Get-Things-Done-with-Prompt-Engineering-and-LangChain and langchain-practical-guide

About Get-Things-Done-with-Prompt-Engineering-and-LangChain

curiousily/Get-Things-Done-with-Prompt-Engineering-and-LangChain

LangChain & Prompt Engineering tutorials on Large Language Models (LLMs) such as ChatGPT with custom data. Jupyter notebooks on loading and indexing data, creating prompt templates, CSV agents, and using retrieval QA chains to query the custom data. Projects for using a private LLM (Llama 2) for chat with PDF files, tweets sentiment analysis.

This project helps AI application developers build custom applications with large language models like ChatGPT. It guides you through integrating your own data sources, creating intelligent agents, and building chatbots that can understand and respond to specific queries. The output is a functional AI application, such as a sentiment analyzer for social media or a chatbot that can answer questions based on your documents. AI/ML engineers and data scientists looking to leverage LLMs for bespoke solutions are the target users.

About langchain-practical-guide

bibekgupta3333/langchain-practical-guide

A comprehensive, hands-on tutorial repository for learning and mastering LangChain - the powerful framework for building applications with Large Language Models (LLMs). This codebase provides a structured learning path with practical examples covering everything from basic chat models to advanced AI agents, organized in a progressive curriculum.