{"id":15039299,"url":"https://github.com/djangopeng/openai-quickstart","last_synced_at":"2025-05-14T04:07:53.783Z","repository":{"id":182272223,"uuid":"667480296","full_name":"DjangoPeng/openai-quickstart","owner":"DjangoPeng","description":"A comprehensive guide to understanding and implementing large language models with hands-on examples using LangChain for GenAI applications.","archived":false,"fork":false,"pushed_at":"2025-03-08T02:10:34.000Z","size":61777,"stargazers_count":1519,"open_issues_count":42,"forks_count":1054,"subscribers_count":44,"default_branch":"main","last_synced_at":"2025-04-20T07:41:08.955Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"apache-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/DjangoPeng.png","metadata":{"files":{"readme":"README-en.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2023-07-17T15:43:10.000Z","updated_at":"2025-04-19T13:27:29.000Z","dependencies_parsed_at":"2025-03-21T10:11:19.327Z","dependency_job_id":null,"html_url":"https://github.com/DjangoPeng/openai-quickstart","commit_stats":null,"previous_names":["djangopeng/openai-quickstart"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/DjangoPeng%2Fopenai-quickstart","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/DjangoPeng%2Fopenai-quickstart/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/DjangoPeng%2Fopenai-quickstart/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/DjangoPeng%2Fopenai-quickstart/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/DjangoPeng","download_url":"https://codeload.github.com/DjangoPeng/openai-quickstart/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":254069599,"owners_count":22009558,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2024-09-24T20:42:21.431Z","updated_at":"2025-05-14T04:07:48.760Z","avatar_url":"https://github.com/DjangoPeng.png","language":"Jupyter Notebook","funding_links":[],"categories":["Langchain"],"sub_categories":[],"readme":"# OpenAI Quickstart\n\n![GitHub stars](https://img.shields.io/github/stars/DjangoPeng/openai-quickstart?style=social)\n![GitHub forks](https://img.shields.io/github/forks/DjangoPeng/openai-quickstart?style=social)\n![GitHub watchers](https://img.shields.io/github/watchers/DjangoPeng/openai-quickstart?style=social)\n![GitHub repo size](https://img.shields.io/github/repo-size/DjangoPeng/openai-quickstart)\n![GitHub language count](https://img.shields.io/github/languages/count/DjangoPeng/openai-quickstart)\n![GitHub top language](https://img.shields.io/github/languages/top/DjangoPeng/openai-quickstart)\n![GitHub last commit](https://img.shields.io/github/last-commit/DjangoPeng/openai-quickstart?color=red)\n![GitHub last commit](https://img.shields.io/github/last-commit/DjangoPeng/openai-quickstart?color=red)\n\n\u003cp align=\"center\"\u003e\n    \u003cbr\u003e English | \u003ca href=\"README.md\"\u003e中文\u003c/a\u003e\n\u003c/p\u003e\n\n\nThis project is designed as a one-stop learning resource for anyone interested in large language models and their application in Generative AI(GenAI) scenarios. By providing theoretical foundations, development basics, and hands-on examples, this project offers comprehensive guidance on these cutting-edge topics.\n\n## Features\n\n- **Theory and Development Basics of Large Language Models**: Deep dive into the inner workings of large language models like BERT and GPT Family, including their architecture, training methods, applications, and more.\n\n- **OpenAI-based Development**: tutorial and best practices for OpenAI's Embedding, GPT-3.5, GPT-4, as well as practical development such as Function Calling and **ChatGPT Plugin**.\n\n- **GenAI Application Development with LangChain**: Hands-on examples and tutorials using LangChain to develop GenAI applications, demonstrating the practical application of large language models(**AutoGPT, RAG-chatbot, Machine Translation**)\n\n- **LLM Tech Stack and Ecosystem**: Data privacy and legal compliance, GPU Technology Selection Guide, Hugging Face quick start, ChatGLM usage.\n\n## Getting Started\n\nYou can start by cloning this repository to your local machine:\n\n```shell\ngit clone https://github.com/DjangoPeng/openai-quickstart.git\n```\n\nThen navigate to the directory and follow the individual module instructions to get started.\n\n\n## Setting Up the Development Environment\n\nThis project is developed using Python v3.10. For a complete list of Python dependency packages, see [requirements.txt](requirements.txt).\n\nOfficial documentation for key dependencies is as follows:\n\n- Python environment management with [Miniconda](https://docs.conda.io/projects/miniconda/en/latest/)\n- Interactive Python development environment [Jupyter Lab](https://jupyterlab.readthedocs.io/en/stable/getting_started/installation.html)\n- Large model application development framework [LangChain](https://python.langchain.com/docs/get_started/installation)\n- [OpenAI Python SDK](https://github.com/openai/openai-python?tab=readme-ov-file#installation)\n\n\n**Below are detailed installation instructions (using Ubuntu OS as an example):**\n\n### Installing Miniconda\n\n```shell\nmkdir -p ~/miniconda3\nwget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O ~/miniconda3/miniconda.sh\nbash ~/miniconda3/miniconda.sh -b -u -p ~/miniconda3\nrm -rf ~/miniconda3/miniconda.sh\n```\n\nAfter installation, it is recommended to create a new Python virtual environment named `langchain`.\n\n```shell\nconda create -n langchain python=3.10\n\n# Activate the environment\nconda activate langchain \n```\n\nThis environment needs to be activated each time before use.\n\n\n### Installing Python Dependency Packages\n\n```shell\npip install -r requirements.txt\n```\n\n### Configuring OpenAI API Key\n\nDepending on the command-line tool you use, set the `OPENAI_API_KEY` environment variable in `~/.bashrc` or `~/.zshrc`:\n\n```shell\nexport OPENAI_API_KEY=\"xxxx\"\n```\n\n### Installing and Configuring Jupyter Lab\n\nAfter the above development environment setup, use Miniconda to install Jupyter Lab:\n\n```shell\n# Generate a Jupyter Lab configuration file\njupyter lab --generate-config\n```\n\nOpen the configuration file and make the following changes:\n\n```python\n# Allowing Jupyter Lab to start as a non-root user (no need to modify if starting as root)\nc.ServerApp.allow_root = True\nc.ServerApp.ip = '*'\n```\n\nUse `nohup` to start Jupyter Lab in the background:\n\n```shell\n$ nohup jupyter lab --port=8000 --NotebookApp.token='replace_with_your_password' --notebook-dir=./ \u0026\n```\n\nJupyter Lab's output log will be saved in the `nohup.out` file (which is already filtered in the `.gitignore` file).\n\n\n## Course Schedule\n\nFor the complete documentation, please refer to the [Quick Start Guide for Large Language Models (LLMs) Application Development - Course Outline](docs/schedule.md#schedule)\n\n\n## Contributing\n\nContributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated. If you have any suggestions or feature requests, please open an issue first to discuss what you would like to change.\n\n\u003ca href='https://github.com/repo-reviews/repo-reviews.github.io/blob/main/create.md' target=\"_blank\"\u003e\u003cimg alt='Github' src='https://img.shields.io/badge/review_me-100000?style=flat\u0026logo=Github\u0026logoColor=white\u0026labelColor=888888\u0026color=555555'/\u003e\u003c/a\u003e\n\n## License\n\nThis project is licensed under the terms of the Apache-2.0 License . See the [LICENSE](LICENSE) file for details.\n\n## Contact\n\nDjango Peng - pjt73651@email.com\n\nProject Link: https://github.com/DjangoPeng/openai-quickstart\n\n## Star History\n\n\u003ca href=\"https://star-history.com/#DjangoPeng/openai-quickstart\u0026Date\"\u003e\n  \u003cpicture\u003e\n    \u003csource media=\"(prefers-color-scheme: dark)\" srcset=\"https://api.star-history.com/svg?repos=DjangoPeng/openai-quickstart\u0026type=Date\u0026theme=dark\" /\u003e\n    \u003csource media=\"(prefers-color-scheme: light)\" srcset=\"https://api.star-history.com/svg?repos=DjangoPeng/openai-quickstart\u0026type=Date\" /\u003e\n    \u003cimg alt=\"Star History Chart\" src=\"https://api.star-history.com/svg?repos=DjangoPeng/openai-quickstart\u0026type=Date\" /\u003e\n  \u003c/picture\u003e\n\u003c/a\u003e","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdjangopeng%2Fopenai-quickstart","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdjangopeng%2Fopenai-quickstart","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdjangopeng%2Fopenai-quickstart/lists"}