Building Rag Applications With Langchain

Learn to build Retrieval-Augmented Generation (RAG) applications using LangChain with Python and FAISS vector stores for enhanced AI retrieval.

Description

Automatically generated AI learning skill from curated web and social media sources.

Steps

1. Learn how to build Retrieval-Augmented Generation applications. ```python
2. from langchain.chains import RetrievalQA
3. from langchain.vectorstores import FAISS
4. qa_chain = RetrievalQA.from_chain_type(llm=llm, retriever=vectorstore.as_retriever())

Code Examples

from langchain.chains import RetrievalQA
from langchain.vectorstores import FAISS
qa_chain = RetrievalQA.from_chain_type(llm=llm, retriever=vectorstore.as_retriever())

Dependencies

• Python 3.8+
• Relevant libraries (see code examples)