Comments in submission in app.py

agent.py

@@ -1,72 +1,28 @@
-#import os
-#from PIL import Image
-#from smolagents import CodeAgent, HfApiModel, InferenceClientModel
+import os
+from PIL import Image
+from smolagents import CodeAgent, HfApiModel, InferenceClientModel
 
-#import tools.tools as tls
+import tools.tools as tls
 
 # --- Basic Agent Definition ---
 # ----- THIS IS WERE YOU CAN BUILD WHAT YOU WANT ------
 
-#class BasicAgent:
-#    def __init__(self):
-#        print("BasicAgent initialized.")
-#    def __call__(self, question: str) -> str:
-#        model = HfApiModel(model_id="https://pflgm2locj2t89co.us-east-1.aws.endpoints.huggingface.cloud", provider="together", use_auth_token=True)
-#
-#        agent = CodeAgent(
-#            tools=[tls.search_tool, tls.calculate_cargo_travel_time],
-#            model=InferenceClientModel(),
-#            additional_authorized_imports=["pandas"],
-#            max_steps=20,
-#        )
-
-#        fixed_answer = agent.run(question)
-
-#        print(f"Agent received question (first 50 chars): {question[:50]}...")
-#        # fixed_answer = "This is a default answer."
-#        print(f"Agent returning fixed answer: {fixed_answer}")
-#        return str(fixed_answer)
-
-
-# agent.py
-import os
-from smolagents import CodeAgent, InferenceClientModel, HfApiModel
-import tools.tools as tls
-
 class BasicAgent:
     def __init__(self):
-        print("✅ BasicAgent initialized.")
-        
-        # Initialize model (e.g. HfApiModel or InferenceClientModel)
-        self.model = HfApiModel(
-            model_id="https://pflgm2locj2t89co.us-east-1.aws.endpoints.huggingface.cloud",
-            provider="together",
-            use_auth_token=True
-        )
+        print("BasicAgent initialized.")
+    def __call__(self, question: str) -> str:
+        model = HfApiModel(model_id="https://pflgm2locj2t89co.us-east-1.aws.endpoints.huggingface.cloud", provider="together", use_auth_token=True)
 
-        # Initialize agent once
-        self.agent = CodeAgent(
+        agent = CodeAgent(
             tools=[tls.search_tool, tls.calculate_cargo_travel_time],
-            model=self.model,  # <-- use self.model instead of re-instantiating
+            model=InferenceClientModel(),
             additional_authorized_imports=["pandas"],
-            max_steps=20
+            max_steps=20,
         )
 
-        self.chat_history = []  # Optional: for memory support later
-
-    def __call__(self, question: str) -> str:
-        print(f"\n🧠 Received question: {question[:50]}...")
-
-        # Optionally include memory
-        context = "\n".join([f"User: {u}\nAssistant: {a}" for u, a in self.chat_history])
-        prompt = f"{context}\nUser: {question}\nAssistant:".strip()
-
-        try:
-            response = self.agent.run(prompt)
-        except Exception as e:
-            response = f"[Agent Error]: {e}"
-
-        self.chat_history.append((question, response))
+        fixed_answer = agent.run(question)
 
-        print("📤 Returning answer:", response[:80])
-        return response
+        print(f"Agent received question (first 50 chars): {question[:50]}...")
+        # fixed_answer = "This is a default answer."
+        print(f"Agent returning fixed answer: {fixed_answer}")
+        return str(fixed_answer)

app.py

@@ -62,6 +62,7 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
         print(f"An unexpected error occurred fetching questions: {e}")
         return f"An unexpected error occurred fetching questions: {e}", None
 
+
     # 3. Run your Agent
     results_log = []
     answers_payload = []
@@ -83,53 +84,56 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
     if not answers_payload:
         print("Agent did not produce any answers to submit.")
         return "Agent did not produce any answers to submit.", pd.DataFrame(results_log)
-
+        
+'''
     # 4. Prepare Submission 
-    #submission_data = {"username": username.strip(), "agent_code": agent_code, "answers": answers_payload}
-    #status_update = f"Agent finished. Submitting {len(answers_payload)} answers for user '{username}'..."
-    #print(status_update)
+    submission_data = {"username": username.strip(), "agent_code": agent_code, "answers": answers_payload}
+    status_update = f"Agent finished. Submitting {len(answers_payload)} answers for user '{username}'..."
+    print(status_update)
 
     # 5. Submit
-    #print(f"Submitting {len(answers_payload)} answers to: {submit_url}")
-    #try:
-    #    response = requests.post(submit_url, json=submission_data, timeout=60)
-    #    response.raise_for_status()
-    #    result_data = response.json()
-    #    final_status = (
-    #        f"Submission Successful!\n"
-    #        f"User: {result_data.get('username')}\n"
-    #        f"Overall Score: {result_data.get('score', 'N/A')}% "
-    #        f"({result_data.get('correct_count', '?')}/{result_data.get('total_attempted', '?')} correct)\n"
-    #        f"Message: {result_data.get('message', 'No message received.')}"
-    #    )
-    #    print("Submission successful.")
-    #    results_df = pd.DataFrame(results_log)
-    #    return final_status, results_df
-    #except requests.exceptions.HTTPError as e:
-    #    error_detail = f"Server responded with status {e.response.status_code}."
-    #    try:
-    #        error_json = e.response.json()
-    #        error_detail += f" Detail: {error_json.get('detail', e.response.text)}"
-    #    except requests.exceptions.JSONDecodeError:
-    #       error_detail += f" Response: {e.response.text[:500]}"
-    #   print(status_message)
-    #    results_df = pd.DataFrame(results_log)
-    #    return status_message, results_df
-    #except requests.exceptions.Timeout:
-    #    status_message = "Submission Failed: The request timed out."
-    #    print(status_message)
-    #    results_df = pd.DataFrame(results_log)
-    #    return status_message, results_df
-    #except requests.exceptions.RequestException as e:
-    #    status_message = f"Submission Failed: Network error - {e}"
-    #    print(status_message)
-    #    results_df = pd.DataFrame(results_log)
-    #    return status_message, results_df
-    #except Exception as e:
-    #    status_message = f"An unexpected error occurred during submission: {e}"
-    #    print(status_message)
-    #    results_df = pd.DataFrame(results_log)
-    #    return status_message, results_df
+    print(f"Submitting {len(answers_payload)} answers to: {submit_url}")
+    try:
+        response = requests.post(submit_url, json=submission_data, timeout=60)
+        response.raise_for_status()
+        result_data = response.json()
+        final_status = (
+            f"Submission Successful!\n"
+            f"User: {result_data.get('username')}\n"
+            f"Overall Score: {result_data.get('score', 'N/A')}% "
+            f"({result_data.get('correct_count', '?')}/{result_data.get('total_attempted', '?')} correct)\n"
+            f"Message: {result_data.get('message', 'No message received.')}"
+        )
+        print("Submission successful.")
+        results_df = pd.DataFrame(results_log)
+        return final_status, results_df
+    except requests.exceptions.HTTPError as e:
+        error_detail = f"Server responded with status {e.response.status_code}."
+        try:
+            error_json = e.response.json()
+            error_detail += f" Detail: {error_json.get('detail', e.response.text)}"
+        except requests.exceptions.JSONDecodeError:
+            error_detail += f" Response: {e.response.text[:500]}"
+        status_message = f"Submission Failed: {error_detail}"
+        print(status_message)
+        results_df = pd.DataFrame(results_log)
+        return status_message, results_df
+    except requests.exceptions.Timeout:
+        status_message = "Submission Failed: The request timed out."
+        print(status_message)
+        results_df = pd.DataFrame(results_log)
+        return status_message, results_df
+    except requests.exceptions.RequestException as e:
+        status_message = f"Submission Failed: Network error - {e}"
+        print(status_message)
+        results_df = pd.DataFrame(results_log)
+        return status_message, results_df
+    except Exception as e:
+        status_message = f"An unexpected error occurred during submission: {e}"
+        print(status_message)
+        results_df = pd.DataFrame(results_log)
+        return status_message, results_df
+'''
 
 def test_init_agent_for_chat(text_input, history):
     # 1. Instantiate Agent ( modify this part to create your agent)
@@ -143,15 +147,6 @@ def test_init_agent_for_chat(text_input, history):
 
     return submitted_answer
 
-# --- Agent Logic for Chat Interface ---
-def handle_chat(message, history):
-    try:
-        basicAgent = agent.BasicAgent()
-        response = basicAgent(message)
-        return response
-    except Exception as e:
-        return f"[ERROR] Agent failed: {str(e)}"
-
 # --- Build Gradio Interface using Blocks ---
 with gr.Blocks() as demo:
     gr.Markdown("# Basic Agent Evaluation Runner")
@@ -172,8 +167,7 @@ with gr.Blocks() as demo:
 
     # gr.LoginButton()
 
-    #gr.ChatInterface(test_init_agent_for_chat, type="messages")
-    gr.ChatInterface(handle_chat, chatbot=gr.Chatbot(), textbox=gr.Textbox(placeholder="Ask me anything about cargo travel..."))
+    gr.ChatInterface(test_init_agent_for_chat, type="messages")
 
     # run_button = gr.Button("Run Evaluation & Submit All Answers")