mirror of
https://github.com/hwchase17/langchain
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29 lines
972 B
Markdown
29 lines
972 B
Markdown
# Private RAG
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This template performs privae RAG (no reliance on external APIs) using:
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* Ollama for the LLM
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* GPT4All for embeddings
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## LLM
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Follow instructions [here](https://python.langchain.com/docs/integrations/chat/ollama) to download Ollama.
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The instructions also show how to download your LLM of interest with Ollama:
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* This template uses `llama2:7b-chat`
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* But you can pick from many [here](https://ollama.ai/library)
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## Set up local embeddings
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This will use [GPT4All](https://python.langchain.com/docs/integrations/text_embedding/gpt4all) embeddings.
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## Chroma
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[Chroma](https://python.langchain.com/docs/integrations/vectorstores/chroma) is an open-source vector database.
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This template will create and add documents to the vector database in `chain.py`.
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By default, this will load a popular blog post on agents.
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However, you can choose from a large number of document loaders [here](https://python.langchain.com/docs/integrations/document_loaders). |