AbeEstrada/mlx-rag
🧠 Retrieval Augmented Generation (RAG) example
This tool helps developers integrate custom documents into a large language model's knowledge base. It takes your documents (like PDFs or text files) and processes them into a format an LLM can understand, then allows the LLM to answer questions using information directly from your provided content. This is useful for AI application developers who want to build custom chatbots or question-answering systems based on specific, private, or niche datasets.
Use this if you are a developer building an AI application and want to enhance an LLM's responses with information from your own documents.
Not ideal if you are an end-user simply looking to chat with an existing LLM or do not have programming experience.
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19
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2
Language
Python
License
MIT
Category
Last pushed
Feb 19, 2026
Commits (30d)
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