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[ARTICLE · art-27300] src=dev.to ↗ pub= topic=large-language-models verified=true sentiment=↑ positive

Chat With Your Documents Locally Using AnythingLLM and Ollama

A developer built a private RAG system using AnythingLLM and Ollama that runs locally on any machine, allowing users to drop in PDFs, Word docs, and code files and ask questions without cloud dependency. The setup uses Qwen3 14B as the default model and nomic-embed-text for embeddings, with options for desktop or Docker deployment.

read1 min publishedJun 14, 2026

A private RAG system where you drop in PDFs, Word docs, and code files and ask questions. Runs on any machine, no cloud dependency.

Component Role
AnythingLLM Desktop/server app with RAG, agents, built-in vector DB
Ollama Serves local LLM for chat + embeddings
Qwen3 14B Default model for answering questions
docker run -d --gpus all -p 11434:11434 --name ollama \
  -v ollama:/root/.ollama ollama/ollama

ollama pull qwen3:14b
ollama pull nomic-embed-text

Desktop app (easiest): Download from anythingllm.com

Docker:

docker run -d -p 3001:3001 --name anythingllm \
  --add-host host.docker.internal:host-gateway \
  -v anythingllm:/app/server/storage \
  mintplexlabs/anythingllm
Local ChatGPT + GPTs
Monthly $0 $20-200
Hardware $0-300 $0
Privacy Stays on your machine Sent to cloud
Documents Unlimited Token-limited

Full guide with troubleshooting: https://everylocalai.com/stack/anythingllm-ollama-rag

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