Update agent.py

agent.py

@@ -49,43 +49,43 @@ def real_number_calculator(
 
 
 
-    class TestAgent:
-        def __init__(self):
-            
-            # import code agent and basic tool from smolagent
-            from smolagents import CodeAgent, OpenAIServerModel, DuckDuckGoSearchTool, FinalAnswerTool, VisitWebpageTool, MCPServerTool
-
-            # import additional tool from langchain @ https://docs.langchain.com/oss/python/integrations/tools
-            from langchain.agents import load_tools
-            from smolagents import Tool
-            wikipedia_tool = Tool.from_langchain(load_tools(["wikipedia"])[0])
-            wikipedia_tool.top_k_results=3
-
-            # import tools from MCP servers @ https://github.com/mcp
-            from mcp import StdioServerParameters
-            server_parameters = StdioServerParameters(command="uvx",
-                                                      args=["--quiet", "youtubeqa@0.2.1"],
-                                                      env={"UV_PYTHON": "3.12", **os.environ},
-                                                     )
-            youtube_tools = MCPServerTool(server_params=server_parameters)
-
-            model = OpenAIServerModel(model_id="gpt-4o")
-            #model = InferenceClientModel("Qwen/Qwen2.5-Coder-32B-Instruct")
-            # Instantiate the agent
-            self.agent = CodeAgent(
-                tools=[real_number_calculator(),        # homemade tool
-                       DuckDuckGoSearchTool(),          # basic tools from smolagent
-                       VisitWebpageTool(),
-                       wikipedia_tool,                  # tool from langchain with extra parmaeters
-                       youtube_tools,                   # tool from MCP server
-                       FinalAnswerTool()],
-                model=model,
-                max_steps=3,
-                verbosity_level=2
-            )
-
-        def __call__(self, question: str) -> str:
-            print(f"Agent received question (first 50 chars): {question[:50]}...")
-            answer = self.agent.invoke(question)
-            print(f"Agent returning his answer: {answer}")
-            return answer
+class TestAgent:
+    def __init__(self):
+        
+        # import code agent and basic tool from smolagent
+        from smolagents import CodeAgent, OpenAIServerModel, DuckDuckGoSearchTool, FinalAnswerTool, VisitWebpageTool, MCPServerTool
+
+        # import additional tool from langchain @ https://docs.langchain.com/oss/python/integrations/tools
+        from langchain.agents import load_tools
+        from smolagents import Tool
+        wikipedia_tool = Tool.from_langchain(load_tools(["wikipedia"])[0])
+        wikipedia_tool.top_k_results=3
+
+        # import tools from MCP servers @ https://github.com/mcp
+        from mcp import StdioServerParameters
+        server_parameters = StdioServerParameters(command="uvx",
+                                                  args=["--quiet", "youtubeqa@0.2.1"],
+                                                  env={"UV_PYTHON": "3.12", **os.environ},
+                                                 )
+        youtube_tools = MCPServerTool(server_params=server_parameters)
+
+        model = OpenAIServerModel(model_id="gpt-4o")
+        #model = InferenceClientModel("Qwen/Qwen2.5-Coder-32B-Instruct")
+        # Instantiate the agent
+        self.agent = CodeAgent(
+            tools=[real_number_calculator(),        # homemade tool
+                   DuckDuckGoSearchTool(),          # basic tools from smolagent
+                   VisitWebpageTool(),
+                   wikipedia_tool,                  # tool from langchain with extra parmaeters
+                   youtube_tools,                   # tool from MCP server
+                   FinalAnswerTool()],
+            model=model,
+            max_steps=3,
+            verbosity_level=2
+        )
+
+    def __call__(self, question: str) -> str:
+        print(f"Agent received question (first 50 chars): {question[:50]}...")
+        answer = self.agent.invoke(question)
+        print(f"Agent returning his answer: {answer}")
+        return answer