Langchain is an Open-source framework that helps developers build applications powered by Large Language Models (LLM) - Like OpenAI's GPT, Gemini Ai etc.

It Provides tools to connect LLM with external data, tools and memory, making them more useful, context-aware and capable.

Example:

• Chatbots that can read and answer from your PDFs.
• AI Search engines over your private docs(RAG Systems).
• Agents that use tools like calculators, Web Search, or APIs.
• Assistants that remember past conservations.

Why use Langchain?

LLMs like ChatGPT are powerful, but limited:

Without Langchain:

• Only know what it's trained on.
• Forget previous chats.
• Can't use tools
• Limited used in apps.

With Langchain:

• Can access your files, APIs, tools.
• Has Memory.
• Can use tools like search or functions.
• Easily integrated into Full-Stack apps.

Key Components of Langchain:

Components	Purpose
LLMs	The core language model
Prompt Templates	Templates to Structure input to the LLMs.
Chains	A sequence of steps using LLMs.
Agens	Allow the llm to decide which tool to use
Tools	External function the agents can use
Memory	For remembering conversation history
Retrievers	To fetch relevant information from a database
Vector store	Store document embeddings for similarity search