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SEC Copilot

CI Python 3.9 Python 3.10 Python 3.11 codecov Ruff uv Linux macOS Unix

SEC Copilot is an LLM-powered chatbot that retrieves financial reports from the SEC EDGAR database, and earnings call transcripts from the Discounting Cash Flows API allowing users to ask questions, summarize details, and gain insights from financial data.

Features

  • Fetch financial reports from the SEC EDGAR database
  • Fetch earnings call transcripts from the Discounting Cash Flows API
  • Ask questions about specific companies or financial metrics
  • Summarize key details from financial reports

Demo

SEC Copilot Demo

Setup

Prerequisites

  • Python 3.9 or higher

Supported Operating Systems

The application and development environment have been tested on Linux and macOS. While Unix systems are supported in principle, they have not been explicitly tested.

  • Linux
  • macOS
  • Unix (untested)

Tip

If you'd like to run this on a Windows machine, I suggest setting up WSL with the documention here.

Environment Setup

  1. Clone the repository:

    git clone https://github.com/gsornsen/secbot.git
cd secbot

  2. Set up the environment:

    make env

    This command will:

    • Install uv if not already present
    • Create a virtual environment
    • Install project dependencies
    • Set up pre-commit hooks

  3. Create a .env file in the project root and add your OpenAI API key:

    OPEN_AI_TOKEN=your_api_key_here

  4. Add your DMC API key to the .env file:

    DMC_API_KEY=your_api_key_here

  5. Create a JWT secret for Chainlit authentication:

    uv run chainlit create-secret

    Add the generated secret to your .env file:

    CHAINLIT_AUTH_SECRET=your_generated_secret_here

  6. Add OAuth keys to your .env file:

    OAUTH_GITHUB_CLIENT_ID=your_github_client_id
OAUTH_GITHUB_CLIENT_SECRET=your_github_client_secret
OAUTH_GOOGLE_CLIENT_ID=your_google_client_id
OAUTH_GOOGLE_CLIENT_SECRET=your_google_client_secret

    For more details on setting up authentication, refer to the Chainlit Authentication Documentation.

Running the Application

To run the application:

make run

Running Tests

To run the test suite:

make test

Development Workflow

This project uses several tools to maintain code quality and consistency:

  1. uv: A fast Python package installer and resolver. It's used instead of pip for faster dependency management.

  2. Ruff: A fast Python linter and formatter. It's configured to run automatically on pre-commit.

  3. Pre-commit hooks: Automatically run before each commit to ensure code quality. They include:

    • Ruff for linting and formatting
    • Pytest for running tests before pushing changes

To manually run pre-commit hooks:

pre-commit run --all-files

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

  1. Fork the repository
  2. Create your feature branch (git checkout -b feature/AmazingFeature)
  3. Commit your changes (git commit -m 'Add some AmazingFeature')
  4. Push to the branch (git push origin feature/AmazingFeature)
  5. Open a Pull Request

License

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

Contributors

Acknowledgments

  • OpenAI for providing the language model capabilities
  • SEC for making financial data accessible