Update app.py

app.py

@@ -58,17 +58,69 @@ class AIAssistant:
     async def initialize(self):
         self.available_tools = await self.mcp_client.list_tools()
 
+    def get_system_prompt(self) -> str:
+        tools_description = "\n".join([
+            f"- {tool['name']}: {tool['description']}"
+            for tool in self.available_tools
+        ])
+        return f"""You are an AI assistant with access to tools:
+{tools_description}
+
+Use these tools explicitly if user queries require external data. 
+
+Respond with 'CALL_TOOL: tool_name(parameter=value)' to invoke tools.
+"""
+
+    def extract_tool_calls(self, response: str) -> List[Dict[str, Any]]:
+        tool_calls = []
+        lines = response.split('\n')
+        for line in lines:
+            if line.startswith('CALL_TOOL:'):
+                tool_part = line[len('CALL_TOOL:'):].strip()
+                tool_name, args = tool_part.split('(', 1)
+                args = args.rstrip(')')
+                arg_dict = {}
+                for arg in args.split(','):
+                    key, value = arg.split('=')
+                    arg_dict[key.strip()] = value.strip().strip('"\'')
+                tool_calls.append({'name': tool_name.strip(), 'arguments': arg_dict})
+        return tool_calls
+
     async def process_message(self, user_message: str) -> Tuple[str, str]:
-        try:
-            response = self.openai_client.chat.completions.create(
+        messages = [
+            {"role": "system", "content": self.get_system_prompt()},
+            {"role": "user", "content": user_message}
+        ]
+        response = self.openai_client.chat.completions.create(
+            model="gpt-3.5-turbo",
+            messages=messages,
+            temperature=0
+        )
+        ai_response = response.choices[0].message.content
+        tool_calls = self.extract_tool_calls(ai_response)
+
+        tool_info = ""
+        if tool_calls:
+            tool_results = []
+            for call in tool_calls:
+                result = await self.mcp_client.call_tool(call['name'], call['arguments'])
+                tool_results.append(result)
+                tool_info += f"Called {call['name']}: {result}\n"
+
+            # Let AI interpret the tool results
+            final_messages = messages + [
+                {"role": "assistant", "content": ai_response},
+                {"role": "user", "content": f"Tool results:\n{json.dumps(tool_results)}"}
+            ]
+
+            final_response = self.openai_client.chat.completions.create(
                 model="gpt-3.5-turbo",
-                messages=[{"role": "user", "content": user_message}],
-                temperature=0.7,
-                max_tokens=1000
+                messages=final_messages,
+                temperature=0
             )
-            return response.choices[0].message.content, ""
-        except Exception as e:
-            return f"❌ Error: {str(e)}", ""
+            return final_response.choices[0].message.content, tool_info
+
+        return ai_response, ""
 
 
 # Globals