moghit/word2vec-embeddings

1from flask import Flask 
2from flask import render_template , request  , jsonify
3from prediction import predict_ , tokenizer, avg_vector
4import os 
5app = Flask(__name__)
6
7@app.route('/')
8def home():
9    return render_template("index.html")
10
11@app.route('/test')
12def testing():
13    return render_template("index_1.html")
14
15
16@app.route('/classification', methods=['POST'])
17def classify():
18
19    data = request.form
20    email_body = data.get("email_body")
21
22    if not email_body:
23        email_body = request.args.get("email_body")
24
25    if not email_body:
26        return jsonify({"error": "Missing email_body parameter"}), 400
27    
28    return jsonify({"prediction": predict_(email_body)[0]})
29
30#----------------------(text vectorization)----------------------------
31#hidden endpoint for vectorization
32@app.route('/vectorization', methods=['GET'])
33def vectorization():
34    data = request.args.get("text")
35    if not data:
36        return jsonify({"error": "Missing text parameter"}), 400
37    
38    tokens = tokenizer(data)
39    vector = avg_vector(tokens)
40    return jsonify({"vector": vector.tolist()})
41
42
43
44if __name__ == '__main__':
45    app.run()