app.py

import os
import gradio as gr
import requests
import inspect
import time
import pandas as pd
from smolagents import DuckDuckGoSearchTool
import threading
from typing import Dict, List, Optional, Tuple
import json
from huggingface_hub import InferenceClient

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

# --- Global Cache for Answers ---
cached_answers = {}
cached_questions = []
processing_status = {"is_processing": False, "progress": 0, "total": 0}

# --- Intelligent Agent with Conditional Search ---
class IntelligentAgent:
    def __init__(self, debug: bool = False, model_name: str = "meta-llama/Llama-3.1-8B-Instruct"):
        self.search = DuckDuckGoSearchTool()
        self.client = InferenceClient(model=model_name)
        self.debug = debug
        if self.debug:
            print(f"IntelligentAgent initialized with model: {model_name}")

    def _should_search(self, question: str) -> bool:
        """
        Use LLM to determine if search is needed for the question.
        Returns True if search is recommended, False otherwise.
        """
        decision_prompt = f"""You are an AI assistant that decides whether a web search is needed to answer questions accurately.