Open Interpreter can use OpenAI-compatible server to run models locally. (LM Studio, jan.ai, ollama etc)

Simply run interpreter with the api_base URL of your inference server (for LM studio it is http://localhost:1234/v1 by default):

interpreter --api_base "http://localhost:1234/v1" --api_key "fake_key"

Alternatively you can use Llamafile without installing any third party software just by running

interpreter --local

for a more detailed guide check out this video by Mike Bird

How to run LM Studio in the background.

  1. Download https://lmstudio.ai/ then start it.
  2. Select a model then click ↓ Download.
  3. Click the ↔️ button on the left (below 💬).
  4. Select your model at the top, then click Start Server.

Once the server is running, you can begin your conversation with Open Interpreter.

(When you run the command interpreter --local and select LMStudio, these steps will be displayed.)

Local mode sets your context_window to 3000, and your max_tokens to 1000. If your model has different requirements, set these parameters manually.

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Python

Compared to the terminal interface, our Python package gives you more granular control over each setting.

You can point interpreter.llm.api_base at any OpenAI compatible server (including one running locally).

For example, to connect to LM Studio, use these settings:

from interpreter import interpreter

interpreter.offline = True # Disables online features like Open Procedures
interpreter.llm.model = "openai/x" # Tells OI to send messages in OpenAI's format
interpreter.llm.api_key = "fake_key" # LiteLLM, which we use to talk to LM Studio, requires this
interpreter.llm.api_base = "http://localhost:1234/v1" # Point this at any OpenAI compatible server

interpreter.chat()

Simply ensure that LM Studio, or any other OpenAI compatible server, is running at api_base.

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