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Hi, i apologize in advance if my question is trivial or I'm making incorrect assumptions. I am just a user and not a developer.. I configured my paperless-ngx instance using an OpenAI-like LLM (Gemini) and HuggingFace as a local embedding. Document suggestions are generated correctly, and the indexing process is also completed on newly uploaded documents. However, I'm having some problems using RAG (document chat). My documents are typically quite large technical manuals. Reading the logs, I noticed that the LLM is passed context along with the question, truncated to 15,000 characters. It also seems that a reduced context window is set somewhere else, causing an error when this limit is exceeded.
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Replies: 4 comments 1 reply
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If you'd like to test out the newer build, #12751 should resolve this (I hope) |
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Asking here because it fits the title... Can someone confirm if RAG embedding using Huggingface is completely local except the model download? i.e. no part of any document is sent to an inference API or other cloud services? |
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This discussion has been automatically locked since there has not been any recent activity after it was closed. Please open a new discussion for related concerns. See our contributing guidelines for more details. |
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If you'd like to test out the newer build, #12751 should resolve this (I hope)