Update 'chatbot/actions/actions.py'

chatbot/actions/actions.py

@@ -1,14 +1,4 @@
-# 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/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
 from flask import request
@@ -24,147 +14,26 @@ class ActionService(Action):
             tracker: Tracker,
             domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
     	buttons=[
-    		{"payload":'/docs{"content_type":"blogs"}',"title":"yes"},
+    		{"payload":'/satisfied',"title":"yes"},
-    		{"payload":'/video{"content_type":"video"}',"title":"no"},
+    		{"payload":'/notsatisfied',"title":"no"},
 
     	]
     	dispatcher.utter_message(text="Are you satisfied with above solution",buttons=buttons)
     	return []
 
 
-
+class action_support_service(Action):
-
-
-class ActionService(Action):
 
     def name(self) -> Text:
-        return "action_suport_service"
+        return "action_support_service"
 
     def run(self, dispatcher: CollectingDispatcher,
             tracker: Tracker,
             domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
         buttons=[
-            {"payload":'/connect_support{"content_type":"text"}',"title":"yes"},
+            {"payload":'/connect_support',"title":"yes"},
-            {"payload":'/noconnect_support{"content_type":"text"}',"title":"no"},
+            {"payload":'/noconnect_support',"title":"no"},
 
         ]
         dispatcher.utter_message(text="do you want me to connect to support team",buttons=buttons)
         return []
-
-question=[]
-answer=[]
-class ActionSaveConversation(Action):
-    def name(self) -> Text:
-        return "action_save_conersation"
-
-    def run(self,
-            dispatcher: CollectingDispatcher,
-            tracker: Tracker,
-            domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
-
-        
-        sender_id = tracker.sender_id
-        #print(tracker.events)
-        conversation=tracker.events
-        import os
-        if not os. path.isfile('chats.txt'):
-            with open('chats.txt ','w') as file:
-                file.write("user_input $$$$ bot_reply\n")
-        chat_data=''
-        for i in conversation:
-            if i['event'] == 'user':
-                chat_data+=i['parse_data']['intent']['name']
-                print('user: {}'.format(i['text']))
-                a='user{}: {}'.format(sender_id,i['text'])
-                question.append(a)
-                if len(i['parse_data']['entities']) > 0:
-                    chat_data+=i['parse_data']['entities'][0]['entity']+', '+i['parse_data']['entities' ][0]['value']+','
-                    print('extra data:', i['parse_data']['entities'][0]['entity'], '=',
-                            i['parse_data']['entities'][0]['value'])
-            elif i['event'] == 'bot':
-                print('{}'.format(i['text']))
-                b='Bot{}: {}'.format(sender_id,i['text'])
-                question.append(b)
-                # try:
-                #     chat_data+=i['metadata']['utter_action']+','+i['text']+'\n'
-                # except KeyError:
-                #     pass 
-                chat_data+=i['text']+'\n'
-
-        else:
-            with open('chats.txt','a') as file:
-                file.write(chat_data)
-        #print(question)
-        import pandas as pd
-        df=pd.DataFrame(question)
-        print(df)
-        conversation=None
-        question.clear()
-        print(conversation)
-        print(question)
-
-        print(sender_id)
-
-     #   print(answer)
-        # a=question
-        # b=answer
-        # import numpy as np
-        # import pandas as pd
-        # if len(a) > len(b):
-        #     b = np.pad(b, (0, len(a) - len(b)), 'constant')
-        # else:
-        #     a = np.pad(a, (0, len(b) - len(a)), 'constant')
-        # df=pd.DataFrame({'question':a,"answer":b})
-        # print(df)
-        dispatcher.utter_message(text="All Chats saved")
-
-        return []
-
-
-
-class ActionSaveConversation(Action):
-    def name(self) -> Text:
-        return "action_save_conersation"
-
-    def run(self, dispatcher: CollectingDispatcher, tracker: Tracker, domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
-        # Get sender_id
-        sender_id = tracker.sender_id
-
-        conversation = tracker.events
-        chat_data = []
-        for i in conversation:
-            if i['event'] == 'user':
-                text = i['text'].replace('/connect_support{"content_type":"text"}', 'yes').replace('/noconnect_support{"content_type":"text"}','No').replace('/docs{"content_type":"blogs"}','yes').replace('/video{"content_type":"video"}','No')
-                chat_data.append({'sender': f'user_{sender_id}', 'message': text})
-                print(f'user_{sender_id}: {i["text"]}')
-                if len(i['parse_data']['entities']) > 0:
-                    print('extra data:', i['parse_data']['entities'][0]['entity'], '=',
-                          i['parse_data']['entities'][0]['value'])
-            elif i['event'] == 'bot':
-                print(f'bot_{sender_id}: {i["text"]}')
-                chat_data.append({'sender': f'bot_{sender_id}', 'message': i['text']})
-
-        with open('chats.json', 'w') as file:
-            json.dump({'conversation': chat_data, 'sender_id': sender_id}, file)
-            file.write('\n')
-            file.close()
-        print(json.dumps({'conversation': chat_data, 'sender_id': sender_id}, indent=4))
-        conversation = None
-
-        return []
-
-
-class ActionClearConversation(Action):
-    def name(self) -> Text:
-        return "action_clear_conversation"
-
-    def run(self, dispatcher: CollectingDispatcher, tracker: Tracker, domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
-
-        sender_id = tracker.sender_id
-        tracker.events = []
-
-        return []
-
-
-
-