openinterpreter/open-interpreter
A natural language interface for computers
Open Interpreter gives LLMs a natural language interface to your local computer. Describe a task in plain English and it writes and executes Python, shell, or JavaScript code locally -- with full file and browser access and no cloud sandbox restrictions in 2026.
Our Review
Killian Lucas released Open Interpreter in September 2023 as a direct response to one constraint in OpenAI's Code Interpreter: it ran in a locked cloud sandbox with no internet access, no persistent files outside sessions, and a narrow allowed set of operations. Open Interpreter stripped that sandbox away -- the same LLM-to-code execution loop, but running locally on the user's own machine with full access to files, the browser, installed applications, and network resources. It hit the top of Hacker News within days of launch and eventually crossed 63,000 GitHub stars as one of the most-starred autonomous agent projects on the platform.
Key capabilities
- •Natural language code execution: describe a task in plain English; the model writes and immediately executes the code on your machine
- •Multi-language execution: runs Python, JavaScript, Shell, HTML, and other languages within the same conversation context
- •Full computer access: reads and writes files, browses websites, controls applications -- with no sandbox restricting what operations are allowed
- •Persistent conversation context: code outputs and variable state persist across messages in a session, enabling iterative workflows
- •Multi-model backend: works with Claude, GPT-4, Gemini, and local models via Ollama -- any OpenAI-compatible endpoint
- •Interactive REPL: open-source terminal interface for local use; programmatic API for integration into applications
Getting started
pip install open-interpreter then run interpreter in your terminal. Type your task in plain English and the model writes and runs the code. To use a specific model: interpreter --model claude-3-5-sonnet or configure via interpreter.llm.model in Python. OS Mode (interpreter --os) enables screen reading and computer control.
Limitation
Full local computer access is the feature and the risk: the model can write and execute code with no sandboxing. Mistakes in generated code affect your actual machine. AGPL-3.0 license requires careful review for commercial integration. Development pace has slowed since the initial viral launch -- some integrations lag newer model APIs. Long agentic sessions can accumulate significant LLM API costs.
Our Verdict
Open Interpreter made a compelling argument in 2023: the most useful version of Code Interpreter is one that runs on the user's own machine with full access to their environment. The viral response confirmed the market wanted this -- 10,000 stars in a week was a clear signal that the sandbox constraint on OpenAI's version was frustrating real users. For automating tasks that require reading local files, writing outputs to specific directories, or interacting with installed applications, Open Interpreter is still the clearest implementation of that vision.
The no-sandbox design is simultaneously the strongest capability and the sharpest risk. A model writing and executing code on your machine can do genuinely useful things that sandboxed tools cannot -- and it can also cause genuine harm if it writes incorrect or dangerous code. The appropriate operating context is tasks where the user understands what the generated code should do and can verify it before trusting its output.
Development pace is a practical consideration for teams evaluating it in 2026. The project attracted enormous attention and then slowed as the team focused on a commercial product. The open-source core still works well for the core use case, but teams needing active maintenance and quick integrations with the newest model APIs should evaluate the release cadence before committing.
Frequently Asked Questions
What is Open Interpreter and how does it differ from OpenAI's Code Interpreter?
Open Interpreter is an open-source Python library that gives LLMs a natural language interface to your local computer -- you describe a task, it writes and executes code. OpenAI's Code Interpreter (now Advanced Data Analysis) runs in a locked cloud sandbox: no internet access during execution, no persistent files outside sessions, limited time per run. Open Interpreter removes those constraints entirely -- it runs locally with full access to your files, browser, and applications. The tradeoff is that a sandbox protects you from bad code; Open Interpreter does not in 2026.
Is it safe to use Open Interpreter on my main computer?
Open Interpreter executes code on your machine with no sandbox. Code that deletes files, writes to system directories, or makes network requests runs exactly as written. For routine tasks with clear scope -- analyze this CSV, rename these files, summarize this document -- the risk is similar to running a script yourself. For open-ended or ambiguous tasks, reviewing the generated code before execution is the safer approach. Running Open Interpreter in a virtual machine or on a dedicated machine provides additional isolation for higher-risk workflows in 2026.
Which AI models work with Open Interpreter?
Open Interpreter works with any OpenAI-compatible model. Common choices are Claude Sonnet (via Anthropic API or OpenRouter), GPT-4o, Gemini 2.5 Pro, and locally-hosted models via Ollama (Llama 3, Qwen3, Mistral). Model quality directly affects the reliability of generated code -- frontier models produce fewer errors and better handle multi-step tasks than smaller models. Local models via Ollama work for offline use but may produce less reliable code on complex tasks in 2026.
What can Open Interpreter actually do on my computer?
Open Interpreter can read and write any file your user account can access, execute shell commands, control your browser (open URLs, scrape pages, download files), call external APIs, run Python scripts, process data with pandas or numpy, create and edit spreadsheets, and interact with installed applications. In OS Mode (interpreter --os), it can also read your screen and control keyboard/mouse input. The scope is limited only by what your user account has permission to do on the operating system in 2026.
What does the AGPL-3.0 license mean for using Open Interpreter commercially?
AGPL-3.0 is a strong copyleft license. If you use Open Interpreter as a library or service that users interact with over a network, the copyleft obligations may require you to open-source your surrounding code. For personal use, internal tooling, and open-source projects it is generally a non-issue. For teams building commercial products that integrate Open Interpreter -- especially SaaS applications -- legal review of AGPL obligations is the right first step before shipping in 2026.
What is open-interpreter?
Open Interpreter gives LLMs a natural language interface to your local computer. Describe a task in plain English and it writes and executes Python, shell, or JavaScript code locally -- with full file and browser access and no cloud sandbox restrictions in 2026.
How do I install open-interpreter?
Visit the GitHub repository at https://github.com/openinterpreter/open-interpreter for installation instructions.
What license does open-interpreter use?
open-interpreter uses the AGPL-3.0 license.
What are alternatives to open-interpreter?
Explore related tools and alternatives on My AI Guide.
Open source & community-verified
AGPL-3.0 licensed: free to use in any project, no strings attached. 63,583 developers have starred this, meaning the community has reviewed and trusted it.
Reviewed by My AI Guide for relevance, quality, and active maintenance before listing.
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