LangChain-OpenTutorial and LangChain-Tutior

These are complementary learning resources that serve different audiences: the first is a comprehensive open tutorial in English for general LangChain learners, while the second is a beginner's guide specifically tied to Andrew Ng's DeepLearning.AI course with multi-language implementations (Python, Node.js, Golang).

LangChain-OpenTutorial
62
Established
LangChain-Tutior
43
Emerging
Maintenance 2/25
Adoption 10/25
Maturity 25/25
Community 25/25
Maintenance 0/25
Adoption 10/25
Maturity 16/25
Community 17/25
Stars: 1,007
Forks: 324
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License: MIT
Stars: 177
Forks: 25
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License: MIT
Stale 6m
Stale 6m No Package No Dependents

About LangChain-OpenTutorial

LangChain-OpenTutorial/LangChain-OpenTutorial

LangChain, LangGraph Open Tutorial for everyone!

This tutorial helps developers learn how to build applications using LangChain and LangGraph. It starts with an overview of these frameworks and provides practical examples, covering new features and real-world applications. The tutorial takes conceptual knowledge and turns it into executable code for building large language model (LLM) powered tools.

AI-development LLM-engineering software-development application-building developer-education

About LangChain-Tutior

ConnectAI-E/LangChain-Tutior

⛓ LangChain 入门指南,配套吴恩达老师deeplearning.ai课程 😎复现语言:Python、NodeJs、Golang

This project provides practical code examples and guides for building applications with large language models using LangChain. It takes the concepts from Andrew Ng's deeplearning.ai course on LangChain and translates them into runnable code. Developers who want to integrate AI capabilities into their software using Python, Node.js, or Go can use this to learn how to structure and implement such applications.

AI application development Large Language Models (LLM) AI integration software engineering AI programming

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