ryan wong
54 lines
2.3 KiB
Python
54 lines
2.3 KiB
Python
from flask import Flask, request, jsonify, render_template
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app = Flask(__name__)
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@app.route('/product-recommendation', methods=['POST'])
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def product_recommendation():
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"""
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Endpoint for product recommendations based on natural language queries.
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Input: Form data containing 'query' (string).
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Output: JSON with 'products' (array of objects) and 'response' (string).
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"""
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query = request.form.get('query', '')
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# Process the query to find matching products
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products = [] # Empty array, to be populated with product data
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response = "" # Empty string, to be filled with a natural language response
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return jsonify({"products": products, "response": response})
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@app.route('/ocr-query', methods=['POST'])
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def ocr_query():
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"""
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Endpoint to process handwritten queries extracted from uploaded images.
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Input: Form data containing 'image_data' (file, base64-encoded image or direct file upload).
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Output: JSON with 'products' (array of objects) and 'response' (string).
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"""
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image_file = request.files.get('image_data')
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# Process the image to extract text and find matching products
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products = [] # Empty array, to be populated with product data
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response = "" # Empty string, to be filled with a natural language response
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return jsonify({"products": products, "response": response})
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@app.route('/image-product-search', methods=['POST'])
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def image_product_search():
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"""
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Endpoint to identify and suggest products from uploaded product images.
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Input: Form data containing 'product_image' (file, base64-encoded image or direct file upload).
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Output: JSON with 'products' (array of objects) and 'response' (string).
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"""
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product_image = request.files.get('product_image')
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# Process the product image to detect and match products
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products = [] # Empty array, to be populated with product data
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response = "" # Empty string, to be filled with a natural language response
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return jsonify({"products": products, "response": response})
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@app.route('/sample_response', methods=['GET'])
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def sample_response():
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"""
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Endpoint to return a sample JSON response for the API.
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Output: JSON with 'products' (array of objects) and 'response' (string).
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"""
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return render_template('sample_response.html')
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if __name__ == '__main__':
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app.run(debug=True)
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