Jupyeter Notebooks that demo Generative AI concepts

Jupyter Notebooks of Course of LangChain for LLM Application Development by DeepLearning.AI

Langraph Understanding

This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. RAG systems combine information retrieval with generative models to provide accurate and contextually rich responses.

A detailed notebook tutorial about LangChain Chains, Memory, Agents, Models, and Prompts.

Archive of python notebooks, code snippets and more written while learning AI agents and workflows

⚠️ [Archived] ⚠️ Web-crawling notebooks to extract, process, and provide data for RAG apps such as buck-ai-guide and utadvisor.

collection of practical LangChain examples using Jupyter Notebooks. Learn how to build LLM-powered apps with embeddings, vector stores, and document loaders. Contributions welcome!

A notebook-driven exploration of next-gen agentic RAG architectures and intelligent retrieval pipelines.

This notebook is used to teach LLMs to provide answers based on information from PDF documents.

These are various Jupyter-Lab notebooks that can help you get familiar with various AI agent frameworks. The notebooks are desinged specifically to run within the Multi-Agent-AI-Research-System environment. Please see my other repository for setting up this environment.

Example langchain usage notebooks

A Langchain, LangGraph, LangSmith self tutorial notebooks

An AI powered note taking app ✏️ 📓

Learning different nodejs dependencies notebook, Not Commercial Use .

Jupyter Notebooks for "Build your own Chatbot" course on KI-Campus

Enhanced notebooks from the DeepLearning.ai course, LangChain for LLM Application Development.

Few notebooks containing the code for building agentic workflow from ground up

This Project is developed in the course: AI Use Case course. These notebooks where the initial work of the hotel booking app using AI.