Get-Things-Done-with-Prompt-Engineering-and-LangChain and langchain-js

Maintenance 0/25
Adoption 10/25
Maturity 16/25
Community 25/25
Maintenance 0/25
Adoption 4/25
Maturity 16/25
Community 12/25
Stars: 1,235
Forks: 375
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License: Apache-2.0
Stars: 5
Forks: 1
Downloads:
Commits (30d): 0
Language: JavaScript
License: MIT
Stale 6m No Package No Dependents
Stale 6m No Package No Dependents

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.

AI application development chatbot creation natural language processing LLM fine-tuning custom data integration

About langchain-js

sergeyleschev/langchain-js

This repository are a series of demonstration scripts highlighting the functionalities of LangChain, a JavaScript library tailored for developing conversational AI applications. @ S. Leschev. Google Engineering Level: L6+

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