Intent classification with rasa-nlu

chatbot.py

@@ -18,6 +18,11 @@
 from googletrans import Translator
 from voice_conf import *
 # from speech_recognition.__main__ import r, audio
+from rasa.cli.utils import print_success
+from rasa.nlu.model import Interpreter
+from rasa.nlu.utils import json_to_string
+import os
+os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'
 from intentClassification.intent_classification import IntentClassification
 
 greetings = ['hey there', 'hello', 'hi', 'Hai', 'hey!', 'hey', 'hi there!']
@@ -61,6 +66,9 @@
 
 intentClassifier = IntentClassification()
 
+rasa_model_path = "intentClassification/rasa/nlu-20200427-002014/nlu"
+interpreter = Interpreter.load(rasa_model_path)
+
 personalized, longitude, latitude = get_location()
 stores = []
 stores_data = {}
@@ -106,6 +114,7 @@
                 engine.runAndWait()
     intent = intentClassifier.intent_identifier(translate)
     print("Intent:", intent)
+    intent_rasa = interpreter.parse(translate)
     # TODO:: entity based weather output
     if intent == "weather":
         print("here")

intentClassification/rasa/actions.py

@@ -0,0 +1,27 @@
+# This files contains your custom actions which can be used to run
+# custom Python code.
+#
+# See this guide on how to implement these action:
+# https://rasa.com/docs/rasa/core/actions/#custom-actions/
+
+
+# This is a simple example for a custom action which utters "Hello World!"
+
+# from typing import Any, Text, Dict, List
+#
+# from rasa_sdk import Action, Tracker
+# from rasa_sdk.executor import CollectingDispatcher
+#
+#
+# class ActionHelloWorld(Action):
+#
+#     def name(self) -> Text:
+#         return "action_hello_world"
+#
+#     def run(self, dispatcher: CollectingDispatcher,
+#             tracker: Tracker,
+#             domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
+#
+#         dispatcher.utter_message(text="Hello World!")
+#
+#         return []

intentClassification/rasa/config.yml

@@ -0,0 +1,26 @@
+# Configuration for Rasa NLU.
+# https://rasa.com/docs/rasa/nlu/components/
+language: en
+pipeline:
+  - name: WhitespaceTokenizer
+  - name: RegexFeaturizer
+  - name: LexicalSyntacticFeaturizer
+  - name: CountVectorsFeaturizer
+  - name: CountVectorsFeaturizer
+    analyzer: "char_wb"
+    min_ngram: 1
+    max_ngram: 4
+  - name: DIETClassifier
+    epochs: 100
+  - name: EntitySynonymMapper
+  - name: ResponseSelector
+    epochs: 100
+
+# Configuration for Rasa Core.
+# https://rasa.com/docs/rasa/core/policies/
+policies:
+  - name: MemoizationPolicy
+  - name: TEDPolicy
+    max_history: 5
+    epochs: 100
+  - name: MappingPolicy

intentClassification/rasa/credentials.yml

@@ -0,0 +1,32 @@
+# This file contains the credentials for the voice & chat platforms
+# which your bot is using.
+# https://rasa.com/docs/rasa/user-guide/messaging-and-voice-channels/
+
+rest:
+#  # you don't need to provide anything here - this channel doesn't
+#  # require any credentials
+
+
+#facebook:
+#  verify: "<verify>"
+#  secret: "<your secret>"
+#  page-access-token: "<your page access token>"
+
+#slack:
+#  slack_token: "<your slack token>"
+#  slack_channel: "<the slack channel>"
+
+#socketio:
+#  user_message_evt: <event name for user message>
+#  bot_message_evt: <event name for but messages>
+#  session_persistence: <true/false>
+
+#mattermost:
+#  url: "https://<mattermost instance>/api/v4"
+#  token: "<bot token>"
+#  webhook_url: "<callback URL>"
+
+# This entry is needed if you are using Rasa X. The entry represents credentials 
+# for the Rasa X "channel", i.e. Talk to your bot and Share with guest testers.
+rasa:
+  url: "http://localhost:5002/api"