feat: ms-bot-framework with dynamic adaptive cards

backend/app/bots/adaptive_cards.py

@@ -0,0 +1,47 @@
+from typing import Dict, Any
+from langchain.chat_models import ChatOpenAI
+from langchain.prompts import ChatPromptTemplate
+from langchain.chains import LLMChain
+import asyncio
+
+class AdaptiveCards:
+    def __init__(self):
+        self.llm = ChatOpenAI(temperature=0)
+        self.prompt = ChatPromptTemplate.from_template("""
+            You are a Microsoft Adaptive Card generator. Given a data schema and known values,
+            generate an Adaptive Card (v1.3) that asks the user only for missing fields.
+
+            Use this schema: https://adaptivecards.io/schemas/adaptive-card.json
+            Respond only with valid Adaptive Card JSON. Do not include explanations.
+            Always include isRequired, and errorMessage in the schema.
+            Always include a submit button at the bottom of the card as defined in the schema.
+
+            ### Schema:
+            {schema}
+
+            ### Known values:
+            {known_values}
+
+            """)
+        self.chain = LLMChain(llm=self.llm, prompt=self.prompt)
+
+    async def generate_card(self, schema: Dict[str, Any], known_values: Dict[str, Any]) -> Dict[str, Any]:
+        loop = asyncio.get_running_loop()
+        return await loop.run_in_executor(None, self.chain.run, {
+            "schema": schema,
+            "known_values": known_values
+        })
+
+    def create_welcome_card(self):
+        """Create a welcome card"""
+        return {
+            "type": "AdaptiveCard",
+            "body": [
+                {
+                    "type": "TextBlock",
+                    "text": "Welcome to the Housing Bot!",
+                    "size": "large"
+                }
+            ],
+            "version": "1.0"
+        }

backend/app/bots/dayta.py

@@ -0,0 +1,115 @@
+import json
+from typing import Annotated
+from fastapi import Depends
+from langchain.chat_models import ChatOpenAI
+from botbuilder.core import ActivityHandler, TurnContext
+from botbuilder.schema import Activity, Attachment, ActivityTypes
+import asyncio
+
+from pydantic import ValidationError
+
+from backend.app.bots.adaptive_cards import AdaptiveCards
+from backend.app.bots.intent_detector import IntentDetector
+from backend.app.bots.slot_filler import SlotFiller
+from backend.app.dtos.house.house_features import HouseFeatures
+from backend.app.services.house_price_predictor import HousePricePredictor
+
+class Dayta(ActivityHandler):
+    def __init__(
+            self, 
+            intent_detector: Annotated[IntentDetector, Depends()], 
+            card_bot: Annotated[AdaptiveCards, Depends()], 
+            slot_filler: Annotated[SlotFiller, Depends()],
+            price_predictor: Annotated[HousePricePredictor, Depends()],):
+        
+        self.intent_detector = intent_detector
+        self.card_bot = card_bot
+        self.slot_filler = slot_filler
+        self.price_predictor = price_predictor
+        self.chat_llm = ChatOpenAI(temperature=0.7)
+        self.user_sessions = {}
+
+    async def on_message_activity(self, turn_context: TurnContext):
+        user_message = turn_context.activity.text
+        user_id = turn_context.activity.from_property.id
+        submitted_values = turn_context.activity.value
+
+        known_values = self.user_sessions.get(user_id, {})
+        schema = HouseFeatures.model_json_schema()
+        #required_fields = list(HouseFeatures.model_fields.keys())
+        required_fields = [
+            name for name, field in HouseFeatures.model_fields.items()
+            if field.is_required()
+        ]
+        print(f"required_fields: {required_fields}")
+        
+        # Update known values
+        if submitted_values is not None:
+            known_values.update(submitted_values)
+        else:
+            extracted = await self.slot_filler.extract_slots(schema, user_message)
+            known_values.update(extracted)
+
+        self.user_sessions[user_id] = known_values
+
+        # Detect intent only if message-based
+        if not submitted_values:
+            intent = await self.intent_detector.detect_intent(user_message)
+            if intent.strip().lower() in ("unknown", ""):
+                response = await asyncio.get_event_loop().run_in_executor(
+                    None,
+                    lambda: self.chat_llm.predict(f"The user said: '{user_message}'. Respond helpfully.")
+                )
+                await turn_context.send_activity(response)
+                return
+
+        # Delegate to common logic
+        await self._handle_collected_data(turn_context, user_id, known_values, required_fields, schema)
+
+    async def _handle_collected_data(
+        self,
+        turn_context: TurnContext,
+        user_id: str,
+        known_values: dict,
+        required_fields: list[str],
+        full_schema: dict
+    ):
+        missing_fields = [f for f in required_fields if f not in known_values]
+        print(f"Missing fields: {missing_fields}")
+
+        if not missing_fields:
+           try:
+             features = HouseFeatures(**known_values)
+             price = self.price_predictor.predict(features)
+             await turn_context.send_activity(f"The estimated price of the house is ${price:.2f}")
+             del self.user_sessions[user_id]
+             return
+           except ValidationError as e:
+            await turn_context.send_activity(f"Validation failed: {e}")
+            return
+      
+
+        # Generate adaptive card for missing fields
+        filtered_schema = {
+            **full_schema,
+            "properties": {
+                k: v for k, v in full_schema["properties"].items() if k in missing_fields
+            },
+            "required": missing_fields
+        }
+
+        card_json = await self.card_bot.generate_card(filtered_schema, known_values)
+        if isinstance(card_json, str):
+            card_json = json.loads(card_json)
+        print(f"card_json: {card_json}")
+        await turn_context.send_activity(
+            Activity(
+                type=ActivityTypes.message,
+                attachments=[
+                    Attachment(
+                        content_type="application/vnd.microsoft.card.adaptive",
+                        content=card_json
+                    )
+                ]
+            )
+        )

backend/app/bots/intent_detector.py

@@ -0,0 +1,23 @@
+from langchain.chat_models import ChatOpenAI
+from langchain.prompts import ChatPromptTemplate
+from langchain.chains import LLMChain
+import asyncio
+
+class IntentDetector:
+    def __init__(self, temperature: float = 0.0):
+        self.llm = ChatOpenAI(temperature=temperature)
+        self.prompt = ChatPromptTemplate.from_template("""
+        You are an intent detection bot. Classify the user input into one of the following intents:
+
+        - Information about house prices
+        - unknown
+
+        If you're unsure, respond with `unknown`.
+
+        User: {message}
+        Intent:""")
+        self.chain = LLMChain(llm=self.llm, prompt=self.prompt)
+
+    async def detect_intent(self, message: str) -> str:
+        loop = asyncio.get_running_loop()
+        return await loop.run_in_executor(None, self.chain.run, {"message": message})

backend/app/bots/slot_filler.py

@@ -0,0 +1,31 @@
+from langchain.chat_models import ChatOpenAI
+from langchain.prompts import ChatPromptTemplate
+from langchain.chains import LLMChain
+from typing import Dict, Any
+import asyncio
+
+class SlotFiller:
+    def __init__(self):
+        self.llm = ChatOpenAI(temperature=0)
+        self.prompt = ChatPromptTemplate.from_template("""
+            You are a helpful assistant. Given a message and a schema, extract all known values.
+
+            Only return a JSON object containing the extracted values and no extra text.
+
+            Schema: {schema}
+            Message: {message}
+            """)
+        self.chain = LLMChain(llm=self.llm, prompt=self.prompt)
+
+    async def extract_slots(self, schema: Dict[str, Any], message: str) -> Dict[str, Any]:
+        loop = asyncio.get_event_loop()
+        result = await loop.run_in_executor(None, self.chain.run, {
+            "schema": schema,
+            "message": message
+        })
+
+        import json
+        try:
+            return json.loads(result)
+        except Exception:
+            return {}