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.

51
/ 100
Established

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.

1,235 stars. No commits in the last 6 months.

Use this if you are an AI/ML developer needing practical guidance and code examples to build custom LLM applications, especially for integrating private data or creating conversational agents.

Not ideal if you are a business user looking for a no-code solution or someone unfamiliar with Python and machine learning development.

AI application development chatbot creation natural language processing LLM fine-tuning custom data integration
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 10 / 25
Maturity 16 / 25
Community 25 / 25

How are scores calculated?

Stars

1,235

Forks

375

Language

Jupyter Notebook

License

Apache-2.0

Last pushed

Jan 07, 2024

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/prompt-engineering/curiousily/Get-Things-Done-with-Prompt-Engineering-and-LangChain"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.