---
title: "Discussion on \"I Built a Production-Grade RAG Framework With Hybrid Search, Contextual Chunking, and Zero Cloud Lock-In\" | Hashnode"
description: "Discussion on \"I Built a Production-Grade RAG Framework With Hybrid Search, Contextual Chunking, and Zero Cloud Lock-In\". How ragpipe combines BM25 + dense vectors, Anthropic's contextual retrieval, HyDE query expansion, and Ollama-first local inference into a modular Python framework"
url: "https://hashnode.com/posts/ragpipe-production-rag-framework-hybrid-search-contextual-chunking/69d188b2231cb87d2b81219c"
---

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# [I Built a Production-Grade RAG Framework With Hybrid Search, Contextual Chunking, and Zero Cloud Lock-In](https://shivamshasheesh.hashnode.dev/ragpipe-production-rag-framework-hybrid-search-contextual-chunking?utm_source=hashnode&utm_medium=feed)

How ragpipe combines BM25 + dense vectors, Anthropic's contextual retrieval, HyDE query expansion, and Ollama-first local inference into a modular Python framework

Oct 20, 2025 · 9 min read · shivamshasheesh.hashnode.dev  
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## Written by

[Shivam Shasheesh](https://hashnode.com/@shivamshasheesh)

@shivamshasheesh · Hyderabad, India

  
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shows reflection, not just execution

Senior Software Engineer | AI Platform Engineering | Full-Stack | Building Intelligent Automation Systems | Automotive & Enterprise Software @ ZF Group

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