📖 Open Source, Now and Forever
🚀 Dcup is your go-to solution for building and scaling Retrieval-Augmented Generation (RAG) systems. Whether you’re a developer looking to integrate AI-driven search capabilities or a team wanting to harness data for smarter retrieval, Dcup is fully open-source, self-hostable, and built with scalability in mind.
- Fully Open Source & Self-Hostable: Maintain control over your data and infrastructure.
- Connected RAG: Easy-to-use integrations with Google Drive, Dropbox, AWS, and direct file uploads.
- Advanced Search Capabilities: LLM re-ranking, summary indexing, hybrid search using OpenAI embeddings and Qdrant vector storage.
- Intuitive Retrieval API: Seamlessly query and refine your data with optional re-ranking.
- Developer-Centric: With clear documentation, easy-to-use APIs, and a modular architecture.
Start by ingesting your data. Dcup offers simple APIs for uploading files or directly connecting to popular sources like Google Drive, Dropbox, and AWS. Your data stays up-to-date automatically with effortless syncing.
Once ingested, Dcup automatically chunks and embeds your data into vectors using OpenAI embeddings. The vectors are stored in a scalable Qdrant vector database, with indexing for enhanced retrieval (vector, summary, and keyword indexing).
The final step is retrieval. With the Dcup Retrieval API, you can query your data and refine results. Features like re-ranking, summary index, entity extraction, flexible filtering, and hybrid search (semantic + keyword) ensure high precision and relevant results for your AI applications.
For more in-depth details about Dcup's features, API endpoints, and usage, check out our comprehensive documentation dcup/docs.
- Clone the repository
- Update your ENV config using .env.example
- Create containers
docker compose -f docker-compose.prod.yml --env-file .env up
If you prefer a hosted solution, try the cloud version of Dcup at app.Dcup . No setup required — just sign up, connect your data, and start querying.
Dcup is designed to be modular and flexible, allowing developers to build custom RAG pipelines effortlessly. With open-source architecture, you can contribute, customize, and scale as needed
We welcome contributions from the community! Check out our Contributing Guide to get started.