● Open Interpreter

Let language models run code on your computer.
An open-source, locally running implementation of OpenAI's Code Interpreter.

Get early access to the desktop application.

windows虚拟环境安装记录

windows下使用conda虚拟环境安装open-interpreter，并本地部署Code-Llama的注意事项
具体创建虚拟环境请搜索相关教程
创建虚拟环境后需要提前使用pip安装 pip install llama-cpp-python，本地编译时可能报错，原因是未安装C++环境，需要安装微软的Visual Studio C++工具：https://visualstudio.microsoft.com/zh-hans/visual-cpp-build-tools/
上述完成后安装open-interpreter，pip install open-interpreter

安装完毕之后执行 interpreter -l 运行本地模型，根据提示选择模型版本和是否使用GPU等。首次运行指定模型需要下载，请确保网络环境配置正确。

模型选择后会将模型下载到 C:\Users\{用户名}\AppData\Local\Open Interpreter\Open Interpreter\models

一旦中途失败，将会重新下载模型而不是断点续传，如果选择较大模型，请确保网络通畅，或者直接使用别的下载器下载相应的模型，放到上述文件夹中，避免浪费时间。各个版本模型下载地址如下：

models = {
    '7B': {
        'Low': {'URL': 'https://huggingface.co/TheBloke/CodeLlama-7B-Instruct-GGUF/resolve/main/codellama-7b-instruct.Q3_K_S.gguf', 'Size': '3.01 GB', 'RAM': '5.51 GB'},
        'Medium': {'URL': 'https://huggingface.co/TheBloke/CodeLlama-7B-Instruct-GGUF/resolve/main/codellama-7b-instruct.Q4_K_M.gguf', 'Size': '4.24 GB', 'RAM': '6.74 GB'},
        'High': {'URL': 'https://huggingface.co/TheBloke/CodeLlama-Instruct-7B-GGUF/resolve/main/codellama-7b-instruct.Q8_0.gguf', 'Size': '7.16 GB', 'RAM': '9.66 GB'}
    },
    '13B': {
        'Low': {'URL': 'https://huggingface.co/TheBloke/CodeLlama-13B-Instruct-GGUF/resolve/main/codellama-13b-instruct.Q3_K_S.gguf', 'Size': '5.66 GB', 'RAM': '8.16 GB'},
        'Medium': {'URL': 'https://huggingface.co/TheBloke/CodeLlama-13B-Instruct-GGUF/resolve/main/codellama-13b-instruct.Q4_K_M.gguf', 'Size': '8.06 GB', 'RAM': '10.56 GB'},
        'High': {'URL': 'https://huggingface.co/TheBloke/CodeLlama-13B-Instruct-GGUF/resolve/main/codellama-13b-instruct.Q8_0.gguf', 'Size': '13.83 GB', 'RAM': '16.33 GB'}
    },
    '34B': {
        'Low': {'URL': 'https://huggingface.co/TheBloke/CodeLlama-34B-Instruct-GGUF/resolve/main/codellama-34b-instruct.Q3_K_S.gguf', 'Size': '14.21 GB', 'RAM': '16.71 GB'},
        'Medium': {'URL': 'https://huggingface.co/TheBloke/CodeLlama-34B-Instruct-GGUF/resolve/main/codellama-34b-instruct.Q4_K_M.gguf', 'Size': '20.22 GB', 'RAM': '22.72 GB'},
        'High': {'URL': 'https://huggingface.co/TheBloke/CodeLlama-34B-Instruct-GGUF/resolve/main/codellama-34b-instruct.Q8_0.gguf', 'Size': '35.79 GB', 'RAM': '38.29 GB'}
    }
}

因为是C盘路径，一般总容量比较吃紧，如果需要修改模型地址，应该是需要手动修改源代码了，源代码文件 interpreter/llama_2.py
```
# Get user data directory
user_data_dir = appdirs.user_data_dir("Open Interpreter")
default_path = os.path.join(user_data_dir, "models")
```

另一种暴力方式是，修改虚拟环境中appdirs.py的源代码：$envPath\${envName}\Lib\site-packages\appdirs.py

# 修改user_data_dir方法，1.4.4版本的在第45行
def user_data_dir(appname=None, appauthor=None, version=None, roaming=False):
    # 直接指定路径，指定后模型路径将变为，例如 D:\AppData\Open Interpreter\models 然后将其他方式下载的模型放到这里面即可
    return r"{指定你自己想放的路径}\%s" % appname

模型下载完毕后就可以愉快的使用了，更多使用说明见原始仓库：open-interpreter
如果不需要使用本地模型，请忽略上述说明，按原仓库说明使用，需要申请OpenAi的API KEY

pip install open-interpreter

interpreter

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.

Demo

Open.Interpreter.Demo.mp4

An interactive demo is also available on Google Colab:

Quick Start

pip install open-interpreter

Terminal

After installation, simply run interpreter:

interpreter

Python

import interpreter

interpreter.chat("Plot APPL 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 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.
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:

interpreter

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

interpreter.chat()

Programmatic Chat

For 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 Chat

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

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):

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.

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

Change the Model

Note: We're working on consolidating these into a unified command.

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

interpreter --local

For gpt-3.5-turbo, use fast mode:

interpreter --fast

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

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"

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

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 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

This is a community-made project. If it looks exciting to you, please don't hesitate to contribute!

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

TonyJiangWJ / open-interpreter