What is LlamaIndex?
LlamaIndex specialises in Retrieval Augmented Generation — connecting LLMs to your data. It handles ingesting documents, chunking, embedding, indexing into vector stores, and retrieval. More focused than LangChain for data-heavy RAG use cases. Supports 160+ data sources and 40+ vector stores.
Quick start
1
pip install llama-index 2
from llama_index.core import VectorStoreIndex, SimpleDirectoryReader 3
docs = SimpleDirectoryReader("data/").load_data()
4
index = VectorStoreIndex.from_documents(docs)
5
index.as_query_engine().query("your question")
Use cases
→Document Q&A over PDFs
→Knowledge base chatbots
→Enterprise search
→Research assistants
Compatible models
OpenAIAnthropicOllama local modelsGemini
Why this matters for India
// india context
Build a Q&A bot over your company's documentation — fully private with local models.