First commit

README.md

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+# GST FAQ Bot with Rasa-NLU
+Set of scripts to build a chatbot which will answer FAQ about Goods and Services Tax (GST) India.
+Copyright (C) 2017 Yogesh H Kulkarni
+
+## License:
+This program is free software; you can redistribute it and/or
+modify it under the terms of the GNU General Public License
+as published by the Free Software Foundation; either version 2
+of the License, or any later version.
+
+## Scripts:
+* app.py: Chatbot UI built using Flask, using templates/*.html
+* engine.py: Chatbot core logic as well as knowledgebase.
+* config.json: Rasa NLU settings for training as well as executing intent extraction
+* run_training: Windows batch file to build trained modeling
+* run_server: Windows batch file to execute Rasa-NLU server.
+
+## Dependencies:
+* Needs Python 3.5
+
+## ToDos
+* Add more training data
+* Entity extraction not working as desired, find out more.
+* Etc.
+
+## References
+* Rasa-NLU [installation](https://github.com/RasaHQ/rasa_nlu)
+* Bhavani Ravi’s event-bot [code](https://github.com/bhavaniravi/rasa-site-bot), Youtube [Video](https://www.youtube.com/watch?v=ojuq0vBIA-g)
+* GST FAQs:
+    * Government [Documentation](http://www.cbec.gov.in/resources//htdocs-cbec/deptt_offcr/faq-on-gst.pdf)
+    * GST India [Documentation](http://www.gstindia.com/frequently-asked-questions-faqs-on-goods-and-services-tax-gst/)
+
+## Disclaimer:
+* Author ([email protected]) gives no guarantee of the results of the program. It is just a fun script. Lot of improvements are still to be made. So, don’t depend on it at all.

app.py

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+# Ref: https://github.com/bhavaniravi/rasa-site-bot
+from flask import Flask
+from flask import render_template,jsonify,request
+import requests
+# from models import *
+from engine import *
+import random
+
+
+app = Flask(__name__)
+app.secret_key = '12345'
+
+@app.route('/')
+def hello_world():
+    return render_template('home.html')
+
+get_random_response = lambda intent:random.choice(intent_response_dict[intent])
+
+
+@app.route('/chat',methods=["POST"])
+def chat():
+    try:
+        user_message = request.form["text"]
+        response = requests.get("http://localhost:5000/parse",params={"q":user_message})
+        response = response.json()
+        entities = response.get("entities")
+        topresponse = response["topScoringIntent"]
+        intent = topresponse.get("intent")
+        print("Intent {}, Entities {}".format(intent,entities))
+        if intent == "gst-info":
+            response_text = gst_info(entities)# "Sorry will get answer soon" #get_event(entities["day"],entities["time"],entities["place"])
+        elif intent == "gst-query":
+            response_text = gst_query(entities)
+        else:
+            response_text = get_random_response(intent)
+        return jsonify({"status":"success","response":response_text})
+    except Exception as e:
+        print(e)
+        return jsonify({"status":"success","response":"Sorry I am not trained to do that yet..."})
+
+
+app.config["DEBUG"] = True
+if __name__ == "__main__":
+    app.run(port=8080)

config.json

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+{
+  "pipeline": "spacy_sklearn",
+  "path" : "models/",
+  "data" : "data/gstfaq-data.json",
+  "num_threads":10
+}