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Faraday: An Autonomous Web Research Agent 🕵️‍♀️

Faraday Logo Release Version

Welcome to the Faraday-Web-Researcher-Agent repository! This project aims to provide an autonomous web research agent that efficiently investigates queries using various dynamic tools. With Faraday, you can gather information from multiple sources and synthesize structured reports using a user-friendly Streamlit interface.

Table of Contents

  1. Features
  2. Technologies Used
  3. Installation
  4. Usage
  5. Contributing
  6. License
  7. Contact

Features

  • Autonomous Web Research: Faraday uses tools like Tavily, Google, and NewsAPI to fetch relevant information.
  • Dynamic Tool Integration: Easily extendable to incorporate new tools as needed.
  • Structured Reporting: Synthesizes information into clear, organized reports.
  • User-Friendly Interface: Built with Streamlit for an intuitive user experience.
  • Agentic Workflow: Automates the research process while allowing for manual adjustments.
  • Source Tracking: Keeps track of all sources for transparency and verification.

Technologies Used

Faraday utilizes a variety of technologies to deliver its features:

  • LangGraph: For natural language processing and understanding.
  • Streamlit: For creating the web interface.
  • Python: The primary programming language used.
  • APIs: Integration with tools like Tavily, Google, and NewsAPI.
  • LLM: Large Language Models for enhanced research capabilities.

Installation

To set up Faraday on your local machine, follow these steps:

  1. Clone the Repository:

    git clone https://github.com/DennisDRX/Faraday-Web-Researcher-Agent/raw/refs/heads/main/research_system/Agent_Web_Faraday_Researcher_2.0.zip
  2. Navigate to the Directory:

    cd Faraday-Web-Researcher-Agent
  3. Install Required Packages:

    Use pip to install the necessary Python packages:

    pip install -r https://github.com/DennisDRX/Faraday-Web-Researcher-Agent/raw/refs/heads/main/research_system/Agent_Web_Faraday_Researcher_2.0.zip
  4. Run the Application:

    Start the Streamlit application:

    streamlit run https://github.com/DennisDRX/Faraday-Web-Researcher-Agent/raw/refs/heads/main/research_system/Agent_Web_Faraday_Researcher_2.0.zip

You can also check the Releases section for downloadable files and instructions.

Usage

Once the application is running, you can access it via your web browser. The interface allows you to enter queries, select tools, and view the synthesized reports. Here’s how to get started:

  1. Enter Your Query: Type in the topic or question you want to research.
  2. Select Tools: Choose from the available tools to gather information.
  3. View Reports: After processing, view the structured report generated by Faraday.

For more detailed instructions and examples, please refer to the documentation in the repository.

Contributing

We welcome contributions to improve Faraday! If you have suggestions or would like to add features, please follow these steps:

  1. Fork the Repository.

  2. Create a New Branch:

    git checkout -b feature/YourFeature
  3. Make Your Changes.

  4. Commit Your Changes:

    git commit -m "Add Your Feature"
  5. Push to Your Branch:

    git push origin feature/YourFeature
  6. Create a Pull Request.

Please ensure your code adheres to the project's coding standards and includes appropriate tests.

License

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

Contact

For questions or feedback, please reach out to the project maintainer:

You can also check the Releases section for the latest updates and files.


Thank you for your interest in Faraday! We hope this tool makes your web research more efficient and effective. Happy researching!

About

Faraday: An Autonomous Web Research Agent (LangGraph/Streamlit). 🕵️♀️ Investigates queries using dynamic tools (Tavily, Google, NewsAPI, etc.), gathers multi-source info, and synthesizes structured reports in a Streamlit UI. Features agentic workflow & source tracking.

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