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An innovative open-source Code Interpreter with (GPT,Gemini,PALM,LLaMa) models.

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Interpreter

Hosting and Spaces:

Colab Replit PyPi Building

Support Project:

Welcome to Open-Code-Interpreter πŸŽ‰, an innovative open-source and free alternative to traditional Code Interpreters. This is powerful tool and it also leverages the power of GPT 3.5 Turbo,PALM 2, HuggingFace models like Code-llama, Mistral 7b, Wizard Coder, and many more to transform your instructions into executable code for free and safe to use environments and even has Vision Models for Image Processing available.

Interpreter

Open-Code-Interpreter is more than just a code generator. It's a versatile tool that can execute a wide range of tasks. Whether you need to find files in your system πŸ“‚, save images from a website and convert them into a different format πŸ–ΌοΈ, create a GIF 🎞️, edit videos πŸŽ₯, or even analyze files for data analysis and creating graphs πŸ“Š, Open-Code-Interpreter can handle it all.

After processing your instructions, Open-Code-Interpreter executes the generated code and provides you with the result. This makes it an invaluable tool for developers πŸ’», data scientists πŸ§ͺ, and anyone who needs to quickly turn ideas into working code and now with Vision Models it can also process images and videos.

Designed with versatility in mind, Open-Code-Interpreter works seamlessly on every operating system, including Windows, MacOS, and Linux. So, no matter what platform you're on, you can take advantage of this powerful tool πŸ’ͺ.

Experience the future of code interpretation with Open-Code-Interpreter today! πŸš€

Why this is Unique Interpreter?

The distinguishing feature of this interpreter, as compared to others, is its commitment to remain free πŸ†“. It does not require any model to download or follow to tedious processes or methods for execution. It is designed to be simple and free for all users and works on all major OS Windows,Linux,MacOS

Future Plans:

  • 🎯 We plan to integrate GPT 3.5 models. 🎯 We have added support for GPT 3.5 models.
  • 🌐 .We plan to provide Vertex AI (PALM 2) models.. We have added support for PALM-2 model using LiteLLM
  • πŸ”— We plan to provide API Base change using LiteLLM. Added Support for LiteLLM
  • πŸ€– More Hugging Face models with free-tier.
  • πŸ’» Support for more Operating Systems.
  • πŸ“ Support for Multi-Modal for Text and Vision.
  • πŸ“Š Support for Google and OpenAI Vision Models.
  • Support for Local models via LM Studio.

Table of Contents

πŸ“₯ Installation

Installtion with Python package manager.

To install Open-Code-Interpreter, run the following command:

pip install open-code-interpreter
  • To run the interpreter with Python:
interpreter -m 'gemini-pro' -md 'code' -dc
  • Make sure you install required packages before running the interpreter.
  • And you have API keys setup in the .env file.

Installtion with Git

To get started with Open-Code-Interpreter, follow these steps:

  1. Clone the repository:
git clone https://github.com/haseeb-heaven/open-code-interpreter.git
cd open-code-interpreter
  1. Install the required packages:
pip install -r requirements.txt
  1. Setup the Keys required.

HUGGING FACE API Key setup.

Step 1: Obtain the HuggingFace API key.

Step 2: Visit the following URL: https://huggingface.co/settings/tokens and get your Access Token.

Step 3: Save the token in a .env file as:

echo "HUGGINGFACE_API_KEY=Your Access Token" > .env

Google GEMINI and PALM-2 API Key setup.

Step 1: Obtain the Google Palm API key.

Step 2: Visit the following URL: https://makersuite.google.com/app/apikey

Step 3: Click on the Create API Key button.

Step 4: The generated key is your API key. Please make sure to copy it and paste it in the required field below.

echo "PALM_API_KEY=Your API Key" > .env
echo "GEMINI_API_KEY=Your API Key" > .env

OpenAI API Key setup.

Step 1: Obtain the OpenAI API key.

Step 2: Visit the following URL: https://platform.openai.com/account/api-keys

Step 3: Sign up for an account or log in if you already have one.

Step 4: Navigate to the API section in your account dashboard.

Step 5: Click on the Create New Key button.

Step 6: The generated key is your API key. Please make sure to copy it and paste it in the required field below.

echo "OPENAI_API_KEY=Your API Key" > .env

Offline models setup.

This Interpreter supports offline models via LM Studio so to download it from here and follow the steps below.

  • Download any model from LM Studio like Phi-2,Code-Llama,Mistral.
  • Then in the app go to Local Server option and select the model.
  • Start the server and copy the URL.
  • Open config file configs/offline-model.config and paste the URL in the api_base field.
  • Now you can use the model with the interpreter set the model name to offline-model and run the interpreter.
  1. Run the interpreter with Python:

Running with Python.

python interpreter.py -md 'code' -m 'gpt-3.5-turbo' -dc 
  1. Run the interpreter directly:

Running Interpreter without Python (Executable MacOs/Linux only).

./interpreter -md 'code' -m 'gpt-3.5-turbo' -dc 

🌟 Features

  • πŸš€ Code Execution: Open-Code-Interpreter can execute the code generated from your instructions.

  • πŸ’Ύ Code Save/Update: It has the ability to save the generated code for future use and edit the code if needed on the fly using advanced editor.

  • πŸ“‘ Offline models: It has the ability to use offline models for code generation using LM Studio.

  • πŸ“œ Command History: It has the ability to save all the commands as history.

  • πŸ“œ Command Mode: Commands entered with '/' are executed as commands like /execute or /edit.

  • πŸ”„ Mode Selection: It allows you to select the mode of operation. You can choose from code for generating code, script for generating shell scripts, or command for generating single line commands.

  • 🧠 Model Selection: You can set the model for code generation. By default, it uses the code-llama model.

  • 🌐 Language Selection: You can set the interpreter language to Python or JavaScript. By default, it uses Python.

  • πŸ‘€ Code Display: It can display the generated code in the output, allowing you to review the code before execution.

  • πŸ’» Cross-Platform: Open-Code-Interpreter works seamlessly on every operating system, including Windows, MacOS, and Linux.

  • 🀝 Integration with HuggingFace: It leverages the power of HuggingFace models like Code-llama, Mistral 7b, Wizard Coder, and many more to transform your instructions into executable code.

  • 🎯 Versatility: Whether you need to find files in your system, save images from a website and convert them into a different format, create a GIF, edit videos, or even analyze files for data analysis and creating graphs, Open-Code-Interpreter can handle it all.

πŸ› οΈ Usage

To use Open-Code-Interpreter, use the following command options:

  • List of all modes are:

    • code - Generates code from your instructions.
    • script - Generates shell scripts from your instructions.
    • command - Generates single line commands from your instructions.
    • vision - Generates description of image or video.
    • chat - Chat with your system in natural language.
  • List of all models are (Contribute - MORE):

    • gpt-3.5-turbo - Generates code using the GPT 3.5 Turbo model.
    • gpt-4 - Generates code using the GPT 4 model.
    • gemini-pro - Generates code using the Gemini Pro model.
    • palm-2 - Generates code using the PALM 2 model.
    • code-llama - Generates code using the Code-llama model.
    • code-llama-phind - Generates code using the Code-llama Phind model.
    • mistral-7b - Generates code using the Mistral 7b model.
    • wizard-coder - Generates code using the Wizard Coder model.
    • star-chat - Generates code using the Star Chat model.
    • offline-model - Generates code using the Offline model.
  • Basic usage (with least options)

python interpreter.py -dc
  • Using different models (replace 'model-name' with your chosen model)
python interpreter.py -md 'code' -m 'model-name' -dc
  • Using different modes (replace 'mode-name' with your chosen mode)
python interpreter.py -m 'model-name' -md 'mode-name'
  • Using auto execution
python interpreter.py -m 'wizard-coder' -md 'code' -dc -e
  • Saving the code
python interpreter.py -m 'code-llama' -md 'code' -s
  • Selecting a language (replace 'language-name' with your chosen language)
python interpreter.py -m 'gemini-pro' -md 'code' -s -l 'language-name'

Interpreter Commands πŸ–₯️

Here are the available commands:

  • πŸ“ /save - Save the last code generated.
  • ✏️ /edit - Edit the last code generated.
  • ▢️ /execute - Execute the last code generated.
  • πŸ”„ /mode - Change the mode of interpreter.
  • πŸ”„ /model - Change the model for interpreter.
  • πŸ“¦ /install - Install a package from npm or pip.
  • 🌐 /language - Change the language of the interpreter.
  • 🧹 /clear - Clear the screen.
  • πŸ†˜ /help - Display this help message.
  • πŸ“ /version - Display the version of the interpreter.
  • πŸšͺ /exit - Exit the interpreter.
  • πŸ“œ /log - Toggle different modes of logging.
  • ⏫ /upgrade - Upgrade the interpreter.
  • πŸ’» /shell - Access the shell.

πŸ“– Examples

Code Interpreter Demo code_interpreter_demo

Example of GPT 3.5 Turbo. chatgpt_command

Example of PALM-2 based on Google Vertex AI. chatgpt_command

Example of Code llama with code mode: code_llama_code

Example of Code llama with command mode: code_llama_command

Example of Mistral with code mode: mistral_code

βš™οΈ Settings

You can customize the settings of the current model from the .config file. It contains all the necessary parameters such as temperature, max_tokens, and more.

Steps to add your own custom API Server

To integrate your own API server for OpenAI instead of the default server, follow these steps:

  1. Navigate to the Configs directory.
  2. Open the configuration file for the model you want to modify. This could be either gpt-3.5-turbo.config or gpt-4.config.
  3. Add the following line at the end of the file:
    api_base = https://my-custom-base.com
    
    Replace https://my-custom-base.com with the URL of your custom API server.
  4. Save and close the file. Now, whenever you select the gpt-3.5-turbo or gpt-4 model, the system will automatically use your custom server.

Steps to add new Hugging Face model

  1. πŸ“‹ Copy the .config file and rename it to configs/hf-model-new.config.
  2. πŸ› οΈ Modify the parameters of the model like start_sep, end_sep, skip_first_line.
  3. πŸ“ Set the model name from Hugging Face to HF_MODEL = 'Model name here'.
  4. πŸš€ Now, you can use it like this: python interpreter.py -m 'hf-model-new' -md 'code' -e.
  5. πŸ“ Make sure the -m 'hf-model-new' matches the config file inside the configs folder.

Star History

Star History Chart

🀝 Contributing

If you're interested in contributing to Open-Code-Interpreter, we'd love to have you! Please fork the repository and submit a pull request. We welcome all contributions and are always eager to hear your feedback and suggestions for improvements.

πŸ“Œ Versioning

πŸš€ v1.0 - Initial release.
πŸ“Š v1.1 - Added Graphs and Charts support.
πŸ”₯ v1.2 - Added LiteLLM Support.
🌟 v1.3 - Added GPT 3.5 Support.
🌴 v1.4 - Added PALM 2 Support.
πŸŽ‰ v1.5 - Added GPT 3.5/4 models official Support.
πŸ“ v1.6 - Updated Code Interpreter for Documents files (JSON, CSV,XML).
🌴 v1.7 - Added Gemini Pro Vision Support for Image Processing.
🌴 v1.8 - Added Interpreter Commands Support.

  • 1.8.1 - Added Interpreter Commands Debugging Support.
  • 1.8.2 - Fixed Interpreter Commands
  • 1.8.3 - Added Interpreter Commands Upgrade and Shell Support.
  • 1.8.4 - Fixed Interpreter Model switcher Bug.

    πŸ—¨οΈ v1.9 - Added new Chat mode πŸ—¨οΈ for Chatting with your Files, Data and more.
  • v1.9.1 - Fixed Unit Tests and History Args
  • v1.9.2 - Updated Google Vision to adapt LiteLLM instead of Google GenAI *.
  • v1.9.3 - Added Local Models Support via LM Studio.

πŸ“œ License

This project is licensed under the MIT License. For more details, please refer to the LICENSE file.

Please note the following additional licensing details:

  • The GPT 3.5/4 models are provided by OpenAI and are governed by their own licensing terms. Please ensure you have read and agreed to their terms before using these models. More information can be found at OpenAI's Terms of Use.

  • The PALM models are officially supported by the Google PALM 2 API. These models have their own licensing terms and support. Please ensure you have read and agreed to their terms before using these models. More information can be found at Google Generative AI's Terms of Service.

  • The Hugging Face models are provided by Hugging Face Inc. and are governed by their own licensing terms. Please ensure you have read and agreed to their terms before using these models. More information can be found at Hugging Face's Terms of Service.

πŸ™ Acknowledgments

  • We would like to express our gratitude to HuggingFace,Google,META,OpenAI for providing the models.
  • A special shout-out to the open-source community. Your continuous support and contributions are invaluable to us.

πŸ“ Author

This project is created and maintained by Haseeb-Heaven.

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An innovative open-source Code Interpreter with (GPT,Gemini,PALM,LLaMa) models.

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