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Language Model

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Model Selection

Specifies which language model to use. Check out the models section for a list of available models. Open Interpreter uses LiteLLM under the hood to support over 100+ models.

interpreter --model "gpt-3.5-turbo"

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Temperature

Sets the randomness level of the model’s output. The default temperature is 0, you can set it to any value between 0 and 1. The higher the temperature, the more random and creative the output will be.

interpreter --temperature 0.7

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Context Window

Manually set the context window size in tokens for the model. For local models, using a smaller context window will use less RAM, which is more suitable for most devices.

interpreter --context_window 16000

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Max Tokens

Sets the maximum number of tokens that the model can generate in a single response.

interpreter --max_tokens 100

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Max Output

Set the maximum number of characters for code outputs.

interpreter --max_output 1000

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API Base

If you are using a custom API, specify its base URL with this argument.

interpreter --api_base "https://api.example.com"

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API Key

Set your API key for authentication when making API calls. For OpenAI models, you can get your API key here.

interpreter --api_key "your_api_key_here"

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API Version

Optionally set the API version to use with your selected model. (This will override environment variables)

interpreter --api_version 2.0.2

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LLM Supports Functions

Inform Open Interpreter that the language model you’re using supports function calling.

interpreter --llm_supports_functions

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LLM Does Not Support Functions

Inform Open Interpreter that the language model you’re using does not support function calling.

interpreter --no-llm_supports_functions

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LLM Supports Vision

Inform Open Interpreter that the language model you’re using supports vision. Defaults to False.

interpreter --llm_supports_vision

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Interpreter

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Vision Mode

Enables vision mode, which adds some special instructions to the prompt and switches to gpt-4-vision-preview.

interpreter --vision

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OS Mode

Enables OS mode for multimodal models. Currently not available in Python. Check out more information on OS mode here.

interpreter --os

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Version

Get the current installed version number of Open Interpreter.

interpreter --version

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Open Local Models Directory

Opens the models directory. All downloaded Llamafiles are saved here.

interpreter --local_models

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Open Profiles Directory

Opens the profiles directory. New yaml profile files can be added to this directory.

interpreter --profiles

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Select Profile

Select a profile to use. If no profile is specified, the default profile will be used.

interpreter --profile local.yaml

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Help

Display all available terminal arguments.

interpreter --help

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Force Task Completion

Runs Open Interpreter in a loop, requiring it to admit to completing or failing every task.

interpreter --force_task_completion

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Verbose

Run the interpreter in verbose mode. Debug information will be printed at each step to help diagnose issues.

interpreter --verbose

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Safe Mode

Enable or disable experimental safety mechanisms like code scanning. Valid options are off, ask, and auto.

interpreter --safe_mode ask

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Auto Run

Automatically run the interpreter without requiring user confirmation.

interpreter --auto_run

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Max Budget

Sets the maximum budget limit for the session in USD.

interpreter --max_budget 0.01

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Local Mode

Run the model locally. Check the models page for more information.

interpreter --local

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Fast Mode

Sets the model to gpt-3.5-turbo and encourages it to only write code without confirmation.

interpreter --fast

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Custom Instructions

Appends custom instructions to the system message. This is useful for adding information about your system, preferred languages, etc.

interpreter --custom_instructions "This is a custom instruction."

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System Message

We don’t recommend modifying the system message, as doing so opts you out of future updates to the core system message. Use --custom_instructions instead, to add relevant information to the system message. If you must modify the system message, you can do so by using this argument, or by changing a profile file.

interpreter --system_message "You are Open Interpreter..."

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Disable Telemetry

Opt out of telemetry.

interpreter --disable_telemetry

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Offline

This boolean flag determines whether to enable or disable some offline features like open procedures. Use this in conjunction with the model parameter to set your language model.

interpreter.offline = True

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Messages

This property holds a list of messages between the user and the interpreter.

You can use it to restore a conversation:

interpreter.chat("Hi! Can you print hello world?")

print(interpreter.messages)

# This would output:

# [
#    {
#       "role": "user",
#       "message": "Hi! Can you print hello world?"
#    },
#    {
#       "role": "assistant",
#       "message": "Sure!"
#    }
#    {
#       "role": "assistant",
#       "language": "python",
#       "code": "print('Hello, World!')",
#       "output": "Hello, World!"
#    }
# ]

#You can use this to restore `interpreter` to a previous conversation.
interpreter.messages = messages # A list that resembles the one above

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Computer

The computer object in interpreter.computer is a virtual computer that the AI controls. Its primary interface/function is to execute code and return the output in real-time.

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Offline

Running the computer in offline mode will disable some online features, like the hosted Computer API. Inherits from interpreter.offline.

interpreter.computer.offline = True

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Verbose

This is primarily used for debugging interpreter.computer. Inherits from interpreter.verbose.

interpreter.computer.verbose = True

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Emit Images

The emit_images attribute in interpreter.computer controls whether the computer should emit images or not. This is inherited from interpreter.llm.supports_vision.

This is used for multimodel vs. text only models. Running computer.display.view() will return an actual screenshot for multimodal models if emit_images is True. If it’s False, computer.display.view() will return all the text on the screen.

Many other functions of the computer can produce image/text outputs, and this parameter controls that.

interpreter.computer.emit_images = True