
Dcup: Open-Source RAG-as-a-Service
Connect any data. chunk. index. query. rag pipelines
What it does
Deploy enterprise-grade RAG pipelines in minutes with Dcup's open-source platform. Connect to data sources, automate AI-powered indexing, and enable intelligent search with hybrid retrieval, entity extraction, and LLM re-ranking.
Does a similar job
all alternatives →- D1Dcup – 100% Open-Source RAG-as-a-Service for AI-Powered Search2025 · dcup.dev · ▲5
Dcup is an open-source RAG-as-a-Service that turns your documents into a self-hostable, extensible AI-powered search engine. Connect AWS S3, Google Drive, Dropbox, or direct uploads, then chunk, embed, and index every file in Qdrant. Leverage hybrid semantic+keyword search, optional re-ranking, and lightning-fast OpenAI responses. I believe any tool that works with data should be fully open source—Dcup gives you full control without black boxes or vendor lock-in.


- RORagas – Open-source library for evaluating RAG pipelines2024 · github.com · ▲121
Ragas is an open-source library for evaluating and testing RAG and other LLM applications. Github: https://docs.ragas.io/en/stable/, docs: https://docs.ragas.io/. Ragas provides you with different sets of metrics and methods like synthetic test data generation to help you evaluate your RAG applications. Ragas started off by scratching our own itch for evaluating our RAG chatbots last year. Problems Ragas can solve - How do you choose the best components for your RAG, such as the retriever, reranker, and LLM? - How do you formulate a test dataset…
- DADemystifying Advanced RAG Pipelines2023 · github.com · ▲131
I've built an advanced RAG (Retrieval-Augmented Generation) pipeline from scratch to demystify the complex mechanics of modern LLM-powered Question Answering systems. This repository features: -- An implementation of a sub-question query engine from scratch to answer complex user questions. -- Illustrative explanations that unveil the inner workings of the system. -- An analysis of the challenges I faced while working with the system, like prompt engineering and cost estimation. -- Qualitative comparison with similar frameworks like LlamaIndex, offering a broader perspective. Key Takeaway:…
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