Package: open-interpreter
● Open InterpreterLet language models run code on your computer.An open-source, locally running implementation of OpenAI's Code Interpreter.Get early access to the desktop app‎ ‎ |‎ ‎DocumentationImportant:●v0.1.18includes breaking changes. Please read ourmigration guideif you use Open Interpreter in Python.pipinstallopen-interpreterinterpreterOpen Interpreterlets LLMs run code (Python, Javascript, Shell, and more) locally. You can chat with Open Interpreter through a ChatGPT-like interface in your terminal by running$ interpreterafter installing.This provides a natural-language interface to your computer's general-purpose capabilities:Create and edit photos, videos, PDFs, etc.Control a Chrome browser to perform researchPlot, clean, and analyze large datasets...etc.⚠️ Note: You'll be asked to approve code before it's run.Demohttps://github.com/KillianLucas/open-interpreter/assets/63927363/37152071-680d-4423-9af3-64836a6f7b60An interactive demo is also available on Google Colab:Along with an example implementation of a voice interface (inspired byHer):Quick Startpipinstallopen-interpreterTerminalAfter installation, simply runinterpreter:interpreterPythonfrominterpreterimportinterpreterinterpreter.chat("Plot AAPL and META's normalized stock prices")# Executes a single commandinterpreter.chat()# Starts an interactive chatComparison to ChatGPT's Code InterpreterOpenAI's release ofCode Interpreterwith GPT-4 presents a fantastic opportunity to accomplish real-world tasks with ChatGPT.However, OpenAI's service is hosted, closed-source, and heavily restricted:No internet access.Limited set of pre-installed packages.100 MB maximum upload, 120.0 second runtime limit.State is cleared (along with any generated files or links) when the environment dies.Open Interpreter overcomes these limitations by running in your local environment. It has full access to the internet, isn't restricted by time or file size, and can utilize any package or library.This combines the power of GPT-4's Code Interpreter with the flexibility of your local development environment.CommandsUpdate:The Generator Update (0.1.5) introduced streaming:message="What operating system are we on?"forchunkininterpreter.chat(message,display=False,stream=True):print(chunk)Interactive ChatTo start an interactive chat in your terminal, either runinterpreterfrom the command line:interpreterOrinterpreter.chat()from a .py file:interpreter.chat()You can also stream each chunk:message="What operating system are we on?"forchunkininterpreter.chat(message,display=False,stream=True):print(chunk)Programmatic ChatFor more precise control, you can pass messages directly to.chat(message):interpreter.chat("Add subtitles to all videos in /videos.")# ... Streams output to your terminal, completes task ...interpreter.chat("These look great but can you make the subtitles bigger?")# ...Start a New ChatIn Python, Open Interpreter remembers conversation history. If you want to start fresh, you can reset it:interpreter.reset()Save and Restore Chatsinterpreter.chat()returns a List of messages, which can be used to resume a conversation withinterpreter.messages = messages:messages=interpreter.chat("My name is Killian.")# Save messages to 'messages'interpreter.reset()# Reset interpreter ("Killian" will be forgotten)interpreter.messages=messages# Resume chat from 'messages' ("Killian" will be remembered)Customize System MessageYou can inspect and configure Open Interpreter's system message to extend its functionality, modify permissions, or give it more context.interpreter.system_message+="""Run shell commands with -y so the user doesn't have to confirm them."""print(interpreter.system_message)Change your Language ModelOpen Interpreter usesLiteLLMto connect to hosted language models.You can change the model by setting the model parameter:interpreter--modelgpt-3.5-turbo
interpreter--modelclaude-2
interpreter--modelcommand-nightlyIn Python, set the model on the object:interpreter.llm.model="gpt-3.5-turbo"Find the appropriate "model" string for your language model here.Running Open Interpreter locallyTerminalOpen Interpreter usesLM Studioto connect to local language models (experimental).Simply runinterpreterin local mode from the command line:interpreter--localYou will need to run LM Studio in the background.Downloadhttps://lmstudio.ai/then start it.Select a model then click↓ Download.Click the↔️button on the left (below 💬).Select your model at the top, then clickStart Server.Once the server is running, you can begin your conversation with Open Interpreter.(When you run the commandinterpreter --local, the steps above will be displayed.)Note:Local mode sets yourcontext_windowto 3000, and yourmax_tokensto 1000. If your model has different requirements, set these parameters manually (see below).PythonOur Python package gives you more control over each setting. To replicate--localand connect to LM Studio, use these settings:frominterpreterimportinterpreterinterpreter.offline=True# Disables online features like Open Proceduresinterpreter.llm.model="openai/x"# Tells OI to send messages in OpenAI's formatinterpreter.llm.api_key="fake_key"# LiteLLM, which we use to talk to LM Studio, requires thisinterpreter.llm.api_base="http://localhost:1234/v1"# Point this at any OpenAI compatible serverinterpreter.chat()Context Window, Max TokensYou can modify themax_tokensandcontext_window(in tokens) of locally running models.For local mode, smaller context windows will use less RAM, so we recommend trying a much shorter window (~1000) if it's is failing / if it's slow. Make suremax_tokensis less thancontext_window.interpreter--local--max_tokens1000--context_window3000Verbose modeTo help contributors inspect Open Interpreter,--verbosemode is highly verbose.You can activate verbose mode by using it's flag (interpreter --verbose), or mid-chat:$interpreter
...
>%verbosetrue<-Turnsonverbosemode

>%verbosefalse<-TurnsoffverbosemodeInteractive Mode CommandsIn the interactive mode, you can use the below commands to enhance your experience. Here's a list of available commands:Available Commands:%verbose [true/false]: Toggle verbose mode. Without arguments or withtrueit
enters verbose mode. Withfalseit exits verbose mode.%reset: Resets the current session's conversation.%undo: Removes the previous user message and the AI's response from the message history.%tokens [prompt]: (Experimental) Calculate the tokens that will be sent with the next prompt as context and estimate their cost. Optionally calculate the tokens and estimated cost of apromptif one is provided. Relies onLiteLLM'scost_per_token()methodfor estimated costs.%help: Show the help message.ConfigurationOpen Interpreter allows you to set default behaviors using aconfig.yamlfile.This provides a flexible way to configure the interpreter without changing command-line arguments every time.Run the following command to open the configuration file:interpreter --configMultiple Configuration FilesOpen Interpreter supports multipleconfig.yamlfiles, allowing you to easily switch between configurations via the--config_fileargument.Note:--config_fileaccepts either a file name or a file path. File names will use the default configuration directory, while file paths will use the specified path.To create or edit a new configuration, run:interpreter --config --config_file $config_pathTo have Open Interpreter load a specific configuration file run:interpreter --config_file $config_pathNote: Replace$config_pathwith the name of or path to your configuration file.ExampleCreate a newconfig.turbo.yamlfileinterpreter --config --config_file config.turbo.yamlEdit theconfig.turbo.yamlfile to setmodeltogpt-3.5-turboRun Open Interpreter with theconfig.turbo.yamlconfigurationinterpreter --config_file config.turbo.yamlSample FastAPI ServerThe generator update enables Open Interpreter to be controlled via HTTP REST endpoints:# server.pyfromfastapiimportFastAPIfromfastapi.responsesimportStreamingResponsefrominterpreterimportinterpreterapp=FastAPI()@app.get("/chat")defchat_endpoint(message:str):defevent_stream():forresultininterpreter.chat(message,stream=True):yieldf"data:{result}\n\n"returnStreamingResponse(event_stream(),media_type="text/event-stream")@app.get("/history")defhistory_endpoint():returninterpreter.messagespipinstallfastapiuvicorn
uvicornserver:app--reloadSafety NoticeSince generated code is executed in your local environment, it can interact with your files and system settings, potentially leading to unexpected outcomes like data loss or security risks.⚠️ Open Interpreter will ask for user confirmation before executing code.You can runinterpreter -yor setinterpreter.auto_run = Trueto bypass this confirmation, in which case:Be cautious when requesting commands that modify files or system settings.Watch Open Interpreter like a self-driving car, and be prepared to end the process by closing your terminal.Consider running Open Interpreter in a restricted environment like Google Colab or Replit. These environments are more isolated, reducing the risks of executing arbitrary code.There isexperimentalsupport for asafe modeto help mitigate some risks.How Does it Work?Open Interpreter equips afunction-calling language modelwith anexec()function, which accepts alanguage(like "Python" or "JavaScript") andcodeto run.We then stream the model's messages, code, and your system's outputs to the terminal as Markdown.ContributingThank you for your interest in contributing! We welcome involvement from the community.Please see ourcontributing guidelinesfor more details on how to get involved.RoadmapVisitour roadmapto preview the future of Open Interpreter.Note: This software is not affiliated with OpenAI.Having access to a junior programmer working at the speed of your fingertips ... can make new workflows effortless and efficient, as well as open the benefits of programming to new audiences.—OpenAI's Code Interpreter Release