litlytics

litlytics

🔥 LitLytics - an affordable, simple analytics platform that leverages LLMs to automate data analysis

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LitLytics is an affordable analytics platform leveraging LLMs for automated data analysis. It simplifies analytics for teams without data scientists, generates custom pipelines, and allows customization. Cost-efficient with low data processing costs. Scalable and flexible, works with CSV, PDF, and plain text data formats.

README:

LitLytics

LitLytics is an affordable, simple analytics platform that leverages LLMs to automate data analysis. It was designed to help teams without dedicated data scientists gain insights from their data.

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Key Features

  • No Data Science Expertise Required: LitLytics simplifies the entire analytics process, making it accessible to anyone.
  • Automatic Pipeline Generation: Describe your analytics task in plain language, and LitLytics will generate a custom pipeline for you.
  • Customizable Pipelines: You can review, update, or modify each step in the analytics pipeline to suit your specific needs.
  • Cost-Efficient: Leveraging modern LLMs allows LitLytics to keep the cost of processing data incredibly low — typically fractions of a cent per document.
  • Scalable & Flexible: Works with various data formats including CSV, PDF, and plain text.

Watch the demo video for more detailed intro.

Running as a Docker container

Make sure you have Docker installed.

Then, start LitLytics from image by running following command:

docker run -d -p 3000:3000 ghcr.io/yamalight/litlytics:latest

This will launch the platform inside a docker container, and you will be able to interact with it in your browser: http://localhost:3000.

Running locally in development mode

Make sure you have Bun (>=1.1.0) installed.

Clone this repository:

git clone https://github.com/yamalight/litlytics.git
cd litlytics

Install dependencies:

bun install

And finally start the LitLytics platform:

bun run dev

This will launch the platform, and you will be able to interact with it in your browser: http://localhost:5173.

Running pipelines via API

POST /api/execute endpoint executes pipeline using given LLM provider and model.
The body should be a JSON object with the following fields:

  • provider: The language model provider you wish to use.
  • model (LLMModel): The specific model to use, based on the selected provider.
  • key (string): The API key to authenticate with the specified provider.
  • pipeline (Pipeline): The configuration for the processing pipeline.

Example request:

{
  "provider": "openai",
  "model": "gpt-4o-mini",
  "key": "sk-your-api-key",
  "pipeline": {
    // your pipeline configuration
  }
}

A response will include new pipeline config that includes results of the task execution.

Contributing

Contributions are welcome! If you’d like to contribute to LitLytics, please fork the repository and submit a pull request with your changes.

  1. Fork the repo
  2. Create your feature branch (git checkout -b feature/YourFeature)
  3. Commit your changes (git commit -m 'Add YourFeature')
  4. Push to the branch (git push origin feature/YourFeature)
  5. Open a pull request

License

This project is licensed under the GNU Affero General Public License v3.0 (AGPL-3.0). This license ensures that the software remains free and open, even when used as part of a network service. If you modify or distribute the project (including deploying it as a service), you must also make your changes available under the same license.

Commercial/Enterprise Licensing

If your use case requires a proprietary license (for example, you do not wish to open-source your modifications or need a more flexible licensing arrangement), we offer commercial and enterprise licenses. Please contact us to discuss licensing options tailored to your needs.

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