Скачать или смотреть LLM Chains using GPT 3.5 and other LLMs — LangChain #3

In the third part of our LangChain series, we'll explore chains, focusing on generic and utility chains like LLMChain. These are key features in LangChain that act as the foundation behind more advanced langchain uses like conversational AI (chatbots), retrieval-augmented generation (RAG), and more.

LangChain is a popular framework that allows users to quickly build apps and pipelines around Large Language Models. It integrates directly with OpenAI's GPT-3 and GPT-3.5 models and Hugging Face's open-source alternatives like Google's flan-t5 models.

It can be used for chatbots, Generative Question-Anwering (GQA), summarization, and much more.

The core idea of the library is that we can "chain" together different components to create more advanced use cases around LLMs. Chains may consist of multiple components from several modules. We'll explore all of this in these videos.

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Part 1 (Intro):    • Prompt Engineering with OpenAI's GPT-...  
Part 2 (PromptTemplate):    • Prompt Templates for GPT 3.5 and othe...  
Part 4 (Conversational Memory):    • Chatbot Memory for Chat-GPT, Davinci ...  

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00:00 What are Langchain chains?
01:01 LLMChain
05:14 Utility chains walkthrough
10:25 All generic chains in langchain
14:07 Langchain hub
15:10 Other chains in langchain