GenAI — LangChain Exploration

A hands-on collection of scripts and notebooks covering core LangChain concepts and integrations.

Structure

Folder	What's inside
`1.LLMs/`	Basic LLM usage
`2.ChatModels/`	Chat model integrations — OpenAI, Anthropic, Google, HuggingFace (API & local)
`3.EmbeddedModels/`	Embedding models, document similarity
`Chains in LangChain/`	Simple, sequential, parallel, and conditional chains
`Document loaders/`	Loaders for text, CSV, PDF, web, and directories
`LangChain OP parsers/`	String, JSON, Pydantic, and structured output parsers
`LangChain Strcutured O:P/`	Structured output with TypedDict, Pydantic, and JSON schema
`LangChain_prompts/`	Prompt templates, chat history, message placeholders, chatbot UI
`Runnables/`	`RunnableSequence`, `RunnableParallel`, `RunnableBranch`, `RunnableLambda`, passthrough
`Text Splitters/`	Length-based, structure-based, markdown, Python code, and semantic splitters
`Youtube Chatbot/`	End-to-end chatbot over YouTube content

pip install -r requirements.txt

Create a .env file with your API keys:

OPENAI_API_KEY=...
ANTHROPIC_API_KEY=...
GOOGLE_API_KEY=...
HUGGINGFACEHUB_API_TOKEN=...

LLM providers: OpenAI, Anthropic, Google Gemini, HuggingFace
Core libs: langchain, langchain-core, langchain-openai, langchain-anthropic, langchain-google-genai, langchain-huggingface

Name		Name	Last commit message	Last commit date
1.LLMs		1.LLMs
2.ChatModels		2.ChatModels
3.EmbeddedModels		3.EmbeddedModels
Chains in LangChain		Chains in LangChain
Document loaders		Document loaders
LangChain OP parsers		LangChain OP parsers
LangChain Strcutured O:P		LangChain Strcutured O:P
LangChain		LangChain
LangChain_prompts		LangChain_prompts
Runnables		Runnables
Text Splitters		Text Splitters
Youtube Chatbot		Youtube Chatbot
.DS_Store		.DS_Store
.gitignore		.gitignore
Langchain.ipynb		Langchain.ipynb
README.md		README.md
prompts_ui.py		prompts_ui.py
requirements.txt		requirements.txt
tool_calling_in_langchain.ipynb		tool_calling_in_langchain.ipynb