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Overview

This project is a web search Q&A system that uses natural language processing (NLP) to answer user queries based on search results from the web. The system uses LLaMA 3 70B to extract content from web pages and generate answers based on the search results and/or an instruction.

Main Features

  • Web Search Q&A
  • Query Type Evaluation
  • Math Query Handling
  • Simple Query Handling
  • Best Answer Selection

Requirements

  • Python 3.8+
  • requests library for making HTTP requests
  • BeautifulSoup library for parsing HTML content
  • Groq API key for answer generation

Server Usage Examples

  1. Web Search Q&A (Default)
  • Query: What is the capital of France?
    • The system will perform a web search and provide an answer based on the results.
  1. Math Queries
  • Query: What is 15 * 7 + 3?
    • The system will detect this as a math query and provide the calculated result.
  1. Simple Queries
  • Query: Who wrote "To Kill a Mockingbird"?
    • For well-known information, the system may provide a direct answer without web search.
  1. Realtime Information
  • Query: What's the current weather in New York?
    • The system will recognize this as requiring up-to-date information and perform a web search.
  • Best Answer Selection
    • For complex queries, the system may generate multiple answers and select the best one.

API Usage

Send a POST request to /ask endpoint with JSON payload:

{
  "query": "Your question here",
  "max_retries": 3  // Optional, default is 3
}

Response format:

{
  "response": "Answer to the query",
  "type": "search" // or "math" or "text"
}

Note: The system automatically determines the query type and processes accordingly.

License

This project is licensed under the MIT License. See the LICENSE file for more information.