commit

agent.py

@@ -216,23 +216,11 @@ def build_graph(provider: str = "groq"):
 if __name__ == "__main__":
     question = "When was a picture of St. Thomas Aquinas first added to the Wikipedia page on the Principle of double effect?"
     # Build the graph
-    graph = build_graph(provider="huggingface") # This needs to actually use the provider
+    graph = build_graph(provider="groq")
     # Run the graph
-    initial_messages = [sys_msg, HumanMessage(content=question)] # PREPEND sys_msg HERE
-    
-    print("Invoking graph with initial messages:")
-    for m in initial_messages:
+    messages = [HumanMessage(content=question)]
+    messages = graph.invoke({"messages": messages})
+    for m in messages["messages"]:
         m.pretty_print()
-    print("-" * 20)
-
-    result_messages = graph.invoke({"messages": initial_messages})
-    
-    print("\nFinal Graph Output:")
-    if result_messages and "messages" in result_messages:
-        for m in result_messages["messages"]:
-            m.pretty_print()
-    else:
-        print("Graph did not return expected messages structure.")
-        print(f"Raw output: {result_messages}")
 
 

app.py

@@ -21,84 +21,15 @@ class BasicAgent:
     """A langgraph agent."""
     def __init__(self):
         print("BasicAgent initialized.")
-        # Assumes build_graph() and sys_msg are available from your agent.py
-        # You need to import them here.
-        # from your_agent_file import build_graph, sys_msg as agent_system_message
-        # self.graph = build_graph()
-        # self.system_message = agent_system_message
-
-        # Let's assume for now agent.py is structured to be imported like this:
-        # Option 1: if agent.py defines them globally
-        # from agent import build_graph, sys_msg
-        # self.graph = build_graph(provider="huggingface") # Or your desired provider
-        # self.sys_msg_for_graph = sys_msg
-
-        # Option 2: If build_graph also returns the sys_msg or if sys_msg is part of the graph object
-        # This depends on how you refactor agent.py for importability
-
-        # For this example, I'll assume you import them directly:
-        from agent import build_graph, sys_msg as agent_sys_msg # Make sure agent.py is in PYTHONPATH or same dir
-        
-        self.graph = build_graph(provider="huggingface") # Specify the provider
-        self.agent_system_message = agent_sys_msg
-
+        self.graph = build_graph()
 
     def __call__(self, question: str) -> str:
         print(f"Agent received question (first 50 chars): {question[:50]}...")
-        
-        # INCORRECT INVOCATION:
-        # messages = [HumanMessage(content=question)] # <-- MISSING SYSTEM MESSAGE
-        # messages = self.graph.invoke({"messages": messages})
-
-        # CORRECTED INVOCATION:
-        # You MUST include the system message that was loaded in agent.py
-        initial_graph_messages = [self.agent_system_message, HumanMessage(content=question)]
-        
-        print("Invoking graph with (system_message + human_question):")
-        # Optional: print the messages being sent for debugging
-        # for m in initial_graph_messages:
-        #     m.pretty_print()
-        # print("-" * 20)
-
-        try:
-            graph_output = self.graph.invoke({"messages": initial_graph_messages})
-        except Exception as e:
-            # This will catch the StopIteration if it propagates from the graph
-            print(f"ERROR during graph.invoke: {e}")
-            # Depending on how your outer loop handles errors,
-            # you might want to return a specific error string or re-raise
-            # For the Hugging Face course, it expects the AGENT ERROR string.
-            # The run_and_submit_all function already handles this by catching exceptions from agent().
-            raise  # Re-raise the exception to be caught by run_and_submit_all
-
-        # Parsing the answer
-        if graph_output and "messages" in graph_output and graph_output["messages"]:
-            final_ai_message = graph_output["messages"][-1] # Get the last message
-            
-            # Debug: print the final AI message object
-            # print("Final AI Message Object from Graph:")
-            # final_ai_message.pretty_print()
-
-            if hasattr(final_ai_message, 'content'):
-                raw_answer = str(final_ai_message.content)
-                
-                # Your specific parsing: "answer = messages['messages'][-1].content; return answer[14:]"
-                # This assumes the answer ALWAYS starts with "FINAL ANSWER: " (14 characters)
-                if raw_answer.upper().startswith("FINAL ANSWER: "):
-                    answer = raw_answer[14:].strip() # Remove "FINAL ANSWER: " and leading/trailing whitespace
-                else:
-                    # The LLM didn't follow the "FINAL ANSWER: " format
-                    print(f"Warning: LLM output did not start with 'FINAL ANSWER: '. Raw output: '{raw_answer}'")
-                    answer = raw_answer # Return the raw answer if format is not met, or handle as error
-            else:
-                answer = "Agent Error: Final message from graph has no content."
-                print(f"Final message object was: {final_ai_message}")
-        else:
-            answer = "Agent Error: Graph did not return expected messages structure."
-            print(f"Raw graph output: {graph_output}")
-            
-        print(f"Agent returning answer: {answer}")
-        return answer
+        # Wrap the question in a HumanMessage from langchain_core
+        messages = [HumanMessage(content=question)]
+        messages = self.graph.invoke({"messages": messages})
+        answer = messages['messages'][-1].content
+        return answer[14:]
 
 
 def run_and_submit_all( profile: gr.OAuthProfile | None):