
RAGPipe (OpenSource)
RAG in 3 lines. Zero config. Any data source.
What it does
RAGPipe does the boring part of RAG: extract → chunk → embed → store → query. 3 functions. 1 package. Works with Ollama, OpenAI, Qdrant, Pinecone, or a JSON file. CLI, YAML pipelines, git hooks, and systemd baked in.
Does the same job
all alternatives →- 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…




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Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
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Launched alongside, March 2026
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Switch from ChatGPT to Claude with import memory feature
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