Private Document Qa With Local Llm

via “private-document-qa-with-local-llm”

Tool for private interaction with your documents

Unique: Integrates local embedding retrieval with local LLM inference in a single privacy-preserving pipeline, allowing users to swap LLM models (Ollama, LM Studio, vLLM) without changing the retrieval layer, and supports quantized models (GGML, GPTQ) for resource-constrained environments

vs others: Eliminates per-query API costs and data exposure compared to ChatGPT+Retrieval plugins or LangChain+OpenAI stacks; slower inference but complete data sovereignty and model flexibility