https://github.com/langchain-opentutorial/langchain-gitbook
https://github.com/langchain-opentutorial/langchain-gitbook
Last synced: 14 days ago
JSON representation
- Host: GitHub
- URL: https://github.com/langchain-opentutorial/langchain-gitbook
- Owner: LangChain-OpenTutorial
- License: mit
- Created: 2024-12-29T20:30:59.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-01-11T06:55:42.000Z (over 1 year ago)
- Last Synced: 2025-01-11T07:34:51.212Z (over 1 year ago)
- Language: Jupyter Notebook
- Size: 77 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
#
# 🦜️🔗 The LangChain Open Tutorial for Everyone
This tutorial delves into [LangChain](https://github.com/langchain-ai/langchain), starting from an overview then providing practical examples.
[](https://github.com/GIScience/badges#experimental)
[](https://opensource.org/licenses/MIT "MIT License")
The LangChain community in Seoul is excited to announce the LangChain OpenTutorial, a brand-new resource designed for everyone. This tutorial builds upon the foundation of the existing tutorial available here: [link](https://github.com/teddylee777/langchain-kr) written in Korean.
Within this new repository, we offer the following enhancements to benefit users of all skill levels:
- **Addressing global use cases** for internatial users,
- **Diving deep into cutting-edge features** including the recent updates available at the latest version of LangChain and LangGraph release, and
- **Demonstrating additional goodies** that showcase real-world uses and further applications.
At this base repository, it serves as a home for both beginners and seasoned LangChain users. The tutorial whould provide a roadmap for learning LangChain, while also offering a valuable refresher for those already familiar with its functionalities.
## 🛠️ Contribution Process
### Steps (in developing)
1. **Open a Pull request (PR)**: Develop at least **one** existing or new content file (`.ipynb`). Optionally, add examples related to open LLMs. Then, Submit a PR with the developed content.
*- Note: Self-Check Before PR Submission (Recommended)*
- **License Compliance & Copyright Issues**: Verify that all dataset and content comply with licensing requirements. Confirm that there are no copyright infringements.
- **Template Compliance**: Follow the provided [templates](https://github.com/LangChain-OpenTutorial/LangChain-OpenTutorial/tree/main/99-TEMPLATE)
- **Execution Platform**: Individual files should be executable on **Google Colab**.
- **Specifications Submission (if Required)**: If using open models or additional packages, specify the required environment to Infra Team.
2. **Team Peer Reviews**: Assign at least **two team members** as reviewers. Reviewers will evaluate the code and content quality and check tutorials are compatible with **Mac**, **Windows**, and **Linux** environments. **Approve** the Pull Request if there are no issues.
4. **Merge Pull Request**: Once the Pull Request has been approved by more than two reviewers, the original author can merge the PR into the 'main' branch.
5. **Proofreading**: During the following week, the proofreading team will review the submitted content for typos, template compliance, and proper citations. If the proofreading team requests any modifications, the original author must make the necessary corrections and resubmit the PR.
## 📚 References
- [langchain-ai](https://github.com/langchain-ai/langchain) 📖
- [LangGraph GitHub](https://github.com/langchain-ai/langgraph)
- [LangChain Documentation](https://python.langchain.com/docs/introduction/)
- [OpenAI API Reference](https://platform.openai.com/docs/introduction) 🤖
## 🔗 Community Links
- **LangChain Korean Tutorial(wikidocs)**: [WikiDocs](https://wikidocs.net/book/14314)
- **LangChain Korean Tutorial(github)**: [GitHub Repository](https://github.com/teddylee777/langchain-kr)
- **YouTube Channel**: [Teddy Note](https://www.youtube.com/channel/UCt2wAAXgm87ACiQnDHQEW6Q) 🎥
- **Blog**: [Teddy Note](https://teddylee777.github.io) 📝
- **Playground**: [LangChain LLM Playground](http://llm.teddynote.com) 🎮
### Related Links
- [GitHub Collaboration Guide](https://docs.google.com/document/d/18VrmTq1o22rzjxZ4PEFaemo0lfXRK9vWsyQPEin7OfY/edit?tab=t.0#heading=h.il7lst7f5t57)
- [Github PR Example](https://github.com/LangChain-OpenTutorial/LangChain-OpenTutorial/pull/5)
- [meeting_1_kickoff](https://drive.google.com/file/d/1TqVonuyda6gnJkdSc-XpsqE6JkTmjquZ/view?usp=drive_link)
- [meeting_2_241228](https://docs.google.com/presentation/d/1xVJXCKV9OC4kQk3VKWL79KHitxcX-Mjj/edit#slide=id.p6)
- [meeting_3_250104](https://docs.google.com/presentation/d/1xVJXCKV9OC4kQk3VKWL79KHitxcX-Mjj/edit#slide=id.p6)
## Licence
Unless stated otherwise, the codebase is released under the [MIT Licence][1]. This covers both the codebase and any sample code in the documentation.
[1]: ./LICENCE
## 🌟 Contributors
[](https://github.com/LangChain-OpenTutorial/LangChain-OpenTutorial/graphs/contributors)
