update

src/agentCore.jl

@@ -5,7 +5,7 @@ export yiemAgent, _agent_loop, OpenAiToUserMessage
 using JSON, DataStructures, Dates, UUIDs, HTTP, Random, PrettyPrinting, Serialization,
       DataFrames, Base.Threads
 using GeneralUtils
-using ..type, ..utils
+using ..type, ..utils, ..toolRegistry
 
 # ---------------------------------------------- 100 --------------------------------------------- #
 
@@ -85,7 +85,7 @@ on `inputChannel` and `followUpChannel` channels concurrently.
 """
 function yiemAgent(
   toolsFolderPath::String,
-  llmCall::Function,
+  llmCall,
   ; 
   systemPrompt::String="You are helpful assistant.",
   model=nothing,
@@ -107,12 +107,12 @@ function yiemAgent(
   outputChannel   = Channel(16)
 
   # load tools from toolsFolderPath
-  toolStore = YiemAgent.toolStore(name="myagent")
-  loadTools(toolStore, toolsFolderPath)
+  toolStore1 = toolStore(name="myagent")
+  loadTools(toolStore1, toolsFolderPath)
 
   # Create struct with a placeholder task, then spawn and replace it
   agent = yiemAgent(
-    agentState(systemPrompt, model, getTools(toolStore), messages),
+    agentState(systemPrompt, model, getTools(toolStore1), messages),
     inputChannel,
     followUp,
     outputChannel,

src/type.jl

@@ -144,7 +144,7 @@ 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)
 end
@@ -309,7 +309,7 @@ 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
@@ -341,21 +341,21 @@ 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=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[],
 )
-    agentState(
-      systemPrompt,
-      model,
-      deepcopy(tools),
-      deepcopy(messages),
-      Vector{String}(),
-      false,
-      nothing,
-    )
+  agentState(
+    systemPrompt,
+    model,
+    deepcopy(tools),
+    deepcopy(messages),
+    Vector{String}(),
+    false,
+    nothing,
+  )
 end