Скачать или смотреть Build a RAG Chatbot in 20 Minutes with LangChain & FAISS (FREE API + Google Colab Tutorial

🚀 Learn how to build a complete Retrieval-Augmented Generation (RAG) system from scratch using LangChain, HuggingFace Embeddings, and FAISS vector database - completely FREE!

  / siddharth-kharche-9a0681217  

https://github.com/siddharth-Kharche/...

In this beginner-friendly tutorial, you'll learn:
✅ What is RAG and why it eliminates AI hallucinations
✅ Setting up Google Colab environment with free APIs
✅ Using Groq API for fast LLM inference (FREE)
✅ Implementing HuggingFace embeddings (nomic-bert-2048)
✅ Building FAISS vector store for semantic search
✅ Creating a RetrievalQA chain with LangChain
✅ Querying documents with grounded AI responses

🔗 Google Colab Notebook: [Your Colab Link]
🔗 GitHub Repository: [Your GitHub Link]

🛠️ TECH STACK:
LangChain 0.3.19
LangChain-Groq 0.2.4
LangChain-HuggingFace 0.1.2
Sentence-Transformers 3.0.1
FAISS-CPU 1.10.0
Python 3.10+

🎁 FREE RESOURCES:
📌 Groq API (Free): https://console.groq.com/keys
📌 HuggingFace Token: https://huggingface.co/settings/tokens
📌 Complete Code Repository: [Your Link]

💡 WHAT IS RAG?
Retrieval-Augmented Generation combines the power of large language models with external knowledge bases, allowing AI to provide accurate, up-to-date responses without hallucinations. This tutorial demonstrates the standard RAG implementation perfect for beginners!

🔔 Subscribe for more AI/ML tutorials on:
Advanced RAG techniques
Vector databases (Weaviate, Pinecone, Chroma)
LangChain agents & chains
LLM fine-tuning
Production AI systems

#RAG #LangChain #AI #MachineLearning #Python #Tutorial #FAISS #HuggingFace #Groq #VectorDatabase #LLM #NLP #AITutorial #CodingTutorial

📧 Questions? Drop them in the comments!
👍 Like if this helped you build your first RAG system!