## πYour First Retrieval Augmented Generation QA Application!
### Steps to Run:
1. Create a Python 3.11 environment
2. `pip install jupyter` so you can run the notebook
# Build ποΈ
Build a Chainlit App that uses this code.
# Ship π’
- Deploy your Chainlit App to Hugging Face
- Make a simple diagram of the RAQA process
# Share π
- Show your App in a loom video and explain the diagram
- Make a social media post about your final application and tag @AIMakerspace
- Share 3 lessons learned
- Share 3 lessons not learned
Here's a template to get your post started!
```
π Exciting News! π
I just built and shipped my very first Retrieval Augmented Generation QA Application using Chainlit and the OpenAI API! π€πΌ
π Three Key Takeaways:
1οΈβ£ The power of combining traditional search methods with state-of-the-art generative models is mind-blowing. π§ β¨
2οΈβ£ Collaboration and leveraging community resources like AI Makerspace can greatly accelerate the learning curve. π±π
3οΈβ£ Dive deep, keep iterating, and never stop learning. Each project brings a new set of challenges and equally rewarding lessons. ππ
A huge shoutout to the @AI Makerspace for their invaluable resources and guidance. π
Looking forward to more AI-driven adventures! π Feel free to connect if you'd like to chat more about it! π€
#OpenAI #Chainlit #AIPowered #Innovation #TechJourney
```