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Private retrieval augmented generation (RAG) with local LLMs. Using Ollama, Mistral, Chroma DB vector store, and LangChain. Adapted from pixegami.

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Retrieval Augmented Generation with local LLMs

Advanced RAG, 'locally' on Google Colab via HuggingFace 🤗

Goal: Complex PDF question answering, many pages including figures.

  • LlamaIndex pipelines, semantic partitioning, re-ranking, response synthesis
  • Efficient LLM : HuggingFace/TinyLlama
  • End to end Evaluation: DeepEval
  • Next experiment: Efficient Multi-modal RAG for more complex visual QA HuggingFace/VILA

Vanilla RAG, locally on M1 macbook.

Goal: Privacy-preserving 🤫 sensistive document question answering 📄.

  • Ollama + Mistral LLM, Chroma DB 🍭, Nomic Embeddings 🍪
  • Langchain 🦜🔗 pipeline

"People who buy things are suckers." - Ron Swanson

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Private retrieval augmented generation (RAG) with local LLMs. Using Ollama, Mistral, Chroma DB vector store, and LangChain. Adapted from pixegami.

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