wip llm steering

pyproject.toml

@@ -18,7 +18,7 @@ repository = "https://github.com/rasahq/rasa"
 documentation = "https://rasa.com/docs"
 classifiers = [ "Development Status :: 5 - Production/Stable", "Intended Audience :: Developers", "License :: OSI Approved :: Apache Software License", "Topic :: Software Development :: Libraries",]
 keywords = [ "nlp", "machine-learning", "machine-learning-library", "bot", "bots", "botkit", "rasa conversational-agents", "conversational-ai", "chatbot", "chatbot-framework", "bot-framework",]
-include = [ "LICENSE.txt", "README.md", "rasa/shared/core/training_data/visualization.html", "rasa/cli/default_config.yml", "rasa/shared/importers/*", "rasa/utils/schemas/*", "rasa/keys", "rasa/core/channels/chat.html", "rasa/core/policies/detectors/prompt_sensitive_topic.jinja2"]
+include = [ "LICENSE.txt", "README.md", "rasa/shared/core/training_data/visualization.html", "rasa/cli/default_config.yml", "rasa/shared/importers/*", "rasa/utils/schemas/*", "rasa/keys", "rasa/core/channels/chat.html", "rasa/core/policies/detectors/prompt_sensitive_topic.jinja2", "rasa/nlu/classifiers/flow_prompt_template.jinja2"]
 readme = "README.md"
 license = "Apache-2.0"
 [[tool.poetry.source]]

rasa/core/actions/action.py

@@ -98,7 +98,6 @@
 def default_actions(action_endpoint: Optional[EndpointConfig] = None) -> List["Action"]:
     """List default actions."""
     from rasa.core.actions.two_stage_fallback import TwoStageFallbackAction
-    from rasa.core.actions.flows import ActionFlowContinueInterupted
 
     return [
         ActionListen(),
@@ -114,7 +113,6 @@ def default_actions(action_endpoint: Optional[EndpointConfig] = None) -> List["A
         ActionSendText(),
         ActionBack(),
         ActionExtractSlots(action_endpoint),
-        ActionFlowContinueInterupted(),
     ]
 
 
@@ -314,6 +312,7 @@ async def run(
         nlg: "NaturalLanguageGenerator",
         tracker: "DialogueStateTracker",
         domain: "Domain",
+        metadata: Optional[Dict[Text, Any]] = None,
     ) -> List[Event]:
         """Simple run implementation uttering a (hopefully defined) response."""
         response_ids_for_response = domain.response_ids_per_response.get(
@@ -372,6 +371,7 @@ async def run(
         nlg: "NaturalLanguageGenerator",
         tracker: "DialogueStateTracker",
         domain: "Domain",
+        metadata: Optional[Dict[Text, Any]] = None,
     ) -> List[Event]:
         """Runs action (see parent class for full docstring)."""
         message = {"text": self.action_text}
@@ -460,6 +460,7 @@ async def run(
         nlg: "NaturalLanguageGenerator",
         tracker: "DialogueStateTracker",
         domain: "Domain",
+        metadata: Optional[Dict[Text, Any]] = None,
     ) -> List[Event]:
         """Query the appropriate response and create a bot utterance with that."""
         latest_message = tracker.latest_message
@@ -520,6 +521,7 @@ async def run(
         nlg: "NaturalLanguageGenerator",
         tracker: "DialogueStateTracker",
         domain: "Domain",
+        metadata: Optional[Dict[Text, Any]] = None,
     ) -> List[Event]:
         """Runs action. Please see parent class for the full docstring."""
         # only utter the response if it is available
@@ -545,6 +547,7 @@ async def run(
         nlg: "NaturalLanguageGenerator",
         tracker: "DialogueStateTracker",
         domain: "Domain",
+        metadata: Optional[Dict[Text, Any]] = None,
     ) -> List[Event]:
         """Runs action. Please see parent class for the full docstring."""
         return []
@@ -570,6 +573,7 @@ async def run(
         nlg: "NaturalLanguageGenerator",
         tracker: "DialogueStateTracker",
         domain: "Domain",
+        metadata: Optional[Dict[Text, Any]] = None,
     ) -> List[Event]:
         """Runs action. Please see parent class for the full docstring."""
         # only utter the response if it is available
@@ -606,6 +610,7 @@ async def run(
         nlg: "NaturalLanguageGenerator",
         tracker: "DialogueStateTracker",
         domain: "Domain",
+        metadata: Optional[Dict[Text, Any]] = None,
     ) -> List[Event]:
         """Runs action. Please see parent class for the full docstring."""
         _events: List[Event] = [SessionStarted()]
@@ -635,6 +640,7 @@ async def run(
         nlg: "NaturalLanguageGenerator",
         tracker: "DialogueStateTracker",
         domain: "Domain",
+        metadata: Optional[Dict[Text, Any]] = None,
     ) -> List[Event]:
         """Runs action. Please see parent class for the full docstring."""
         # only utter the response if it is available
@@ -655,6 +661,7 @@ async def run(
         nlg: "NaturalLanguageGenerator",
         tracker: "DialogueStateTracker",
         domain: "Domain",
+        metadata: Optional[Dict[Text, Any]] = None,
     ) -> List[Event]:
         """Runs action. Please see parent class for the full docstring."""
         return [ActiveLoop(None), SlotSet(REQUESTED_SLOT, None)]
@@ -769,6 +776,7 @@ async def run(
         nlg: "NaturalLanguageGenerator",
         tracker: "DialogueStateTracker",
         domain: "Domain",
+        metadata: Optional[Dict[Text, Any]] = None,
     ) -> List[Event]:
         """Runs action. Please see parent class for the full docstring."""
         json_body = self._action_call_format(tracker, domain)
@@ -895,6 +903,7 @@ async def run(
         nlg: "NaturalLanguageGenerator",
         tracker: "DialogueStateTracker",
         domain: "Domain",
+        metadata: Optional[Dict[Text, Any]] = None,
     ) -> List[Event]:
         """Runs action. Please see parent class for the full docstring."""
         from rasa.core.policies.two_stage_fallback import has_user_rephrased
@@ -925,6 +934,7 @@ async def run(
         nlg: "NaturalLanguageGenerator",
         tracker: "DialogueStateTracker",
         domain: "Domain",
+        metadata: Optional[Dict[Text, Any]] = None,
     ) -> List[Event]:
         """Runs action. Please see parent class for the full docstring."""
         return []
@@ -1005,6 +1015,7 @@ async def run(
         nlg: "NaturalLanguageGenerator",
         tracker: "DialogueStateTracker",
         domain: "Domain",
+        metadata: Optional[Dict[Text, Any]] = None,
     ) -> List[Event]:
         """Runs action. Please see parent class for the full docstring."""
         latest_message = tracker.latest_message
@@ -1273,6 +1284,7 @@ async def run(
         nlg: "NaturalLanguageGenerator",
         tracker: "DialogueStateTracker",
         domain: "Domain",
+        metadata: Optional[Dict[Text, Any]] = None,
     ) -> List[Event]:
         """Runs action. Please see parent class for the full docstring."""
         slot_events: List[Event] = []
@@ -1354,6 +1366,16 @@ def extract_slot_value_from_predefined_mapping(
     tracker: "DialogueStateTracker",
 ) -> List[Any]:
     """Extracts slot value if slot has an applicable predefined mapping."""
+
+    if tracker.has_bot_message_after_latest_user_message():
+        # TODO: this needs further validation - not sure if this breaks something!!!
+
+        # If the bot sent a message after the user sent a message, we can't
+        # extract any slots from the user message. We assume that the user
+        # message was already processed by the bot and the slot value was
+        # already extracted (e.g. for a prior form slot).
+        return []
+
     should_fill_entity_slot = (
         mapping_type == SlotMappingType.FROM_ENTITY
         and SlotMapping.entity_is_desired(mapping, tracker)

rasa/core/actions/flows.py

@@ -5,10 +5,7 @@
 from rasa.core.policies.flow_policy import FlowStack, FlowStackFrame, StackFrameType
 from rasa.shared.constants import FLOW_PREFIX
 
-from rasa.shared.core.constants import (
-    ACTION_FLOW_CONTINUE_INERRUPTED_NAME,
-    FLOW_STACK_SLOT,
-)
+from rasa.shared.core.constants import FLOW_STACK_SLOT
 from rasa.shared.core.domain import Domain
 from rasa.shared.core.events import (
     ActiveLoop,
@@ -47,10 +44,13 @@ async def run(
         metadata: Optional[Dict[Text, Any]] = None,
     ) -> List[Event]:
         """Trigger the flow."""
-
         stack = FlowStack.from_tracker(tracker)
         if tracker.active_loop_name and not stack.is_empty():
             frame_type = StackFrameType.INTERRUPT
+        elif self._flow_name == "pattern_continue_interrupted":
+            frame_type = StackFrameType.RESUME
+        elif self._flow_name == "pattern_correction":
+            frame_type = StackFrameType.CORRECTION
         else:
             frame_type = StackFrameType.REGULAR
 
@@ -61,43 +61,15 @@ async def run(
             )
         )
 
-        events: List[Event] = [SlotSet(FLOW_STACK_SLOT, stack.as_dict())]
+        slots_to_be_set = metadata.get("slots", {}) if metadata else {}
+        slot_set_events: List[Event] = [
+            SlotSet(key, value) for key, value in slots_to_be_set.items()
+        ]
+
+        events: List[Event] = [
+            SlotSet(FLOW_STACK_SLOT, stack.as_dict())
+        ] + slot_set_events
         if tracker.active_loop_name:
             events.append(ActiveLoop(None))
 
         return events
-
-
-UTTER_FLOW_CONTINUE_INTERRUPTED = "utter_flow_continue_interrupted"
-
-
-class ActionFlowContinueInterupted(action.Action):
-    """Action triggered when an interrupted flow is continued."""
-
-    def name(self) -> Text:
-        """Return the flow name."""
-        return ACTION_FLOW_CONTINUE_INERRUPTED_NAME
-
-    async def run(
-        self,
-        output_channel: "OutputChannel",
-        nlg: "NaturalLanguageGenerator",
-        tracker: "DialogueStateTracker",
-        domain: "Domain",
-        metadata: Optional[Dict[Text, Any]] = None,
-    ) -> List[Event]:
-        """Trigger the flow."""
-
-        fallback = {"text": "Let's return to the previous topic."}
-        flow_name = metadata.get("flow_name") if metadata else None
-
-        generated = await nlg.generate(
-            UTTER_FLOW_CONTINUE_INTERRUPTED,
-            tracker,
-            output_channel.name(),
-            flow_name=flow_name,
-        )
-
-        utterance: Event = action.create_bot_utterance(generated or fallback)
-
-        return [utterance]

rasa/core/actions/loops.py

@@ -1,5 +1,5 @@
 from abc import ABC
-from typing import List, TYPE_CHECKING
+from typing import Any, Dict, List, TYPE_CHECKING, Optional, Text
 
 from rasa.core.actions.action import Action
 from rasa.shared.core.events import Event, ActiveLoop
@@ -18,6 +18,7 @@ async def run(
         nlg: "NaturalLanguageGenerator",
         tracker: "DialogueStateTracker",
         domain: "Domain",
+        metadata: Optional[Dict[Text, Any]] = None,
     ) -> List[Event]:
         events: List[Event] = []
 

rasa/core/policies/default_flows.yml

@@ -0,0 +1,68 @@
+responses:
+  utter_flow_continue_interrupted: 
+    - text: Let's continue with the topic {rasa_previous_flow}.
+      metadata: 
+        rephrase: True
+
+  utter_ask_confirm_correction:
+    - text: "Do you want to update your information?"
+      buttons:
+        - payload: /affirm
+          title: Yes
+        - payload: /deny
+          title: No, please keep the previous information
+      metadata: 
+        rephrase: True
+
+  utter_corrected_previous_input:
+    - text: "Ok, I corrected the previous input."
+      metadata: 
+        rephrase: True
+
+  utter_not_corrected_previous_input:
+    - text: "Ok, I did not correct the previous input."
+      metadata: 
+        rephrase: True
+
+slots:
+  confirm_correction:
+    type: text
+    mappings:
+      - intent: affirm
+        type: from_intent
+        value: "True"
+        conditions:
+          - active_loop: question_confirm_correction
+      - intent: deny
+        type: from_intent
+        value: "False"
+        conditions:
+          - active_loop: question_confirm_correction
+
+flows:  
+  pattern_continue_interrupted:
+    description: A meta flow that should be started to continue an interrupted flow. 
+
+    steps:
+      - id: "0"
+        action: utter_flow_continue_interrupted
+
+  pattern_correction:
+    description: A meta flow that should be started to correct a previous user input.
+
+    steps:
+      - id: "0"
+        question: confirm_correction
+        next:
+          - if: confirm_correction
+            then: "1"
+          - else: "2"
+      - id: "1"
+        action: utter_corrected_previous_input
+      - id: "2"
+        set_slots:
+          - rasa_corrected_slots: None
+        next: "3"
+      - id: "3"
+        action: utter_not_corrected_previous_input
+

rasa/core/policies/detectors/sensitive_topic.py

@@ -43,7 +43,8 @@ def check(self, user_msg: Text) -> bool:
             user_msg: user message to check
 
         Returns:
-            True if the message contains sensitive topic, False otherwise"""
+        True if the message contains sensitive topic, False otherwise
+        """
         ...
 
     def action(self) -> Text:
@@ -104,7 +105,7 @@ def check(self, user_msg: Optional[Text]) -> bool:
         if self._use_stub:
             return self._stub.check(user_msg)
         try:
-            resp = openai.Completion.create(
+            resp = openai.Completion.create(  # type: ignore[no-untyped-call]
                 model=self._model_name,
                 prompt=self._make_prompt(user_msg),
                 temperature=0.0,
@@ -125,7 +126,8 @@ def _make_prompt(self, user_message: Text) -> Text:
     def _parse_response(text: Text) -> bool:
         """Parse response from OpenAI ChatGPT model.
 
-        Expected responses are "YES" and "NO" (case-insensitive)."""
+        Expected responses are "YES" and "NO" (case-insensitive).
+        """
         return "YES" in text.upper()