update

src/agentCore.jl

@@ -3,7 +3,7 @@ module agentCore
 export yiemAgent, _agentLoop, OpenAiToUserMessage
 
 using JSON, DataStructures, Dates, UUIDs, HTTP, Random, PrettyPrinting, Serialization,
-      DataFrames, Base.Threads
+      DataFrames, Base.Threads, NATS
 using GeneralUtils
 using ..type, ..utils, ..toolRegistry
 
@@ -342,20 +342,23 @@ function _processMessage(
   agentEventSink("_processMessage 1")
   # loop until llmCall() response didn't use tool calls
   final_response = nothing
+
+  """ example message in inputChannel
+  Dict(
+      "role" => "user",
+      "content" => [
+        Dict("type" => "text", "text" => "Do you have something similar to the one in the image?"),
+        Dict(
+          "type" => "image_url",
+          "image_url" => Dict("url" => "data:mime_type;base64,image2_base64_string")
+        ),
+      ]
+    )
+  """
+
   while true
 
-    """ example message in inputChannel
+    
-    Dict(
-        "role" => "user",
-        "content" => [
-          Dict("type" => "text", "text" => "Do you have something similar to the one in the image?"),
-          Dict(
-            "type" => "image_url",
-            "image_url" => Dict("url" => "data:mime_type;base64,image2_base64_string")
-          ),
-        ]
-      )
-    """
 
     # Drain inputChannel and convert OpenAI-format messages to userMessage type
     while isready(inputChannel)
@@ -377,22 +380,26 @@ function _processMessage(
     # call prepareContext()
     state = agentState(systemPrompt, nothing, tools, messages)
     agentEventSink("_processMessage 8")
-    preparedContext = prepareContext(state)
+    preparedContext = prepareContext(state, agentEventSink)
     agentEventSink("_processMessage 8")
     # Call formatMessagesForLLM() to format for LLM
-    formattedMessages = formatMessagesForLLM(preparedContext)
+    formattedMessages = formatMessagesForLLM(preparedContext, agentEventSink)
 
     agentEventSink("_processMessage 10")
     # Call llmCall() (blocking — the task waits here)
     response = llmCall(formattedMessages)
-    agentEventSink(response)
+
+    """ response example
+    response = JSON.Object{String, Any}("finish_reason" => "tool_calls", "index" => 0, "message" => JSON.Object{String, Any}("role" => "assistant", "content" => "", "reasoning_content" => "Here's a thinking process:\n\n1.  **Identify User Request**: The user is asking for the weather in Bangkok.\n2.  **Locate Relevant Tool**: I have a `getWeather` function available.\n3.  **Check Function Parameters**:\n   - `city` (required): City and country, e.g., 'San Francisco, CA' or 'Tokyo, Japan'\n   - `units` (optional, default \"celsius\"): Temperature scale (\"celsius\" or \"fahrenheit\")\n4.  **Prepare Parameters**:\n   - `city`: \"Bangkok, Thailand\" (adding country for clarity, though just \"Bangkok\" might work, following the example format is safer)\n   - `units`: Not specified, so I'll use the default (\"celsius\")\n5.  **Execute Tool Call**: Call `getWeather` with `city: \"Bangkok, Thailand\"`\n6.  **Anticipate Response**: The function will return current weather and forecast data for Bangkok. I'll then format it nicely for the user.\n   - *Self-Correction/Verification during thought*: The prompt says \"city: City and country, e.g., 'San Francisco, CA' or 'Tokyo, Japan'\". I'll use \"Bangkok, Thailand\". The `units` parameter is optional, so I'll omit it to use the default.\n   - Proceed with tool call.✅\n", "tool_calls" => Any[JSON.Object{String, Any}("type" => "function", "function" => JSON.Object{String, Any}("name" => "getWeather", "arguments" => "{\"city\":\"Bangkok, Thailand\"}"), "id" => "6fOilR5QPcdppbAAHluhkRyUDu3oWMAL")]))
+    """
+
+    agentEventSink(string(response))
     agentEventSink("_processMessage 11")
-    error("debug marker")
+    #WORKING Check if LLM used tool calls (inspect content for tool_call blocks)
-    # Check if LLM used tool calls (inspect content for tool_call blocks)
     hasToolCalls = false
     toolCallList = agentToolCall[]
 
-    for content_block in response.content
+    for content_block in response.content # extract response
       if content_block isa Dict
         if get(content_block, :type, "") == "tool_calls"
           hasToolCalls = true

src/type.jl

@@ -291,7 +291,7 @@ 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 +299,7 @@ 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
 end
 
 

src/utils.jl

@@ -2,10 +2,10 @@ module utils
 
 export clearhistory, availableWineToText, prepareContext, formatMsgForLLM, validateRequiredArgs, 
       validateToolArguments, _userMessageToOpenAI, 
-      _assistantMessageToOpenAI, _toolResultMessageToOpenAI, _messageContentToBlocks,
+      _assistantMessageToOpenAI, _toolResultMessageToOpenAI, _messageContentToBlocks, _toolsToOpenAI,
       beforeToolCall, afterToolCall, agentEventSink
 
-using UUIDs, Dates, DataStructures, HTTP, JSON
+using UUIDs, Dates, DataStructures, HTTP, JSON, NATS
 using GeneralUtils
 using ..type
 
@@ -75,7 +75,6 @@ function availableWineToText(vecd::Vector)::String
 end
 
 
-
 """
     prepareContext(state::agentState) -> agentContext
 
@@ -110,7 +109,7 @@ prepareContext(state).messages == deepcopy(state.messages)
 # end
 ```
 """
-function prepareContext(state::agentState)::agentContext
+function prepareContext(state::agentState, agentEventSink)::agentContext
   
   #TODO filter tools from state.tools based on user intend in user message and tool description
   filteredTools = state.tools
@@ -157,7 +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(
@@ -185,18 +184,12 @@ function formatMsgForLLM(ctx::agentContext)::Dict{String, Any}
           Dict("type" => "text", "text" => "let me check."),
         ]
       ),
-      Dict(
-        "role" => "toolResult",
-        "content" => [
-          Dict("type" => "text", "text" => "name: Chateau Montelena ..."),
-        ]
-      ),
     ],
     "tools"=> [
       Dict(
         "type" => "function",
         "function" => Dict(
-          "name" => "get_weather",
+          "name" => "getWeather",
           "description" => "Get current weather",
           "parameters" => Dict(
             "type" => "object",
@@ -212,8 +205,10 @@ function formatMsgForLLM(ctx::agentContext)::Dict{String, Any}
   )
   """
 
+  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(
@@ -221,7 +216,7 @@ 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
@@ -232,14 +227,18 @@ function formatMsgForLLM(ctx::agentContext)::Dict{String, Any}
       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
 
-  #WORKING convert ctx.tools into openai's tools format.
+  if !isempty(tools_array)
-  # ctx.tools has the following format
+    openaiReadyMsg["tools"] = tools_array
-  # tools = OrderedDict{String, YiemAgent.type.agentTool}("getTime" => YiemAgent.type.agentTool("getTime", "Time Lookup", "Get current local time for a timezone or city.", Dict{String, Any}("properties" => Dict("city" => Dict("type" => "string", "description" => "City name as fallback"), "timezone" => Dict("type" => "string", "description" => "IANA timezone, e.g. 'America/New_York'")), "required" => Any[], "type" => "object"), YiemAgent.toolRegistry._tool_getTime.executeTool, nothing, YiemAgent.toolRegistry._tool_getTime.validateRequiredArgs, false), "getWeather" => YiemAgent.type.agentTool("getWeather", "Weather Lookup", "Fetch current weather and forecast for a given city.", Dict{String, Any}("properties" => Dict{String, Dict{String}}("units" => Dict{String, Any}("default" => "celsius", "type" => "string", "description" => "Temperature scale", "enum" => ["celsius", "fahrenheit"]), "city" => Dict("type" => "string", "description" => "City and country, e.g., 'San Francisco, CA' or 'Tokyo, Japan'")), "required" => ["city"], "type" => "object"), YiemAgent.toolRegistry._tool_getWeather.executeTool, nothing, nothing, false), "listTools" => YiemAgent.type.agentTool("listTools", "List Tools", "List all available tools with their names, labels, and descriptions. Use this before creating a new tool to check for name collisions.", Dict{String, Any}("properties" => Dict{String, Any}(), "required" => Any[], "type" => "object"), YiemAgent.toolRegistry.var"#listTool##0#listTool##1"{YiemAgent.toolRegistry.toolStore}(YiemAgent.toolRegistry.toolStore(OrderedDict{String, YiemAgent.type.agentTool}(#= circular reference @-4 =#), "myagent")), nothing, nothing, false))
+  end
-  
 
-
+  return openaiReadyMsg
-  return Dict("messages" => messages)
 end
 
 #TODO
@@ -331,6 +330,40 @@ 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}