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Learn to build a Flask API backend that integrates large language models (LLMs) in this 11-minute video tutorial. Master the process of combining chat and inference functionalities by setting up Flask with necessary dependencies like Flask-CORS for cross-origin resource sharing. Explore image data processing techniques including Base64 encoding, and implement inference functions to extract labels and class information from images. Develop chatbot functionality by implementing conversation history parsing and image class data processing to generate contextual responses. Configure Flask routes for handling image uploads and chatbot interactions, including file upload management, Base64 image decoding, and data processing for frontend communication. Create a robust backend system ready for frontend integration by implementing chat routes that ensure proper processing of user messages through the chatbot model.
