Update app.py

app.py

@@ -7,7 +7,6 @@ import pandas as pd
 
 import google.generativeai as genai
 from smolagents import CodeAgent, DuckDuckGoSearchTool
-from smolagents.models.base import BaseModel
 
 # Define the system prompt
 SYSTEM_PROMPT = """You are a general AI assistant. I will ask you a question.
@@ -18,13 +17,13 @@ If you're asked for a string, don’t use articles or abbreviations (e.g. for ci
 
 DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 
-# Gemini model wrapper
-class GeminiFlashModel(BaseModel):
+# Gemini model wrapper (lightweight, no smolagents.model.base)
+class GeminiFlashModel:
     def __init__(self, model_name="gemini-1.5-flash", api_key=None):
         self.model_name = model_name
-        self.api_key = api_key or os.getenv("GOOGLE_API_KEY")
+        self.api_key = api_key or os.getenv("GEMINI_API_KEY")
         if not self.api_key:
-            raise ValueError("GOOGLE_API_KEY is not set in environment variables.")
+            raise ValueError("GEMINI_API_KEY is not set.")
         genai.configure(api_key=self.api_key)
         self.model = genai.GenerativeModel(model_name)
 
@@ -34,10 +33,9 @@ class GeminiFlashModel(BaseModel):
             if not any(m["role"] == "system" for m in messages):
                 messages = [{"role": "system", "content": SYSTEM_PROMPT}] + messages
         else:
-            raise TypeError("Expected 'messages' to be a list of message dicts")
+            raise TypeError("Expected 'messages' to be a list of dicts.")
 
-        # Convert messages to a single string (Gemini expects plain prompt)
-        prompt = "\n".join([f"{m['role'].capitalize()}: {m['content']}" for m in messages])
+        prompt = "\n".join(f"{m['role'].capitalize()}: {m['content']}" for m in messages)
 
         try:
             response = self.model.generate_content(prompt)
@@ -45,7 +43,7 @@ class GeminiFlashModel(BaseModel):
         except Exception as e:
             return f"GENERATION ERROR: {e}"
 
-# Agent using Gemini-1.5-flash
+# Agent using Gemini
 class MyAgent:
     def __init__(self):
         self.model = GeminiFlashModel(model_name="gemini-1.5-flash")
@@ -54,7 +52,6 @@ class MyAgent:
     def __call__(self, question: str) -> str:
         return self.agent.run(question)
 
-# Evaluation & submission flow
 def run_and_submit_all(profile: gr.OAuthProfile | None):
     space_id = os.getenv("SPACE_ID")
 
@@ -63,31 +60,26 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
         print(f"User logged in: {username}")
     else:
         print("User not logged in.")
-        return "Please login to Hugging Face with the button.", None
+        return "Please login to Hugging Face.", None
 
-    api_url = DEFAULT_API_URL
-    questions_url = f"{api_url}/questions"
-    submit_url = f"{api_url}/submit"
+    questions_url = f"{DEFAULT_API_URL}/questions"
+    submit_url = f"{DEFAULT_API_URL}/submit"
 
     try:
         agent = MyAgent()
     except Exception as e:
         return f"Error initializing agent: {e}", None
 
-    agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main"
-    print(f"Fetching questions from: {questions_url}")
     try:
         response = requests.get(questions_url, timeout=15)
         response.raise_for_status()
         questions_data = response.json()
-        if not questions_data:
-            return "Fetched questions list is empty or invalid format.", None
-        print(f"Fetched {len(questions_data)} questions.")
     except Exception as e:
         return f"Error fetching questions: {e}", None
 
     results_log = []
     answers_payload = []
+
     for item in questions_data:
         task_id = item.get("task_id")
         question_text = item.get("question")
@@ -98,15 +90,18 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
             answers_payload.append({"task_id": task_id, "submitted_answer": submitted_answer})
             results_log.append({"Task ID": task_id, "Question": question_text, "Submitted Answer": submitted_answer})
         except Exception as e:
-            error_msg = f"AGENT ERROR: {e}"
-            results_log.append({"Task ID": task_id, "Question": question_text, "Submitted Answer": error_msg})
+            results_log.append({
+                "Task ID": task_id,
+                "Question": question_text,
+                "Submitted Answer": f"AGENT ERROR: {e}"
+            })
 
     if not answers_payload:
-        return "Agent did not produce any answers to submit.", pd.DataFrame(results_log)
+        return "Agent did not return any answers.", pd.DataFrame(results_log)
 
     submission_data = {
-        "username": username.strip(),
-        "agent_code": agent_code,
+        "username": profile.username.strip(),
+        "agent_code": f"https://huggingface.co/spaces/{space_id}/tree/main",
         "answers": answers_payload
     }
 
@@ -117,56 +112,33 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
         final_status = (
             f"Submission Successful!\n"
             f"User: {result_data.get('username')}\n"
-            f"Overall Score: {result_data.get('score', 'N/A')}% "
+            f"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.')}"
         )
-        results_df = pd.DataFrame(results_log)
-        return final_status, results_df
-    except requests.exceptions.HTTPError as e:
-        try:
-            detail = e.response.json().get("detail", e.response.text)
-        except Exception:
-            detail = e.response.text[:500]
-        return f"Submission Failed: {detail}", pd.DataFrame(results_log)
-    except requests.exceptions.Timeout:
-        return "Submission Failed: The request timed out.", pd.DataFrame(results_log)
+        return final_status, pd.DataFrame(results_log)
     except Exception as e:
-        return f"An unexpected error occurred during submission: {e}", pd.DataFrame(results_log)
+        return f"Submission failed: {e}", pd.DataFrame(results_log)
 
 # Gradio UI
 with gr.Blocks() as demo:
     gr.Markdown("# Basic Agent Evaluation Runner")
     gr.Markdown("""
     **Instructions:**
-    1. Clone this space and modify it to define your agent's logic.
-    2. Log in with Hugging Face.
-    3. Click 'Run Evaluation & Submit All Answers' to run and submit.
+    1. Clone this space and configure your Gemini API key.
+    2. Log in to Hugging Face.
+    3. Run your agent on evaluation tasks and submit answers.
     """)
 
     gr.LoginButton()
     run_button = gr.Button("Run Evaluation & Submit All Answers")
-
-    status_output = gr.Textbox(label="Run Status / Submission Result", lines=5, interactive=False)
-    results_table = gr.DataFrame(label="Questions and Agent Answers", wrap=True)
+    status_output = gr.Textbox(label="Submission Result", lines=5, interactive=False)
+    results_table = gr.DataFrame(label="Results", wrap=True)
 
     run_button.click(fn=run_and_submit_all, outputs=[status_output, results_table])
 
 if __name__ == "__main__":
-    print("\n" + "="*10 + " App Startup " + "="*10)
-    space_host = os.getenv("SPACE_HOST")
-    space_id = os.getenv("SPACE_ID")
-
-    if space_host:
-        print(f"✅ SPACE_HOST: {space_host} -> https://{space_host}.hf.space")
-    else:
-        print("ℹ️  SPACE_HOST not set.")
-
-    if space_id:
-        print(f"✅ SPACE_ID: {space_id}")
-    else:
-        print("ℹ️  SPACE_ID not set.")
-
+    print("🔧 App starting...")
     demo.launch(debug=True, share=False)