README.md

---
title: LLM-Enhanced Internet Search Agent
emoji: 🕵🏻‍♂️
colorFrom: indigo
colorTo: indigo
sdk: gradio
sdk_version: 5.25.2
app_file: app.py
pinned: false
hf_oauth: true
# optional, default duration is 8 hours/480 minutes. Max duration is 30 days/43200 minutes.
hf_oauth_expiration_minutes: 480
---

# LLM-Enhanced Internet Search Agent

This agent uses a two-step approach to answer questions:

1. **Question Breakdown**: The agent first uses an LLM (GPT-3.5) to break down complex questions into 2-3 key search queries
2. **Targeted Search**: Each search query is sent to Wikipedia's API to retrieve relevant information
3. **Answer Synthesis**: The agent then uses the LLM to synthesize a comprehensive answer based on all search results

## Features

- **Smart Query Generation**: Transforms natural language questions into optimized search queries
- **Parallel Search Processing**: Searches for multiple key aspects of the question simultaneously
- **Knowledge Synthesis**: Combines information from multiple sources into a cohesive answer
- **Fallback Mechanisms**: Graceful handling of errors at each step of the process

## Setup Requirements

1. Clone this repository
2. Install required packages: `pip install -r requirements.txt`
3. Set your OpenAI API key as an environment variable: `OPENAI_API_KEY=your-api-key`

## How It Works

1. User submits a question
2. LLM breaks down the question into key search terms
3. Search terms are used to query Wikipedia API
4. Results from multiple searches are collected
5. LLM synthesizes the information into a comprehensive answer
6. Answer is returned to the user

This approach is more effective than direct internet searches because:
- It identifies the most relevant aspects of complex questions
- It can break multi-part questions into their components
- It leverages the LLM's understanding of natural language
- It provides more targeted and accurate search results

Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference