Building a RAG System From Scratch — Four Components, One Working Pipeline

Most RAG tutorials explain the concept. This one shows the code — a complete working pipeline using LangChain, ChromaDB, and a local LLM via LM Studio. No OpenAI API key. No cloud costs.

The business problem: A company has hundreds of pages of HR documentation. Employees ask questions. An AI answers accurately from the actual documents in seconds.

Stack: Python, LangChain, ChromaDB, nomic-embed-text, Qwen 9B via LM Studio

pip install langchain langchain-community langchain-chroma langchain-openai langchain-text-splitters langchain-core openai requests

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Building a RAG System From Scratch — Four Components, One Working Pipeline

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