Analyse any Github repository with AI Agent || Langchain Part 2 in Hindi

🔥 Want to **summarise ANY GitHub repository using AI** in minutes?
In this video, I’ll show you how to build a **powerful AI Agent using LangChain** that can understand entire codebases, explain them, and answer your questions like a pro.

This is **LangChain Part 2** of the *Zero to Hero* series — and we’re going deep into **real-world AI agents** 🚀

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💡 **What you’ll learn in this video:**

* How to analyze ANY GitHub repo using AI
* Build a **code understanding agent (RAG + LLM)**
* Break down repositories into chunks for smarter retrieval
* How AI “reads” and understands large codebases
* Step-by-step: **3 Steps to Build AI Agents**

1. Load Data
2. Reason (LLM + Retrieval)
3. Respond (Final Output)

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🧠 **Why this matters:**
Imagine pasting a GitHub link and instantly understanding:

* What the project does
* How the code is structured
* Where key logic lives

This is how **top AI engineers** are building productivity tools.

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⚙️ **Tech Stack used:**

* LangChain
* RAG (Retrieval-Augmented Generation)
* Vector Databases (ChromaDB)
* LLM APIs (Groq / OpenAI / Local Models)
* Streamlit UI

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📦 **Use Cases:**

* Developers understanding unknown repos
* Students learning faster
* Building SaaS products
* AI-powered code assistants

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🚀 **Series Roadmap:**
Part 1 → Basics of LangChain
Part 2 → AI Agent (This video)
Next → Memory, Tools, Multi-Agent Systems

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💬 **Comment below:**
What AI Agent should I build next? 👇

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📌 **Subscribe for more:**
I’m building the **#1 AI learning channel in India** — from beginner to advanced.

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#LangChain #AI #GitHub #AIAgents #RAG #MachineLearning #Coding #Developers #Tech #AIProjects

Видео Analyse any Github repository with AI Agent || Langchain Part 2 in Hindi канала NextGuyy