Pytext上手——Intent-Slot 模型实战

pip install pytext-nlp

python3 demo/atis_joint_model/data_processor.py --download-folder atis/ --output-directory demo/atis_joint_model/

pytext train < demo/atis_joint_model/atis_joint_config.json

CONFIG=demo/atis_joint_model/atis_joint_config.json

pytext export --output-path exported_model.c2 < "$CONFIG"

pytext test < "$CONFIG"

import sys
import flask
import pytext
config_file = sys.argv[1]
model_file = sys.argv[2]
config = pytext.load_config(config_file)
predictor = pytext.create_predictor(config, model_file)
app = flask.Flask(__name__)
@app.route('/get_flight_info', methods=['GET', 'POST'])
def get_flight_info():
    text = flask.request.data.decode()
    # Pass the inputs to PyText's prediction API
    result = predictor({"raw_text": text})
    # Results is a list of output blob names and their scores.
    # The blob names are different for joint models vs doc models
    # Since this tutorial is for both, let's check which one we should look at.
    doc_label_scores_prefix = (
        'scores:' if any(r.startswith('scores:') for r in result)
        else 'doc_scores:'
    )
    # For now let's just output the top document label!
    best_doc_label = max(
        (label for label in result if label.startswith(doc_label_scores_prefix)),
        key=lambda label: result[label][0],
    # Strip the doc label prefix here
    )[len(doc_label_scores_prefix):]
    return flask.jsonify({"question": f"Are you asking about {best_doc_label}?"})
app.run(host='0.0.0.0', port='8080', debug=True)

python flask_app.py "$CONFIG" exported_model.c2

curl http://localhost:8080/get_flight_info -H "Content-Type: text/plain" -d  "I am looking for flights from San Francisco to Minneapolis"
{
  "question": "Are you asking about flight?"
}

curl http://localhost:8080/get_flight_info -H "Content-Type: text/plain" -d  "How much does a trip to NY cost?"
{
  "question": "Are you asking about airfare?"
}

curl http://localhost:8080/get_flight_info -H "Content-Type: text/plain" -d  "Which airport should I go to?"
{
  "question": "Are you asking about airport?"
}