I am serving my machine learning model on Flask as a POST request.
I am able to successfully make a POST request in Postman, however, on the client, I receive a CORS error when trying to fetch that endpoint in Next.
I have the following server.py
from flask import Flask, request, jsonify
import pickle
from flask_cors import CORS
app = Flask(__name__)
cors = CORS(app)
@app.route('/predict', methods=['POST'])
def predict():
if request.method == 'POST':
data = request.get_json()
sentence = data['sentence']
vectoriser, LRmodel = load_models()
if vectoriser and LRmodel:
vector = vectoriser.transform([sentence])
prediction = LRmodel.predict(vector)
# return jsonify({'prediction': str(prediction[0])})
if prediction[0] == 1:
return jsonify({'prediction': 'Positive'})
else :
return jsonify({'prediction': 'Negative'})
else:
return jsonify("Error")
return 'Error'
if __name__ == '__main__':
app.run(debug=True)
Here is how I am trying to call this endpoint on the client
const Sentiment = (props: any) => {
return (
<>
<h1 style={{ textAlign: 'center' }}>Sentiment</h1>
<div style={{ textAlign: 'center' }}>
<form action="/sentiment" method="POST" onSubmit={handleSubmit}>
<input type="text" name="sentiment" />
<button type="submit">Submit</button>
</form>
</div>
</>
)
}
const handleSubmit = async (e: React.FormEvent<HTMLFormElement>) => {
e.preventDefault()
console.log(e.currentTarget.sentiment.value)
const res = await fetch('http://127.0.0.1:5000/sentiment', {
method: 'POST',
headers: {
'Content-Type': 'application/json',
},
body: JSON.stringify({ sentence: e.currentTarget.sentiment.value }),
})
await res.json()
}
export default Sentiment
I get this error: Access to fetch at 'http://127.0.0.1:5000/sentiment' from origin 'http://localhost:3000' has been blocked by CORS policy: Response to preflight request doesn't pass access control check: It does not have HTTP ok status.
Also when I submit the form I am getting "OPTIONS /sentiment HTTP/1.1" 404 - Instead of a POST
Any ideas on what I am doing wrong?
CodePudding user response:
try setting constructor like this
app = Flask(__name__)
cors = CORS(app, resources={r"/*": {"origins": "*"}})
if that doesn't work try adding cross_origin decorator
from flask_cors import CORS,cross_origin
@app.route('/predict', methods=['POST'])
@cross_origin()
def predict():
if request.method == 'POST':
data = request.get_json()
sentence = data['sentence']
vectoriser, LRmodel = load_models()
if vectoriser and LRmodel:
vector = vectoriser.transform([sentence])
prediction = LRmodel.predict(vector)
# return jsonify({'prediction': str(prediction[0])})
if prediction[0] == 1:
res = jsonify({'prediction': 'Positive'})
res.headers.add("Access-Control-Allow-Origin", "*")
return res
else :
res = jsonify({'prediction': 'Positive'})
res.headers.add("Access-Control-Allow-Origin", "*")
return res
else:
return jsonify("Error")
return 'Error'