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<p align = "center" draggable=”false” ><img src="https://github.com/AI-Maker-Space/LLM-Dev-101/assets/37101144/d1343317-fa2f-41e1-8af1-1dbb18399719" 
     width="200px"
     height="auto"/>
</p>

## <h1 align="center" id="heading">🔍Your First Retrieval Augmented Generation QA Application!</h1>

### Steps to Run:

1. Create a Python 3.11 environment
2. `pip install jupyter` so you can run the notebook

# Build 🏗️
Build a Chainlit App that uses this code.

# Ship 🚢
- Deploy your Chainlit App to Hugging Face
- Make a simple diagram of the RAQA process

# Share 🚀
- 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!

```
🚀 Exciting News! 🎉

I just built and shipped my very first Retrieval Augmented Generation QA Application using Chainlit and the OpenAI API! 🤖💼 

🔍 Three Key Takeaways:
1️⃣ The power of combining traditional search methods with state-of-the-art generative models is mind-blowing. 🧠✨
2️⃣ Collaboration and leveraging community resources like AI Makerspace can greatly accelerate the learning curve. 🌱📈
3️⃣ Dive deep, keep iterating, and never stop learning. Each project brings a new set of challenges and equally rewarding lessons. 🔄📚

A huge shoutout to the @AI Makerspace for their invaluable resources and guidance. 🙌

Looking forward to more AI-driven adventures! 🌟 Feel free to connect if you'd like to chat more about it! 🤝

#OpenAI #Chainlit #AIPowered #Innovation #TechJourney
```