PRISM

PRISM is an open-source, self-hosted tool that automates research. It uses a team of specialized AI agents to go from a single question to a comprehensive, transparent, and well-supported report.

✨ Features

• Multi-Agent System: A team of specialized AI agents collaborate to produce high-quality research.
• "Glass Box" Philosophy: The entire research process is transparent. You can see every search query, every website visited, and every piece of information used to construct the final report.
• Self-Hosted & Private: Run PRISM on your own machine. Your research queries and results remain private and under your control.
• Customizable Models: While PRISM provides a free-to-use default LLM provider, you can easily configure it to use your own API keys for providers like OpenAI, Anthropic, Google Gemini, OpenRouter, or any other OpenAI-compatible API.
• Secure Code Execution: The CodeExecutor agent runs Python code in a secure, isolated Docker container to perform calculations safely.
• Modern Tech Stack: Built with a high-performance Python/FastAPI backend and a sleek, reactive Next.js/React frontend.

🛠️ Prerequisites

Before you begin, ensure you have the following installed on your system:

• Python (version 3.11 or newer)
• Node.js (version 20.x or newer)
• Docker Desktop: Must be running for the CodeExecutor agent to function.

🚀 Getting Started

Follow these steps to get PRISM up and running on your local machine.

1. Clone the Repository

First, clone the PRISM repository to your local machine using Git:

git clone https://github.com/KHROTU/prism.git
cd prism

2. Backend Setup

The backend server orchestrates the AI agents and tools.

1. Navigate to the backend directory:

   cd backend

2. Create and activate a Python virtual environment:

   • For Windows

     python -m venv venv
     .\venv\Scripts\activate

   • For macOS/Linux

     python3 -m venv venv
     source venv/bin/activate

3. Install the required Python dependencies:

   pip install -r requirements.txt

4. Configure Environment Variables: The ResearcherAgent requires Google Search API keys to function.

   • Copy the example environment file:

     cp .env.example .env

   • Open the newly created .env file and add your credentials:

     • GOOGLE_API_KEY: Get this from the Google Cloud Console. You will need to enable the "Custom Search API".
     • GOOGLE_CX_ID: This is your Programmable Search Engine ID. You can create one using the Programmable Search Engine control panel. Make sure to configure it to search the entire web and include image search results.

5. Run the Backend Server:

   uvicorn main:app --host 0.0.0.0 --port 8000

   The backend server is now running on http://localhost:8000. Keep this terminal window open.

3. Frontend Setup

The frontend is the web interface where you interact with PRISM.

1. Open a new terminal window.

2. Navigate to the frontend directory:

   cd frontend

3. Install the required Node.js dependencies:

   npm install

4. Run the Frontend Development Server:

   npm run dev

   The frontend is now running on http://localhost:3000.

4. Usage

• Open your web browser and navigate to http://localhost:3000.
• If both servers are running correctly, the status indicators in the header should be green.
• Enter a research query on the homepage and start your research!
• Go to the Settings page to configure custom Large Language Models for each agent if you prefer not to use the default provider.

🤝 Contributing

Contributions are welcome! If you have suggestions for improvements or want to report a bug, please open an issue or submit a pull request on our GitHub repository.

📄 License

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