Sentence processing can now be used with the REST API
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06b8be8026
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@ -2,11 +2,12 @@ import os
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import torch
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from unidecode import unidecode
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import get_path_file
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from ia.model import NeuralNet
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from ia.nltk_utils import bag_of_words, tokenize
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print("Loading, might take a few seconds...")
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path = os.path.dirname(get_path_file.__file__)
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device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
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@ -53,11 +54,6 @@ def get_tag_for_sentence(input_sentence):
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probs = torch.softmax(output, dim=1)
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prob = probs[0][predicted.item()]
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if prob.item() > 0.75 and len(sentence) > 2:
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return "MATCHING INTENT : " + tag + " (" + str(prob.item()) + ")"
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# return intents.intents.get_matching_intent_for_tag(tag).get('tag')
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return tag
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else:
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return 'dont_understand'
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if __name__ == '__main__':
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print(get_tag_for_sentence("Hey, est il"))
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return 'dont_understand'
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15
main.py
15
main.py
@ -1,6 +1,7 @@
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import flask
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from flask import Flask, request, jsonify, Response
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import ia.process
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from utils import config_utils, flask_utils
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app = Flask(__name__)
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@ -10,14 +11,18 @@ app = Flask(__name__)
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def process_request():
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data = flask_utils.get_data_in_request(request)
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if 'sentence' not in data:
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flask.abort(Response('You must provide a \'sentence\' parameter!'))
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if 'sentence' not in data or not data['sentence']:
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flask.abort(Response('You must provide a \'sentence\' parameter (not empty aswell)!'))
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print(data)
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return jsonify(data)
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sentence = data['sentence']
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tag_for_request = ia.process.get_tag_for_sentence(sentence)
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print("SENTENCE : " + sentence + " /// TAG : " + tag_for_request)
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return jsonify(tag_for_request)
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if __name__ == '__main__':
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# start the flask server
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app.config['JSON_AS_ASCII'] = False
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app.run(port=config_utils.get_in_config("PORT"), debug=False, host='0.0.0.0', threaded=True)
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app.run(port=config_utils.get_in_config("PORT"), debug=False, host='0.0.0.0', threaded=True)
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