Create app.py

app.py

@@ -0,0 +1,33 @@
+from flask import Flask, request, jsonify
+import tensorflow as tf
+import numpy as np
+
+app = Flask(__name__)
+
+# Load the TensorFlow Lite model
+interpreter = tf.lite.Interpreter(model_path="quote_model.tflite")  # Use your model file name
+interpreter.allocate_tensors()
+
+# Get input & output details
+input_details = interpreter.get_input_details()
+output_details = interpreter.get_output_details()
+
+@app.route("/predict", methods=["POST"])
+def predict():
+    try:
+        data = request.json  # Get input JSON
+        embedding = np.array([data["embedding"]], dtype=np.float32)  # Convert to tensor
+
+        # Run inference
+        interpreter.set_tensor(input_details[0]['index'], embedding)
+        interpreter.invoke()
+        output_data = interpreter.get_tensor(output_details[0]['index'])
+
+        return jsonify({"predictions": output_data.tolist()})
+
+    except Exception as e:
+        return jsonify({"error": str(e)})
+
+# Run the Flask server
+if __name__ == "__main__":
+    app.run(host="0.0.0.0", port=7860)