#76 · Primary category： Prompt Engineering Tools
Get-Things-Done-with-Prompt-Engineering-and-LangChain
Hands-on tutorials and Jupyter notebooks for prompt engineering and LangChain, covering custom data QA, CSV agents, and Llama 2-based PDF chat.
Project last updated：01/07/24
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1.3K
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372
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License
Apache-2.0
Why we included this project
This repo is a practical way to learn LangChain and prompt engineering by working through real code instead of reading docs. Each notebook walks through a concrete task, like loading and indexing your own data, building prompt templates, setting up CSV agents, or using retrieval QA chains to query custom content, so you see how the pieces fit together. Several projects also show how to run a private model like Llama 2 for chatting with PDFs or analyzing tweet sentiment, which matters if you want to keep data off external APIs. The notebooks run in Colab and come with YouTube walkthroughs and written guides, so it's a reasonable on-ramp for developers ready to build their first LLM app.
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