26 lines
663 B
Python
26 lines
663 B
Python
from flask import Flask, request, jsonify
|
|
import joblib
|
|
import sklearn
|
|
import numpy as np
|
|
|
|
model = joblib.load("model/category_model.pkl")
|
|
vectorizer = joblib.load("model/vectorizer.pkl")
|
|
|
|
app = Flask(__name__)
|
|
|
|
@app.route("/api/predict", methods=["POST"])
|
|
def predict():
|
|
data = request.json
|
|
description = data.get("description", "")
|
|
|
|
if not description:
|
|
return jsonify({"error": "Description is required"}), 400
|
|
|
|
# Preprocess and predict
|
|
X = vectorizer.transform([description])
|
|
prediction = model.predict(X)[0]
|
|
|
|
return jsonify({"category": prediction})
|
|
|
|
if __name__ == "__main__":
|
|
app.run(host="0.0.0.0", port=5000)
|