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🔹 Backend wrap-up: preparing for front-end integration and testing.
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Building a Plant Information Chatbot Backend with YOLOv8, Flask and LLM Integration
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- 1 🔹 Setting up the backend folder structure, including assets and app.py.
- 2 🔹 Installing dependencies: Python 3.9+, UltraLytics, Flask, and Embed Chain.
- 3 🔹 Building inference with YOLOv8 to classify images and map labels using JSON.
- 4 🔹 Integrating Wikipedia and Google Search for reliable chatbot sources.
- 5 🔹 Designing a detailed query template for plant-specific information.
- 6 🔹 Creating a Flask API to handle image uploads and chatbot responses.
- 7 🔹 Managing chatbot sessions to ensure unique results for each upload.
- 8 🔹 Backend wrap-up: preparing for front-end integration and testing.
