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How to run Baize on a local Ollama model so data never leaves your machine with Baize

Use a local Ollama model as the backend for coding or analysis on sensitive material at zero API cost.

Who it is forA developer or analyst working with confidential code or data who does not want to send it to a cloud API.

The problemCloud LLM backends require sending prompts to a remote provider, which may be unacceptable for sensitive work.

The outcomeBaize runs its agent loop against a local model served by Ollama, with no API key needed.

What you need first

  • Python 3.10 or newer with pip
  • An API key for DeepSeek or another supported backend, or a local Ollama install
  • Optional: IBM SPSS Statistics or a reachable SQL database, depending on the use case

Steps

  1. Install Ollama from https://ollama.com/download
  2. ollama pull qwen2.5:7b
  3. ollama serve
  4. Open ~/.baize/config.toml and set active_provider = "ollama", then save the file. (inferred, check the README)
  5. baize

Prompt for your agent

Using the Baize CLI from the Xu123-Bob/Baize repo with active_provider set to ollama, ask it to summarize the files in <project-path>. Expected output: a summary generated by the local qwen2.5:7b model. Verify that Ollama is serving on localhost:11434 before the decree runs.

Caveat. A 7B local model is less capable than the cloud backends, and the README recommends qwen2.5:7b for strong Chinese while listing llama3.1:8b and deepseek-r1:7b as alternatives.

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