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"
MAX_ITERATIONS = 7

# --- HYBRID: Re-introducing the WebSearchTool ---
class WebSearchTool:
    """A tool to search the web using the Perplexity API."""
    def __init__(self, api_key):
        self.api_key = api_key
        self.url = "https://api.perplexity.ai/chat/completions"
        print("WebSearchTool initialized.")
    def execute(self, query: str) -> str:
        print(f"Executing WebSearchTool with query: {query}")
        payload = {"model": "llama-3-sonar-small-32k-online", "messages": [{"role": "system", "content": "You are a research assistant. Provide a precise and factual answer to the query."}, {"role": "user", "content": query}]}
        headers = {"accept": "application/json", "content-type": "application/json", "Authorization": f"Bearer {self.api_key}"}
        try:
            response = requests.post(self.url, json=payload, headers=headers, timeout=40)
            response.raise_for_status()
            return response.json()['choices'][0]['message']['content']
        except requests.exceptions.RequestException as e:
            return f"Error: Web search failed. {e}"

# --- The New Hybrid Agent ---
class HybridAgent:
    def __init__(self, gemini_api_key: str, pplx_api_key: str, api_url: str):
        print("Initializing HybridAgent...")
        genai.configure(api_key=gemini_api_key)
        
        self.api_url = api_url
        self.web_search_tool = WebSearchTool(pplx_api_key)
        
        # Using the stable, powerful model that we know works.
        self.model_name = 'gemini-2.5-flash-preview-05-20'
        
        # HYBRID: We do NOT enable the native search tool, as it's not supported by all models.
        self.model = genai.GenerativeModel(
            model_name=self.model_name,
            system_instruction="""You are a powerful reasoning agent. You can understand files and URLs provided to you directly. 
For general web searches or to find new information, you MUST use the `WebSearch` tool.
Follow the ReAct format: Thought, Action, Observation, Final Answer.""",
            safety_settings={
                HarmCategory.HARM_CATEGORY_DANGEROUS_CONTENT: HarmBlockThreshold.BLOCK_NONE,
                # Add other categories as needed
            }
        )
        print(f"Agent initialized with {self.model_name} and an external WebSearchTool.")

    def _get_mime_type(self, url: str) -> str:
        # (Using the robust MIME type detection from your last recommendation)
        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('.pdf'): return "application/pdf"
        # Add other types as needed...
        else: return "application/octet-stream"

    def _check_if_file_exists(self, url: str) -> bool:
        try:
            response = requests.head(url, timeout=15, allow_redirects=True)
            return response.status_code == 200
        except requests.exceptions.RequestException:
            return False

    def __call__(self, question: str, task_id: str) -> str:
        print(f"\n{'='*20}\nProcessing Task ID: {task_id}")
        
        # --- HYBRID: Multi-modal part preparation ---
        prompt_parts = [
            "You will solve the following question. You have been provided with the question and any relevant files or URLs.",
            "Remember, for web searches, you must use the `WebSearch` tool in the ReAct format (Thought, Action, Observation).",
            f"\n--- QUESTION ---\n{question}"
        ]
        
        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"Appended URL to prompt parts: {url}")
            except Exception as e: print(f"Failed to add URL {url}: {e}")

        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"Appended file to prompt parts: {file_url}")
            except Exception as e: print(f"Failed to add file {file_url}: {e}")
        
        # --- HYBRID: ReAct Loop ---
        for i in range(MAX_ITERATIONS):
            print(f"\n--- Hybrid Iteration {i+1} ---")
            try:
                response = self.model.generate_content(
                    prompt_parts,
                    generation_config=genai.types.GenerationConfig(temperature=0.1)
                )
                response_text = response.text
            except Exception as e: return f"AGENT_ERROR: {e}"

            print(f"LLM Response:\n{response_text}")

            final_answer_match = re.search(r"Final Answer:\s*(.*)", response_text, re.DOTALL)
            if final_answer_match:
                return final_answer_match.group(1).strip()

            action_match = re.search(r"Action:\s*WebSearch\[(.*?)\]", response_text, re.DOTALL)
            if action_match:
                query = action_match.group(1).strip()
                observation = self.web_search_tool.execute(query)
                prompt_parts.append(f"\nThought: {response_text.split('Thought:')[1]}")
                prompt_parts.append(f"Observation: {observation}")
            else:
                # If the model gives a direct answer without the "Final Answer:" tag
                return response_text.strip()
                
        return "AGENT_ERROR: Max iterations reached."

# --- 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.", None
    username = f"{profile.username}"

    # HYBRID: We need both keys again.
    gemini_key = os.getenv("GEMINI_API_KEY")
    pplx_key = os.getenv("PPLX_API_KEY")
    if not gemini_key or not pplx_key: return "CRITICAL ERROR: GEMINI_API_KEY or PPLX_API_KEY not found.", None
    
    api_url = DEFAULT_API_URL
    try:
        agent = HybridAgent(gemini_api_key=gemini_key, pplx_api_key=pplx_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:
             results_log.append({"Task ID": task_id, "Question": question_text, "Submitted Answer": f"AGENT CRASH: {e}"})
        
        print(f"--- Waiting for 10 seconds... ---")
        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("# Hybrid GAIA Agent")
    gr.Markdown("This agent uses Gemini 1.5 Pro's native multi-modality (files, URLs) combined with an external Perplexity web search tool.")
    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)