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Boosting AI: Build A Chatbot With Your Data | LangChain Templates Using the RAG Pattern

11 min • Published Apr 26, 2024
Python
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✅ Find the written article here → https://mdb.link/article-9zyL1_8X8rQ ✅ Sign-up for a free cluster → https://mdb.link/free-9zyL1_8X8rQ ✅ Get help on our Community Forums → https://mdb.link/community-9zyL1_8X8rQ Discover how to enhance your AI chatbot using MongoDB Atlas Vector Search combined with LangChain Templates in our comprehensive tutorial. This video will guide you through the innovative process of integrating retrieval-augmented generation (RAG) pattern to improve your chatbot’s response accuracy and relevance. We'll walk you through the key technologies, including the use of MongoDB's Vector Search and the deployment of LangChain templates to seamlessly fuse external data with LLMs for more dynamic interactions. What You Will Learn: - How to use MongoDB Atlas Vector Search to pinpoint relevant data. - Setting up LangChain Templates for efficient AI integrations. - Step-by-step guide on deploying a chatbot using the RAG pattern. --- Subscribe to MongoDB YouTube→ https://mdb.link/subscribe
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