LangChain Basics

• This repo includes basics of LangChain, OpenAI, ChromaDB and Pinecone (Vector databases).
• It covers interacting with OpenAI GPT-3.5 model using LangChain.
• It also combines LangChain agents with OpenAI to search on Internet using Google SERP API and Wikipedia.
• It covers LangChain Chains using Sequential Chains
• Also covers loading your private data using LangChain documents loaders
• Splitting data into chunks using LangChain document splitters,
• Embedding splitted chunks into Chroma DB an PineCone databases using OpenAI Embeddings for search retrieval.

Tech Stack

• LangChain
• OpenAI
• ChromaDB
• Pinecone
• Serp API
• Wikipedia

Features:

• Complete LangChain Guide: Covers all key concepts, including chains, agents, and document loaders.
• Python Code Examples: Practical and easy-to-follow code snippets for each topic.
• Chroma DB & Pinecone: Learn how to integrate Chroma DB and Pinecone with OpenAI embeddings for powerful data management.
• Structured Learning Path: Start from the basics and progress to advanced topics.

Topics Covered:

• Introduction to LangChain and its components
• Building and using chains in LangChain
• Implementing agents for dynamic workflows
• Document loaders with Chroma DB and Pinecone
• Working with OpenAI embeddings for enhanced capabilities

How to Use:

• Clone the Repository: git clone https://github.com/BuildWithLal/langchain-bascis-using-pinecone-chromadb-openai.git
• Explore the Topics: Each folder contains code examples and a README for easy navigation.
• Practice and Learn: Follow the code and examples to deepen your understanding of LangChain.