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.
ORIGINAL REPOSITORY
curiousily/Get-Things-Done-with-Prompt-Engineering-and-LangChain ↗GitHub activity
- Stars
- 1,259
- Forks
- 373
- Open issues and PRs
- 9
- Repository size
- ~15,783 KB
- Default branch
- master
- Created
- Apr 12, 2023
- Repository updated
- Nov 2, 2026
- Last push
- Jan 7, 2024
- Language
- Jupyter Notebook
- License
- Apache-2.0
Topics artificial-intelligence · chatgpt · deep-learning · gpt-4 · gpt4 · langchain · language-models · large-language-models · llama2 · openai · prompt-engineering · python
Repository-wide figures from GitHub, checked Nov 11, 2026. Stars are endorsements, not a Mega AI Hub quality rating. Repository size is GitHub’s estimate; a ZIP download may differ.
Resource information
- Original repository
- curiousily/Get-Things-Done-with-Prompt-Engineering-and-LangChain
- Credit basis
- GitHub repository owner or organization; individual authorship is not asserted
- Publisher
- curiousily
- Upstream last modified
- Nov 2, 2026
- Official website
- https://github.com/curiousily/Get-Things-Done-with-Prompt-Engineering-and-LangChain
- Languages
- Jupyter Notebook
- Access
- Open original GitHub repository; publisher terms apply
- Last checked
- Nov 3, 2026
- License
- Apache-2.0
- Last record update
- Nov 3, 2026