#openai #langchain #langchainjs
Retrieval chains allow us to connect our AI-application to external data sources to improve question answering. This is one of the most important skills to have as an AI developer, and in this video we will break down the process step-by-step.
We will cover Document Loaders, Text Splitters, Embeddings, Vector Stores and Retrieval using the retrievalChain.
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📑 Useful Links:
Langchain JS docs: js.langchain.com/docs/get_sta...
Langchain LCEL: js.langchain.com/docs/express...
Source Code: github.com/leonvanzyl/langcha...
OpenAI: platform.openai.com
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🕒 TIMESTAMPS:
00:00 - Intro to Retrieval Chains
00:50 - Project setup
02:44 - Project Explanation
04:35 - Adding Prompt Context
05:32 - Langchain Documents
06:47 - createStuffDocumentsChain
09:11 - Document Loaders
12:07 - Text Splitters
15:04 - Intro to Vector Stores
16:13 - Embeddings
16:38 - Create Vector Store
18:16 - Retrieval
19:17 - RetrievalChain
21:18 - Congrats
Негізгі бет Ғылым және технология LangChain Tutorial (JS) #4: Chatting with Documents using Retrieval Chains
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