Update server/client.py

server/client.py

@@ -1,72 +1,29 @@
-import asyncio
-
-from dotenv import load_dotenv
-from langchain_groq import ChatGroq
-
-from mcp_use import MCPAgent, MCPClient
-import os
-
-async def run_memory_chat():
-    """Run a chat using MCPAgent's built-in conversation memory."""
-    # Load environment variables for API keys
-    load_dotenv()
-    os.environ["GROQ_API_KEY"]=os.getenv("GROQ_API_KEY")
-
-    # Config file path - change this to your config file
-    config_file = "server/weather.json"
-
-    print("Initializing chat...")
-
-    # Create MCP client and agent with memory enabled
-    client = MCPClient.from_config_file(config_file)
-    llm = ChatGroq(model="qwen-qwq-32b")
-
-    # Create agent with memory_enabled=True
-    agent = MCPAgent(
-        llm=llm,
-        client=client,
-        max_steps=15,
-        memory_enabled=True,  # Enable built-in conversation memory
-    )
-
-    print("\n===== Interactive MCP Chat =====")
-    print("Type 'exit' or 'quit' to end the conversation")
-    print("Type 'clear' to clear conversation history")
-    print("==================================\n")
-
-    try:
-        # Main chat loop
-        while True:
-            # Get user input
-            user_input = input("\nYou: ")
-
-            # Check for exit command
-            if user_input.lower() in ["exit", "quit"]:
-                print("Ending conversation...")
-                break
-
-            # Check for clear history command
-            if user_input.lower() == "clear":
-                agent.clear_conversation_history()
-                print("Conversation history cleared.")
-                continue
-
-            # Get response from agent
-            print("\nAssistant: ", end="", flush=True)
-
-            try:
-                # Run the agent with the user input (memory handling is automatic)
-                response = await agent.run(user_input)
-                print(response)
-
-            except Exception as e:
-                print(f"\nError: {e}")
-
-    finally:
-        # Clean up
-        if client and client.sessions:
-            await client.close_all_sessions()
-
-
-if __name__ == "__main__":
-    asyncio.run(run_memory_chat())
+ import asyncio
+from dotenv import load_dotenv
+from langchain_groq import ChatGroq
+from mcp_use import MCPAgent, MCPClient
+import os
+
+# Load env once
+load_dotenv()
+os.environ["GROQ_API_KEY"] = os.getenv("GROQ_API_KEY")
+
+# Initialize MCP client and agent once (memory preserved)
+CONFIG_FILE = "server/weather.json"
+client = MCPClient.from_config_file(CONFIG_FILE)
+llm = ChatGroq(model="qwen-qwq-32b")
+
+agent = MCPAgent(
+    llm=llm,
+    client=client,
+    max_steps=15,
+    memory_enabled=True  # Keep memory for conversation
+)
+
+async def run_memory_chat(question: str) -> str:
+    """Run a single question through the MCPAgent and get a response."""
+    try:
+        response = await agent.run(question)
+        return response
+    except Exception as e:
+        return f"Error: {e}"