open-interpreter-bmo 0.1.2
Let language models run code locally.
Requires Python: >=3.10,<4.0

<h1 align="center">● Open Interpreter</h1>

<p align="center">
    <a href="https://discord.gg/6p3fD6rBVm"><img alt="Discord" src="https://img.shields.io/discord/1146610656779440188?logo=discord&style=flat&logoColor=white"></a> <img src="https://img.shields.io/static/v1?label=license&message=MIT&color=white&style=flat" alt="License">
<br>
    <b>Let language models run code on your computer.</b><br>
    An open-source, locally running implementation of OpenAI's Code Interpreter.<br>
    <br><a href="https://openinterpreter.com">Get early access to the desktop application.</a><br>
</p>

<br>

![poster](https://github.com/KillianLucas/open-interpreter/assets/63927363/08f0d493-956b-4d49-982e-67d4b20c4b56)

<br>

```shell
pip install open-interpreter
```

```shell
interpreter
```

<br>

**Open Interpreter** lets 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 `$ interpreter` after 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 research
- Plot, clean, and analyze large datasets
- ...etc.

**⚠️ Note: You'll be asked to approve code before it's run.**

<br>

## Demo

https://github.com/KillianLucas/open-interpreter/assets/63927363/37152071-680d-4423-9af3-64836a6f7b60

#### An interactive demo is also available on Google Colab:

[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1WKmRXZgsErej2xUriKzxrEAXdxMSgWbb?usp=sharing)

## Quick Start

```shell
pip install open-interpreter
```

### Terminal

After installation, simply run `interpreter`:

```shell
interpreter
```

### Python

```python
import interpreter

interpreter.chat("Plot AAPL and META's normalized stock prices") # Executes a single command
interpreter.chat() # Starts an interactive chat
```

## Comparison to ChatGPT's Code Interpreter

OpenAI's release of [Code Interpreter](https://openai.com/blog/chatgpt-plugins#code-interpreter) with 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](https://wfhbrian.com/mastering-chatgpts-code-interpreter-list-of-python-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 on 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.

## Commands

### Interactive Chat

To start an interactive chat in your terminal, either run `interpreter` from the command line:

```shell
interpreter
```

Or `interpreter.chat()` from a .py file:

```python
interpreter.chat()
```

### Programmatic Chat

For more precise control, you can pass messages directly to `.chat(message)`:

```python
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 Chat

In Python, Open Interpreter remembers conversation history. If you want to start fresh, you can reset it:

```python
interpreter.reset()
```

### Save and Restore Chats

`interpreter.chat()` returns a List of messages when return_messages=True, which can be used to resume a conversation with `interpreter.load(messages)`:

```python
messages = interpreter.chat("My name is Killian.", return_messages=True) # Save messages to 'messages'
interpreter.reset() # Reset interpreter ("Killian" will be forgotten)

interpreter.load(messages) # Resume chat from 'messages' ("Killian" will be remembered)
```

### Customize System Message

You can inspect and configure Open Interpreter's system message to extend its functionality, modify permissions, or give it more context.

```python
interpreter.system_message += """
Run shell commands with -y so the user doesn't have to confirm them.
"""
print(interpreter.system_message)
```

### Change the Model

ⓘ  **Issues running locally?** Read our new [GPU setup guide](/docs/GPU.md) and [Windows setup guide](/docs/WINDOWS.md).

You can run `interpreter` in local mode from the command line to use `Code Llama`:

```shell
interpreter --local
```

For `gpt-3.5-turbo`, use fast mode:

```shell
interpreter --fast
```

In Python, you will need to set the model manually:

```python
interpreter.model = "gpt-3.5-turbo"
```

### Azure Support

To connect to an Azure deployment, the `--use-azure` flag will walk you through setting this up:

```
interpreter --use-azure
```

In Python, set the following variables:

```
interpreter.use_azure = True
interpreter.api_key = "your_openai_api_key"
interpreter.azure_api_base = "your_azure_api_base"
interpreter.azure_api_version = "your_azure_api_version"
interpreter.azure_deployment_name = "your_azure_deployment_name"
interpreter.azure_api_type = "azure"
```

### Debug mode

To help contributors inspect Open Interpreter, `--debug` mode is highly verbose. 

You can activate debug mode by using it's flag (`interpreter --debug`), or mid-chat:

```
$ interpreter
...
> %debug # <- Turns on debug mode
```

### Configuration with .env
Open Interpreter allows you to set default behaviors using a .env file. This provides a flexible way to configure the interpreter without changing command-line arguments every time.

Here's a sample .env configuration:

```
INTERPRETER_CLI_AUTO_RUN=False
INTERPRETER_CLI_FAST_MODE=False
INTERPRETER_CLI_LOCAL_RUN=False
INTERPRETER_CLI_DEBUG=False
INTERPRETER_CLI_USE_AZURE=False
```

- INTERPRETER_CLI_AUTO_RUN: If set to True, the interpreter will execute code without user confirmation.
- INTERPRETER_CLI_FAST_MODE: If set to True, the interpreter will use gpt-3.5-turbo instead of gpt-4.
- INTERPRETER_CLI_LOCAL_RUN: If set to True, the interpreter will run fully locally with Code Llama.
- INTERPRETER_CLI_DEBUG: If set to True, the interpreter will print extra debugging information.
- INTERPRETER_CLI_USE_AZURE: If set to True, the interpreter will use Azure OpenAI Services.

You can modify these values in the .env file to change the default behavior of the Open Interpreter.

## Safety Notice

Since 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 run `interpreter -y` or set `interpreter.auto_run = True` to 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 associated with executing arbitrary code.

## How Does it Work?

Open Interpreter equips a [function-calling language model](https://platform.openai.com/docs/guides/gpt/function-calling) with an `exec()` function, which accepts a `language` (like "python" or "javascript") and `code` to run.

We then stream the model's messages, code, and your system's outputs to the terminal as Markdown.

# Contributing

Thank you for your interest in contributing! We welcome involvement from the community. 

Please see our [Contributing Guidelines](/docs/contributing.md) for more details on how to get involved.

## License

Open Interpreter is licensed under the MIT License. You are permitted to use, copy, modify, distribute, sublicense and sell copies of the software.

**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_

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