RunPod: [ Ссылка ]
🚀 Introduction:
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In this tutorial, we’ll build and deploy a complete coffee shop customer service AI chatbot that takes orders, provides menu info, blocks irrelevant conversations, and even recommends products based on Market Basket Analysis! We'll cover cutting-edge topics like Prompt Engineering, Retrieval-Augmented Generation (RAG), and the modular power of Agent-Based Systems. You'll also learn how to deploy Large Language Models (LLMs) and custom APIs using RunPod, and build a full React Native app that connects to Firebase and the RunPod endpoints. By the end, you’ll have a fully functional chatbot app and level up your AI, development, and deployment skills!
🔄 Update:
Runpod seems to have changed the place to access the openAI URL
here it is: [ Ссылка ]
and the RunPod endpoint ID is the string right under the endpoint name.
here is a link for more information: [ Ссылка ]
💡 What You’ll Learn:
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1. 🧠 Prompt Engineering: Guide your chatbot with precise instructions.
2. 🔍 Retrieval-Augmented Generation (RAG): Enhance chatbot answers using personalized data.
3. 🛠️ Agent-Based Systems: Create specialized components for efficient and accurate chatbot responses.
4. 📊 Market Basket Analysis Recommendation Engine: Build a recommendation engine from scratch.
5. 🖥️ RunPod Deployment: Deploy LLMs, embedding models, and custom APIs effortlessly.
6. 📱 React Native App: Build an end-to-end mobile app connected to Firebase and RunPod.
🔗 Links:
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RunPod: [ Ссылка ]
Github Repo: [ Ссылка ]
Coffee Shop Transactions Kaggle Dataset Link: [ Ссылка ]
🎁 Free Credit Codes:
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Grab one of the 20 credit codes in the description to get free credits on RunPod!
How to Redeem: Go to the left panel, click on Billing, scroll down to Credit Codes, and paste one of the codes below.
1602zubevdxd7xbzm4ap
mpbictqmksolp73td4mq
opruk1yoqatfc1jw2nry
7l6kusubtdy3cb95906t
7rhjrmch9ilvnwd3dt0r
oiykzqwrk2vhqgkvyh8c
4s5vjcl2irojl1bnkh89
vn7wpd7jkpdnamq3q516
6st9nt72etun8xcvlb6j
svsg0g0fjiuozkaam82t
8kjapravfr1se22126it
6itba529k8083pm15dtj
oy9k1wombmml0pyoo1ba
vyoryb2v9q4tr58etfjh
v6smwvna8c10racrv5si
🔑 TIMESTAMPS
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0:00 - Introduction
5:27 - Deploy Llama LLM with RunPod
30:15 - Prompt Engineering Tutorial
52:00 - RAG Introduction
1:15:35 - Recommendation engine Development
2:17:20 - Firebase DB setup
2:47:10 - Pinecone Vector DB setup
3:13:13 - Agent Based System
5:49:20 - Deploy chatbot API with RunPod
6:15:31 - React Native application Front End
11:14:30 - ChatBot React Native Page
