Update app.py

app.py

@@ -1,71 +1,71 @@
 import os
 import gradio as gr
 import requests
-import time
 import pandas as pd
-from dotenv import load_dotenv
-
-# Load environment variables
-load_dotenv()
+from huggingface_hub import InferenceClient
 
 # --- Constants ---
 DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
-HF_API_URL = "https://api-inference.huggingface.co/models/mistralai/Mistral-7B-Instruct-v0.2"
-HUGGINGFACE_TOKEN = os.getenv("HUGGINGFACE_TOKEN")
+MODEL_NAME = "mistralai/Mixtral-8x7B-Instruct-v0.1"  # Free inference endpoint
 
-# --- Agent Definition ---
+# --- Enhanced BasicAgent ---
 class BasicAgent:
     def __init__(self):
-        self.headers = {"Authorization": f"Bearer {HUGGINGFACE_TOKEN}"}
+        self.client = InferenceClient(model=MODEL_NAME)
+        self.system_prompt = """You are a GAIA question answering agent. Follow these rules:
+1. Answer EXACTLY as required - no extra text
+2. Use correct pluralization and ordering
+3. Never explain your answer
+4. Format lists as comma-separated values
+5. Use only facts from verified sources"""
     
     def __call__(self, question: str) -> str:
-        prompt = f"""Answer the question concisely and factually. Provide only the answer in the exact format required by the question, with no additional text, explanations, or formatting. Do not use quotation marks, bullet points, or any other formatting. Ensure correct casing and pluralization as specified.
-
-Question: {question}
-Answer: """
-        payload = {
-            "inputs": prompt,
-            "parameters": {
-                "max_new_tokens": 100,
-                "return_full_text": False
-            }
-        }
-        max_retries = 3
-        for _ in range(max_retries):
-            try:
-                response = requests.post(HF_API_URL, headers=self.headers, json=payload, timeout=30)
-                response.raise_for_status()
-                answer = response.json()[0]['generated_text'].strip()
-                # Clean up answer
-                answer = answer.strip().rstrip('.').strip()
-                return answer
-            except requests.exceptions.HTTPError as e:
-                if e.response.status_code == 503:
-                    time.sleep(10)
-                else:
-                    print(f"HTTP Error: {e.response.text}")
-                    break
-            except requests.exceptions.RequestException as e:
-                print(f"Request failed: {e}, retrying...")
-                time.sleep(5)
-            except Exception as e:
-                print(f"Error: {e}")
-                break
-        return "Error: Unable to generate answer."
+        try:
+            response = self.client.chat(
+                model=MODEL_NAME,
+                messages=[{
+                    "role": "system",
+                    "content": self.system_prompt
+                },{
+                    "role": "user",
+                    "content": question
+                }],
+                max_tokens=100,
+                stop_sequences=["\n"]
+            )
+            
+            # Clean and format response
+            answer = response.content.split("Answer:")[-1].strip()
+            answer = answer.replace('"', '').replace('.', '').strip()
+            return answer
+            
+        except Exception as e:
+            print(f"Error in agent: {str(e)}")
+            return "Error generating answer"
 
-# --- Submission Logic ---
+# --- Keep Original Submission Logic Intact ---
 def run_and_submit_all(profile: gr.OAuthProfile | None):
     if profile:
         username = f"{profile.username}"
+        print(f"User logged in: {username}")
     else:
+        print("User not logged in.")
         return "Please Login to Hugging Face with the button.", None
 
-    agent = BasicAgent()
+    api_url = DEFAULT_API_URL
+    questions_url = f"{api_url}/questions"
+    submit_url = f"{api_url}/submit"
+
+    try:
+        agent = BasicAgent()
+    except Exception as e:
+        return f"Error initializing agent: {e}", None
+
     space_id = os.getenv("SPACE_ID")
     agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main" if space_id else ""
 
     try:
-        response = requests.get(f"{DEFAULT_API_URL}/questions", timeout=15)
+        response = requests.get(questions_url, timeout=15)
         response.raise_for_status()
         questions_data = response.json()
     except Exception as e:
@@ -76,7 +76,7 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
     for item in questions_data:
         task_id = item.get("task_id")
         question_text = item.get("question")
-        if not task_id or not question_text:
+        if not task_id or question_text is None:
             continue
         try:
             submitted_answer = agent(question_text)
@@ -92,27 +92,32 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
     }
 
     try:
-        response = requests.post(f"{DEFAULT_API_URL}/submit", json=submission_data, timeout=60)
+        response = requests.post(submit_url, json=submission_data, timeout=60)
         response.raise_for_status()
         result_data = response.json()
-        final_status = f"Success! Score: {result_data.get('score', 'N/A')}%"
+        final_status = (
+            f"Submission Successful!\n"
+            f"Score: {result_data.get('score', 'N/A')}% "
+            f"({result_data.get('correct_count', '?')}/{result_data.get('total_attempted', '?')} correct)"
+        )
         return final_status, pd.DataFrame(results_log)
     except Exception as e:
         return f"Submission failed: {e}", pd.DataFrame(results_log)
 
-# --- Gradio Interface ---
+# --- Keep Original Gradio Interface ---
 with gr.Blocks() as demo:
-    gr.Markdown("# GAIA Evaluation Agent")
-    gr.Markdown("""
-    **Instructions:**
-    1. Log in to your Hugging Face account using the button below.
-    2. Click 'Run Evaluation & Submit Answers' to fetch questions, run your agent, and submit answers.
-    """)
+    gr.Markdown("# Basic Agent Evaluation Runner")
+    gr.Markdown("""... (original markdown content) ...""")
+    
     gr.LoginButton()
-    run_button = gr.Button("Run Evaluation & Submit Answers")
-    status_output = gr.Textbox(label="Status")
-    results_table = gr.DataFrame(label="Results")
-    run_button.click(run_and_submit_all, outputs=[status_output, results_table])
+    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)
+
+    run_button.click(
+        fn=run_and_submit_all,
+        outputs=[status_output, results_table]
+    )
 
 if __name__ == "__main__":
     demo.launch()