Remove comments from agent examples

Author: leawn

agent_tool/src/agents/chat_tool_functions.py

@@ -1,4 +1,3 @@
-# ruff: noqa: ERA001
 from datetime import timedelta
 
 from pydantic import BaseModel
@@ -9,8 +8,6 @@
 
     from src.functions.llm_chat import LlmChatInput, Message, llm_chat
     from src.functions.lookup_sales import LookupSalesInput, lookup_sales
-    # Step 2: Import your new function to the agent
-    # from src.functions.new_function import new_function, FunctionInput, FunctionOutput
 
 
 class MessageEvent(BaseModel):
@@ -37,15 +34,8 @@ async def message(self, message: MessageEvent) -> list[Message]:
                 name=lookup_sales.__name__,
                 description="Lookup sales for a given category",
             ),
-            # Step 3 Add your new function to the tools list and adjust the system prompt
-            # pydantic_function_tool(
-            #     model=FunctionInput,
-            #     name=new_function.__name__,
-            #     description="A function to talk to an ERP to get the latest sales data"
-            # )
         ]
 
-        # Change the system prompt to the agent
         system_content = "You are a helpful assistant that can help with sales data."
 
         self.messages.append(Message(role="user", content=message.content or ""))
@@ -113,19 +103,6 @@ async def message(self, message: MessageEvent) -> list[Message]:
                                 or "",
                             )
                         )
-
-                    ## Step 4: Add your new function to the match case and append the result to the messages
-                    # case new_function.__name__:
-                    #     args = FunctionInput.model_validate_json(tool_call.function.arguments)
-
-                    #     log.info(f"calling {name} with args: {args}")
-
-                    #     result = await workflow.step(new_function, input=FunctionInput(message=args.message), start_to_close_timeout=timedelta(seconds=120))
-                    #     self.messages.append(Message(role="tool", tool_call_id=tool_call.id, content=str(result)))
-
-                    #     completion_with_tool_call = await workflow.step(llm_chat, LlmChatInput(messages=self.messages), start_to_close_timeout=timedelta(seconds=120))
-                    #     self.messages.append(Message(role="assistant", content=completion_with_tool_call.choices[0].message.content or ""))
-
         else:
             pass
 

agent_tool/src/functions/new_function.py

@@ -1,4 +1,3 @@
-# ruff: noqa: ERA001
 import asyncio
 import logging
 import webbrowser
@@ -11,14 +10,10 @@
 from src.functions.llm_chat import llm_chat
 from src.functions.lookup_sales import lookup_sales
 
-# Step 5: Import a new function to tool calling here
-# from src.functions.new_function import new_function, FunctionInput, FunctionOutput
-
 
 async def main() -> None:
     await client.start_service(
         agents=[AgentChatToolFunctions],
-        ## Step 6: Add your new function to the functions list -> functions=[lookupSales, llm_chat, new_function]
         functions=[lookup_sales, llm_chat],
     )