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https://github.com/dataprofessor/langchain-quickstart
Build your first LLM powered app with Langchain and Streamlit.
https://github.com/dataprofessor/langchain-quickstart
langchain langchain-python large-language-models llm streamlit
Last synced: about 1 month ago
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Build your first LLM powered app with Langchain and Streamlit.
- Host: GitHub
- URL: https://github.com/dataprofessor/langchain-quickstart
- Owner: dataprofessor
- Created: 2023-05-20T06:06:31.000Z (over 1 year ago)
- Default Branch: master
- Last Pushed: 2024-06-24T05:16:07.000Z (6 months ago)
- Last Synced: 2024-08-13T07:07:27.410Z (4 months ago)
- Topics: langchain, langchain-python, large-language-models, llm, streamlit
- Language: Python
- Homepage: https://langchain-quickstart.streamlit.app/
- Size: 228 KB
- Stars: 62
- Watchers: 2
- Forks: 133
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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- jimsghstars - dataprofessor/langchain-quickstart - Build your first LLM powered app with Langchain and Streamlit. (Python)
README
# 🦜🔗 Langchain - Quickstart App
Build your first LLM powered app with Langchain and Streamlit.
## Overview of the App
- Accepts input text (*e.g.* `What are the three key pieces of advice for learning how to code?`) as prompt input using Streamlit's `st.text_area()`, then assign this to the `text` variable.
- LLM model is called via `llm()` and it is applied on the prompt input `text` to generate a response via `llm(text)`## Demo App
[![Streamlit App](https://static.streamlit.io/badges/streamlit_badge_black_white.svg)](https://langchain-quickstart.streamlit.app/)
## Get an OpenAI API key
You can get your own OpenAI API key by following the following instructions:
1. Go to https://platform.openai.com/account/api-keys.
2. Click on the `+ Create new secret key` button.
3. Next, enter an identifier name (optional) and click on the `Create secret key` button.## Try out the app
Once the app is loaded, go ahead and enter your OpenAI API key and type a question in the text box and wait for a generated response.