LangChain-Tutorials

Each Notebook illustrate of how Langchain work through OPenAi and Hugging face

1 - Build First Hugging Face

First tutriol INtroducing you to llm and openAi and how to call your LLM from each openAi and Hugging Face

2 - LLM Template

In this Notebook we start to show what is prompt and how it works and How should we pass it to LLM model with multiply inputs

3 - LLM Schema

In this Notebook we start to Build conversation with ChatGpt chat and build dialog for chatbot

4 - Few Shot Learning

In this Notebook we start to explain one of technquies which help our chat model to understand some tricks or equation which it would understand

5 - Output Parser

In this Notebook we start to explain different formats of chat outut and how we could control it

In this Notebook we start to explain one of technquies which help our chat model to understand previous message to answer correctly by using different types of memory (buffer , buffer window , Enitty .. )

7 - RAG-Chunking and Loader

In this Notebook we start to display different types of loader in langchain and how we could make chunks through different mehtods

8 - RAG-Embedding and Indexing

In this Notebook we start to display different types of Embedding in langchain and how we could build vector database with different ways and indexing chuncks with its embedding

9 - RAG-QNA Chain

In this Notebook we start to display different types of Qna (suff, map reduce , refine) in langchain and how we could build the whole rag

All metrails has been come from Langchain docments , Hugging Face documents , OpenAI documents AND ENG.Abu Bakr Soliman

MAHMOUDRR707/LangChain-Tutorials