added user stories from tutorial, changed way partially fulfilled gui…

…delines are handled upon re-application

src/parlant/core/engines/alpha/guideline_proposer.py

@@ -315,6 +315,7 @@ def _format_prompt(
 Conversely, actions dictating one-time behavior (e.g., "send the user our address") should be re-applied more conservatively.
 Only re-apply these if the condition ceased to be true earlier in the conversation before being fulfilled again in the current context.
 
+IMPORTANT: Some guidelines include multiple actions. If only a portion of those actions were fulfilled earlier in the conversation, treat the guideline as though it has been fully executed. In such cases, re-apply the guideline only if its condition becomes true again later in the conversation, unless it is marked as continuous.
 
 Examples of Condition Evaluations:
 -------------------
@@ -443,7 +444,7 @@ def _format_prompt(
 - Guidelines: ###
 1) condition: the customer asks about the value of a stock. action: provide the price using the 'check_stock_price' tool
 2) condition: the weather at a certain location is discussed. action: check the weather at that location using the 'check_weather' tool
-
+3) condition: the customer asked about the weather. action: provide the customre with the temperature and the chances of precipitation  
 ###
 - **Expected Result**:
 ```json
@@ -467,6 +468,18 @@ def _format_prompt(
         "condition_application_rationale": "while weather was discussed earlier, the conversation have moved on to an entirely different topic (stock prices)",
         "applies_score": 3
     }},
+    {{
+        "guideline_number": 3,
+        "condition": "the customer asked about the weather.",
+        "condition_applies": true,
+        "condition_application_rationale": "The customer asked about the weather earlier, though the conversation has somewhat moved on to a new topic",
+        "action": "provide the customre with the temperature and the chances of precipitation",
+        "guideline_is_continuous": false,
+        "guideline_previously_applied_rationale": "The action was partially fulfilled by reporting the temperature without the chances of precipitation. As partially fulfilled guidelines are treated as completed, this guideline is considered applied",
+        "guideline_previously_applied": true,
+        "guideline_should_reapply": false,
+        "applies_score": 4
+    }},
     ]
 }}
 ```

src/parlant/core/engines/alpha/message_event_generator.py

@@ -693,7 +693,7 @@ def _get_output_format(
         """
         else:
             insights_output_format = """
-            <Additional entires for all insights>
+            <Additional entries for all insights>
 """
 
         return f"""

tests/core/engines/alpha/features/user_stories/conversation.feature

@@ -87,3 +87,38 @@ Feature: Conversation
         Then a single message event is emitted
         And the message contains 'productivity', 'professional', and 'development'
 
+    Scenario: The agent correctly applies greeting guidelines based on auxillary data
+        Given an agent named "Chip Bitman" whose job is to work at a tech store and help customers choose what to buy. You're clever, witty, and slightly sarcastic. At the same time you're kind and funny.
+        And a customer with the name "Beef Wellington"
+        And an empty session with "Beef Wellingotn"
+        And the term "Bug" defined as The name of our tech retail store, specializing in gadgets, computers, and tech services.
+        And the term "Bug-Free" defined as Our free warranty and service package that comes with every purchase and covers repairs, replacements, and tech support beyond the standard manufacturer warranty.
+        And a customer tagged as "tag::business"
+        And a context variable "plan" set to "Business Plan" for the tag "tag::business"
+        And a guideline to just welcome them to the store and ask how you can help when the customer greets you
+        And a guideline to refer to them by their first name only, and welcome them 'back' when a customer greets you
+        And a guideline to assure them you will escalate it internally and get back to them when a business-plan customer is having an issue
+        And a customer message, "Hi there"
+        When processing is triggered
+        Then a single message event is emitted
+        And the message contains the name 'Beef'
+        And the message contains a welcoming back of the customer to the store and asking how the agent could help
+
+    Scenario: The agent doesnt wrongly reapply partially fulfilled guideline
+        Given an agent named "Chip Bitman" whose job is to work at a tech store and help customers choose what to buy. You're clever, witty, and slightly sarcastic. At the same time you're kind and funny.
+        And a customer with the name "Beef Wellington"
+        And an empty session with "Beef Wellingotn"
+        And the term "Bug" defined as The name of our tech retail store, specializing in gadgets, computers, and tech services.
+        And the term "Bug-Free" defined as Our free warranty and service package that comes with every purchase and covers repairs, replacements, and tech support beyond the standard manufacturer warranty.
+        And a customer tagged as "tag::business"
+        And a context variable "plan" set to "Business Plan" for the tag "tag::business"
+        And a guideline to just welcome them to the store and ask how you can help when the customer greets you
+        And a guideline to refer to them by their first name only, and welcome them 'back' when a customer greets you
+        And a guideline to assure them you will escalate it internally and get back to them when a business-plan customer is having an issue
+        And a customer message, "Hi there"
+        And an agent message, "Hey Beef, welcome to Bug! How can I help you today?"
+        And a customer message, "I'm having issues with my web camera"
+        When processing is triggered
+        Then a single message event is emitted
+        And the message contains no welcoming back of the customer
+        And the message contains that the request will be escelated

tests/core/engines/alpha/steps/agents.py

@@ -38,3 +38,22 @@ def given_an_agent_with_identity(
         )
     )
     return agent.id
+
+
+@step(
+    given,
+    parsers.parse('an agent named "{name}" whose job is {description}'),
+    target_fixture="agent_id",
+)
+def given_an_agent_with_identity_and_name(
+    context: ContextOfTest,
+    description: str,
+    name: str,
+) -> AgentId:
+    agent = context.sync_await(
+        context.container[AgentStore].create_agent(
+            name=name,
+            description=f"Your job is {description}",
+        )
+    )
+    return agent.id

tests/core/engines/alpha/steps/events.py

@@ -15,9 +15,9 @@
 from typing import Optional, cast
 from pytest_bdd import given, then, parsers, when
 
-from parlant.core.agents import Agent
+from parlant.core.agents import AgentId, AgentStore
 from parlant.core.common import JSONSerializable
-from parlant.core.customers import Customer
+from parlant.core.customers import CustomerStore
 from parlant.core.engines.alpha.utils import emitted_tool_event_to_dict
 from parlant.core.emissions import EmittedEvent
 from parlant.core.nlp.moderation import ModerationTag
@@ -45,10 +45,13 @@ def given_an_agent_message(
     context: ContextOfTest,
     agent_message: str,
     session_id: SessionId,
-    agent: Agent,
+    agent_id: AgentId,
 ) -> SessionId:
-    store = context.container[SessionStore]
-    session = context.sync_await(store.read_session(session_id=session_id))
+    session_store = context.container[SessionStore]
+    agent_store = context.container[AgentStore]
+
+    session = context.sync_await(session_store.read_session(session_id=session_id))
+    agent = context.sync_await(agent_store.read_agent(agent_id))
 
     message_data: MessageEventData = {
         "message": agent_message,
@@ -59,7 +62,7 @@ def given_an_agent_message(
     }
 
     event = context.sync_await(
-        store.create_event(
+        session_store.create_event(
             session_id=session.id,
             source="ai_agent",
             kind="message",
@@ -82,10 +85,13 @@ def given_a_human_message_on_behalf_of_the_agent(
     context: ContextOfTest,
     agent_message: str,
     session_id: SessionId,
-    agent: Agent,
+    agent_id: AgentId,
 ) -> SessionId:
-    store = context.container[SessionStore]
-    session = context.sync_await(store.read_session(session_id=session_id))
+    session_store = context.container[SessionStore]
+    agent_store = context.container[AgentStore]
+
+    session = context.sync_await(session_store.read_session(session_id=session_id))
+    agent = context.sync_await(agent_store.read_agent(agent_id))
 
     message_data: MessageEventData = {
         "message": agent_message,
@@ -96,7 +102,7 @@ def given_a_human_message_on_behalf_of_the_agent(
     }
 
     event = context.sync_await(
-        store.create_event(
+        session_store.create_event(
             session_id=session.id,
             source="human_agent_on_behalf_of_ai_agent",
             kind="message",
@@ -115,10 +121,12 @@ def given_a_customer_message(
     context: ContextOfTest,
     session_id: SessionId,
     customer_message: str,
-    customer: Customer,
 ) -> SessionId:
-    store = context.container[SessionStore]
-    session = context.sync_await(store.read_session(session_id=session_id))
+    session_store = context.container[SessionStore]
+    customer_store = context.container[CustomerStore]
+
+    session = context.sync_await(session_store.read_session(session_id=session_id))
+    customer = context.sync_await(customer_store.read_customer(customer_id=session.customer_id))
 
     message_data: MessageEventData = {
         "message": customer_message,
@@ -129,7 +137,7 @@ def given_a_customer_message(
     }
 
     event = context.sync_await(
-        store.create_event(
+        session_store.create_event(
             session_id=session.id,
             source="customer",
             kind="message",
@@ -154,18 +162,24 @@ def given_a_flagged_customer_message(
     customer_message: str,
     moderation_tag: ModerationTag,
 ) -> SessionId:
-    store = context.container[SessionStore]
-    session = context.sync_await(store.read_session(session_id=session_id))
+    session_store = context.container[SessionStore]
+    customer_store = context.container[CustomerStore]
+
+    session = context.sync_await(session_store.read_session(session_id=session_id))
+    customer = context.sync_await(customer_store.read_customer(customer_id=session.customer_id))
 
     message_data: MessageEventData = {
         "message": customer_message,
-        "participant": {"display_name": ""},
+        "participant": {
+            "id": customer.id,
+            "display_name": customer.name,
+        },
         "flagged": True,
         "tags": [moderation_tag],
     }
 
     event = context.sync_await(
-        store.create_event(
+        session_store.create_event(
             session_id=session.id,
             source="customer",
             kind="message",

tests/core/engines/alpha/test_user_story_scenarios.py

@@ -25,6 +25,7 @@
     "sessions",
     "terms",
     "tools",
+    "customers",
 )
 
 scenarios(