LangChain Tutorials

A collection of Jupyter notebooks demonstrating various LangChain functionalities and use cases.

Contents

Basic Tutorials

• translation.ipynb - Translation app using LangChain
• classification.ipynb - Text classification and labeling

Chatbots

• chatbot.ipynb - Basic chatbot with LangGraph
• chatbot_v2.ipynb - Enhanced chatbot version
• chatbot_v3.ipynb - Latest chatbot implementation

RAG Applications

• rag_v1.ipynb - Retrieval Augmented Generation app
• rag_v2.ipynb - Improved RAG implementation

Agents

• basic_agent.ipynb - Simple agent with tools

Advanced Features

• langgraph_quick_start.ipynb - LangGraph framework basics
• extraction_chain.ipynb - Data extraction with tool calling
• sematic_search_engine.ipynb - Semantic search implementation

Setup

1. Install dependencies:

pip install langchain langchain-core langchain-community
pip install langchain-openai langchain-deepseek
pip install langgraph langchain-text-splitters
pip install python-dotenv beautifulsoup4 langchain-tavily

2. Create a .env file with your API keys:

OPENAI_API_KEY=your_key
DEEPSEEK_API_KEY=your_key
OPENROUTER_API_KEY=your_key
LANGSMITH_API_KEY=your_key
TAVILY_API_KEY=your_key

Requirements

• Python 3.8+
• Jupyter Notebook
• API keys for various services (OpenAI, DeepSeek, etc.)