Update app.py

app.py

@@ -5,9 +5,7 @@ import asyncio, json, os, sys
 from dotenv import load_dotenv
 from langchain_core.tools import Tool
 from langchain_groq import ChatGroq
-from langgraph.prebuilt import create_react_agent
-from langchain.agents import create_tool_calling_agent
-from langchain.tools import convert_to_openai_tool
+from langgraph.prebuilt import create_react_agent  # Keep this (works fine)
 
 load_dotenv()
 
@@ -30,7 +28,7 @@ class MCPClient:
                 "params": params or {},
                 "id": self._req_id,
             }
-            self.process.stdin.write(json.dumps(request).encode() + b'\n')
+            self.process.stdin.write(json.dumps(request).encode() + b"\n")
             await self.process.stdin.drain()
 
             while line := await self.process.stdout.readline():
@@ -52,7 +50,7 @@ class MCPClient:
             Tool(
                 name=s['name'],
                 description=s['description'],
-                func=None,  # <-- CRITICAL FIX: Add func=None for async tools
+                func=None,
                 coroutine=self._create_tool_coro(s['name']),
                 args_schema=s['args_schema']
             )
@@ -62,8 +60,7 @@ class MCPClient:
     def _create_tool_coro(self, tool_name: str):
         async def _tool_coro(tool_input):
             return await self._send_request(
-                "execute",
-                {"tool_name": tool_name, "tool_args": tool_input}
+                "execute", {"tool_name": tool_name, "tool_args": tool_input}
             )
         return _tool_coro
 
@@ -78,25 +75,20 @@ async def get_agent_executor():
             raise ValueError("GROQ_API_KEY secret not set.")
         
         client = MCPClient(command=sys.executable, args=["server.py"])
-        tools_raw = await client.get_tools()
-
-        # Convert to OpenAI-compatible structured tools (CRITICAL FIX)
-        tools = [convert_to_openai_tool(t) for t in tools_raw]
+        tools = await client.get_tools()
 
         model = ChatGroq(model="openai/gpt-oss-20b")
-
-        # Stick to create_react_agent (compatible with your LangChain version)
+        
+        # Keep create_react_agent (compatible with your environment)
         _agent_executor = create_react_agent(model, tools)
 
     return _agent_executor
 
 
-
 # --- Gradio Chat Logic ---
 async def respond_to_chat(message: str, history: list):
     agent = await get_agent_executor()
 
-    # Convert history to LangChain format
     history_langchain_format = []
     for human, ai in history:
         history_langchain_format.append({"role": "user", "content": human})
@@ -112,7 +104,7 @@ async def respond_to_chat(message: str, history: list):
         return "Sorry, an error occurred while processing your request."
 
 
-# --- Gradio User Interface ---
+# --- UI ---
 demo = gr.ChatInterface(
     fn=respond_to_chat,
     title="Gold & Silver AI Forecast",
@@ -123,7 +115,5 @@ demo = gr.ChatInterface(
     ]
 )
 
-
-# --- Start the App ---
 if __name__ == "__main__":
     demo.launch()