It's good that you explain things step by step. However, it would be even better if you could also update the libraries. Of course, it's fine even if I do it myself.

armis9

This is a course to learn the concepts and usage methods of the LangChain library, and to build your own ChatGPT using the LangChain library.

aischool

Large Language Models (LLM) for Everyone Part 2 - Building Your Own ChatGPT with LangChain

chatgpt

AISchool

입문

초급

중급이상

대규모 언어 모델

랭체인

LangChain

챗지피티

ChatGPT

Practicum Information

Download Lecture Slides

What is LangChain?

Let's Load External Text - Document Loaders Module

Let's divide text into small semantic units - Document transformers module

Let's convert and save text into Vectors - Embeddings and Vector Stores

Let's integrate LLM and a vector store - Retriever

Let's link various Embedding models.

Leveraging Past Conversations - 메모리(Memory)

Prompt Template (PromptTemplate) - Let's easily try Prompt Engineering (Prompt Engineering)

My Own ChatGPT Making Lab 1 - JudgeGPT (JudgeGPT) Making

My Own ChatGPT: Practice 2 - Building PatentGPT (PatentGPT)

Let's do Entity Extraction with LangChain.

My Own ChatGPT Creation Practical Exercise 3 - Building Review Sentiment Analysis GPT (SentimentGPT)

Integrating Llama Model with LangChain

VectorDB: A Look

Text-To-SQL - Natural Language to SQL Queries with LangChain and LLM

SelfQueryRetriever - Let's perform a query (Query) based on metadata (metadata) filtering.

Creating My Own ChatGPT: Practical Exercise 4 - Building a Product Recommendation GPT (RecommendationGPT)