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‎README.md‎

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This is Codeinterpreter-codebox, a cloud service for executing Code Interpreter code.
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# Features
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## 📜 Table of Contents
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- [🎯 Key Features](#-key-features)
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- [💡 What Can You Do?](#-what-can-you-do)
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- [📋 Related Projects & Their Differences](#-related-projects--their-differences)
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- [💻 Sample Codes](#-sample-codes)
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- [📦 Deployment](#-deployment)
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- [📧 Contact](#-contact)
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## 🎯 Key Features
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1. 🐍 **Independent Jupyter Sandbox Environment**
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A completely isolated Jupyter sandbox environment that supports state-preserving code execution. Supports file uploads and downloads.
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2. 🐳 **Dockerized One-click Deployment**
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5. 🚀 **More Flexible**
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Supports the opening of more ports to achieve more custom functionality requirements, such as: connecting to databases, connecting to the internet, connecting to other servers.
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## Function Descriptions
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## 💡 What Can You Do?
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1. Execute Python code.
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2. Supports reading of uploaded files ([Upload and Analyze Files](./examples/client/codeinterpreter_session.py)).
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```
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4. Supports dynamic scaling for commercial deployments.
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5. Supports custom feature modifications, open ports, network connections, etc., supports web crawlers.
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## Related Projects and Differences
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## 📋 Related Projects & Their Differences
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1. [Code Interpreter api](https://github.com/shroominic/codeinterpreter-api)
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2. [open-interpreter](https://github.com/KillianLucas/open-interpreter)
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3. [E2B](https://github.com/e2b-dev/e2b)
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| **Supports Local Execution** |||||
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| **Direct Invocation Without Deployment** |||||
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## Code Examples
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1. [jupyter server communicate](./examples/jupyter/jupyter_api_test.ipynb) showcases the details of interaction between the server and the Jupyter container.
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2. [jupyter call](./examples/jupyter/execute_dynamic_code.ipynb) demonstrates how to invoke a web service via an HTTP request, execute code, and retrieve results.
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## 💻 Sample Codes
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1. **Server-Client Interaction**: [jupyter server communicate](./examples/jupyter/jupyter_api_test.ipynb) showcases the details of interaction between the server and the Jupyter container.
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2. **Remote Execution**: [jupyter call](./examples/jupyter/execute_dynamic_code.ipynb) demonstrates how to invoke a web service via an HTTP request, execute code, and retrieve results.
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```
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test_code="""
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import docker
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#output
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Execute Result= {"output_type":"text/plain","content":"6.1.3\n","files":null}
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```
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3. [client session invocation](./examples/client/codeinterpreter_session.py) shows how to allow LLM to invoke and execute code in a project through session and HTTP request.
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3. **Client Session Demonstration**: [client session invocation](./examples/client/codeinterpreter_session.py) shows how to allow LLM to invoke and execute code in a project through session and HTTP request.
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```
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session=CodeinterpreterSession()
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try:
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```
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## Deployment
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## 📦 Deployment
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In [docker compose](./app/docker_dev.yml), replace 'CODEBOX_ROOT_PATH' and 'YOUR_MNT_PATH:/codebox' with your own file path for 'YOUR_MNT_PATH' to mount.
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## Contact
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## 📧 Contact
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WeChat: zjajzzj1996
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Email: [zhangzhehian@gmail.com](zhangzhehian@gmail.com)

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