Added user_question embedded field in PromptAction data_object with t…

…ype and value and fixed test cases.

kairon/actions/definitions/prompt.py

@@ -8,7 +8,6 @@
 from kairon.actions.definitions.base import ActionsBase
 from kairon.shared.actions.data_objects import ActionServerLogs
 from kairon.shared.actions.exception import ActionFailure
-from rasa_sdk.forms import REQUESTED_SLOT
 from kairon.shared.actions.models import ActionType, UserMessageType
 from kairon.shared.actions.utils import ActionUtility
 from kairon.shared.constants import FAQ_DISABLED_ERR, KaironSystemSlots, KAIRON_USER_MSG_ENTITY
@@ -61,8 +60,8 @@ async def execute(self, dispatcher: CollectingDispatcher, tracker: Tracker, doma
 
         try:
             k_faq_action_config, bot_settings = self.retrieve_config()
-            prompt_question = k_faq_action_config.get('prompt_question')
-            user_msg = self.__get_user_msg(tracker, prompt_question)
+            user_question = k_faq_action_config.get('user_question')
+            user_msg = self.__get_user_msg(tracker, user_question)
             llm_params = await self.__get_llm_params(k_faq_action_config, dispatcher, tracker, domain)
             llm = LLMFactory.get_instance("faq")(self.bot, bot_settings["llm_settings"])
             llm_response = await llm.predict(user_msg, **llm_params)
@@ -183,9 +182,10 @@ def __add_user_context_to_http_response(http_response, tracker_data):
         return response_context
 
     @staticmethod
-    def __get_user_msg(tracker: Tracker, prompt_question: UserMessageType):
-        if prompt_question == UserMessageType.from_slot.value:
-            slot = tracker.get_slot(REQUESTED_SLOT)
+    def __get_user_msg(tracker: Tracker, user_question: Dict):
+        user_question_type = user_question.get('type')
+        if user_question_type == UserMessageType.from_slot.value:
+            slot = user_question.get('value')
             user_msg = tracker.get_slot(slot)
         else:
             user_msg = tracker.latest_message.get('text')

kairon/api/models.py

@@ -889,11 +889,16 @@ class LlmPromptRequest(BaseModel):
     is_enabled: bool = True
 
 
+class UserQuestionModel(BaseModel):
+    type: UserMessageType = UserMessageType.from_user_message.value
+    value: str = None
+
+
 class PromptActionConfigRequest(BaseModel):
     name: constr(to_lower=True, strip_whitespace=True)
     num_bot_responses: int = 5
     failure_message: str = DEFAULT_NLU_FALLBACK_RESPONSE
-    prompt_question: UserMessageType = UserMessageType.from_user_message.value
+    user_question: UserQuestionModel = UserQuestionModel()
     top_results: int = 10
     similarity_threshold: float = 0.70
     enable_response_cache: bool = False

kairon/shared/actions/data_objects.py

@@ -655,6 +655,12 @@ def validate(self, clean=True):
             raise ValidationError("System prompt must have static source!")
 
 
+class UserQuestion(EmbeddedDocument):
+    type = StringField(default=UserMessageType.from_user_message.value,
+                       choices=[p_type.value for p_type in UserMessageType])
+    value = StringField(default=None)
+
+
 @auditlogger.log
 @push_notification.apply
 class PromptAction(Auditlog):
@@ -664,8 +670,7 @@ class PromptAction(Auditlog):
     similarity_threshold = FloatField(default=0.70)
     enable_response_cache = BooleanField(default=False)
     failure_message = StringField(default=DEFAULT_NLU_FALLBACK_RESPONSE)
-    prompt_question = StringField(default=UserMessageType.from_user_message.value,
-                                  choices=[p_type.value for p_type in UserMessageType])
+    user_question = EmbeddedDocumentField(UserQuestion, default=UserQuestion())
     bot = StringField(required=True)
     user = StringField(required=True)
     timestamp = DateTimeField(default=datetime.utcnow)

kairon/shared/data/processor.py

@@ -43,7 +43,7 @@
     SlotSetAction, FormValidationAction, EmailActionConfig, GoogleSearchAction, JiraAction, ZendeskAction, \
     PipedriveLeadsAction, SetSlots, HubspotFormsAction, HttpActionResponse, SetSlotsFromResponse, \
     CustomActionRequestParameters, KaironTwoStageFallbackAction, QuickReplies, RazorpayAction, PromptAction, \
-    LlmPrompt, FormSlotSet, DatabaseAction, DbOperation, DbQuery, PyscriptActionConfig, WebSearchAction
+    LlmPrompt, FormSlotSet, DatabaseAction, DbOperation, DbQuery, PyscriptActionConfig, WebSearchAction, UserQuestion
 from kairon.shared.actions.models import ActionType, HttpRequestContentType, ActionParameterType, DbQueryValueType
 from kairon.shared.data.audit.data_objects import AuditLogData
 from kairon.shared.importer.processor import DataImporterLogProcessor
@@ -5433,7 +5433,7 @@ def edit_prompt_action(self, prompt_action_id: str, request_data: dict, bot: Tex
         action = PromptAction.objects(id=prompt_action_id, bot=bot, status=True).get()
         action.name = request_data.get("name")
         action.failure_message = request_data.get("failure_message")
-        action.prompt_question = request_data.get("prompt_question")
+        action.user_question = UserQuestion(**request_data.get("user_question"))
         action.top_results = request_data.get("top_results")
         action.enable_response_cache = request_data.get("enable_response_cache", False)
         action.similarity_threshold = request_data.get("similarity_threshold")

tests/integration_test/action_service_test.py

@@ -16,7 +16,7 @@
     EmailActionConfig, ActionServerLogs, GoogleSearchAction, JiraAction, ZendeskAction, PipedriveLeadsAction, SetSlots, \
     HubspotFormsAction, HttpActionResponse, HttpActionRequestBody, SetSlotsFromResponse, CustomActionRequestParameters, \
     KaironTwoStageFallbackAction, TwoStageFallbackTextualRecommendations, RazorpayAction, PromptAction, FormSlotSet, \
-    DatabaseAction, DbOperation, DbQuery, PyscriptActionConfig, WebSearchAction
+    DatabaseAction, DbOperation, DbQuery, PyscriptActionConfig, WebSearchAction, UserQuestion
 from kairon.shared.actions.models import ActionType, ActionParameterType, DispatchType
 from kairon.shared.actions.utils import ActionUtility
 from kairon.shared.admin.constants import BotSecretType
@@ -9598,11 +9598,11 @@ def test_prompt_action_response_action_with_prompt_question_from_slot(mock_searc
     Actions(name=action_name, type=ActionType.prompt_action.value, bot=bot, user=user).save()
     BotSettings(llm_settings=LLMSettings(enable_faq=True), bot=bot, user=user).save()
     PromptAction(name=action_name, bot=bot, user=user, num_bot_responses=2, llm_prompts=llm_prompts,
-                 prompt_question="from_slot").save()
+                 user_question=UserQuestion(type="from_slot", value="prompt_question")).save()
     BotSecrets(secret_type=BotSecretType.gpt_key.value, value=value, bot=bot, user=user).save()
 
     request_object = json.load(open("tests/testing_data/actions/action-request.json"))
-    request_object["tracker"]["slots"] = {"bot": bot, "user_question": user_msg, "requested_slot": "user_question"}
+    request_object["tracker"]["slots"] = {"bot": bot, "prompt_question": user_msg}
     request_object["next_action"] = action_name
     request_object["tracker"]["sender_id"] = user
     request_object['tracker']['events'] = [{"event": "user", 'text': 'hello',

tests/integration_test/services_test.py

@@ -2036,7 +2036,7 @@ def _mock_get_bot_settings(*args, **kwargs):
         return BotSettings(bot=pytest.bot, user="[email protected]", llm_settings=LLMSettings(enable_faq=True))
 
     monkeypatch.setattr(MongoProcessor, 'get_bot_settings', _mock_get_bot_settings)
-    action = {'name': 'test_add_prompt_action', 'prompt_question': 'from_user_message',
+    action = {'name': 'test_add_prompt_action', 'user_question': {'type': 'from_user_message'},
               'llm_prompts': [{'name': 'System Prompt', 'data': 'You are a personal assistant.', 'type': 'system',
                                'source': 'static', 'is_enabled': True},
                               {'name': 'Similarity Prompt',
@@ -2268,7 +2268,7 @@ def test_update_prompt_action_with_query_prompt_with_false():
 
 
 def test_update_prompt_action():
-    action = {'name': 'test_update_prompt_action', 'prompt_question': 'from_slot',
+    action = {'name': 'test_update_prompt_action', 'user_question': {'type': 'from_slot', 'value': 'prompt_question'},
               'llm_prompts': [{'name': 'System Prompt', 'data': 'You are a personal assistant.', 'type': 'system',
                                'source': 'static', 'is_enabled': True},
                               {'name': 'Similarity_analytical Prompt',
@@ -2311,7 +2311,7 @@ def test_get_prompt_action():
     assert actual["data"] == [
         {'name': 'test_update_prompt_action', 'num_bot_responses': 5, 'top_results': 9, 'similarity_threshold': 0.5,
          'enable_response_cache': False, 'failure_message': 'updated_failure_message',
-         'prompt_question': 'from_slot',
+         'user_question': {'type': 'from_slot', 'value': 'prompt_question'},
          'hyperparameters': {'temperature': 0.0, 'max_tokens': 300, 'model': 'gpt-3.5-turbo', 'top_p': 0.0, 'n': 1,
                              'stream': False, 'stop': None, 'presence_penalty': 0.0, 'frequency_penalty': 0.0,
                              'logit_bias': {}},

tests/unit_test/action/action_test.py

@@ -2692,7 +2692,7 @@ def test_get_prompt_action_config(self):
         actual_config.pop("status")
         actual_config.pop("user")
         assert actual_config == {'name': 'kairon_faq_action', 'num_bot_responses': 5, 'top_results': 10,
-                                 'prompt_question': 'from_user_message',
+                                 'user_question': {'type': 'from_user_message'},
                                  'similarity_threshold': 0.7,
                                  'failure_message': "I'm sorry, I didn't quite understand that. Could you rephrase?",
                                  'bot': 'test_action_server', 'enable_response_cache': False,
@@ -3977,7 +3977,7 @@ def test_get_prompt_action_config_2(self):
         assert k_faq_action_config == {'name': 'kairon_faq_action', 'num_bot_responses': 5, 'top_results': 10,
                                        'similarity_threshold': 0.7,
                                        'enable_response_cache': False,
-                                       'prompt_question': 'from_user_message',
+                                       'user_question': {'type': 'from_user_message'},
                                        'failure_message': "I'm sorry, I didn't quite understand that. Could you rephrase?",
                                        'bot': 'test_bot_action_test', 'user': 'test_user_action_test',
                                        'hyperparameters': {'temperature': 0.0, 'max_tokens': 300, 'model': 'gpt-3.5-turbo',

tests/unit_test/data_processor/data_processor_test.py

@@ -495,7 +495,8 @@ def test_add_prompt_action_faq_action_with_default_values_and_instructions(self)
         processor = MongoProcessor()
         bot = 'test_bot'
         user = 'test_user'
-        request = {'name': 'test_add_prompt_action_faq_action_with_default_values', 'prompt_question': 'from_slot',
+        request = {'name': 'test_add_prompt_action_faq_action_with_default_values',
+                   'user_question': {'type': 'from_slot', 'value': 'prompt_question'},
                    'llm_prompts': [{'name': 'System Prompt', 'data': 'You are a personal assistant.', 'type': 'system',
                                     'source': 'static', 'is_enabled': True},
                                    {'name': 'History Prompt', 'type': 'user', 'source': 'history', 'is_enabled': True}],
@@ -511,7 +512,7 @@ def test_add_prompt_action_faq_action_with_default_values_and_instructions(self)
             {'name': 'test_add_prompt_action_faq_action_with_default_values',
              'num_bot_responses': 5, 'top_results': 10, 'similarity_threshold': 0.7,
              'failure_message': "I'm sorry, I didn't quite understand that. Could you rephrase?",
-             'enable_response_cache': False, 'prompt_question': 'from_slot',
+             'enable_response_cache': False, 'user_question': {'type': 'from_slot', 'value': 'prompt_question'},
              'hyperparameters': {'temperature': 0.0, 'max_tokens': 300, 'model': 'gpt-3.5-turbo', 'top_p': 0.0, 'n': 1,
                                  'stream': False, 'stop': None, 'presence_penalty': 0.0, 'frequency_penalty': 0.0,
                                  'logit_bias': {}},
@@ -753,7 +754,8 @@ def test_edit_prompt_action_faq_action(self):
         processor = MongoProcessor()
         bot = 'test_bot'
         user = 'test_user'
-        request = {'name': 'test_edit_prompt_action_faq_action', 'prompt_question': 'from_user_message',
+        request = {'name': 'test_edit_prompt_action_faq_action',
+                   'user_question': {'type': 'from_user_message'},
                    'llm_prompts': [{'name': 'System Prompt', 'data': 'You are a personal assistant.', 'type': 'system',
                                     'source': 'static', 'is_enabled': True},
                                    {'name': 'Similarity Prompt',
@@ -783,7 +785,7 @@ def test_edit_prompt_action_faq_action(self):
              'hyperparameters': {'temperature': 0.0, 'max_tokens': 300, 'model': 'gpt-3.5-turbo', 'top_p': 0.0, 'n': 1,
                                  'stream': False, 'stop': None, 'presence_penalty': 0.0, 'frequency_penalty': 0.0,
                                  'logit_bias': {}},
-             'prompt_question': 'from_user_message',
+             'user_question': {'type': 'from_user_message'},
              'llm_prompts': [{'name': 'System Prompt', 'data': 'You are a personal assistant.', 'type': 'system',
                               'source': 'static', 'is_enabled': True},
                              {'name': 'Similarity Prompt',
@@ -798,7 +800,8 @@ def test_edit_prompt_action_faq_action(self):
              "set_slots": [{"name": "gpt_result", "value": "${data}", "evaluation_type": "expression"},
                            {"name": "gpt_result_type", "value": "${data.type}", "evaluation_type": "script"}],
              "dispatch_response": False}]
-        request = {'name': 'test_edit_prompt_action_faq_action_again', 'prompt_question': 'from_slot',
+        request = {'name': 'test_edit_prompt_action_faq_action_again',
+                   'user_question': {'type': 'from_slot', 'value': 'prompt_question'},
                    'llm_prompts': [{'name': 'System Prompt', 'data': 'You are a personal assistant.', 'type': 'system',
                                     'source': 'static'}], 'instructions': ['Answer in a short manner.', 'Keep it simple.']}
         processor.edit_prompt_action(pytest.action_id, request, bot, user)
@@ -807,7 +810,8 @@ def test_edit_prompt_action_faq_action(self):
         assert action == [
             {'name': 'test_edit_prompt_action_faq_action_again', 'num_bot_responses': 5, 'top_results': 10,
              'similarity_threshold': 0.7, 'failure_message': "I'm sorry, I didn't quite understand that. Could you rephrase?",
-             'enable_response_cache': False, 'prompt_question': 'from_slot',
+             'enable_response_cache': False,
+             'user_question': {'type': 'from_slot', 'value': 'prompt_question'},
              'hyperparameters': {'temperature': 0.0, 'max_tokens': 300, 'model': 'gpt-3.5-turbo', 'top_p': 0.0, 'n': 1,
                                  'stream': False, 'stop': None, 'presence_penalty': 0.0, 'frequency_penalty': 0.0,
                                  'logit_bias': {}},
@@ -821,21 +825,22 @@ def test_edit_prompt_action_with_less_hyperparameters(self):
         processor = MongoProcessor()
         bot = 'test_bot'
         user = 'test_user'
-        request = {'name': 'test_edit_prompt_action_with_less_hyperparameters', 'prompt_question': 'from_slot',
-            'llm_prompts': [
-                {'name': 'System Prompt', 'data': 'You are a personal assistant.', 'type': 'system', 'source': 'static',
-                 'is_enabled': True},
-                {'name': 'Similarity Prompt',
-                 'instructions': 'Answer question based on the context above, if answer is not in the context go check previous logs.',
-                 'type': 'user', 'source': 'bot_content', 'is_enabled': True},
-                {'name': 'Query Prompt',
-                 'data': 'A programming language is a system of notation for writing computer programs.[1] Most programming languages are text-based formal languages, but they may also be graphical. They are a kind of computer language.',
-                 'instructions': 'Answer according to the context', 'type': 'query', 'source': 'static',
-                 'is_enabled': True},
-                {'name': 'Query Prompt',
-                 'data': 'If there is no specific query, assume that user is aking about java programming.',
-                 'instructions': 'Answer according to the context', 'type': 'query',
-                 'source': 'static', 'is_enabled': True}],
+        request = {'name': 'test_edit_prompt_action_with_less_hyperparameters',
+                   'user_question': {'type': 'from_slot', 'value': 'prompt_question'},
+                   'llm_prompts': [
+                       {'name': 'System Prompt', 'data': 'You are a personal assistant.', 'type': 'system',
+                        'source': 'static', 'is_enabled': True},
+                       {'name': 'Similarity Prompt',
+                        'instructions': 'Answer question based on the context above, if answer is not in the context go check previous logs.',
+                        'type': 'user', 'source': 'bot_content', 'is_enabled': True},
+                       {'name': 'Query Prompt',
+                        'data': 'A programming language is a system of notation for writing computer programs.[1] Most programming languages are text-based formal languages, but they may also be graphical. They are a kind of computer language.',
+                        'instructions': 'Answer according to the context', 'type': 'query', 'source': 'static',
+                        'is_enabled': True},
+                       {'name': 'Query Prompt',
+                        'data': 'If there is no specific query, assume that user is aking about java programming.',
+                        'instructions': 'Answer according to the context', 'type': 'query',
+                        'source': 'static', 'is_enabled': True}],
                    "failure_message": "updated_failure_message", "top_results": 10, "similarity_threshold": 0.70,
                    "use_query_prompt": True, "use_bot_responses": True, "query_prompt": "updated_query_prompt",
                    "num_bot_responses": 5, "hyperparameters": {"temperature": 0.0,
@@ -853,7 +858,7 @@ def test_edit_prompt_action_with_less_hyperparameters(self):
              'hyperparameters': {'temperature': 0.0, 'max_tokens': 300, 'model': 'gpt-3.5-turbo', 'top_p': 0.0, 'n': 1,
                                  'stream': False, 'stop': None, 'presence_penalty': 0.0, 'frequency_penalty': 0.0,
                                  'logit_bias': {}},
-             'prompt_question': 'from_slot',
+             'user_question': {'type': 'from_slot', 'value': 'prompt_question'},
              'llm_prompts': [{'name': 'System Prompt', 'data': 'You are a personal assistant.', 'type': 'system',
                               'source': 'static', 'is_enabled': True},
                              {'name': 'Similarity Prompt', 'instructions': 'Answer question based on the context above, if answer is not in the context go check previous logs.',
@@ -881,7 +886,7 @@ def test_get_prompt_faq_action(self):
              'hyperparameters': {'temperature': 0.0, 'max_tokens': 300, 'model': 'gpt-3.5-turbo', 'top_p': 0.0, 'n': 1,
                                  'stream': False, 'stop': None, 'presence_penalty': 0.0, 'frequency_penalty': 0.0,
                                  'logit_bias': {}},
-             'prompt_question': 'from_slot',
+             'user_question': {'type': 'from_slot', 'value': 'prompt_question'},
              'llm_prompts': [{'name': 'System Prompt', 'data': 'You are a personal assistant.', 'type': 'system',
                               'source': 'static', 'is_enabled': True},
                              {'name': 'Similarity Prompt', 'instructions': 'Answer question based on the context above, if answer is not in the context go check previous logs.',