/IBMGenStarterKit

A simple example showing how to use watsonx with Langchain and Streamlit.

Primary LanguagePython

Building Apps with watsonx.ai and Streamlit

So I'm guessing you've been hearing a bit about watsonx. Well...now you can build your very own app with it🙌 (I know...crazy right?!). In this tutorial you'll learn how to build your own LLM powered Streamlit with the IBMGen library.

See it live and in action 📺

Startup 🚀

  1. Create a virtual environment python -m venv watxonx
  2. Activate it:
    • Windows:.\watxonx\Scripts\activate
    • Mac: source watxonx/bin/activate
  3. Clone this repo by running git clone <this repo name>
  4. Install the dependencies by running pip install -r requirements.txt
  5. Update your watsonx.ai API key on Line 11 of app.py e.g. APIKEY = 'pak-2SuHPQ8y9eDznqXa-7ml-ecMAUJGLseuC3j8Cc41ZVQ'
  6. Run the app by running the command streamlit run app.py

Other References 🔗

-IBMGen Documentation:documentation for the IBMGen library available through the tech preview UI.

-IBMGen Langchain Extension:Langchain is a highly popular LLM library, it's used to structure prompt chains and llm workflows. In this tutorial we use the IBMGen langchain extension to generate responses.

Who, When, Why?

👨🏾‍💻 Author: Nick Renotte
📅 Version: 1.x
📜 License: This project is licensed under the MIT License