[1] isa textContent
+    @test occursin("Tokyo", result_t.content[1].text)
+
+    # execute getTime with timezone
+    result_tz = time_tool.execute("call-2", Dict{String,Any}("timezone" => "America/New_York"), sig, op)
+    @test result_tz isa agentToolResult
+    @test occursin("America/New_York", result_tz.content[1].text)
+
+    # execute getWeather
+    result_w = weather.execute("call-3", Dict{String,Any}("city" => "Bangkok"), sig, op)
+    @test result_w isa agentToolResult
+    @test result_w.content[1] isa textContent
+    @test occursin("Bangkok", result_w.content[1].text)
+
+    # execute getWeather with units
+    result_w2 = weather.execute("call-4", Dict{String,Any}("city" => "London", "units" => "fahrenheit"), sig, op)
+    @test occursin("72\u00b0F", result_w2.content[1].text)
+
+    # ------------------------------------------------------------------ #
+    # 5. getTools / registerTool / clearTools (per-store isolation)      #
+    # ------------------------------------------------------------------ #
+    store3 = toolStore(name="test3")
+    registry_tools = getTools(store3)
+    @test isempty(registry_tools)
+
+    # Register tools manually
+    registerTool(store3, loaded["getTime"])
+    registerTool(store3, loaded["getWeather"])
+    registerTool(store3, loaded["writeTool"])
+
+    reg = getTools(store3)
+    @test !isempty(reg)
+    @test "getTime" in keys(reg)
+    @test "getWeather" in keys(reg)
+    @test "writeTool" in keys(reg)
+    @test collect(keys(reg))[1] == "getTime"
+    @test collect(keys(reg))[2] == "getWeather"
+    @test collect(keys(reg))[3] == "writeTool"
+
+    clearTools(store3)
+    @test isempty(getTools(store3))
+
+    test_tool = agentTool(
+        name = "manualTool",
+        label = "Manual Tool",
+        description = "Registered manually",
+        inputSchema = Dict{String,Any}("type" => "object", "properties" => Dict{String,Any}(), "required" => Any[]),
+        execute = (toolCallId, args, signal, onPartialResult) ->
+            agentToolResult([textContent("manual")], Dict{Any,Any}(), nothing, false),
+        prepareArguments = nothing,
+        validateRequiredArgs = nothing,
+        parallelToolExecute = true
+    )
+    registerTool(store3, test_tool)
+    reg = getTools(store3)
+    @test haskey(reg, "manualTool")
+    @test length(reg) == 1
+    @test reg["manualTool"].parallelToolExecute == true
+
+    # ------------------------------------------------------------------ #
+    # 6. getTools returns direct reference (mutations affect registry)   #
+    # ------------------------------------------------------------------ #
+    copy1 = getTools(store3)
+    copy2 = getTools(store3)
+    @test copy1 === copy2  # same reference, not a deep copy
+    empty!(copy1)
+    @test isempty(getTools(store3))  # mutation propagates
+
+    # ------------------------------------------------------------------ #
+    # 7. Per-store isolation — two stores don't share tools              #
+    # ------------------------------------------------------------------ #
+    storeA = toolStore(name="isolationA")
+    storeB = toolStore(name="isolationB")
+
+    registerTool(storeA, loaded["getTime"])
+    registerTool(storeB, loaded["getWeather"])
+
+    regA = getTools(storeA)
+    regB = getTools(storeB)
+
+    @test "getTime" in keys(regA)
+    @test "getWeather" ∉ keys(regA)
+    @test "getWeather" in keys(regB)
+    @test "getTime" ∉ keys(regB)
+
+    clearTools(storeA)
+    @test isempty(getTools(storeA))
+    @test !isempty(getTools(storeB))  # storeB unaffected
+end
+
+@testset "listTool" begin
+    store = toolStore(name="test_list")
+    register_all_tools(store)  # auto-registers getWeather, getTime, writeTool + listTools
+
+    # register_all_tools auto-registers listTool
+    @test "listTools" in keys(store.tools)
+
+    # listTool returns an agentTool, not a string or array
+    list_t = listTool(store)
+    @test list_t isa agentTool
+    @test list_t.name == "listTools"
+    @test list_t.label == "List Tools"
+    @test isempty(list_t.inputSchema["required"])
+
+    # Verify all tools appear (3 loaded + listTools = 4)
+    result = list_t.execute("call-1", Dict{String,Any}(), nothing, x -> x)
+    @test result isa agentToolResult
+    @test result.content[1] isa textContent
+    @test occursin("listTools", result.content[1].text)
+    @test occursin("getWeather", result.content[1].text)
+    @test occursin("getTime", result.content[1].text)
+    @test occursin("writeTool", result.content[1].text)
+    @test result.details["count"] == 4
+
+    # Each listTool call creates an independent closure
+    storeB = toolStore(name="test_listB")
+    registerTool(storeB, store.tools["getWeather"])
+    list_tB = listTool(storeB)
+
+    resultA = list_t.execute("call-3", Dict{String,Any}(), nothing, x -> x)
+    resultB = list_tB.execute("call-4", Dict{String,Any}(), nothing, x -> x)
+
+    @test occursin("getWeather", resultA.content[1].text)
+    @test occursin("getWeather", resultB.content[1].text)
+    @test occursin("getTime", resultA.content[1].text)
+    @test occursin("getTime", resultB.content[1].text) == false  # storeB only has getWeather
+end
+
+@testset "executePreparedToolCall with static tools" begin
+    # Tests executePreparedToolCall with statically loaded tools.
+    # The world-age issue is resolved because tool.execute comes from
+    # a statically included module, not a dynamically created one.
+
+    store = toolStore(name="test_static")
+    register_all_tools(store)
+
+    weather_tool = store.tools["getWeather"]
+
+    # Create a preparedToolCall that mimics what prepareToolCall() returns
+    tool_call = agentToolCall(
+        "function", "call-static-1", "getWeather",
+        Dict{String,Any}("city" => "San Francisco")
+    )
+    prep = preparedToolCall(
+        weather_tool, tool_call, Dict{String,Any}("city" => "San Francisco")
+    )
+    sig = abortSignal(false)
+
+    # This call goes through: executePreparedToolCall -> prep.tool.execute(...)
+    result = executePreparedToolCall(
+        prep, sig, x -> nothing
+    )
+
+    @test result isa executedOutcome
+    @test result.isError == false
+    @test result.result.content[1] isa textContent
+    @test occursin("San Francisco", result.result.content[1].text)
+end
+
+@testset "executePreparedToolCall with validation (static tools)" begin
+    # Tests executePreparedToolCall with a tool that has custom validation hooks.
+    # This exercises the full tool execution path including validation.
+
+    store = toolStore(name="test_static_validate")
+    register_all_tools(store)
+
+    time_tool = store.tools["getTime"]
+
+    tool_call = agentToolCall(
+        "function", "call-static-2", "getTime",
+        Dict{String,Any}("timezone" => "America/New_York")
+    )
+    prep = preparedToolCall(
+        time_tool, tool_call, Dict{String,Any}("timezone" => "America/New_York")
+    )
+    sig = abortSignal(false)
+
+    result = executePreparedToolCall(
+        prep, sig, x -> nothing
+    )
+
+    @test result isa executedOutcome
+    @test result.isError == false
+    @test result.result.content[1] isa textContent
+    @test occursin("America/New_York", result.result.content[1].text)
+end
+
+@testset "executeToolCallsSequential with static tools (full pipeline)" begin
+    # Tests the full tool execution pipeline: executeToolCallsSequential
+    # which calls prepareToolCall -> executePreparedToolCall -> finalizeExecutedToolCall
+    # with statically loaded tools.
+
+    store = toolStore(name="test_full_pipeline")
+    register_all_tools(store)
+
+    # Build agentContext from the store's tools
+    tools = getTools(store)
+    ctx = agentContext(
+        "test system prompt",
+        agentMessage[],
+        tools
+    )
+
+    # Create an assistant message containing tool calls
+    assistant_msg = assistantMessage(
+        role="assistant",
+        content=Vector{messageContent}(),
+        api="openai",
+        provider="test",
+        model="test-model",
+        usage=llmUsage(0, 0),
+        stopReason="tool_calls",
+        errorMessage=nothing,
+        timestamp=now()
+    )
+
+    # Create tool calls for multiple statically loaded tools
+    tool_calls = [
+        agentToolCall(
+            "function", "call-seq-1", "getWeather",
+            Dict{String,Any}("city" => "Tokyo")
+        ),
+        agentToolCall(
+            "function", "call-seq-2", "getTime",
+            Dict{String,Any}("timezone" => "Europe/London")
+        ),
+    ]
+
+    config = agentLoopConfig(
+        nothing, nothing, "sequential"
+    )
+    sig = abortSignal(false)
+
+    # Execute the full pipeline
+    batch = executeToolCallsSequential(
+        ctx, assistant_msg, tool_calls, config, sig, x -> nothing
+    )
+
+    @test batch.messages isa Vector{toolResultMessage}
+    @test length(batch.messages) == 2
+    @test batch.messages[1].toolName == "getWeather"
+    @test batch.messages[1].isError == false
+    @test occursin("Tokyo", batch.messages[1].content[1].text)
+    @test batch.messages[2].toolName == "getTime"
+    @test batch.messages[2].isError == false
+    @test occursin("Europe/London", batch.messages[2].content[1].text)
+end
+
+@testset "executeToolCallsParallel with static tools (full pipeline)" begin
+    # Same as above but tests parallel execution path.
+
+    store = toolStore(name="test_parallel")
+    register_all_tools(store)
+
+    tools = getTools(store)
+    ctx = agentContext(
+        "test system prompt",
+        agentMessage[],
+        tools
+    )
+
+    assistant_msg = assistantMessage(
+        role="assistant",
+        content=Vector{messageContent}(),
+        api="openai",
+        provider="test",
+        model="test-model",
+        usage=llmUsage(0, 0),
+        stopReason="tool_calls",
+        errorMessage=nothing,
+        timestamp=now()
+    )
+
+    tool_calls = [
+        agentToolCall(
+            "function", "call-par-1", "getWeather",
+            Dict{String,Any}("city" => "Paris")
+        ),
+        agentToolCall(
+            "function", "call-par-2", "getTime",
+            Dict{String,Any}("city" => "Sydney")
+        ),
+    ]
+
+    config = agentLoopConfig(
+        nothing, nothing, "parallel"
+    )
+    sig = abortSignal(false)
+
+    batch = executeToolCallsParallel(
+        ctx, assistant_msg, tool_calls, config, sig, x -> nothing
+    )
+
+    @test batch.messages isa Vector{toolResultMessage}
+    @test length(batch.messages) == 2
+    @test batch.messages[1].toolName == "getWeather"
+    @test batch.messages[1].isError == false
+    @test batch.messages[2].toolName == "getTime"
+    @test batch.messages[2].isError == false
+end

user_code.jl

@@ -0,0 +1,113 @@
+using Revise, JSON, Dates, UUIDs, PrettyPrinting, LibPQ, Base64, DataFrames, DataStructures, HTTP, Base64,
+      NATS, Base.Threads
+using YiemAgent, GeneralUtils, msghandler
+
+
+""" Debug 
+
+using JSON, NATS, msghandler
+using NATS
+
+conn = NATS.connect("nats.yiem.cc")
+
+sub = NATS.subscribe(conn, "sommanion.debug") do msg
+  payload = NATS.payload(msg)
+  @info "debug" payload
+
+  open("./log/error.log", "a") do io
+    println(io, payload)
+  end
+end
+
+NATS.publish(conn, "sommanion.debug", "order-123")
+
+
+# ---------------------------- inject this code into codebase to debug --------------------------- #
+try
+  batch = someFunction(x, y, z)
+catch e
+  bt = catch_backtrace()
+  err_msg = sprint() do io
+      showerror(io, e, bt)
+      println(io)
+  end
+
+  agentEventSink(err_msg)
+end
+
+"""
+
+struct text2textInstructLLM
+  natsConn::NATS.Connection
+  topic::String
+  senderID::String
+  fileserver_url::String
+end
+
+function (t::text2textInstructLLM)(openai_msg::Dict{String, Any})
+
+  payloads = [("msg", openai_msg, "dictionary")]  # List of tuples
+  _, msg_envelope_json_str = msghandler.smartpack(
+        t.topic, 
+        payloads;
+        sender_id=t.senderID,
+        msg_purpose="text2text",  
+        fileserver_url=t.fileserver_url)
+
+  reply = NATS.request(t.natsConn, t.topic, msg_envelope_json_str, timeout=180)
+
+  incoming_env_json_str = String(reply.payload)
+  incoming_env = msghandler.smartunpack(incoming_env_json_str)
+  _llm_response = incoming_env["payloads"][1][2]
+  llm_response = _llm_response["choices"][1]
+
+  return llm_response
+end
+
+
+
+struct agentEventSink
+  natsConn::NATS.Connection
+  topic::String
+  senderID::String
+end
+
+function (aes::agentEventSink)(msg::String)
+  NATS.publish(aes.natsConn, aes.topic, msg)
+end
+
+
+
+config = JSON.parsefile("./appconfig.json")
+agent_conn  = NATS.connect(config["nats_server_info"]["url"])
+
+
+#WORKING load tools
+text2text_llm = text2textInstructLLM(agent_conn, 
+                                    config["externalservice"]["servicesloadbalancer"]["nats"], 
+                                    "sender", 
+                                    config["externalservice"]["fileserver"]["url"])
+
+debugNats = agentEventSink(agent_conn, "sommanion.debug", "sender")
+
+agent = YiemAgent.yiemAgent(
+  text2text_llm;
+  agentEventSink=debugNats
+)
+
+msg = Dict(
+        "role" => "user",
+        "content" => [
+          Dict("type" => "text", "text" => "What's the weather in Bangkok?"),
+          # Dict(
+          #   "type" => "image_url",
+          #   "image_url" => Dict("url" => "data:mime_type;base64,image2_base64_string")
+          # ),
+        ]
+      )
+      
+push!(agent.inputChannel, msg)
+
+
+
+