| <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 | |
| ``` | |