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)