app.py

import os
import gradio as gr
import requests
import re
import time
import pandas as pd
import google.generativeai as genai
from google.generativeai.types import HarmCategory, HarmBlockThreshold

# --- Constants ---
DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"

# --- User's Corrected NativeGeminiAgent Class ---
# This is the superior implementation provided by you.
class NativeGeminiAgent:
    def __init__(self, gemini_api_key: str, api_url: str):
        print("Initializing NativeGeminiAgent with corrected configuration...")
        genai.configure(api_key=gemini_api_key)
        
        self.api_url = api_url
        self.model_name = 'gemini-2.5-flash-preview-05-20' # Using the stable, powerful model
        
        # Correct tool configuration using the recommended string-based method
        self.model = genai.GenerativeModel(
            model_name=self.model_name,
            tools=['google_search_retrieval'],
            system_instruction="""You are a world-class problem solver and researcher. 
            Analyze the question carefully, use available tools to gather information, 
            and provide accurate, concise answers. Focus on factual information and 
            avoid speculation.""",
            safety_settings={
                HarmCategory.HARM_CATEGORY_DANGEROUS_CONTENT: HarmBlockThreshold.BLOCK_NONE,
                HarmCategory.HARM_CATEGORY_HARASSMENT: HarmBlockThreshold.BLOCK_NONE,
                HarmCategory.HARM_CATEGORY_HATE_SPEECH: HarmBlockThreshold.BLOCK_NONE,
                HarmCategory.HARM_CATEGORY_SEXUALLY_EXPLICIT: HarmBlockThreshold.BLOCK_NONE,
            }
        )
        print(f"Agent initialized with {self.model_name} and Google Search grounding.")

    def _get_mime_type(self, url: str) -> str:
        """Enhanced MIME type detection."""
        url_lower = url.lower()
        if url_lower.endswith(('.jpg', '.jpeg')): return "image/jpeg"
        elif url_lower.endswith('.png'): return "image/png"
        elif url_lower.endswith('.gif'): return "image/gif"
        elif url_lower.endswith('.pdf'): return "application/pdf"
        elif url_lower.endswith('.txt'): return "text/plain"
        elif url_lower.endswith('.csv'): return "text/csv"
        elif url_lower.endswith(('.mp4', '.avi', '.mov')): return "video/mp4"
        elif url_lower.endswith('.json'): return "application/json"
        else: return "application/octet-stream"

    def _check_if_file_exists(self, url: str) -> bool:
        """Enhanced file existence check."""
        try:
            response = requests.head(url, timeout=15, allow_redirects=True)
            return response.status_code == 200
        except requests.exceptions.RequestException as e:
            print(f"File check failed for {url}: {e}")
            return False

    def __call__(self, question: str, task_id: str) -> str:
        print(f"\n{'='*20}\nProcessing Task ID: {task_id}")
        
        prompt_parts = [question]
        
        # Enhanced URL detection
        urls_in_question = re.findall(r'https?://[^\s<>"{}|\\^`\[\]]+', question)
        for url in urls_in_question:
            try:
                mime_type = self._get_mime_type(url)
                prompt_parts.append(genai.Part.from_uri(uri=url, mime_type=mime_type))
                print(f"Added URL: {url} (MIME: {mime_type})")
            except Exception as e:
                print(f"Failed to add URL {url}: {e}")

        # Check for associated files
        file_url = f"{self.api_url}/files/{task_id}"
        if self._check_if_file_exists(file_url):
            try:
                mime_type = self._get_mime_type(file_url)
                prompt_parts.append(genai.Part.from_uri(uri=file_url, mime_type=mime_type))
                print(f"Added file: {file_url} (MIME: {mime_type})")
            except Exception as e:
                print(f"Failed to add file {file_url}: {e}")

        try:
            # Use the specified generation config for more stable outputs
            response = self.model.generate_content(
                prompt_parts,
                request_options={'timeout': 120},
                generation_config=genai.types.GenerationConfig(
                    temperature=0.1,
                    top_p=0.8,
                    max_output_tokens=2048
                )
            )
            
            if response.text:
                # Thoroughly clean the response text
                final_answer = response.text.strip()
                final_answer = re.sub(r'\[\d+\]', '', final_answer) # Remove citations
                final_answer = re.sub(r'\s+', ' ', final_answer).strip() # Normalize whitespace
                return final_answer
            else:
                return "AGENT_ERROR: Empty response from model"
                
        except Exception as e:
            error_msg = f"AGENT_ERROR: {str(e)}"
            print(error_msg)
            return error_msg

# --- Main run_and_submit_all function ---
def run_and_submit_all(profile: gr.OAuthProfile | None):
    space_id = os.getenv("SPACE_ID")
    if not profile: return "Please Login to Hugging Face with the button.", None
    username = f"{profile.username}"

    gemini_key = os.getenv("GEMINI_API_KEY")
    if not gemini_key: return "CRITICAL ERROR: GEMINI_API_KEY not found in Space secrets.", None
    
    api_url = DEFAULT_API_URL
    try:
        agent = NativeGeminiAgent(gemini_api_key=gemini_key, api_url=api_url)
        questions_data = requests.get(f"{api_url}/questions", timeout=15).json()
    except Exception as e: return f"Error during setup: {e}", None

    results_log, answers_payload = [], []
    for item in questions_data:
        task_id, question_text = item.get("task_id"), item.get("question")
        if not task_id or question_text is None: continue
        try:
            submitted_answer = agent(question_text, task_id)
            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_message = f"AGENT CRASH: {e}"
             print(error_message)
             results_log.append({"Task ID": task_id, "Question": question_text, "Submitted Answer": error_message})
        
        print(f"--- Waiting for 10 seconds before next question... ---")
        time.sleep(10)

    if not answers_payload: return "Agent did not produce any answers to submit.", pd.DataFrame(results_log)
    
    agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main"
    submission_data = {"username": username.strip(), "agent_code": agent_code, "answers": answers_payload}
    
    try:
        response = requests.post(f"{api_url}/submit", json=submission_data, timeout=120)
        response.raise_for_status()
        result_data = response.json()
        final_status = (f"Submission Successful!\nUser: {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.')}")
        return final_status, pd.DataFrame(results_log)
    except requests.exceptions.RequestException as e:
        return f"Submission Failed: {e}", pd.DataFrame(results_log)

# --- Gradio Interface ---
with gr.Blocks() as demo:
    gr.Markdown("# Native Multi-Modal GAIA Agent (Corrected)")
    gr.Markdown("This agent uses the improved architecture with proper tool configuration, MIME type detection, and error handling.")
    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)
    run_button.click(fn=run_and_submit_all, outputs=[status_output, results_table])

if __name__ == "__main__":
    demo.launch(debug=True, share=False)