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Build ChatGPT for Your Documents | RAG Chatbot 🔥| Day 22 (Streamlit & Snowflake) Welcome to Day 22 of the 30 Days of AI Coding Challenge 🚀 Yesterday, we asked one question and got one answer. Today… we’re having a conversation with LLM using our documents. This is ChatGPT — but trained on your data. Welcome to a complete RAG pipeline. 🧠 By End of today’ s challenge we will have knowledge on How conversational RAG works How to keep full chat history How AI answers stay grounded in documents How real-world RAG chatbots are built 🛠 Prerequisites Completed Days 1–21 of the challenge (If not, check the earlier videos and complete them first.) • 30 Days of AI Coding Challenge 🚀 | Build A... Timecodes 0:00 - Introduction 0:13 - What you will Learn today 0:31 - Why AI Coding Challenge 0:55 - Demo of the Vector Embeddings for RAG 3:57 - Code walkthrough : Initialize State 4:38 - Smart Service Selection 5:35 - Search Function 7:04 - Chat Input & Response Generation from LLM 10:19 - More Details - RAG based Chatbot 10:43 - Outcome of Day 22 of AI Coding Challenge 11:17 - What you will learn tomorrow 👉 Resources Day 22 challenge guide: [https://30daysofai.streamlit.app/?day=22] Official challenge announcement: [https://discuss.streamlit.io/t/the-30...] Code reference (all days): [https://github.com/sudeepkumar10x/30D...] --- 💼🧑💻 Join Our Data Engineering Community Get exclusive learning resources, updates, and discussions. 👉 https://chat.whatsapp.com/FBv72iezg9M... #30DaysOfAI #Streamlit #Snowflake #AICoding #DataEngineering #SudeepKumar10x #AIChallenge #LLM #RAG #CortexSearch #SemanticSearch #Ragchatbot #chatbot #cortexai #snowflakecortexsearch #cortexAI