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πŸ”Your 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 πŸ—οΈ

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 πŸš€

  • 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!

πŸš€ Exciting News! πŸŽ‰

I just built and shipped my very first Retrieval Augmented Generation QA Application using Chainlit and the OpenAI API! πŸ€–πŸ’Ό 

πŸ” 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. πŸŒ±πŸ“ˆ
3️⃣ Dive deep, keep iterating, and never stop learning. Each project brings a new set of challenges and equally rewarding lessons. πŸ”„πŸ“š

A huge shoutout to the @AI Makerspace for their invaluable resources and guidance. πŸ™Œ

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