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Deep Research Agent

This directory contains the Deep Research Agent example for the Atomic Agents project. This example demonstrates how to create an intelligent research assistant that performs web searches and provides detailed answers with relevant follow-up questions.

Getting Started

  1. Clone the main Atomic Agents repository:

    git clone https://github.com/BrainBlend-AI/atomic-agents

  2. Navigate to the Deep Research directory:

    cd atomic-agents/atomic-examples/deep-research

  3. Install dependencies using Poetry:

    poetry install

  4. Set up environment variables: Create a .env file in the deep-research directory with:

    OPENAI_API_KEY=your_openai_api_key

  5. Set up SearxNG:

    • Install SearxNG from the official repository
    • Default configuration expects SearxNG at http://localhost:8080

  6. Run the Deep Research Agent:

    poetry run python deep_research/main.py

File Explanation

1. Agents (agents/)

  • ChoiceAgent (choice_agent.py): Determines when new searches are needed
  • QueryAgent (query_agent.py): Generates optimized search queries
  • QuestionAnsweringAgent (qa_agent.py): Processes information and generates responses

2. Tools (tools/)

  • SearxNG Search (searxng_search.py): Performs web searches across multiple engines
  • Webpage Scraper (webpage_scraper.py): Extracts and processes web content

3. Main (main.py)

The entry point for the Deep Research Agent application. It orchestrates the research process:

  • Deciding when to perform new searches
  • Generating and executing search queries
  • Processing information and providing answers
  • Suggesting relevant follow-up questions

Example Usage

The agent can handle various research queries and provides:

  • Detailed answers based on current web information
  • Relevant citations and sources
  • Specific follow-up questions for deeper exploration
  • Context-aware responses that build on previous interactions

Contributing

Contributions are welcome! Please fork the repository and submit a pull request with your improvements.

License

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