added some docs

* Initial plan

* Refactor services into individual Dockerfiles

Co-authored-by: velocitatem <60182044+velocitatem@users.noreply.github.com>

* Add EXPOSE directives to all Dockerfiles with port documentation

Co-authored-by: velocitatem <60182044+velocitatem@users.noreply.github.com>

---------

Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com>
Co-authored-by: velocitatem <60182044+velocitatem@users.noreply.github.com>

.github/workflows/pytest.yml

@@ -1,30 +0,0 @@
-name: Run Tests
-on:
-  push:
-    paths:
-      - 'experiments/**'
-      - 'backend/**'
-      - 'requirements.txt'
-      - '.github/workflows/pytest.yml'
-  pull_request:
-    paths:
-      - 'experiments/**'
-      - 'backend/**'
-      - 'requirements.txt'
-      - '.github/workflows/pytest.yml'
-jobs:
-  test:
-    runs-on: ubuntu-latest
-    steps:
-      - uses: actions/checkout@v4
-      - uses: actions/setup-python@v5
-        with:
-          python-version: '3.13'
-          cache: 'pip'
-      - name: Install dependencies
-        run: |
-          python -m venv .venv
-          .venv/bin/pip install --upgrade pip
-          .venv/bin/pip install -r requirements.txt
-      - name: Run tests
-        run: .venv/bin/pytest -v

.gitignore

@@ -1,8 +1,6 @@
 **/.env
 **/.venv
-**/__pycache__
+PHANTOM.wiki/
-**/.ipynb_checkpoints/
 **/.virtual_documents/
-**/session_*.svg
+**/__pycache__/
-**/*graph.svg
+**/.ipynb_checkpoints/
-paper/src/bib/auto

Makefile

@@ -4,10 +4,6 @@ BUILDDIR  := build
 TEX       := main.tex
 JOBNAME   := main
 PDF       := paper/$(BUILDDIR)/$(JOBNAME).pdf
-VENV      := .venv
-PYTHON    := $(VENV)/bin/python
-PIP       := $(VENV)/bin/pip
-PYTEST    := $(VENV)/bin/pytest
 
 .DEFAULT_GOAL := help
 
@@ -39,14 +35,5 @@ clean:
 	$(LATEXMK) -C -jobname=$(JOBNAME) -outdir=../$(BUILDDIR) || true
 	rm -rf paper/$(BUILDDIR)/*
 
-$(VENV):
-	python3 -m venv $(VENV)
-	$(PIP) install --upgrade pip
 
-install: $(VENV)
+.PHONY: all pdf clean watch run.webapp
-	$(PIP) install -r requirements.txt
-
-test: $(VENV)
-	$(PYTEST) -v
-
-.PHONY: all pdf clean watch run.webapp install test

backend/server/app.py

@@ -7,11 +7,8 @@ import uvicorn
 import os
 import json
 from datetime import datetime
-from kafka import KafkaProducer, KafkaAdminClient, KafkaConsumer
+from kafka import KafkaProducer
-from kafka.admin import NewTopic
-from kafka.errors import TopicAlreadyExistsError
 from dotenv import load_dotenv
-from supabase import create_client, Client
 load_dotenv()
 
 app = FastAPI()
@@ -19,43 +16,21 @@ app = FastAPI()
 # kafka producer - lazy init
 _producer: Optional[KafkaProducer] = None
 
-# supabase client - lazy init
-_supabase: Optional[Client] = None
-
-def get_supabase() -> Client:
-    global _supabase
-    if _supabase is None:
-        url = os.getenv('NEXT_PUBLIC_SUPABASE_URL')
-        key = os.getenv('NEXT_PUBLIC_SUPABASE_ANON_KEY')
-        if not url or not key:
-            raise ValueError("Supabase credentials not configured")
-        _supabase = create_client(url, key)
-    return _supabase
-
 def get_producer() -> KafkaProducer:
     global _producer
     if _producer is None:
         host = os.getenv('KAFKA_HOST', 'localhost')
         port = os.getenv('KAFKA_PORT', '9092')
         broker = f'{host}:{port}' if port else host
-        print(f"[KAFKA_INIT] Connecting to broker: {broker}")
         _producer = KafkaProducer(
             bootstrap_servers=[broker],
             value_serializer=lambda v: json.dumps(v).encode('utf-8'),
             key_serializer=lambda k: k.encode('utf-8') if k else None,
-            acks=1,
-            retries=3,
-            max_in_flight_requests_per_connection=5,
-            request_timeout_ms=30000,
-            api_version_auto_timeout_ms=10000,
-            max_block_ms=5000,  # don't block send() for more than 5s
         )
-        print(f"[KAFKA_INIT] Producer created successfully")
     return _producer
 
 class EventPayload(BaseModel):
     sessionId: str
-    experimentId: Optional[str] = None
     eventName: str
     page: str
     productId: Optional[str] = None
@@ -64,14 +39,6 @@ class EventPayload(BaseModel):
     userAgent: Optional[str] = None
     ts: Optional[str] = None
 
-class PriceLogPayload(BaseModel):
-    productId: str
-    price: float
-    sessionId: str
-    experimentId: Optional[str] = None
-    storeMode: str
-    ts: Optional[str] = None
-
 app.add_middleware(
     CORSMiddleware,
     allow_origins=["*"],
@@ -80,34 +47,6 @@ app.add_middleware(
     allow_headers=["*"],
 )
 
-@app.on_event("startup")
-async def startup_event():
-    """create kafka topics on startup"""
-    host = os.getenv('KAFKA_HOST', 'localhost')
-    port = os.getenv('KAFKA_PORT', '9092')
-    broker = f'{host}:{port}'
-
-    try:
-        print(f"[STARTUP] Creating Kafka topics on {broker}")
-        admin = KafkaAdminClient(
-            bootstrap_servers=[broker],
-            request_timeout_ms=10000,
-        )
-
-        topics = [
-            NewTopic(name='user-interactions', num_partitions=3, replication_factor=1),
-            NewTopic(name='price-logs', num_partitions=3, replication_factor=1)
-        ]
-
-        admin.create_topics(new_topics=topics, validate_only=False)
-        print(f"[STARTUP] Topics created successfully")
-        admin.close()
-    except TopicAlreadyExistsError:
-        print(f"[STARTUP] Topics already exist, skipping creation")
-    except Exception as e:
-        print(f"[STARTUP] Failed to create topics: {e}")
-        print(f"[STARTUP] Will rely on auto-creation on first message")
-
 @app.get("/health")
 async def health():
     kafka_status = "unknown"
@@ -133,13 +72,12 @@ async def ingest_logs(event: EventPayload):
             event.ts = datetime.utcnow().isoformat() + 'Z'
 
         producer = get_producer()
-        future = producer.send(
+        producer.send(
             'user-interactions',
             key=event.sessionId,
             value=event.model_dump()
         )
-        # add callback for error logging but don't block
+        producer.flush(timeout=5)
-        future.add_errback(lambda e: print(f"[KAFKA_SEND_ERROR] {e}"))
 
         return {"success": True}
     except Exception as e:
@@ -148,212 +86,11 @@ async def ingest_logs(event: EventPayload):
         print(traceback.format_exc())
         raise HTTPException(status_code=500, detail=str(e))
 
-@app.post("/api/kafka/price-log")
-async def ingest_price_log(price_log: PriceLogPayload):
-    try:
-        if not price_log.ts:
-            price_log.ts = datetime.utcnow().isoformat() + 'Z'
-
-        producer = get_producer()
-        future = producer.send(
-            'price-logs',
-            key=price_log.productId,
-            value=price_log.model_dump()
-        )
-        future.add_errback(lambda e: print(f"[KAFKA_PRICE_LOG_ERROR] {e}"))
-
-        return {"success": True}
-    except Exception as e:
-        import traceback
-        print(f"[PRICE_LOG_ERROR] {e}")
-        print(traceback.format_exc())
-        raise HTTPException(status_code=500, detail=str(e))
-
 @app.get("/api/kafka/dump")
-def dump_logs(
+def dump_logs():
-    topic: str = 'user-interactions',
+    # TODO: implement a dump of logs of time period t_start to t_end (params of get)
-    last_n: Optional[int] = None,
+    # OR: allow for params of last_n logs as a param - creating two modes of the dumping
-    t_start: Optional[str] = None,
+    pass
-    t_end: Optional[str] = None
-):
-    """dump all messages from specified kafka topic
-
-    params:
-        topic: kafka topic to dump (default: user-interactions)
-        last_n: return only last n messages (default: all)
-        t_start: filter by start timestamp iso format
-        t_end: filter by end timestamp iso format
-    """
-    if topic not in ['user-interactions', 'price-logs']:
-        raise HTTPException(status_code=400, detail="Invalid topic")
-
-    host = os.getenv('KAFKA_HOST', 'localhost')
-    port = os.getenv('KAFKA_PORT', '9092')
-    broker = f'{host}:{port}'
-
-    try:
-        consumer = KafkaConsumer(
-            topic,
-            bootstrap_servers=[broker],
-            auto_offset_reset='earliest',
-            enable_auto_commit=False,
-            value_deserializer=lambda x: json.loads(x.decode('utf-8')),
-            consumer_timeout_ms=5000
-        )
-
-        events = []
-        for msg in consumer:
-            events.append(msg.value)
-
-        consumer.close()
-
-        # apply filters
-        if t_start or t_end:
-            filtered = []
-            for e in events:
-                ts = e.get('ts')
-                if ts:
-                    if t_start and ts < t_start:
-                        continue
-                    if t_end and ts > t_end:
-                        continue
-                filtered.append(e)
-            events = filtered
-
-        if last_n and last_n > 0:
-            events = events[-last_n:]
-
-        return {"success": True, "count": len(events), "data": events}
-
-    except Exception as e:
-        import traceback
-        print(f"[DUMP_ERROR] {e}")
-        print(traceback.format_exc())
-        raise HTTPException(status_code=500, detail=str(e))
-
-@app.get("/api/products/{product_id}")
-async def get_product_by_id(product_id: str):
-    """fetch single product by id from either hotel_products or airline_products"""
-    try:
-        supabase = get_supabase()
-
-        # try hotel_products first
-        response = supabase.table('hotel_products').select('*').eq('id', product_id).execute()
-        if response.data and len(response.data) > 0:
-            return {"success": True, "data": response.data[0]}
-
-        # try airline_products
-        response = supabase.table('airline_products').select('*').eq('id', product_id).execute()
-        if response.data and len(response.data) > 0:
-            return {"success": True, "data": response.data[0]}
-
-        raise HTTPException(status_code=404, detail="Product not found")
-
-    except HTTPException:
-        raise
-    except Exception as e:
-        import traceback
-        print(f"[PRODUCT_BY_ID_ERROR] {e}")
-        print(traceback.format_exc())
-        raise HTTPException(status_code=500, detail=str(e))
-
-@app.get("/api/products/type/{product_type}")
-async def get_products(
-    product_type: str,
-    dateIndex: Optional[int] = None,
-    origin: Optional[str] = None,
-    destination: Optional[str] = None,
-    tripType: Optional[str] = None,
-    adults: Optional[int] = None,
-    children: Optional[int] = None,
-    infants: Optional[int] = None,
-    rooms: Optional[int] = None
-):
-    """fetch products from supabase based on type (hotel or airline)
-
-    params:
-        product_type: either 'hotel' or 'airline'
-        dateIndex: optional days offset from today (e.g., 0=today, 1=tomorrow, -1=yesterday)
-        origin: (airline) departure airport code
-        destination: (airline/hotel) arrival airport or hotel location
-        tripType: (airline) roundtrip, oneway, multicity
-        adults, children, infants: passenger counts
-        rooms: (hotel) number of rooms
-    """
-    if product_type not in ['hotel', 'airline']:
-        raise HTTPException(status_code=400, detail="product_type must be 'hotel' or 'airline'")
-
-    try:
-        supabase = get_supabase()
-        table = f'{product_type}_products'
-
-        query = supabase.table(table).select('*')
-
-        # filter by exact date_index if provided
-        if dateIndex is not None:
-            query = query.eq('date_index', dateIndex)
-
-        response = query.execute()
-        results = response.data
-
-        # apply in-memory filters based on metadata for airline products
-        if product_type == 'airline' and results:
-            filtered = []
-            for product in results:
-                metadata = product.get('metadata', {})
-
-                # filter by origin airport
-                if origin:
-                    dep = metadata.get('departure', {})
-                    if dep.get('airport') != origin:
-                        continue
-
-                # filter by destination airport
-                if destination:
-                    arr = metadata.get('arrival', {})
-                    if arr.get('airport') != destination:
-                        continue
-
-                # passenger count validation (ensure total capacity)
-                if adults is not None or children is not None or infants is not None:
-                    total_pax = (adults or 0) + (children or 0) + (infants or 0)
-                    avail = product.get('availability', 0)
-                    if avail < total_pax:
-                        continue
-
-                filtered.append(product)
-
-            results = filtered
-
-        # apply in-memory filters for hotel products
-        elif product_type == 'hotel' and results:
-            filtered = []
-            for product in results:
-                metadata = product.get('metadata', {})
-
-                # filter by occupancy capacity
-                if adults is not None:
-                    max_occ = metadata.get('max_occupancy', 2)
-                    if max_occ < adults:
-                        continue
-
-                # filter by room availability
-                if rooms is not None:
-                    avail = product.get('availability', 0)
-                    if avail < rooms:
-                        continue
-
-                filtered.append(product)
-
-            results = filtered
-
-        return {"success": True, "count": len(results), "data": results}
-
-    except Exception as e:
-        import traceback
-        print(f"[PRODUCTS_ERROR] {e}")
-        print(traceback.format_exc())
-        raise HTTPException(status_code=500, detail=str(e))
 
 
 

backend/server/requirements.txt

@@ -3,4 +3,3 @@ uvicorn[standard]==0.24.0
 kafka-python==2.0.2
 pydantic==2.5.0
 python-dotenv==1.0.0
-supabase==2.9.1

docker-compose.yml

@@ -9,9 +9,6 @@ services:
     environment:
       - KAFKA_HOST=kafka
       - KAFKA_PORT=29092
-      - BACKEND_PORT=5000
-      - NEXT_PUBLIC_SUPABASE_URL=${NEXT_PUBLIC_SUPABASE_URL}
-      - NEXT_PUBLIC_SUPABASE_ANON_KEY=${NEXT_PUBLIC_SUPABASE_ANON_KEY}
     depends_on:
       - kafka
     restart: unless-stopped

experiments/agents/__init__.py

@@ -1 +0,0 @@
-"""Agentic behavior runner for PHANTOM research platform."""

experiments/agents/agent.py

@@ -1,47 +0,0 @@
-from .base import Agent as BaseAgent
-from browser_use import Browser, Agent, ChatOpenAI
-from enum import Enum
-
-class AgentTypes(str, Enum):
-    GENERIC_BROWSER_USE_AGENT = "generic_browser_use_agent"
-
-def _build_prompt(goal : str, environment_url : str) -> str:
-    #TODO: Improve prompt engineering here and experiment with
-    return f"""You are an autonomous agent tasked with achieving the following goal: {goal}
-You have access to a web browser to interact with the environment at {environment_url}.
-Use the browser to navigate, gather information, and perform actions necessary to accomplish your goal.
-Be thorough and ensure you complete the task fully."""
-
-class GenericBrowserUseAgent(BaseAgent):
-    def __init__(self,
-                 goal: str,
-                 url: str = "http://localhost:3000",
-                 timeout: int = 300,
-                 llm_model: str = "gpt-5-mini",
-                 headless: bool = True):
-        super().__init__(goal, url, timeout)
-        self.llm_model = ChatOpenAI(model=llm_model)
-        self.browser = Browser(headless=headless)
-        self.agent = Agent(task=_build_prompt(goal, url),
-                           llm=self.llm_model,
-                           browser=self.browser)
-    async def act(self) -> str:
-        self.result = await self.agent.run()
-        # https://github.com/browser-use/browser-use/blob/main/browser_use/agent/views.py#L301
-        return self.result.final_result()
-
-def get_agent(agent_type: AgentTypes,  **kwargs) -> Agent:
-    if agent_type == AgentTypes.GENERIC_BROWSER_USE_AGENT:
-        return GenericBrowserUseAgent(**kwargs)
-    else:
-        raise ValueError(f"Unknown agent type: {agent_type}")
-
-if __name__ == "__main__":
-    import asyncio
-    JTBD= "Find me the cheapest room in Madrid for 2 people in the next two days, review each hotel room in detail and then add it to cart."
-    agent = get_agent(AgentTypes.GENERIC_BROWSER_USE_AGENT,
-                      goal=JTBD,
-                      url="http://localhost:3000/start-task?uuid=d10f5ab3-a7b7-4e97-8d94-ab06f1537c0a",
-                      timeout=300)
-    R=asyncio.run(agent.act())
-    print(R)

experiments/agents/base.py

@@ -1,19 +0,0 @@
-from abc import ABC, abstractmethod
-from typing import Optional
-
-class Agent(ABC):
-    """Base interface for browser automation agents"""
-
-    def __init__(self, goal: str, url: str = "http://localhost:3000", timeout: int = 300):
-        self.goal = goal
-        self.url = url
-        self.timeout = timeout
-        self.result: Optional[str] = None
-
-    @abstractmethod
-    async def act(self) -> str:
-        """Execute goal and return result text"""
-        pass
-
-    def final_result(self) -> Optional[str]:
-        return self.result

experiments/agents/test.py

@@ -1,30 +0,0 @@
-import pytest
-import asyncio
-from experiments.agents.agent import get_agent, AgentTypes
-import os
-
-
-def test_agent_init():
-    agent = get_agent(AgentTypes.GENERIC_BROWSER_USE_AGENT, goal="test", url="http://example.com", timeout=100)
-    assert agent.goal == "test"
-    assert agent.url == "http://example.com"
-    assert agent.timeout == 100
-
-
-def test_invalid_agent():
-    with pytest.raises(ValueError):
-        get_agent("invalid", goal="test")
-
-
-@pytest.mark.asyncio
-@pytest.mark.skipif("OPENAI_API_KEY" not in os.environ, reason="OPENAI_API_KEY not set")
-async def test_agent_execution():
-    agent = get_agent(AgentTypes.GENERIC_BROWSER_USE_AGENT, goal="get page title", url="https://example.com", timeout=60)
-
-    result = await agent.act()
-    assert result
-    assert agent.final_result()
-    assert agent.final_result().history[-1].result[-1].is_done == True
-    assert isinstance(result, str)
-    assert "example" in result.lower()
-    assert len(result) > 0

experiments/procesing/__init__.py

@@ -1,19 +0,0 @@
-from .extract import (
-    KafkaDataFetcher,
-    ExperimentJoiner,
-    EventTitleAugmenter,
-)
-from .demand import DemandEstimator
-from .mapping import SessionTransitionProbMatrixTransformer, render_graph
-from .pipeline import etl_pipeline, pricing_pipeline
-
-__all__ = [
-    'KafkaDataFetcher',
-    'ExperimentJoiner',
-    'EventTitleAugmenter',
-    'DemandEstimator',
-    'SessionTransitionProbMatrixTransformer',
-    'render_graph',
-    'etl_pipeline',
-    'pricing_pipeline',
-]

experiments/procesing/demand.py

@@ -1,119 +0,0 @@
-from sklearn.base import BaseEstimator, TransformerMixin
-import numpy as np
-import pandas as pd
-from supabase import create_client, Client
-from typing import Optional, Literal
-import os
-import logging
-log = logging.getLogger(__name__)
-
-SUPABASE_URL = os.getenv("NEXT_PUBLIC_SUPABASE_URL", "")
-SUPABASE_KEY = os.getenv("NEXT_PUBLIC_SUPABASE_ANON_KEY", "")
-
-supabase: Client = create_client(SUPABASE_URL, SUPABASE_KEY)
-
-class ChunkInteractionsIntoSteps(BaseEstimator, TransformerMixin):
-    """
-    Split interaction data into time windows for temporal analysis.
-    Returns a list of dataframes, one per time window.
-    """
-    def __init__(self,
-                 window_size:str='1h',
-                 ts_col:str='ts',
-                 return_metadata:bool=True):
-        """
-        Args:
-            window_size: pandas freq string ('1h', '30T', '1D', etc)
-            ts_col: timestamp column name
-            return_metadata: if True, return dict with metadata per chunk
-        """
-        self.window_size = window_size
-        self.ts_col = ts_col
-        self.return_metadata = return_metadata
-
-    def fit(self, X):
-        return self
-
-    def transform(self, interactions: pd.DataFrame):
-        """
-        Returns:
-            if return_metadata=False: list of dataframes, one per window
-            if return_metadata=True: list of dicts with keys:
-                - 'data': dataframe for this window
-                - 'window_start': start timestamp
-                - 'window_end': end timestamp
-                - 'window_idx': integer index
-        """
-        if interactions.empty:
-            return []
-
-        df = interactions.copy()
-
-        # ensure timestamp is datetime
-        if not pd.api.types.is_datetime64_any_dtype(df[self.ts_col]):
-            df[self.ts_col] = pd.to_datetime(df[self.ts_col])
-
-        # sort by time
-        df = df.sort_values(self.ts_col)
-
-        # assign window
-        df['_window'] = df[self.ts_col].dt.floor(self.window_size)
-
-        # group by window
-        chunks = []
-        for idx, (window_start, group) in enumerate(df.groupby('_window')):
-            chunk_data = group.drop(columns=['_window'])
-
-            if self.return_metadata:
-                chunks.append({
-                    'data': chunk_data,
-                    'window_start': window_start,
-                    'window_end': window_start + pd.Timedelta(self.window_size),
-                    'window_idx': idx
-                })
-            else:
-                chunks.append(chunk_data)
-
-        return chunks
-
-
-class DemandEstimator(BaseEstimator, TransformerMixin):
-    def __init__(self,
-                 store_mode:str='hotel',
-                 session_filter:str="",
-                 experiment_filter:str=""):
-        self.store=store_mode
-        self.session_filter=session_filter if len(session_filter)>0 else None
-        self.experiment_filter=experiment_filter if len(experiment_filter)>0 else None
-    def fit(self, X):
-        return self
-
-    def transform(self, interactions : pd.DataFrame):
-        if interactions.empty:
-            return pd.DataFrame(columns=["productId", "demand_score"])
-        if self.session_filter:
-            interactions = interactions[interactions['sessionId'] == self.session_filter]
-        if self.experiment_filter:
-            interactions = interactions[interactions['experimentId'] == self.experiment_filter]
-
-        products=supabase.table(f'{self.store}_products').select("id, room_type, date_index, metadata, availability").execute()
-        products = pd.DataFrame(products.data)
-        unique_products = products['id'].unique()
-        log.info(f"Demand estimator found {len(unique_products)} in data")
-
-        # filter out rows without productId
-        interactions_with_products = interactions.dropna(subset=['productId'])
-
-        if interactions_with_products.empty:
-            # no interactions with products, return all zeros
-            return pd.DataFrame({
-                'productId': unique_products,
-                'demand_score': 0
-            })
-
-        # TODO: improve demand score calculation rather than just counting interactions (use weights..)
-        # while maintaining simplicity of a simple cross tab approach
-        product_demand = pd.crosstab(interactions_with_products['productId'], "no_of_interactions")
-        product_demand = product_demand.reindex(unique_products, fill_value=0).reset_index()
-        product_demand.columns = ['productId', 'demand_score']
-        return product_demand

experiments/procesing/elasticity.py

@@ -1,333 +0,0 @@
-import numpy as np
-import pandas as pd
-from typing import List, Dict, Optional
-from sklearn.base import BaseEstimator, TransformerMixin
-from supabase import create_client, Client
-import os
-
-SUPABASE_URL = os.getenv("NEXT_PUBLIC_SUPABASE_URL", "")
-SUPABASE_KEY = os.getenv("NEXT_PUBLIC_SUPABASE_ANON_KEY", "")
-
-supabase: Client = create_client(SUPABASE_URL, SUPABASE_KEY)
-
-class TemporalElasticityEstimator(BaseEstimator, TransformerMixin):
-    """
-    Compute price elasticity from time-series demand and price data.
-
-    Elasticity = (% change in quantity) / (% change in price)
-
-    Works with chunked time-window data from ChunkInteractionsIntoSteps.
-    """
-
-    def __init__(self,
-                 method:str='point',
-                 min_observations:int=2,
-                 smooth_window:Optional[int]=None):
-        """
-        Args:
-            method: 'point' (point elasticity) or 'arc' (arc elasticity)
-            min_observations: min data points needed per product
-            smooth_window: if set, apply rolling avg smoothing to time series
-        """
-        self.method = method
-        self.min_observations = min_observations
-        self.smooth_window = smooth_window
-
-    def fit(self, X):
-        return self
-
-    def transform(self,
-                  demand_chunks: List[Dict],
-                  price_chunks: List[Dict],
-                  store_mode: str = 'hotel') -> pd.DataFrame:
-        """
-        Args:
-            demand_chunks: list from ChunkInteractionsIntoSteps + DemandEstimator
-                           each item: {'window_start', 'window_end', 'demand_vector'}
-            price_chunks: list of dicts with {'window_start', 'window_end', 'price_vector'}
-            store_mode: 'hotel' or 'airline' to fetch all products
-
-        Returns:
-            df with [productId, elasticity, std_error, n_observations]
-        """
-        # fetch all products from database
-        all_products = supabase.table(f'{store_mode}_products').select("id").execute()
-        all_product_ids = [p['id'] for p in all_products.data]
-
-        aligned = self._align_chunks(demand_chunks, price_chunks)
-        if not aligned:
-            # return all products with zero elasticity
-            return pd.DataFrame({
-                'productId': all_product_ids,
-                'elasticity': 0.0,
-                'std_error': 0.0,
-                'n_obs': 0
-            })
-
-        # build time series per product
-        product_series = self._build_product_timeseries(aligned)
-
-        # compute elasticity per product
-        elasticities = []
-        for pid, series in product_series.items():
-            if len(series) < self.min_observations:
-                # assign 0 elasticity for products with insufficient data
-                elasticities.append({
-                    'productId': pid,
-                    'elasticity': 0.0,
-                    'std_error': 0.0,
-                    'n_obs': len(series)
-                })
-                continue
-
-            # apply smoothing if requested
-            if self.smooth_window and len(series) >= self.smooth_window:
-                series = self._smooth_series(series, self.smooth_window)
-
-            elast = self._compute_elasticity(series)
-            elasticities.append({
-                'productId': pid,
-                'elasticity': elast['value'],
-                'std_error': elast.get('std_error', 0.0),
-                'n_obs': len(series)
-            })
-
-        result_df = pd.DataFrame(elasticities)
-
-        # fill in missing products with zero elasticity
-        observed_pids = set(result_df['productId'].unique())
-        missing_pids = [pid for pid in all_product_ids if pid not in observed_pids]
-
-        if missing_pids:
-            missing_df = pd.DataFrame({
-                'productId': missing_pids,
-                'elasticity': 0.0,
-                'std_error': 0.0,
-                'n_obs': 0
-            })
-            result_df = pd.concat([result_df, missing_df], ignore_index=True)
-
-        return result_df
-
-    def _align_chunks(self, demand_chunks, price_chunks):
-        """Align demand and price data by matching time windows."""
-        aligned = []
-
-        # create lookup for price chunks by window_start
-        price_lookup = {chunk['window_start']: chunk for chunk in price_chunks}
-
-        for demand_chunk in demand_chunks:
-            window_start = demand_chunk['window_start']
-            if window_start in price_lookup:
-                aligned.append({
-                    'window_start': window_start,
-                    'window_end': demand_chunk['window_end'],
-                    'demand': demand_chunk['demand_vector'],
-                    'prices': price_lookup[window_start]['price_vector']
-                })
-
-        return aligned
-
-    def _build_product_timeseries(self, aligned_chunks):
-        """Build time series [price, quantity] per product."""
-        series_by_product = {}
-
-        for chunk in aligned_chunks:
-            demand_df = chunk['demand']
-            price_df = chunk['prices']
-
-            # merge on productId
-            merged = demand_df.merge(price_df, on='productId', how='inner')
-
-            for _, row in merged.iterrows():
-                pid = row['productId']
-                if pid not in series_by_product:
-                    series_by_product[pid] = []
-
-                series_by_product[pid].append({
-                    'timestamp': chunk['window_start'],
-                    'price': row['price'],
-                    'quantity': row['demand_score']
-                })
-
-        return series_by_product
-
-    def _smooth_series(self, series, window):
-        """Apply rolling average smoothing."""
-        df = pd.DataFrame(series)
-        df['price_smooth'] = df['price'].rolling(window=window, center=True).mean()
-        df['quantity_smooth'] = df['quantity'].rolling(window=window, center=True).mean()
-        df = df.dropna()
-
-        return [{'timestamp': row['timestamp'],
-                 'price': row['price_smooth'],
-                 'quantity': row['quantity_smooth']}
-                for _, row in df.iterrows()]
-
-    def _compute_elasticity(self, series):
-        """Compute elasticity from time series."""
-        if len(series) < 2:
-            return {'value': 0.0, 'std_error': 0.0}
-
-        prices = np.array([s['price'] for s in series])
-        quantities = np.array([s['quantity'] for s in series])
-
-        # filter out zero/negative values
-        valid = (prices > 0) & (quantities > 0)
-        if valid.sum() < 2:
-            return {'value': 0.0, 'std_error': 0.0}
-
-        prices = prices[valid]
-        quantities = quantities[valid]
-
-        if self.method == 'point':
-            return self._point_elasticity(prices, quantities)
-        elif self.method == 'arc':
-            return self._arc_elasticity(prices, quantities)
-        else:
-            raise ValueError(f"Unknown method: {self.method}")
-
-    def _point_elasticity(self, prices, quantities):
-        """
-        Point elasticity using log-log regression.
-        log(Q) = a + b*log(P), elasticity = b
-        """
-        if len(prices) < 2:
-            return {'value': 0.0, 'std_error': 0.0}
-
-        log_p = np.log(prices)
-        log_q = np.log(quantities)
-
-        # simple linear regression
-        if log_p.std() == 0:
-            return {'value': 0.0, 'std_error': 0.0}
-
-        cov = np.cov(log_p, log_q)[0, 1]
-        var = np.var(log_p)
-        b = cov / var
-
-        # std error estimate (avoid div by zero)
-        if len(prices) <= 2:
-            se_b = 0.0
-        else:
-            residuals = log_q - (log_q.mean() + b * (log_p - log_p.mean()))
-            mse = (residuals ** 2).sum() / (len(prices) - 2)
-            se_b = np.sqrt(mse / (len(prices) * var))
-
-        return {'value': b, 'std_error': se_b}
-
-    def _arc_elasticity(self, prices, quantities):
-        """
-        Arc elasticity: average of period-over-period elasticities.
-        E_t = (ΔQ/Q_avg) / (ΔP/P_avg)
-        """
-        elasticities = []
-
-        for i in range(1, len(prices)):
-            p1, p2 = prices[i-1], prices[i]
-            q1, q2 = quantities[i-1], quantities[i]
-
-            p_avg = (p1 + p2) / 2
-            q_avg = (q1 + q2) / 2
-
-            if p_avg == 0 or q_avg == 0:
-                continue
-
-            delta_p = p2 - p1
-            delta_q = q2 - q1
-
-            if delta_p == 0:
-                continue
-
-            e = (delta_q / q_avg) / (delta_p / p_avg)
-            elasticities.append(e)
-
-        if not elasticities:
-            return None
-
-        return {
-            'value': np.mean(elasticities),
-            'std_error': np.std(elasticities) / np.sqrt(len(elasticities))
-        }
-
-
-def aggregate_price_logs(price_logs: pd.DataFrame,
-                         window_size: str = '1H',
-                         ts_col: str = 'ts',
-                         store_mode : str = 'hotel') -> List[Dict]:
-    """
-    Recover price vectors treating prices as persistent state changes.
-
-    Prices are set-operations that persist until next change. For each window:
-    - If price logs exist: average all changes within window
-    - If no logs: carry forward last price before window end
-
-    Args:
-        price_logs: df with [productId, price, ts, ...]
-        window_size: time window size matching ChunkInteractionsIntoSteps
-        ts_col: timestamp column name
-
-    Returns:
-        list of dicts with {'window_start', 'window_end', 'price_vector'}
-        where price_vector is df with [productId, price]
-    """
-    if price_logs.empty:
-        return []
-
-    df = price_logs.copy()
-
-    if not pd.api.types.is_datetime64_any_dtype(df[ts_col]):
-        df[ts_col] = pd.to_datetime(df[ts_col])
-
-    df = df.sort_values([ts_col, 'productId'])
-    all_products=supabase.table(f'{store_mode}_products').select("id, room_type, date_index, metadata, availability").execute()
-    all_products = pd.DataFrame(all_products.data)
-    unique_products = all_products['id'].unique()
-
-    # generate windows across data range
-    min_time, max_time = df[ts_col].min(), df[ts_col].max()
-    windows = pd.date_range(
-        start=min_time.floor(window_size),
-        end=max_time,
-        freq=window_size
-    )
-
-    chunks = []
-
-    for window_start in windows:
-        window_end = window_start + pd.Timedelta(window_size)
-        price_vector = []
-
-        # all products with price history by window_end
-        #historical_products = df[df[ts_col] < window_end]['productId'].unique()
-        historical_products = unique_products.tolist()
-
-        for pid in historical_products:
-            product_data = df[df['productId'] == pid]
-
-            # logs within window
-            in_window = product_data[
-                (product_data[ts_col] >= window_start) &
-                (product_data[ts_col] < window_end)
-            ]
-
-            if not in_window.empty:
-                # average changes within window
-                price = in_window['price'].mean()
-            else:
-                # carry forward: last price before window end
-                before_window = product_data[product_data[ts_col] < window_end]
-                if before_window.empty:
-                    continue
-                price = before_window['price'].iloc[-1]
-
-            price_vector.append({'productId': pid, 'price': price})
-
-        if price_vector:
-            chunks.append({
-                'window_start': window_start,
-                'window_end': window_end,
-                'price_vector': pd.DataFrame(price_vector)
-            })
-
-    return chunks

experiments/procesing/extract.py

@@ -1,207 +0,0 @@
-import pandas as pd
-import json
-import numpy as np
-import os
-import requests
-from dotenv import load_dotenv
-from sklearn.base import BaseEstimator, TransformerMixin
-from supabase import create_client, Client
-from typing import Tuple, List, Dict
-load_dotenv()
-
-BACKEND_URL = os.getenv("BACKEND_URL", "http://localhost:5000")
-SUPABASE_URL = os.getenv("NEXT_PUBLIC_SUPABASE_URL")
-SUPABASE_KEY = os.getenv("NEXT_PUBLIC_SUPABASE_ANON_KEY")
-N_PRICE_BUCKETS = 5
-
-supabase: Client = create_client(SUPABASE_URL, SUPABASE_KEY)
-
-
-class KafkaDataFetcher(BaseEstimator, TransformerMixin):
-    def __init__(self, topic: str = "user-interactions"):
-        self.topic = topic # also can be price-logs
-    def fit(self, X=None, y=None):
-        return self
-
-    def transform(self, X=None):
-        resp = requests.get(f"{BACKEND_URL}/api/kafka/dump?topic={self.topic}")
-        resp.raise_for_status()
-        data = resp.json()
-
-        if not data.get('success') or not data.get('data'):
-            return pd.DataFrame()
-
-        df = pd.DataFrame(data['data'])
-        if self.topic == 'user-interactions':
-            if 'metadata' in df.columns: # explode metadata col json
-                df = df.join(pd.json_normalize(df.pop("metadata"), sep=".").add_prefix("metadata_"))
-            df = df.dropna(subset=['eventName'])
-            # remape dateIndex
-            df['dateIndex'] = df['metadata_dateIndex'].astype('Int64')
-        return df
-
-
-class ExperimentJoiner(BaseEstimator, TransformerMixin):
-    def fit(self, X=None, y=None):
-        return self
-
-    def transform(self, df):
-        if df.empty or 'experimentId' not in df.columns:
-            return df
-
-        unique_exp_ids = df['experimentId'].dropna().unique()
-        if len(unique_exp_ids) == 0:
-            return df
-
-        resp = supabase.table('experiments').select(
-            'id, subject_name, xp_human_only, xp_market_mode, xp_task_id, task:tasks(task_name, task_description, task_def_of_done)'
-        ).in_('id', unique_exp_ids.tolist()).execute()
-
-        if not resp.data:
-            return df
-
-        exp_df = pd.DataFrame(resp.data)
-
-        # flatten task nested object if present
-        if 'task' in exp_df.columns and exp_df['task'].notnull().any():
-            task_normalized = pd.json_normalize(exp_df['task'].dropna())
-            task_normalized.index = exp_df[exp_df['task'].notnull()].index
-            exp_df = exp_df.drop(columns=['task']).join(task_normalized, rsuffix='_task')
-
-        # rename experiment columns for clarity
-        exp_df = exp_df.rename(columns={
-            'id': 'experimentId',
-            'subject_name': 'exp_subject',
-            'xp_human_only': 'exp_human_only',
-            'xp_market_mode': 'exp_market_mode',
-            'xp_task_id': 'exp_task_id'
-        })
-
-        df = df.merge(exp_df, on='experimentId', how='left')
-        return df
-
-
-class EventTitleAugmenter(BaseEstimator, TransformerMixin):
-    def fit(self, X=None, y=None):
-        return self
-
-    def transform(self, df):
-        # from taking standard view_item_page in eventName to view_item_page_{metadata_schema}
-        # we want metadata schema to create product specific event names
-
-        # only create price buckets if we have enough unique prices
-        if df["metadata_price"].notnull().sum() > 0:
-            try:
-                price_buckets = pd.qcut(
-                    df["metadata_price"],
-                    q=N_PRICE_BUCKETS,
-                    labels=[f"PB_{i+1}" for i in range(N_PRICE_BUCKETS)],
-                    duplicates='drop'  # handle duplicate bin edges
-                )
-            except ValueError:
-                # fallback: if still not enough unique values, use cut with fixed ranges or just use raw price
-                price_buckets = df["metadata_price"].apply(lambda x: f"P_{int(x)}" if pd.notnull(x) else "")
-        else:
-            price_buckets = pd.Series([""] * len(df), index=df.index)
-
-        # metadata_schema: _product_id@price_bucket_{i} only if we have product metadata otherswise keep original event name
-        # TODO: make this adaptive, if we have hover_over_title we append the title, if its view_page we say which page
-        df["metadata_schema"] = np.where(
-            df["productId"].notnull() & df["metadata_price"].notnull(),
-            "_" + df["productId"].astype(str) + "@" + price_buckets.astype(str),
-            ""
-        )
-        df["eventName"] = df["eventName"] + df["metadata_schema"].astype(str)
-        return df
-
-
-def chunk_shared_data(interactions_df: pd.DataFrame,
-                      price_logs_df: pd.DataFrame,
-                      window_size: str = '30s',
-                      ts_col: str = 'ts') -> Tuple[List[Dict], List[Dict]]:
-    """
-    Chunk interaction and price data into aligned time windows.
-
-    Args:
-        interactions_df: interaction data with timestamp column
-        price_logs_df: price log data with timestamp column
-        window_size: pandas freq string ('30s', '1min', '1h', etc)
-        ts_col: name of timestamp column
-
-    Returns:
-        tuple of (interaction_chunks, price_chunks) where each is list of dicts:
-        {
-            'window_start': timestamp,
-            'window_end': timestamp,
-            'data': dataframe for this window
-        }
-    """
-    if interactions_df.empty and price_logs_df.empty:
-        return [], []
-
-    # convert timestamps to datetime
-    interactions_df = interactions_df.copy()
-    price_logs_df = price_logs_df.copy()
-
-    if not interactions_df.empty:
-        if not pd.api.types.is_datetime64_any_dtype(interactions_df[ts_col]):
-            interactions_df[ts_col] = pd.to_datetime(interactions_df[ts_col])
-
-    if not price_logs_df.empty:
-        if not pd.api.types.is_datetime64_any_dtype(price_logs_df[ts_col]):
-            price_logs_df[ts_col] = pd.to_datetime(price_logs_df[ts_col])
-
-    # find global time bounds
-    times = []
-    if not interactions_df.empty:
-        times.extend([interactions_df[ts_col].min(), interactions_df[ts_col].max()])
-    if not price_logs_df.empty:
-        times.extend([price_logs_df[ts_col].min(), price_logs_df[ts_col].max()])
-
-    if not times:
-        return [], []
-
-    earliest = min(times)
-    latest = max(times)
-
-    # create shared time windows
-    windows = pd.date_range(start=earliest, end=latest, freq=window_size)
-
-    if len(windows) < 2:
-        return [], []
-
-    # chunk both datasets
-    interaction_chunks = []
-    price_chunks = []
-
-    for i in range(len(windows) - 1):
-        window_start = windows[i]
-        window_end = windows[i + 1]
-
-        # filter interactions in this window
-        if not interactions_df.empty:
-            mask = (interactions_df[ts_col] >= window_start) & (interactions_df[ts_col] < window_end)
-            interaction_chunk = interactions_df[mask]
-        else:
-            interaction_chunk = pd.DataFrame()
-
-        interaction_chunks.append({
-            'window_start': window_start,
-            'window_end': window_end,
-            'data': interaction_chunk
-        })
-
-        # filter price logs in this window
-        if not price_logs_df.empty:
-            mask = (price_logs_df[ts_col] >= window_start) & (price_logs_df[ts_col] < window_end)
-            price_chunk = price_logs_df[mask]
-        else:
-            price_chunk = pd.DataFrame()
-
-        price_chunks.append({
-            'window_start': window_start,
-            'window_end': window_end,
-            'data': price_chunk
-        })
-
-    return interaction_chunks, price_chunks

experiments/procesing/mapping.py

@@ -1,158 +0,0 @@
-import numpy as np
-import pandas as pd
-from sklearn.base import BaseEstimator, TransformerMixin
-
-def build_transition_prob_matrix(df: pd.DataFrame):
-    df = df.dropna(subset=['eventName'])
-    events = df['eventName'].tolist()
-    labels = pd.Index(events).unique().tolist()
-    idx = {e:i for i,e in enumerate(labels)}
-    M = np.zeros((len(labels), len(labels)), dtype=float)
-    for a, b in zip(events, events[1:]):
-        M[idx[a], idx[b]] += 1
-    row_sums = M.sum(axis=1, keepdims=True)
-    with np.errstate(divide='ignore', invalid='ignore'):
-        P = np.divide(M, row_sums, where=row_sums>0)  # row-normalized
-    return P, labels
-
-# https://medium.com/data-science/time-series-data-markov-transition-matrices-7060771e362b
-from graphviz import Digraph
-import numpy as np
-import pandas as pd
-
-def _as_prob_df(matrix, labels=None):
-    """Return a square DataFrame with index=columns=labels."""
-    if isinstance(matrix, pd.DataFrame):
-        # Ensure square and aligned
-        assert (matrix.index == matrix.columns).all(), "Index/columns must match."
-        return matrix
-    matrix = np.asarray(matrix, dtype=float)
-    assert matrix.shape[0] == matrix.shape[1], "Matrix must be square."
-    if labels is None:
-        raise ValueError("labels are required when matrix is not a DataFrame")
-    assert len(labels) == matrix.shape[0], "labels length must match matrix size."
-    return pd.DataFrame(matrix, index=list(labels), columns=list(labels))
-
-def _df_to_edgelist(P: pd.DataFrame, threshold=0.0, round_digits=2):
-    """Build weighted edges > threshold."""
-    edges = []
-    for src in P.index:
-        for dst in P.columns:
-            w = float(P.loc[src, dst])
-            if w > threshold:
-                edges.append((str(src), str(dst), f"{w:.{round_digits}f}"))
-    return edges
-
-def render_graph(fname, matrix, ls_index=None, threshold=0.0, fmt="svg", view=False):
-    """
-    fname: output file stem (no extension)
-    matrix: NumPy array or pandas DataFrame of transition PROBABILITIES
-    ls_index: ordered labels (required if matrix is not a DataFrame)
-    threshold: hide edges with weight <= threshold
-    fmt: 'svg'|'png'|'pdf' etc.
-    view: open after rendering
-    """
-    P = _as_prob_df(matrix, labels=ls_index)
-    edges = _df_to_edgelist(P, threshold=threshold)
-
-    g = Digraph(format=fmt)
-    g.attr(rankdir="LR", size="30")
-    g.attr("node", shape="circle")
-
-    # ensure isolated nodes appear
-    for node in P.index:
-        g.node(str(node), width="1", height="1")
-
-    for src, dst, label in edges:
-        g.edge(src, dst, label=label)
-
-    g.render(fname, view=view, cleanup=True)
-    return g
-
-
-class TransitionProbMatrixTransformer(BaseEstimator, TransformerMixin):
-    def __init__(self, threshold=0.0):
-        self.threshold = threshold
-        self.P_ = None
-        self.labels_ = None
-
-    def fit(self, X: pd.DataFrame, y=None):
-        P, labels = build_transition_prob_matrix(X)
-        self.P_ = P
-        self.labels_ = labels
-        return self
-
-    def transform(self, X: pd.DataFrame = None):
-        return self.P_, self.labels_
-
-    def render(self, fname: str, fmt="svg", view=False):
-        if self.P_ is None or self.labels_ is None:
-            raise ValueError("Transformer has not been fitted yet.")
-        return render_graph(
-            fname,
-            self.P_,
-            ls_index=self.labels_,
-            threshold=self.threshold,
-            fmt=fmt,
-            view=view
-        )
-
-
-class SessionTransitionProbMatrixTransformer(BaseEstimator, TransformerMixin):
-    def __init__(self, threshold=0.0, session_col='sessionId'):
-        self.threshold = threshold
-        self.session_col = session_col
-        self.session_matrices_ = None
-
-    def fit(self, X: pd.DataFrame, y=None):
-        if self.session_col not in X.columns:
-            raise ValueError(f"Column '{self.session_col}' not found in DataFrame")
-
-        session_matrices = {}
-        for session_id, grp in X.groupby(self.session_col):
-            if len(grp) > 1:  # need at least 2 events for transitions
-                P, labels = build_transition_prob_matrix(grp)
-                session_matrices[session_id] = {'matrix': P, 'labels': labels}
-
-        self.session_matrices_ = session_matrices
-        return self
-
-    def transform(self, X: pd.DataFrame = None):
-        if self.session_matrices_ is None:
-            raise ValueError("Transformer has not been fitted yet.")
-        return pd.Series(self.session_matrices_)
-
-    def render_session(self, session_id: str, fname: str, fmt="svg", view=False):
-        if self.session_matrices_ is None:
-            raise ValueError("Transformer has not been fitted yet.")
-        if session_id not in self.session_matrices_:
-            raise ValueError(f"Session '{session_id}' not found in fitted data.")
-
-        sess_data = self.session_matrices_[session_id]
-        return render_graph(
-            fname,
-            sess_data['matrix'],
-            ls_index=sess_data['labels'],
-            threshold=self.threshold,
-            fmt=fmt,
-            view=view
-        )
-if __name__ == "__main__":
-    # Example usage
-    data = {
-        'eventName': [
-            'A', 'B', 'A', 'C', 'B', 'A', 'A', 'C', 'B', 'C',
-            'A', 'B', 'C', 'A', 'B', 'C', 'A', 'B', 'C', 'A'
-        ]
-    }
-    df = pd.DataFrame(data)
-
-    transformer = TransitionProbMatrixTransformer(threshold=0.1)
-    transformer.fit(df)
-    P, labels = transformer.transform(None)
-
-    print("Transition Probability Matrix:")
-    print(pd.DataFrame(P, index=labels, columns=labels))
-
-    # Render the graph
-    transformer.render("transition_graph", fmt="svg", view=False)

experiments/procesing/pipeline.py

@@ -1,90 +0,0 @@
-from sklearn.pipeline import Pipeline
-from sklearn.preprocessing import StandardScaler
-import pandas as pd
-import logging
-log = logging.getLogger(__name__)
-
-from extract import KafkaDataFetcher, ExperimentJoiner, EventTitleAugmenter, chunk_shared_data
-from mapping import SessionTransitionProbMatrixTransformer, render_graph
-from demand import DemandEstimator, ChunkInteractionsIntoSteps
-from elasticity import TemporalElasticityEstimator, aggregate_price_logs
-
-
-
-# elasticity pipeline components (not sklearn compatible, manual orchestration)
-def elasticity_pipeline(interactions_df, price_logs_df, window_size='30s', store_mode='hotel'):
-    """
-    Compute price elasticity from interaction and price data.
-
-    Args:
-        interactions_df: raw interaction data from demand_data_pipeline
-        price_logs_df: price log data from price_data_pipeline
-        window_size: time window for chunking
-        store_mode: 'hotel' or 'airline'
-
-    Returns:
-        df with [productId, elasticity, std_error, n_obs]
-    """
-    # step 1: chunk interactions into time windows
-    chunker = ChunkInteractionsIntoSteps(window_size=window_size, return_metadata=True)
-    interaction_chunks = chunker.transform(interactions_df)
-    log.info(f"Chunked interactions into {len(interaction_chunks)} windows of size {window_size}")
-
-    if not interaction_chunks:
-        return None
-
-    # step 2: compute demand per window
-    demand_estimator = DemandEstimator(store_mode=store_mode)
-    demand_chunks = []
-    for chunk in interaction_chunks:
-        demand_vector = demand_estimator.transform(chunk['data'])
-        demand_chunks.append({
-            'window_start': chunk['window_start'],
-            'window_end': chunk['window_end'],
-            'demand_vector': demand_vector # each has a full list of all products, even if demand is 0
-        })
-    # [q_chunk1, q_chunk2, ...]
-
-    # step 3: aggregate price logs into windows
-    price_chunks = aggregate_price_logs(price_logs_df, window_size=window_size)
-
-    # step 4: compute elasticity
-    elasticity_estimator = TemporalElasticityEstimator(method='point', min_observations=2)
-    elasticity_df = elasticity_estimator.transform(demand_chunks, price_chunks, store_mode=store_mode)
-
-    return elasticity_df
-
-
-# exposable pipelines
-interaction_pipeline = Pipeline([
-    ('kafka_fetch', KafkaDataFetcher(topic='user-interactions')),
-    ('experiment_join', ExperimentJoiner()),
-    ('event_augment', EventTitleAugmenter()),
-])
-
-price_data_pipeline = Pipeline([
-    ('kafka_fetch', KafkaDataFetcher(topic='price-logs')),
-])
-
-# interaction_data + price_data -> elasticity (demand)
-# elasticity -> pricing
-
-pricing_pipeline = Pipeline([
-    ('demand_estimation', DemandEstimator()),
-])
-if __name__ == "__main__":
-    # fetch both datasets
-    interaction_data = interaction_pipeline.fit_transform(None)
-    pricing_data = price_data_pipeline.fit_transform(None)
-    if interaction_data.empty or pricing_data.empty:
-        print("Insufficient data for elasticity computation"); exit(0)
-    # compute elasticity via unified pipeline
-    window_size = "30s"
-    elasticity_results = elasticity_pipeline(interaction_data, pricing_data, window_size=window_size)
-    elasticity_value_array = elasticity_results['elasticity'].values if elasticity_results is not None else np.array([])
-    print(elasticity_value_array)
-
-    if elasticity_results is not None and not elasticity_results.empty:
-        print(elasticity_results.to_string(index=False))
-    else:
-        print("\nInsufficient data for elasticity computation")

experiments/procesing/pricing.py

@@ -1,153 +0,0 @@
-r"""
-Our state space comes as:
-$Q_t in R^n$ - our demand at a time t
-$P_t in R^n$ - prices at time t
-$S_t$ some form of interaction session features
-
-This is a single sate which we map under
-
-$f: (Q, S, H) \to P_{t+1}$
-
-With:
-
-$H_t = \{Q_{t-k}, P_{t-k}, S_{t-k}\}$
-
-
-We can have f be literally anything, analytical or learned or rule based or an RL policy.
-
-Our goal is to mazimize the expected revenue:
-
-$E[R_T] = E[\sum_{t=1}^T P_t^T \dot Q_t]$
-
-subject to Q_t = g(P_t, S_t) : demand response to price (estimated via elasticity) and P_t ≥ C : prices above cost floor and additionally minimizing the following:
-
-$L_{agent} = R_{oracle} - R_{observed}
-
-where: R_oracle = revenue if we knew agent intentions (from recon session) and R_observed = revenue under current pricing policy f
-
-I would start be defning a pricing function interface and standardizing how to train that based on historical data and define how to make it behave for online training (if we do that)
-
-We also need to develop a solid benchmark with mapping revenue and full KPIs from session interactions to measure differences between different price learning methods
-"""
-
-from abc import ABC, abstractmethod
-from sklearn.base import BaseEstimator, TransformerMixin
-import numpy as np
-import pandas as pd
-import os
-from supabase import create_client, Client
-from pipeline import interaction_pipeline, price_data_pipeline, elasticity_pipeline
-
-SUPABASE_URL = os.getenv("NEXT_PUBLIC_SUPABASE_URL", "")
-SUPABASE_KEY = os.getenv("NEXT_PUBLIC_SUPABASE_ANON_KEY", "")
-supabase: Client = create_client(SUPABASE_URL, SUPABASE_KEY)
-
-def expected_revenue(prices: np.ndarray, demand: np.ndarray) -> float:
-    """Returns: expected revenue R_t = P_t^T * Q_t"""
-    return float(np.dot(prices, demand))
-
-class StateSpace:
-    def __init__(self,
-                 demand : np.ndarray, # at time t, only values (assuming aligned by productId order)
-                 prices : np.ndarray, # at time t, only values (assuming aligned by productId order)
-                 session_features : pd.DataFrame):
-        self.demand = demand  # Q_t
-        self.prices = prices  # P_t
-        self.session_features = session_features  # S_t
-        self.history = []  # H_t
-
-class PricingFunction(BaseEstimator, TransformerMixin, ABC):
-    def __init__(self):
-        pass
-
-    def fit(self, historical_data):
-        """
-        Train the pricing function based on historical data.
-        historical_data: list of StateSpace instances with known outcomes
-        """
-        raise NotImplementedError("Train method must be implemented by subclass.")
-
-    def transform(self, state_space) -> np.ndarray:
-        """
-        Predict the next prices given the current state space.
-        state_space: StateSpace instance
-        Returns: predicted prices P_{t+1}
-        """
-        raise NotImplementedError("Predict method must be implemented by subclass.")
-
-
-class SimpleLinearPricingFunction(PricingFunction):
-    def __init__(self, price_sensitivity: float = -0.1):
-        super().__init__()
-        self.price_sensitivity = price_sensitivity  # simple coefficient
-
-    def fit(self, historical_data):
-        return self
-
-    def transform(self, state_space: StateSpace) -> np.ndarray:
-        # Simple linear adjustment: P_{t+1} = P_t + sensitivity * Q_t
-        new_prices = state_space.prices + self.price_sensitivity * state_space.demand # this is not great
-        return np.maximum(new_prices, 0)
-
-# Example usage:
-if __name__ == "__main__":
-    store_mode = 'hotel'
-    interaction_data = interaction_pipeline.fit_transform(None)
-    price_data = price_data_pipeline.fit_transform(None)
-
-    elasticity_df = elasticity_pipeline(interaction_data, price_data, window_size="30s", store_mode=store_mode)
-
-    # fetch all products with base prices from database
-    products_resp = supabase.table(f'{store_mode}_products').select("id, metadata").execute()
-    products_df = pd.DataFrame(products_resp.data)
-
-    # extract base_price from metadata
-    products_df['base_price'] = products_df['metadata'].apply(lambda m: m.get('base_price', 0) if isinstance(m, dict) else 0)
-    products_df = products_df.rename(columns={'id': 'productId'})[['productId', 'base_price']]
-
-    # override with logged prices where available
-    if not price_data.empty:
-        if 'ts' in price_data.columns and not pd.api.types.is_datetime64_any_dtype(price_data['ts']):
-            price_data['ts'] = pd.to_datetime(price_data['ts'])
-
-        # get latest logged price per product
-        price_logs_agg = price_data.sort_values('ts').groupby('productId', as_index=False).last()
-
-        # merge: start with all products (base prices), override with logged prices
-        products_df = products_df.merge(
-            price_logs_agg[['productId', 'price']],
-            on='productId',
-            how='left'
-        )
-        products_df['final_price'] = products_df['price'].fillna(products_df['base_price'])
-    else:
-        products_df['final_price'] = products_df['base_price']
-
-    # merge with elasticity
-    if elasticity_df is not None and not elasticity_df.empty:
-        price_data_merged = products_df[['productId', 'final_price']].merge(
-            elasticity_df[['productId', 'elasticity']],
-            on='productId',
-            how='left'
-        ).fillna({'elasticity': 0.0})
-
-        prices = price_data_merged['final_price'].values
-        elasticities = price_data_merged['elasticity'].values
-    else:
-        prices = np.array([])
-        elasticities = np.array([])
-
-    print(elasticities)
-    print(prices)
-
-    state_space = StateSpace(
-        demand=elasticities,
-        prices=prices,
-        session_features=interaction_data
-    )
-
-    pricing_function = SimpleLinearPricingFunction(price_sensitivity=-0.05)
-    pricing_function.fit([])  # No training data for simple model
-    predicted_prices = pricing_function.transform(state_space)
-
-    print("Predicted Prices:", predicted_prices)

experiments/seed_products.py

@@ -1,125 +0,0 @@
-import random
-import json
-import os
-import logging
-from dotenv import load_dotenv
-from supabase import create_client, Client
-from tqdm import tqdm
-
-load_dotenv()
-
-logging.basicConfig(level=logging.INFO, format='%(levelname)s: %(message)s')
-log = logging.getLogger(__name__)
-
-SUPABASE_URL = os.getenv("NEXT_PUBLIC_SUPABASE_URL")
-SUPABASE_SERVICE_KEY = os.getenv("SUPABASE_SERVICE_ROLE_KEY")
-
-if not SUPABASE_SERVICE_KEY:
-    log.error("SUPABASE_SERVICE_ROLE_KEY not found in environment")
-    raise ValueError("Missing SUPABASE_SERVICE_ROLE_KEY - required for admin operations")
-
-supabase: Client = create_client(SUPABASE_URL, SUPABASE_SERVICE_KEY)
-
-DAYS = 14
-
-# hotel room configurations
-ROOMS = {
-    "Presidential Suite": {'amenities': ['ocean_view', 'balcony', 'jacuzzi', 'butler_service', 'premium_minibar'], 'total': 1, 'image_url': "", "base_price": 450, 'name': 'Presidential Suite', 'refundable': True, 'max_occupancy': 4},
-    "Executive Suite": {'amenities': ['city_view', 'balcony', 'workspace', 'lounge_access'], 'total': 2, 'image_url': "", "base_price": 280, 'name': 'Executive Suite', 'refundable': True, 'max_occupancy': 3},
-    "Junior Suite": {'amenities': ['garden_view', 'mini_fridge', 'coffee_maker'], 'total': 5, 'image_url': "", "base_price": 180, 'name': 'Junior Suite', 'refundable': True, 'max_occupancy': 2},
-    "Deluxe Room": {'amenities': ['city_view', 'work_desk', 'coffee_maker'], 'total': 8, 'image_url': "", "base_price": 140, 'name': 'Deluxe Room', 'refundable': False, 'max_occupancy': 2},
-    "Superior Room": {'amenities': ['wifi', 'tv', 'safe'], 'total': 12, 'image_url': "", "base_price": 110, 'name': 'Superior Room', 'refundable': False, 'max_occupancy': 2},
-    "Standard Room": {'amenities': ['wifi', 'tv'], 'total': 20, 'image_url': "", "base_price": 85, 'name': 'Standard Room', 'refundable': False, 'max_occupancy': 2},
-}
-
-# flight configurations
-FLIGHTS = {
-    "JFK-LAX-Economy": {'departure': {'time': '08:00', 'airport': 'JFK'}, 'arrival': {'time': '11:30', 'airport': 'LAX'}, 'duration': '5h 30m', 'stops': 0, 'cabin_class': 'economy', 'fare_rule': 'standard', 'refundable': False, 'total': 180, 'base_price': 250},
-    "JFK-LAX-Business": {'departure': {'time': '08:00', 'airport': 'JFK'}, 'arrival': {'time': '11:30', 'airport': 'LAX'}, 'duration': '5h 30m', 'stops': 0, 'cabin_class': 'business', 'fare_rule': 'flexible', 'refundable': True, 'total': 30, 'base_price': 850},
-    "ORD-MIA-Economy": {'departure': {'time': '14:15', 'airport': 'ORD'}, 'arrival': {'time': '18:45', 'airport': 'MIA'}, 'duration': '3h 30m', 'stops': 0, 'cabin_class': 'economy', 'fare_rule': 'basic', 'refundable': False, 'total': 200, 'base_price': 180},
-    "SFO-SEA-Premium": {'departure': {'time': '06:30', 'airport': 'SFO'}, 'arrival': {'time': '08:45', 'airport': 'SEA'}, 'duration': '2h 15m', 'stops': 0, 'cabin_class': 'premium', 'fare_rule': 'standard', 'refundable': False, 'total': 60, 'base_price': 420},
-    "ATL-DFW-First": {'departure': {'time': '16:00', 'airport': 'ATL'}, 'arrival': {'time': '17:30', 'airport': 'DFW'}, 'duration': '2h 30m', 'stops': 0, 'cabin_class': 'first', 'fare_rule': 'flexible', 'refundable': True, 'total': 12, 'base_price': 1600},
-    "LAX-SFO-Economy": {'departure': {'time': '10:00', 'airport': 'LAX'}, 'arrival': {'time': '11:30', 'airport': 'SFO'}, 'duration': '1h 30m', 'stops': 0, 'cabin_class': 'economy', 'fare_rule': 'standard', 'refundable': False, 'total': 150, 'base_price': 120},
-    "MIA-ATL-Premium": {'departure': {'time': '19:00', 'airport': 'MIA'}, 'arrival': {'time': '20:45', 'airport': 'ATL'}, 'duration': '1h 45m', 'stops': 0, 'cabin_class': 'premium', 'fare_rule': 'standard', 'refundable': True, 'total': 50, 'base_price': 380},
-    "DFW-ORD-Economy": {'departure': {'time': '07:30', 'airport': 'DFW'}, 'arrival': {'time': '10:15', 'airport': 'ORD'}, 'duration': '2h 45m', 'stops': 0, 'cabin_class': 'economy', 'fare_rule': 'basic', 'refundable': False, 'total': 190, 'base_price': 160},
-    "SEA-LAX-Business": {'departure': {'time': '13:00', 'airport': 'SEA'}, 'arrival': {'time': '15:30', 'airport': 'LAX'}, 'duration': '2h 30m', 'stops': 0, 'cabin_class': 'business', 'fare_rule': 'flexible', 'refundable': True, 'total': 40, 'base_price': 720},
-    "LAX-JFK-First": {'departure': {'time': '18:00', 'airport': 'LAX'}, 'arrival': {'time': '02:15', 'airport': 'JFK'}, 'duration': '5h 15m', 'stops': 0, 'cabin_class': 'first', 'fare_rule': 'flexible', 'refundable': True, 'total': 16, 'base_price': 1850},
-}
-
-def gen_hotel_products():
-    """generate hotel room products for next DAYS days"""
-    data = []
-    for day in range(DAYS):
-        for room_type, rdata in ROOMS.items():
-            data.append({
-                'room_type': room_type,
-                'date_index': day + 1,
-                'metadata': rdata,
-                'availability': random.randint(0, rdata['total'])
-            })
-    return data
-
-def gen_airline_products():
-    """generate flight products for next DAYS days"""
-    data = []
-    for day in range(DAYS):
-        for flight_type, fdata in FLIGHTS.items():
-            data.append({
-                'flight_type': flight_type,
-                'date_index': day + 1,
-                'metadata': fdata,
-                'availability': random.randint(0, fdata['total'])
-            })
-    return data
-
-def clear_table(table_name: str):
-    """clear all records from a table"""
-    try:
-        resp = supabase.table(table_name).select('id').execute()
-        if resp.data:
-            ids = [row['id'] for row in resp.data]
-            chunk_size = 100
-            for i in tqdm(range(0, len(ids), chunk_size), desc=f"Clearing {table_name}", unit="chunk"):
-                chunk = ids[i:i+chunk_size]
-                supabase.table(table_name).delete().in_('id', chunk).execute()
-            log.info(f"Deleted {len(ids)} records from {table_name}")
-        else:
-            log.info(f"{table_name} already empty")
-    except Exception as e:
-        log.error(f"Failed to clear {table_name}: {e}")
-        raise
-
-def seed_table(table_name: str, data: list[dict]):
-    """insert records into a table"""
-    try:
-        chunk_size = 100
-        total = len(data)
-        for i in tqdm(range(0, total, chunk_size), desc=f"Seeding {table_name}", unit="chunk"):
-            chunk = data[i:i+chunk_size]
-            supabase.table(table_name).insert(chunk).execute()
-        log.info(f"Inserted {total} records into {table_name}")
-    except Exception as e:
-        log.error(f"Failed to seed {table_name}: {e}")
-        raise
-
-def main():
-
-    log.info("Generating hotel products...")
-    hotel_products = gen_hotel_products()
-    log.info(f"Generated {len(hotel_products)} hotel products")
-
-    log.info("Generating airline products...")
-    airline_products = gen_airline_products()
-    log.info(f"Generated {len(airline_products)} airline products\n")
-
-    log.info("Clearing existing products...")
-    clear_table('hotel_products')
-    clear_table('airline_products')
-
-    log.info("Seeding products...")
-    seed_table('hotel_products', hotel_products)
-    seed_table('airline_products', airline_products)
-
-
-if __name__ == "__main__":
-    main()

paper/concat_code.sh

@@ -16,15 +16,11 @@ mkdir -p "$(dirname "$OUTPUT_FILE")"
 add_file() {
     local filepath="$1"
     local relpath="${filepath#$PROJECT_ROOT/}"
-    local escaped_path="${relpath//_/\\_}"
 
     # Add section header and code listing (no language-specific highlighting)
-    echo "\\subsection{${escaped_path}}" >> "$OUTPUT_FILE"
+    echo "\\subsection{${relpath}}" >> "$OUTPUT_FILE"
-    echo "\\begin{lstlisting}[caption={${escaped_path}}]" >> "$OUTPUT_FILE"
+    echo "\\begin{lstlisting}[caption={${relpath}}]" >> "$OUTPUT_FILE"
-    # Convert to ASCII: transliterate what's possible, drop the rest
+    cat "$filepath" >> "$OUTPUT_FILE"
-    # LC_ALL=C forces ASCII locale for consistent behavior across environments
-    LC_ALL=C iconv -f UTF-8 -t ASCII//TRANSLIT//IGNORE "$filepath" 2>/dev/null >> "$OUTPUT_FILE" || \
-        LC_ALL=C tr -cd '\11\12\15\40-\176' < "$filepath" >> "$OUTPUT_FILE"
     echo "" >> "$OUTPUT_FILE"
     echo "\\end{lstlisting}" >> "$OUTPUT_FILE"
     echo "" >> "$OUTPUT_FILE"

pytest.ini

@@ -1,7 +0,0 @@
-[pytest]
-testpaths = experiments
-python_files = test*.py
-python_classes = Test*
-python_functions = test_*
-asyncio_mode = auto
-asyncio_default_fixture_loop_scope = function

requirements.txt

@@ -5,9 +5,3 @@ jupyter
 ipykernel
 matplotlib
 graphviz
-browser-use
-pytest
-pytest-asyncio
-uv
-scikit-learn
-supabase

web/package-lock.json

@@ -8,8 +8,6 @@
       "name": "web",
       "version": "0.1.0",
       "dependencies": {
-        "@supabase/ssr": "^0.7.0",
-        "@supabase/supabase-js": "^2.81.1",
         "next": "16.0.0",
         "react": "19.2.0",
         "react-dom": "19.2.0",
@@ -659,97 +657,6 @@
         "node": ">= 10"
       }
     },
-    "node_modules/@supabase/auth-js": {
-      "version": "2.81.1",
-      "resolved": "https://registry.npmjs.org/@supabase/auth-js/-/auth-js-2.81.1.tgz",
-      "integrity": "sha512-K20GgiSm9XeRLypxYHa5UCnybWc2K0ok0HLbqCej/wRxDpJxToXNOwKt0l7nO8xI1CyQ+GrNfU6bcRzvdbeopQ==",
-      "license": "MIT",
-      "dependencies": {
-        "tslib": "2.8.1"
-      },
-      "engines": {
-        "node": ">=20.0.0"
-      }
-    },
-    "node_modules/@supabase/functions-js": {
-      "version": "2.81.1",
-      "resolved": "https://registry.npmjs.org/@supabase/functions-js/-/functions-js-2.81.1.tgz",
-      "integrity": "sha512-sYgSO3mlgL0NvBFS3oRfCK4OgKGQwuOWJLzfPyWg0k8MSxSFSDeN/JtrDJD5GQrxskP6c58+vUzruBJQY78AqQ==",
-      "license": "MIT",
-      "dependencies": {
-        "tslib": "2.8.1"
-      },
-      "engines": {
-        "node": ">=20.0.0"
-      }
-    },
-    "node_modules/@supabase/postgrest-js": {
-      "version": "2.81.1",
-      "resolved": "https://registry.npmjs.org/@supabase/postgrest-js/-/postgrest-js-2.81.1.tgz",
-      "integrity": "sha512-DePpUTAPXJyBurQ4IH2e42DWoA+/Qmr5mbgY4B6ZcxVc/ZUKfTVK31BYIFBATMApWraFc8Q/Sg+yxtfJ3E0wSg==",
-      "license": "MIT",
-      "dependencies": {
-        "tslib": "2.8.1"
-      },
-      "engines": {
-        "node": ">=20.0.0"
-      }
-    },
-    "node_modules/@supabase/realtime-js": {
-      "version": "2.81.1",
-      "resolved": "https://registry.npmjs.org/@supabase/realtime-js/-/realtime-js-2.81.1.tgz",
-      "integrity": "sha512-ViQ+Kxm8BuUP/TcYmH9tViqYKGSD1LBjdqx2p5J+47RES6c+0QHedM0PPAjthMdAHWyb2LGATE9PD2++2rO/tw==",
-      "license": "MIT",
-      "dependencies": {
-        "@types/phoenix": "^1.6.6",
-        "@types/ws": "^8.18.1",
-        "tslib": "2.8.1",
-        "ws": "^8.18.2"
-      },
-      "engines": {
-        "node": ">=20.0.0"
-      }
-    },
-    "node_modules/@supabase/ssr": {
-      "version": "0.7.0",
-      "resolved": "https://registry.npmjs.org/@supabase/ssr/-/ssr-0.7.0.tgz",
-      "integrity": "sha512-G65t5EhLSJ5c8hTCcXifSL9Q/ZRXvqgXeNo+d3P56f4U1IxwTqjB64UfmfixvmMcjuxnq2yGqEWVJqUcO+AzAg==",
-      "license": "MIT",
-      "dependencies": {
-        "cookie": "^1.0.2"
-      },
-      "peerDependencies": {
-        "@supabase/supabase-js": "^2.43.4"
-      }
-    },
-    "node_modules/@supabase/storage-js": {
-      "version": "2.81.1",
-      "resolved": "https://registry.npmjs.org/@supabase/storage-js/-/storage-js-2.81.1.tgz",
-      "integrity": "sha512-UNmYtjnZnhouqnbEMC1D5YJot7y0rIaZx7FG2Fv8S3hhNjcGVvO+h9We/tggi273BFkiahQPS/uRsapo1cSapw==",
-      "license": "MIT",
-      "dependencies": {
-        "tslib": "2.8.1"
-      },
-      "engines": {
-        "node": ">=20.0.0"
-      }
-    },
-    "node_modules/@supabase/supabase-js": {
-      "version": "2.81.1",
-      "resolved": "https://registry.npmjs.org/@supabase/supabase-js/-/supabase-js-2.81.1.tgz",
-      "integrity": "sha512-KSdY7xb2L0DlLmlYzIOghdw/na4gsMcqJ8u4sD6tOQJr+x3hLujU9s4R8N3ob84/1bkvpvlU5PYKa1ae+OICnw==",
-      "license": "MIT",
-      "dependencies": {
-        "@supabase/auth-js": "2.81.1",
-        "@supabase/functions-js": "2.81.1",
-        "@supabase/postgrest-js": "2.81.1",
-        "@supabase/realtime-js": "2.81.1",
-        "@supabase/storage-js": "2.81.1"
-      },
-      "engines": {
-        "node": ">=20.0.0"
-      }
-    },
     "node_modules/@swc/helpers": {
       "version": "0.5.15",
       "resolved": "https://registry.npmjs.org/@swc/helpers/-/helpers-0.5.15.tgz",
@@ -1034,17 +941,12 @@
       "version": "20.19.23",
       "resolved": "https://registry.npmjs.org/@types/node/-/node-20.19.23.tgz",
       "integrity": "sha512-yIdlVVVHXpmqRhtyovZAcSy0MiPcYWGkoO4CGe/+jpP0hmNuihm4XhHbADpK++MsiLHP5MVlv+bcgdF99kSiFQ==",
+      "dev": true,
       "license": "MIT",
       "dependencies": {
         "undici-types": "~6.21.0"
       }
     },
-    "node_modules/@types/phoenix": {
-      "version": "1.6.6",
-      "resolved": "https://registry.npmjs.org/@types/phoenix/-/phoenix-1.6.6.tgz",
-      "integrity": "sha512-PIzZZlEppgrpoT2QgbnDU+MMzuR6BbCjllj0bM70lWoejMeNJAxCchxnv7J3XFkI8MpygtRpzXrIlmWUBclP5A==",
-      "license": "MIT"
-    },
     "node_modules/@types/react": {
       "version": "19.2.2",
       "resolved": "https://registry.npmjs.org/@types/react/-/react-19.2.2.tgz",
@@ -1065,15 +967,6 @@
         "@types/react": "^19.2.0"
       }
     },
-    "node_modules/@types/ws": {
-      "version": "8.18.1",
-      "resolved": "https://registry.npmjs.org/@types/ws/-/ws-8.18.1.tgz",
-      "integrity": "sha512-ThVF6DCVhA8kUGy+aazFQ4kXQ7E1Ty7A3ypFOe0IcJV8O/M511G99AW24irKrW56Wt44yG9+ij8FaqoBGkuBXg==",
-      "license": "MIT",
-      "dependencies": {
-        "@types/node": "*"
-      }
-    },
     "node_modules/caniuse-lite": {
       "version": "1.0.30001751",
       "resolved": "https://registry.npmjs.org/caniuse-lite/-/caniuse-lite-1.0.30001751.tgz",
@@ -1100,15 +993,6 @@
       "integrity": "sha512-IV3Ou0jSMzZrd3pZ48nLkT9DA7Ag1pnPzaiQhpW7c3RbcqqzvzzVu+L8gfqMp/8IM2MQtSiqaCxrrcfu8I8rMA==",
       "license": "MIT"
     },
-    "node_modules/cookie": {
-      "version": "1.0.2",
-      "resolved": "https://registry.npmjs.org/cookie/-/cookie-1.0.2.tgz",
-      "integrity": "sha512-9Kr/j4O16ISv8zBBhJoi4bXOYNTkFLOqSL3UDB0njXxCXNezjeyVrJyGOWtgfs/q2km1gwBcfH8q1yEGoMYunA==",
-      "license": "MIT",
-      "engines": {
-        "node": ">=18"
-      }
-    },
     "node_modules/csstype": {
       "version": "3.1.3",
       "resolved": "https://registry.npmjs.org/csstype/-/csstype-3.1.3.tgz",
@@ -1721,29 +1605,9 @@
       "version": "6.21.0",
       "resolved": "https://registry.npmjs.org/undici-types/-/undici-types-6.21.0.tgz",
       "integrity": "sha512-iwDZqg0QAGrg9Rav5H4n0M64c3mkR59cJ6wQp+7C4nI0gsmExaedaYLNO44eT4AtBBwjbTiGPMlt2Md0T9H9JQ==",
+      "dev": true,
       "license": "MIT"
     },
-    "node_modules/ws": {
-      "version": "8.18.3",
-      "resolved": "https://registry.npmjs.org/ws/-/ws-8.18.3.tgz",
-      "integrity": "sha512-PEIGCY5tSlUt50cqyMXfCzX+oOPqN0vuGqWzbcJ2xvnkzkq46oOpz7dQaTDBdfICb4N14+GARUDw2XV2N4tvzg==",
-      "license": "MIT",
-      "engines": {
-        "node": ">=10.0.0"
-      },
-      "peerDependencies": {
-        "bufferutil": "^4.0.1",
-        "utf-8-validate": ">=5.0.2"
-      },
-      "peerDependenciesMeta": {
-        "bufferutil": {
-          "optional": true
-        },
-        "utf-8-validate": {
-          "optional": true
-        }
-      }
-    },
     "node_modules/zod": {
       "version": "4.1.12",
       "resolved": "https://registry.npmjs.org/zod/-/zod-4.1.12.tgz",

web/package.json

@@ -8,8 +8,6 @@
     "start": "next start"
   },
   "dependencies": {
-    "@supabase/ssr": "^0.7.0",
-    "@supabase/supabase-js": "^2.81.1",
     "next": "16.0.0",
     "react": "19.2.0",
     "react-dom": "19.2.0",

web/src/app/admin/experiments/page.tsx

@@ -1,26 +1,20 @@
 'use client';
 
 import { useEffect, useState } from 'react';
-import { TaskManager } from '@/components/admin/TaskManager';
+import { useSession } from '@/hooks/useSession';
-import { ExperimentForm } from '@/components/admin/ExperimentForm';
 
 type Experiment = {
   id: string;
-  subject_name: string;
+  status: 'active' | 'stopped';
-  xp_human_only: boolean;
+  sessionIds: string[];
-  xp_market_mode: string;
+  createdAt: number;
-  created_at: string;
-  task?: {
-    id: string;
-    task_name: string;
-  };
 };
 
 export default function ExperimentsAdmin() {
+  const { sessionId, isLoading: sessionLoading } = useSession();
   const [exps, setExps] = useState<Experiment[]>([]);
-  const [selectedTaskId, setSelectedTaskId] = useState<string | undefined>();
+  const [loading, setLoading] = useState(false);
   const [error, setError] = useState<string | null>(null);
-  const [showForm, setShowForm] = useState(false);
 
   const fetchExps = async () => {
     try {
@@ -37,23 +31,87 @@ export default function ExperimentsAdmin() {
     fetchExps();
   }, []);
 
-  const handleExperimentCreated = async () => {
+  const handleStart = async () => {
-    setShowForm(false);
+    if (!sessionId) {
-    setSelectedTaskId(undefined);
+      setError('no session available');
-    await fetchExps();
+      return;
+    }
+
+    setLoading(true);
+    setError(null);
+
+    try {
+      const res = await fetch('/api/admin/experiments/start', {
+        method: 'POST',
+        headers: { 'Content-Type': 'application/json' },
+        body: JSON.stringify({ sessionId }),
+      });
+
+      if (!res.ok) {
+        const data = await res.json();
+        throw new Error(data.error || 'start failed');
+      }
+
+      await fetchExps(); // refresh list
+    } catch (err: any) {
+      setError(err.message);
+    } finally {
+      setLoading(false);
+    }
   };
 
+  const handleStop = async (expId: string) => {
+    setLoading(true);
+    setError(null);
+
+    try {
+      const res = await fetch('/api/admin/experiments/stop', {
+        method: 'POST',
+        headers: { 'Content-Type': 'application/json' },
+        body: JSON.stringify({ experimentId: expId }),
+      });
+
+      if (!res.ok) {
+        const data = await res.json();
+        throw new Error(data.error || 'stop failed');
+      }
+
+      await fetchExps(); // refresh list
+    } catch (err: any) {
+      setError(err.message);
+    } finally {
+      setLoading(false);
+    }
+  };
+
+  if (sessionLoading) {
+    return (
+      <div className="flex min-h-screen items-center justify-center bg-zinc-50 dark:bg-black">
+        <p className="text-zinc-600 dark:text-zinc-400">loading session...</p>
+      </div>
+    );
+  }
+
   return (
     <div className="min-h-screen bg-zinc-50 px-6 py-12 dark:bg-black">
-      <div className="mx-auto max-w-7xl">
+      <div className="mx-auto max-w-5xl">
-        <div className="mb-8">
+        <div className="mb-8 flex items-center justify-between">
+          <div>
             <h1 className="text-3xl font-semibold tracking-tight text-black dark:text-zinc-50">
-            Experiment Management
+              Experiments
             </h1>
             <p className="mt-2 text-sm text-zinc-600 dark:text-zinc-400">
-            configure tasks and run experiments
+              current session: {sessionId || 'none'}
             </p>
           </div>
+          <button
+            onClick={handleStart}
+            disabled={loading || !sessionId}
+            className="rounded-lg bg-black px-4 py-2 text-sm font-medium text-white transition-colors hover:bg-zinc-800 disabled:opacity-50 dark:bg-zinc-50 dark:text-black dark:hover:bg-zinc-200"
+          >
+            {loading ? 'starting...' : 'start experiment'}
+          </button>
+        </div>
 
         {error && (
           <div className="mb-4 rounded-lg bg-red-50 p-4 text-sm text-red-800 dark:bg-red-950 dark:text-red-200">
@@ -61,57 +119,24 @@ export default function ExperimentsAdmin() {
           </div>
         )}
 
-        <div className="grid grid-cols-1 gap-6 lg:grid-cols-3">
-          {/* left column: task manager */}
-          <div className="lg:col-span-1">
-            <TaskManager
-              onTaskSelect={setSelectedTaskId}
-              selectedTaskId={selectedTaskId}
-            />
-          </div>
-
-          {/* right column: experiment form + list */}
-          <div className="space-y-6 lg:col-span-2">
-            <div className="flex items-center justify-between">
-              <h2 className="text-lg font-semibold text-zinc-900 dark:text-zinc-100">
-                Experiments
-              </h2>
-              <button
-                onClick={() => setShowForm(!showForm)}
-                className="rounded-lg bg-black px-4 py-2 text-sm font-medium text-white transition-colors hover:bg-zinc-800 dark:bg-zinc-50 dark:text-black dark:hover:bg-zinc-200"
-              >
-                {showForm ? 'hide form' : 'new experiment'}
-              </button>
-            </div>
-
-            {showForm && (
-              <ExperimentForm
-                selectedTaskId={selectedTaskId}
-                onSuccess={handleExperimentCreated}
-              />
-            )}
-
         <div className="overflow-hidden rounded-lg border border-zinc-200 bg-white dark:border-zinc-800 dark:bg-zinc-950">
           <table className="w-full text-left text-sm">
             <thead className="border-b border-zinc-200 bg-zinc-50 dark:border-zinc-800 dark:bg-zinc-900">
               <tr>
-                    <th className="px-4 py-3 font-medium text-zinc-900 dark:text-zinc-100">
+                <th className="px-6 py-3 font-medium text-zinc-900 dark:text-zinc-100">
-                      subject
+                  experiment id
                 </th>
-                    <th className="px-4 py-3 font-medium text-zinc-900 dark:text-zinc-100">
+                <th className="px-6 py-3 font-medium text-zinc-900 dark:text-zinc-100">
-                      mode
+                  status
                 </th>
-                    <th className="px-4 py-3 font-medium text-zinc-900 dark:text-zinc-100">
+                <th className="px-6 py-3 font-medium text-zinc-900 dark:text-zinc-100">
-                      human
+                  session count
                 </th>
-                    <th className="px-4 py-3 font-medium text-zinc-900 dark:text-zinc-100">
+                <th className="px-6 py-3 font-medium text-zinc-900 dark:text-zinc-100">
-                      task
-                    </th>
-                    <th className="px-4 py-3 font-medium text-zinc-900 dark:text-zinc-100">
                   created
                 </th>
-                    <th className="px-4 py-3 font-medium text-zinc-900 dark:text-zinc-100">
+                <th className="px-6 py-3 font-medium text-zinc-900 dark:text-zinc-100">
-                      link
+                  action
                 </th>
               </tr>
             </thead>
@@ -119,67 +144,56 @@ export default function ExperimentsAdmin() {
               {exps.length === 0 ? (
                 <tr>
                   <td
-                        colSpan={6}
+                    colSpan={5}
-                        className="px-4 py-8 text-center text-zinc-500 dark:text-zinc-400"
+                    className="px-6 py-8 text-center text-zinc-500 dark:text-zinc-400"
                   >
                     no experiments yet
                   </td>
                 </tr>
               ) : (
-                    exps.map((exp) => {
+                exps.map((exp) => (
-                      const baseUrl = exp.xp_market_mode === 'airline'
-                        ? 'https://phantom-airline.vercel.app'
-                        : 'https://phantom-hotel.vercel.app';
-                      const link = `${baseUrl}/start-task?uuid=${exp.id}`;
-
-                      return (
                   <tr
                     key={exp.id}
                     className="hover:bg-zinc-50 dark:hover:bg-zinc-900"
                   >
-                          <td className="px-4 py-3 font-medium text-zinc-900 dark:text-zinc-100">
+                    <td className="px-6 py-4 font-mono text-xs text-zinc-700 dark:text-zinc-300">
-                            {exp.subject_name}
+                      {exp.id.slice(0, 8)}...
                     </td>
-                          <td className="px-4 py-3">
+                    <td className="px-6 py-4">
-                            <span className="inline-block rounded-full bg-zinc-100 px-2 py-1 text-xs font-medium text-zinc-800 dark:bg-zinc-800 dark:text-zinc-200">
+                      <span
-                              {exp.xp_market_mode || 'none'}
+                        className={`inline-block rounded-full px-2 py-1 text-xs font-medium ${
+                          exp.status === 'active'
+                            ? 'bg-green-100 text-green-800 dark:bg-green-950 dark:text-green-200'
+                            : 'bg-zinc-100 text-zinc-800 dark:bg-zinc-800 dark:text-zinc-200'
+                        }`}
+                      >
+                        {exp.status}
                       </span>
                     </td>
-                          <td className="px-4 py-3">
+                    <td className="px-6 py-4 text-zinc-700 dark:text-zinc-300">
-                            {exp.xp_human_only ? (
+                      {exp.sessionIds.length}
-                              <span className="text-xs text-green-600 dark:text-green-400">
+                    </td>
-                                yes
+                    <td className="px-6 py-4 text-zinc-700 dark:text-zinc-300">
-                              </span>
+                      {new Date(exp.createdAt).toLocaleString()}
-                            ) : (
+                    </td>
-                              <span className="text-xs text-zinc-500">no</span>
+                    <td className="px-6 py-4">
+                      {exp.status === 'active' && (
+                        <button
+                          onClick={() => handleStop(exp.id)}
+                          disabled={loading}
+                          className="text-sm font-medium text-red-600 hover:text-red-700 disabled:opacity-50 dark:text-red-400 dark:hover:text-red-300"
+                        >
+                          stop
+                        </button>
                       )}
                     </td>
-                          <td className="px-4 py-3 text-xs text-zinc-600 dark:text-zinc-400">
-                            {exp.task ? exp.task.task_name : '—'}
-                          </td>
-                          <td className="px-4 py-3 text-xs text-zinc-600 dark:text-zinc-400">
-                            {new Date(exp.created_at).toLocaleDateString()}
-                          </td>
-                          <td className="px-4 py-3">
-                            <button
-                              onClick={() => {
-                                navigator.clipboard.writeText(link);
-                              }}
-                              className="text-xs font-medium text-zinc-900 hover:text-zinc-600 dark:text-zinc-100 dark:hover:text-zinc-400"
-                            >
-                              copy link
-                            </button>
-                          </td>
                   </tr>
-                      );
+                ))
-                    })
               )}
             </tbody>
           </table>
         </div>
       </div>
     </div>
-      </div>
-    </div>
   );
 }

web/src/app/airline/products/[id]/page.tsx

@@ -1,106 +0,0 @@
-'use client';
-
-import { useState, useEffect } from 'react';
-import { useParams, useRouter } from 'next/navigation';
-import { Navigation } from '@/components/ui';
-import { useCart } from '@/contexts/CartContext';
-import AirlineDetails from '@/components/feats/airline/AirlineDetails';
-import { transformProduct, type Flight, type AirlineProduct } from '@/lib/airline-utils';
-import type { EventName } from '@/lib/events';
-
-const dispatchInteraction = (eventName: EventName, productId?: string, metadata?: Record<string, unknown>) => {
-    const e = new CustomEvent('definedInteraction', {
-        detail: { eventName, productId, metadata },
-    });
-    document.dispatchEvent(e);
-};
-
-export default function AirlineProductPage() {
-    const params = useParams();
-    const router = useRouter();
-    const { addItem } = useCart();
-    const [product, setProduct] = useState<Flight | null>(null);
-    const [loading, setLoading] = useState(true);
-    const [error, setError] = useState<string | null>(null);
-    const [added, setAdded] = useState(false);
-
-    const productId = params.id as string;
-
-    useEffect(() => {
-        const fetchProduct = async () => {
-            try {
-                const res = await fetch(`/api/products/${productId}`);
-                if (!res.ok) throw new Error(`Failed to fetch: ${res.status}`);
-                const json = await res.json();
-                const transformed = transformProduct(json.data as AirlineProduct);
-                setProduct(transformed);
-
-                // fire learn_more_about_item event when product loads
-                dispatchInteraction('learn_more_about_item', productId, {
-                    type: 'airline',
-                    dateIndex: transformed.dateIndex,
-                    flightType: transformed.flightType,
-                });
-            } catch (e) {
-                setError(e instanceof Error ? e.message : 'Failed to load product');
-                console.error('[FETCH_FLIGHT_ERROR]', e);
-            } finally {
-                setLoading(false);
-            }
-        };
-        fetchProduct();
-    }, [productId]);
-
-    const handleAddToCart = () => {
-        if (!product) return;
-
-        addItem({
-            id: productId,
-            type: 'airline',
-            name: product.flightType,
-            price: product.basePrice,
-            metadata: {
-                departure: product.departure,
-                arrival: product.arrival,
-                duration: product.duration,
-                cabinClass: product.cabinClass,
-            },
-            dateIndex: product.dateIndex,
-        });
-
-        dispatchInteraction('add_item_to_cart', productId, {
-            type: 'airline',
-            price: product.basePrice,
-        });
-
-        setAdded(true);
-        setTimeout(() => setAdded(false), 2000);
-    };
-
-    return (
-        <>
-            <Navigation />
-            <main className="max-w-4xl mx-auto px-4 py-8">
-                {loading && <div className="text-center py-8">Loading flight details...</div>}
-                {error && <div className="text-red-500 text-center py-8">{error}</div>}
-
-                {!loading && !error && product && (
-                    <>
-                        <button
-                            onClick={() => router.back()}
-                            className="mt-6 text-blue-600 hover:underline"
-                        >
-                            ← Back to flights
-                        </button>
-                        <AirlineDetails
-                            product={product}
-                            onAddToCart={handleAddToCart}
-                            addedToCart={added}
-                        />
-
-                    </>
-                )}
-            </main>
-        </>
-    );
-}

web/src/app/airline/products/page.tsx

@@ -1,69 +1,73 @@
 'use client';
 
-import { useState, useEffect, Suspense } from 'react';
-import { useSearchParams } from 'next/navigation';
 import { Navigation } from '@/components/ui';
 import AirlineCard from '@/components/feats/airline/AirlineCard';
-import { transformProduct, type Flight, type AirlineProduct } from '@/lib/airline-utils';
 
-function FlightsList() {
+type CabinClass = 'economy' | 'premium' | 'business' | 'first';
-  const searchParams = useSearchParams();
+type FareRule = 'flexible' | 'standard' | 'basic';
-  const [flights, setFlights] = useState<Flight[]>([]);
-  const [loading, setLoading] = useState(true);
-  const [error, setError] = useState<string | null>(null);
 
-  useEffect(() => {
+interface Flight {
-    const fetchFlights = async () => {
+  id: string;
-      try {
+  departure: { time: string; airport: string };
-        const url = new URL('/api/products', window.location.origin);
+  arrival: { time: string; airport: string };
-        url.searchParams.set('type', 'airline');
+  duration: string;
+  stops: number;
+  cabinClass: CabinClass;
+  fareRule: FareRule;
+  refundable: boolean;
+  basePrice: number;
+}
 
-        // forward all relevant search params to the API
+const genRandomFlights = (): Flight[] => {
-        const params = ['dateIndex', 'origin', 'destination', 'tripType', 'adults', 'children', 'infants'];
+  const airports = ['JFK', 'LAX', 'ORD', 'ATL', 'DFW', 'SFO', 'SEA', 'MIA'];
-        params.forEach(param => {
+  const cabins: CabinClass[] = ['economy', 'premium', 'business', 'first'];
-          const val = searchParams.get(param);
+  const fareRules: FareRule[] = ['flexible', 'standard', 'basic'];
-          if (val) url.searchParams.set(param, val);
-        });
 
-        const res = await fetch(url.toString());
+  return Array.from({ length: 12 }, (_, i) => {
-        if (!res.ok) throw new Error(`Failed to fetch: ${res.status}`);
+    const depHour = Math.floor(Math.random() * 24);
-        const json = await res.json();
+    const arrHour = (depHour + Math.floor(Math.random() * 6) + 2) % 24;
-        const transformed = json.data.map((p: AirlineProduct) => transformProduct(p));
+    const stops = Math.random() > 0.6 ? 0 : Math.floor(Math.random() * 2) + 1;
-        setFlights(transformed);
+    const cabin = cabins[Math.floor(Math.random() * cabins.length)];
-      } catch (e) {
+    const fareRule = fareRules[Math.floor(Math.random() * fareRules.length)];
-        setError(e instanceof Error ? e.message : 'Failed to load products');
+
-        console.error('[FETCH_ERROR]', e);
+    const basePrice = Math.floor(
-      } finally {
+      (cabin === 'economy' ? 200 : cabin === 'premium' ? 400 : cabin === 'business' ? 800 : 1500) +
-        setLoading(false);
+      Math.random() * 300
-      }
+    );
+
+    return {
+      id: `flt-${i}`,
+      departure: {
+        time: `${depHour.toString().padStart(2, '0')}:${Math.floor(Math.random() * 60).toString().padStart(2, '0')}`,
+        airport: airports[Math.floor(Math.random() * airports.length)],
+      },
+      arrival: {
+        time: `${arrHour.toString().padStart(2, '0')}:${Math.floor(Math.random() * 60).toString().padStart(2, '0')}`,
+        airport: airports[Math.floor(Math.random() * airports.length)],
+      },
+      duration: `${Math.floor(Math.random() * 5) + 2}h ${Math.floor(Math.random() * 60)}m`,
+      stops,
+      cabinClass: cabin,
+      fareRule,
+      refundable: Math.random() > 0.7,
+      basePrice,
     };
-    fetchFlights();
+  });
-  }, [searchParams]);
+};
+
+export default function AirlineProducts() {
+  const flights = genRandomFlights();
 
   return (
     <>
+      <Navigation />
+      <main className="max-w-7xl mx-auto px-4 py-8">
         <h1 className="text-3xl font-bold mb-6">Available Flights</h1>
-      {loading && <div className="text-center py-8">Loading...</div>}
-      {error && <div className="text-red-500 text-center py-8">{error}</div>}
-      {!loading && !error && (
         <div className="space-y-4">
           {flights.map((f) => (
             <AirlineCard key={f.id} flight={f} />
           ))}
         </div>
-      )}
-    </>
-  );
-}
-
-export default function AirlineProducts() {
-  return (
-    <>
-      <Navigation />
-      <main className="max-w-7xl mx-auto px-4 py-8">
-        <Suspense fallback={<div className="text-center py-8">Loading...</div>}>
-          <FlightsList />
-        </Suspense>
       </main>
     </>
   );

web/src/app/api/admin/experiments/route.ts

@@ -1,40 +1,10 @@
-import { NextRequest, NextResponse } from 'next/server';
+import { NextResponse } from 'next/server';
-import { createClient } from '@/utils/supabase/server';
+import { getAllExperiments } from '@/lib/sessionStore';
-import { cookies } from 'next/headers';
 
-export async function GET(req: NextRequest) {
+export async function GET() {
   try {
-    const cookieStore = await cookies();
+    const exps = getAllExperiments();
-    const supabase = createClient(cookieStore);
+    return NextResponse.json({ experiments: exps });
-
-    const { searchParams } = new URL(req.url);
-    const id = searchParams.get('id');
-
-    if (id) {
-      const { data, error } = await supabase
-        .from('experiments')
-        .select(`
-          *,
-          task:tasks(*)
-        `)
-        .eq('id', id)
-        .single();
-
-      if (error) throw error;
-      return NextResponse.json({ experiment: data });
-    }
-
-    const { data, error } = await supabase
-      .from('experiments')
-      .select(`
-        *,
-        task:tasks(*)
-      `)
-      .order('created_at', { ascending: false });
-
-    if (error) throw error;
-
-    return NextResponse.json({ experiments: data || [] });
   } catch (err: any) {
     console.error('experiments list error:', err);
     return NextResponse.json(
@@ -43,44 +13,3 @@ export async function GET(req: NextRequest) {
     );
   }
 }
-
-export async function POST(req: NextRequest) {
-  try {
-    const cookieStore = await cookies();
-    const supabase = createClient(cookieStore);
-    const body = await req.json();
-
-    const { subject_name, xp_human_only, xp_market_mode, xp_task_id } = body;
-
-    if (!subject_name) {
-      return NextResponse.json(
-        { error: 'subject_name is required' },
-        { status: 400 }
-      );
-    }
-
-    const { data, error } = await supabase
-      .from('experiments')
-      .insert([{
-        subject_name,
-        xp_human_only: xp_human_only ?? false,
-        xp_market_mode: xp_market_mode || null,
-        xp_task_id: xp_task_id || null,
-      }])
-      .select(`
-        *,
-        task:tasks(*)
-      `)
-      .single();
-
-    if (error) throw error;
-
-    return NextResponse.json({ experiment: data });
-  } catch (err: any) {
-    console.error('experiment creation error:', err);
-    return NextResponse.json(
-      { error: err.message || 'unknown error' },
-      { status: 500 }
-    );
-  }
-}

web/src/app/api/admin/tasks/route.ts

@@ -1,58 +0,0 @@
-import { NextRequest, NextResponse } from 'next/server';
-import { createClient } from '@/utils/supabase/server';
-import { cookies } from 'next/headers';
-
-export async function GET() {
-  try {
-    const cookieStore = await cookies();
-    const supabase = createClient(cookieStore);
-
-    const { data, error } = await supabase
-      .from('tasks')
-      .select('*')
-      .order('created_at', { ascending: false });
-
-    if (error) throw error;
-
-    return NextResponse.json({ tasks: data || [] });
-  } catch (err: any) {
-    console.error('tasks fetch error:', err);
-    return NextResponse.json(
-      { error: err.message || 'unknown error' },
-      { status: 500 }
-    );
-  }
-}
-
-export async function POST(req: NextRequest) {
-  try {
-    const cookieStore = await cookies();
-    const supabase = createClient(cookieStore);
-    const body = await req.json();
-
-    const { task_name, task_description, task_def_of_done } = body;
-
-    if (!task_name) {
-      return NextResponse.json(
-        { error: 'task_name is required' },
-        { status: 400 }
-      );
-    }
-
-    const { data, error } = await supabase
-      .from('tasks')
-      .insert([{ task_name, task_description, task_def_of_done }])
-      .select()
-      .single();
-
-    if (error) throw error;
-
-    return NextResponse.json({ task: data });
-  } catch (err: any) {
-    console.error('task creation error:', err);
-    return NextResponse.json(
-      { error: err.message || 'unknown error' },
-      { status: 500 }
-    );
-  }
-}

web/src/app/api/pricing/route.ts

@@ -13,6 +13,17 @@ export async function GET(req: NextRequest) {
     const experimentId = searchParams.get('experimentId');
     const storeMode = process.env.NEXT_PUBLIC_STORE_MODE || 'shop';
 
+    // log in dev
+    if (process.env.NODE_ENV === 'development') {
+        console.log('[pricing-api]', {
+            productId,
+            sessionId,
+            experimentId,
+            storeMode,
+            timestamp: new Date().toISOString(),
+        });
+    }
+
     if (!productId) {
         return NextResponse.json(
             { error: 'productId is required' },
@@ -23,46 +34,11 @@ export async function GET(req: NextRequest) {
     // stub: call external pricing provider (random for now)
     const basePrice = 100 + Math.random() * 900; // 100-1000 range
     const price = Math.round(basePrice * 100) / 100;
-    const timestamp = new Date().toISOString();
-
-    // log price to kafka for elasticity computation
-    if (sessionId) {
-        const backendUrl = process.env.BACKEND_URL || 'http://localhost:5000';
-        try {
-            await fetch(`${backendUrl}/api/kafka/price-log`, {
-                method: 'POST',
-                headers: { 'Content-Type': 'application/json' },
-                body: JSON.stringify({
-                    productId,
-                    price,
-                    sessionId,
-                    experimentId: experimentId || undefined,
-                    storeMode,
-                    ts: timestamp,
-                }),
-            });
-        } catch (err) {
-            console.error('[price-log-error]', err);
-            // don't fail the pricing request if logging fails
-        }
-    }
-
-    // log in dev
-    if (process.env.NODE_ENV === 'development') {
-        console.log('[pricing-api]', {
-            productId,
-            sessionId,
-            experimentId,
-            storeMode,
-            price,
-            timestamp,
-        });
-    }
 
     const response: PricingResponse = {
         price,
         currency: 'EUR',
-        cachedAt: timestamp,
+        cachedAt: new Date().toISOString(),
     };
 
     return NextResponse.json(response);

web/src/app/api/products/[id]/route.ts

@@ -1,35 +0,0 @@
-import { NextRequest, NextResponse } from 'next/server';
-
-export async function GET(
-  req: NextRequest,
-  { params }: { params: Promise<{ id: string }> }
-) {
-  const { id } = await params;
-
-  if (!id) {
-    return NextResponse.json(
-      { error: 'product id is required' },
-      { status: 400 }
-    );
-  }
-
-  try {
-    const backendUrl = process.env.BACKEND_URL || 'http://localhost:5000';
-    const url = new URL(`${backendUrl}/api/products/${id}`);
-
-    const res = await fetch(url.toString());
-
-    if (!res.ok) {
-      throw new Error(`Backend returned ${res.status}`);
-    }
-
-    const data = await res.json();
-    return NextResponse.json(data);
-  } catch (error) {
-    console.error('[PRODUCT_DETAIL_ERROR]', error);
-    return NextResponse.json(
-      { error: 'Failed to fetch product details' },
-      { status: 500 }
-    );
-  }
-}

web/src/app/api/products/route.ts

@@ -1,40 +0,0 @@
-import { NextRequest, NextResponse } from 'next/server';
-
-export async function GET(req: NextRequest) {
-  const { searchParams } = new URL(req.url);
-  const type = searchParams.get('type');
-
-  if (!type || !['hotel', 'airline'].includes(type)) {
-    return NextResponse.json(
-      { error: 'type parameter must be "hotel" or "airline"' },
-      { status: 400 }
-    );
-  }
-
-  try {
-    const backendUrl = process.env.BACKEND_URL || 'http://localhost:5000';
-    const url = new URL(`${backendUrl}/api/products/type/${type}`);
-
-    // forward all query params to backend (excluding 'type')
-    searchParams.forEach((value, key) => {
-      if (key !== 'type') {
-        url.searchParams.set(key, value);
-      }
-    });
-
-    const res = await fetch(url.toString());
-
-    if (!res.ok) {
-      throw new Error(`Backend returned ${res.status}`);
-    }
-
-    const data = await res.json();
-    return NextResponse.json(data);
-  } catch (error) {
-    console.error('[PRODUCTS_PROXY_ERROR]', error);
-    return NextResponse.json(
-      { error: 'Failed to fetch products' },
-      { status: 500 }
-    );
-  }
-}

web/src/app/api/session/route.ts

@@ -1,12 +1,13 @@
 import { NextRequest, NextResponse } from 'next/server';
 import { randomUUID } from 'crypto';
-import { getSession, createSession, setExperiment } from '@/lib/sessionStore';
+import { getSession, createSession } from '@/lib/sessionStore';
 
 const COOKIE_NAME = 'phantom_session_id';
 const isProd = process.env.NODE_ENV === 'production';
 
 export async function GET(req: NextRequest) {
     try {
+        // check for existing session cookie
         const existingSession = req.cookies.get(COOKIE_NAME)?.value;
 
         if (existingSession) {
@@ -17,11 +18,13 @@ export async function GET(req: NextRequest) {
             });
         }
 
+        // mint new session id
         const sessionId = randomUUID();
         createSession(sessionId);
 
         const res = NextResponse.json({ sessionId, experimentId: undefined });
 
+        // set httpOnly cookie with security flags
         res.cookies.set({
             name: COOKIE_NAME,
             value: sessionId,
@@ -29,7 +32,7 @@ export async function GET(req: NextRequest) {
             sameSite: 'lax',
             secure: isProd,
             path: '/',
-            maxAge: 60 * 60 * 24 * 30,
+            maxAge: 60 * 60 * 24 * 30, // 30 days
         });
 
         return res;
@@ -41,52 +44,3 @@ export async function GET(req: NextRequest) {
         );
     }
 }
-
-export async function POST(req: NextRequest) {
-    try {
-        const body = await req.json();
-        const { experimentId } = body;
-
-        if (!experimentId) {
-            return NextResponse.json(
-                { error: 'experimentId is required' },
-                { status: 400 }
-            );
-        }
-
-        let sessionId = req.cookies.get(COOKIE_NAME)?.value;
-
-        if (!sessionId) {
-            sessionId = randomUUID();
-            createSession(sessionId);
-        }
-
-        setExperiment(sessionId, experimentId);
-
-        const res = NextResponse.json({
-            sessionId,
-            experimentId,
-            success: true
-        });
-
-        if (!req.cookies.get(COOKIE_NAME)) {
-            res.cookies.set({
-                name: COOKIE_NAME,
-                value: sessionId,
-                httpOnly: true,
-                sameSite: 'lax',
-                secure: isProd,
-                path: '/',
-                maxAge: 60 * 60 * 24 * 30,
-            });
-        }
-
-        return res;
-    } catch (err: any) {
-        console.error('session update error:', err);
-        return NextResponse.json(
-            { error: err.message || 'unknown error' },
-            { status: 500 }
-        );
-    }
-}

web/src/app/cart/page.tsx

@@ -1,110 +0,0 @@
-'use client';
-
-import { Navigation } from '@/components/ui';
-import { useCart } from '@/contexts/CartContext';
-import type { EventName } from '@/lib/events';
-
-const dispatchInteraction = (eventName: EventName, productId?: string, metadata?: Record<string, unknown>) => {
-    const e = new CustomEvent('definedInteraction', {
-        detail: { eventName, productId, metadata },
-    });
-    document.dispatchEvent(e);
-};
-
-export default function CartPage() {
-    const { items, removeItem, clearCart, itemCount } = useCart();
-
-    const handleRemove = (id: string, type: string) => {
-        removeItem(id);
-        dispatchInteraction('remove_item', id, { type });
-    };
-    let itemTypes = Array.from(new Set(items.map(item => item.type)))[0] || 'items';
-
-
-    const total = items.reduce((sum, item) => sum + item.price, 0);
-
-    return (
-        <>
-            <Navigation />
-            <main className="max-w-4xl mx-auto px-4 py-8">
-                <div className="flex justify-between items-center mb-6">
-                    <h1 className="text-3xl font-bold">Shopping Cart</h1>
-                    {itemCount > 0 && (
-                        <button
-                            onClick={clearCart}
-                            className="text-sm text-red-600 hover:underline"
-                        >
-                            Clear cart
-                        </button>
-                    )}
-                </div>
-
-                {itemCount === 0 ? (
-                    <div className="text-center py-12">
-                        <p className="text-gray-500 mb-4">Your cart is empty</p>
-                        <a href="/" className="text-blue-600 hover:underline">Browse our selection</a>
-                    </div>
-                ) : (
-                    <>
-                        <div className="space-y-4 mb-8">
-                            {items.map(item => (
-                                <div
-                                    key={item.id}
-                                    className="flex justify-between items-start p-4 border rounded-lg hover:bg-gray-50"
-                                >
-                                    <div className="flex-1">
-                                        <div className="flex items-center gap-2 mb-1">
-                                            <span className="px-2 py-0.5 text-xs font-medium rounded bg-blue-100 text-blue-800">
-                                                {item.type}
-                                            </span>
-                                            <h3 className="font-semibold">{item.name}</h3>
-                                        </div>
-
-                                        {item.type === 'hotel' && (
-                                            <div className="text-sm text-gray-600">
-                                                <p>{String(item.metadata.roomType)}</p>
-                                                <p>{String(item.metadata.checkIn)} - {String(item.metadata.checkOut)}</p>
-                                                <p>{String(item.metadata.nights)} night{Number(item.metadata.nights) > 1 ? 's' : ''}</p>
-                                            </div>
-                                        )}
-
-                                        {item.type === 'airline' && (
-                                            <div className="text-sm text-gray-600">
-                                                <p>{String(item.metadata.cabinClass)} Class</p>
-                                                <p>{String((item.metadata.departure as any)?.airport)} → {String((item.metadata.arrival as any)?.airport)}</p>
-                                                <p>Duration: {String(item.metadata.duration)}</p>
-                                            </div>
-                                        )}
-                                    </div>
-
-                                    <div className="text-right ml-4">
-                                        <p className="text-xl font-bold mb-2">${item.price}</p>
-                                        <button
-                                            onClick={() => handleRemove(item.id, item.type)}
-                                            className="text-sm text-red-600 hover:underline"
-                                        >
-                                            Remove
-                                        </button>
-                                    </div>
-                                </div>
-                            ))}
-                        </div>
-
-                        <div className="border-t pt-4">
-                            <div className="flex justify-between items-center mb-4">
-                                <span className="text-xl font-semibold">Total</span>
-                                <span className="text-3xl font-bold">${total.toFixed(2)}</span>
-                            </div>
-                            <button
-                                onClick={() => dispatchInteraction('checkout_start', undefined, { total, itemCount })}
-                                className="w-full py-3 bg-blue-600 hover:bg-blue-700 text-white rounded-lg font-medium transition-colors"
-                            >
-                                Proceed to Checkout
-                            </button>
-                        </div>
-                    </>
-                )}
-            </main>
-        </>
-    );
-}

web/src/app/hotel/products/[id]/page.tsx

@@ -1,106 +0,0 @@
-'use client';
-
-import { useState, useEffect } from 'react';
-import { useParams, useRouter } from 'next/navigation';
-import { Navigation } from '@/components/ui';
-import { useCart } from '@/contexts/CartContext';
-import HotelDetails from '@/components/feats/hotel/HotelDetails';
-import { transformProduct, type Hotel, type HotelProduct } from '@/lib/hotel-utils';
-import type { EventName } from '@/lib/events';
-
-const dispatchInteraction = (eventName: EventName, productId?: string, metadata?: Record<string, unknown>) => {
-    const e = new CustomEvent('definedInteraction', {
-        detail: { eventName, productId, metadata },
-    });
-    document.dispatchEvent(e);
-};
-
-export default function HotelProductPage() {
-    const params = useParams();
-    const router = useRouter();
-    const { addItem } = useCart();
-    const [product, setProduct] = useState<Hotel | null>(null);
-    const [loading, setLoading] = useState(true);
-    const [error, setError] = useState<string | null>(null);
-    const [added, setAdded] = useState(false);
-
-    const productId = params.id as string;
-
-    useEffect(() => {
-        const fetchProduct = async () => {
-            try {
-                const res = await fetch(`/api/products/${productId}`);
-                if (!res.ok) throw new Error(`Failed to fetch: ${res.status}`);
-                const json = await res.json();
-                const transformed = transformProduct(json.data as HotelProduct);
-                setProduct(transformed);
-
-                // fire learn_more_about_item event when product loads
-                dispatchInteraction('learn_more_about_item', productId, {
-                    type: 'hotel',
-                    dateIndex: transformed.dateIndex,
-                    roomType: transformed.roomType,
-                });
-            } catch (e) {
-                setError(e instanceof Error ? e.message : 'Failed to load product');
-                console.error('[FETCH_HOTEL_ERROR]', e);
-            } finally {
-                setLoading(false);
-            }
-        };
-        fetchProduct();
-    }, [productId]);
-
-    const handleAddToCart = () => {
-        if (!product) return;
-
-        addItem({
-            id: productId,
-            type: 'hotel',
-            name: product.name,
-            price: product.pricePerNight,
-            metadata: {
-                roomType: product.roomType,
-                nights: product.nights,
-                checkIn: product.checkIn,
-                checkOut: product.checkOut,
-            },
-            dateIndex: product.dateIndex,
-        });
-
-        dispatchInteraction('add_item_to_cart', productId, {
-            type: 'hotel',
-            price: product.pricePerNight,
-        });
-
-        setAdded(true);
-        setTimeout(() => setAdded(false), 2000);
-    };
-
-    return (
-        <>
-            <Navigation />
-            <main className="max-w-4xl mx-auto px-4 py-8">
-                {loading && <div className="text-center py-8">Loading hotel details...</div>}
-                {error && <div className="text-red-500 text-center py-8">{error}</div>}
-
-                {!loading && !error && product && (
-                    <>
-                        <button
-                            onClick={() => router.back()}
-                            className="mt-6 text-blue-600 hover:underline"
-                        >
-                            ← Back to rooms
-                        </button>
-                        <HotelDetails
-                            product={product}
-                            onAddToCart={handleAddToCart}
-                            addedToCart={added}
-                        />
-
-                    </>
-                )}
-            </main>
-        </>
-    );
-}

web/src/app/hotel/products/page.tsx

@@ -1,69 +1,74 @@
 'use client';
 
-import { useState, useEffect, Suspense } from 'react';
-import { useSearchParams } from 'next/navigation';
 import { Navigation } from '@/components/ui';
 import HotelCard from '@/components/feats/hotel/HotelCard';
-import { transformProduct, type Hotel, type HotelProduct } from '@/lib/hotel-utils';
 
-function RoomsList() {
+interface Hotel {
-  const searchParams = useSearchParams();
+  id: string;
-  const [rooms, setRooms] = useState<Hotel[]>([]);
+  name: string;
-  const [loading, setLoading] = useState(true);
+  roomType: string;
-  const [error, setError] = useState<string | null>(null);
+  checkIn: string;
-
+  checkOut: string;
-  useEffect(() => {
+  amenities: string[];
-    const fetchRooms = async () => {
+  refundable: boolean;
-      try {
+  pricePerNight: number;
-        const url = new URL('/api/products', window.location.origin);
+  nights: number;
-        url.searchParams.set('type', 'hotel');
-
-        // forward all relevant search params to the API
-        const params = ['dateIndex', 'destination', 'adults', 'rooms'];
-        params.forEach(param => {
-          const val = searchParams.get(param);
-          if (val) url.searchParams.set(param, val);
-        });
-
-        const res = await fetch(url.toString());
-        if (!res.ok) throw new Error(`Failed to fetch: ${res.status}`);
-        const json = await res.json();
-        const transformed = json.data.map((p: HotelProduct) => transformProduct(p));
-        setRooms(transformed);
-      } catch (e) {
-        setError(e instanceof Error ? e.message : 'Failed to load products');
-        console.error('[FETCH_ERROR]', e);
-      } finally {
-        setLoading(false);
-      }
-    };
-    fetchRooms();
-  }, [searchParams]);
-
-  return (
-    <>
-      <h1 className="text-3xl font-bold mb-6">Available Rooms</h1>
-      {loading && <div className="text-center py-8">Loading...</div>}
-      {error && <div className="text-red-500 text-center py-8">{error}</div>}
-      {!loading && !error && (
-        <div className="space-y-4">
-          {rooms.map((r) => (
-            <HotelCard key={r.id} hotel={r} />
-          ))}
-        </div>
-      )}
-    </>
-  );
 }
 
+const genRandomHotels = (): Hotel[] => {
+  const names = [
+    'Grand Plaza Hotel',
+    'Seaside Resort',
+    'Downtown Suites',
+    'Mountain View Lodge',
+    'City Center Inn',
+    'Luxury Beach Resort',
+    'Urban Boutique Hotel',
+    'Garden View Hotel',
+  ];
+  const roomTypes = ['Standard Room', 'Deluxe Room', 'Suite', 'Executive Suite', 'Premium Room'];
+  const amenities = ['wifi', 'pool', 'gym', 'parking', 'breakfast', 'spa'];
+
+  return Array.from({ length: 10 }, (_, i) => {
+    const nights = Math.floor(Math.random() * 5) + 1;
+    const basePrice = Math.floor(80 + Math.random() * 220);
+    const selectedAmenities = amenities
+      .sort(() => Math.random() - 0.5)
+      .slice(0, Math.floor(Math.random() * 3) + 2);
+
+    const today = new Date();
+    const checkInDate = new Date(today);
+    checkInDate.setDate(today.getDate() + Math.floor(Math.random() * 10));
+    const checkOutDate = new Date(checkInDate);
+    checkOutDate.setDate(checkInDate.getDate() + nights);
+
+    return {
+      id: `htl-${i}`,
+      name: names[i % names.length],
+      roomType: roomTypes[Math.floor(Math.random() * roomTypes.length)],
+      checkIn: checkInDate.toLocaleDateString('en-US', { month: 'short', day: 'numeric' }),
+      checkOut: checkOutDate.toLocaleDateString('en-US', { month: 'short', day: 'numeric' }),
+      amenities: selectedAmenities,
+      refundable: Math.random() > 0.5,
+      pricePerNight: basePrice,
+      nights,
+    };
+  });
+};
+
 export default function HotelProducts() {
+  const hotels = genRandomHotels();
+
   return (
     <>
       <Navigation />
       <main className="max-w-7xl mx-auto px-4 py-8">
-        <Suspense fallback={<div className="text-center py-8">Loading...</div>}>
+        <h1 className="text-3xl font-bold mb-6">Available Hotels</h1>
-          <RoomsList />
+        <div className="space-y-4">
-        </Suspense>
+          {hotels.map((h) => (
+            <HotelCard key={h.id} hotel={h} />
+          ))}
+        </div>
       </main>
     </>
   );

web/src/app/layout.tsx

@@ -2,7 +2,6 @@ import type { Metadata } from "next";
 import { Geist, Geist_Mono } from "next/font/google";
 import "./globals.css";
 import { TrackingProvider } from "@/components/TrackingProvider";
-import { CartProvider } from "@/contexts/CartContext";
 
 const geistSans = Geist({
   variable: "--font-geist-sans",
@@ -29,9 +28,7 @@ export default function RootLayout({
       <body
         className={`${geistSans.variable} ${geistMono.variable} antialiased`}
       >
-        <CartProvider>
         <TrackingProvider>{children}</TrackingProvider>
-        </CartProvider>
       </body>
     </html>
   );

web/src/app/start-task/page.tsx

@@ -1,93 +0,0 @@
-'use client';
-
-import { useEffect, useState, Suspense } from 'react';
-import { useSearchParams, useRouter } from 'next/navigation';
-
-const StartTaskContent = () => {
-  const searchParams = useSearchParams();
-  const router = useRouter();
-  const [status, setStatus] = useState<'loading' | 'error' | 'redirecting'>('loading');
-  const [error, setError] = useState<string | null>(null);
-
-  useEffect(() => {
-    const uuid = searchParams.get('uuid');
-
-    if (!uuid) {
-      setError('no experiment UUID provided');
-      setStatus('error');
-      return;
-    }
-
-    const validateAndStore = async () => {
-      try {
-        const res = await fetch(`/api/admin/experiments?id=${uuid}`);
-        if (!res.ok) throw new Error('experiment not found');
-
-        const data = await res.json();
-        const exp = data.experiment;
-
-        if (!exp) throw new Error('invalid experiment UUID');
-
-        localStorage.setItem('phantom_experiment_id', uuid);
-
-        await fetch('/api/session', {
-          method: 'POST',
-          headers: { 'Content-Type': 'application/json' },
-          body: JSON.stringify({ experimentId: uuid }),
-        });
-
-        setStatus('redirecting');
-
-        setTimeout(() => {
-          router.push("/");
-        }, 800);
-
-      } catch (err: any) {
-        setError(err.message || 'failed to start task');
-        setStatus('error');
-      }
-    };
-
-    validateAndStore();
-  }, [searchParams, router]);
-
-  return (
-    <div className="flex min-h-screen items-center justify-center bg-zinc-50 dark:bg-black">
-      <div className="text-center">
-        {status === 'loading' && (
-          <div>
-            <div className="mb-4 h-8 w-8 animate-spin rounded-full border-4 border-zinc-200 border-t-zinc-900 dark:border-zinc-800 dark:border-t-zinc-100 mx-auto" />
-            <p className="text-zinc-600 dark:text-zinc-400">validating browser...</p>
-          </div>
-        )}
-
-        {status === 'redirecting' && (
-          <div>
-            <div className="mb-4 text-4xl">✓</div>
-            <p className="text-zinc-900 dark:text-zinc-100 font-medium">website loaded</p>
-            <p className="mt-2 text-sm text-zinc-600 dark:text-zinc-400">redirecting to page...</p>
-          </div>
-        )}
-
-        {status === 'error' && (
-          <div className="rounded-lg bg-red-50 p-6 dark:bg-red-950">
-            <p className="text-red-900 dark:text-red-100 font-medium">error</p>
-            <p className="mt-2 text-sm text-red-700 dark:text-red-300">{error}</p>
-          </div>
-        )}
-      </div>
-    </div>
-  );
-};
-
-export default function StartTaskPage() {
-  return (
-    <Suspense fallback={
-      <div className="flex min-h-screen items-center justify-center bg-zinc-50 dark:bg-black">
-        <p className="text-zinc-600 dark:text-zinc-400">loading...</p>
-      </div>
-    }>
-      <StartTaskContent />
-    </Suspense>
-  );
-}

web/src/components/admin/ExperimentForm.tsx

@@ -1,118 +0,0 @@
-'use client';
-
-import { useState } from 'react';
-
-type ExperimentFormProps = {
-  selectedTaskId?: string;
-  onSuccess?: () => void;
-};
-
-export const ExperimentForm = ({ selectedTaskId, onSuccess }: ExperimentFormProps) => {
-  const [loading, setLoading] = useState(false);
-  const [error, setError] = useState<string | null>(null);
-  const [form, setForm] = useState({
-    subject_name: '',
-    xp_human_only: false,
-    xp_market_mode: 'hotel' as 'hotel' | 'airline',
-  });
-
-  const handleSubmit = async (e: React.FormEvent) => {
-    e.preventDefault();
-    setLoading(true);
-    setError(null);
-
-    try {
-      const res = await fetch('/api/admin/experiments', {
-        method: 'POST',
-        headers: { 'Content-Type': 'application/json' },
-        body: JSON.stringify({
-          ...form,
-          xp_task_id: selectedTaskId || null,
-        }),
-      });
-
-      if (!res.ok) {
-        const data = await res.json();
-        throw new Error(data.error || 'creation failed');
-      }
-
-      setForm({ subject_name: '', xp_human_only: false, xp_market_mode: 'hotel' });
-      onSuccess?.();
-    } catch (err: any) {
-      setError(err.message);
-    } finally {
-      setLoading(false);
-    }
-  };
-
-  return (
-    <form onSubmit={handleSubmit} className="space-y-4 rounded-lg border border-zinc-200 bg-white p-6 dark:border-zinc-800 dark:bg-zinc-950">
-      <h2 className="text-lg font-semibold text-zinc-900 dark:text-zinc-100">
-        Create Experiment
-      </h2>
-
-      {error && (
-        <div className="rounded-lg bg-red-50 p-3 text-sm text-red-800 dark:bg-red-950 dark:text-red-200">
-          {error}
-        </div>
-      )}
-
-      <div>
-        <label className="block text-sm font-medium text-zinc-700 dark:text-zinc-300">
-          subject name
-        </label>
-        <input
-          type="text"
-          value={form.subject_name}
-          onChange={(e) => setForm({ ...form, subject_name: e.target.value })}
-          className="mt-1 w-full rounded-lg border border-zinc-300 bg-white px-3 py-2 text-sm text-zinc-900 focus:border-zinc-900 focus:outline-none dark:border-zinc-700 dark:bg-zinc-900 dark:text-zinc-100 dark:focus:border-zinc-100"
-          placeholder="e.g., baseline_dynamic_pricing_v1"
-          required
-        />
-      </div>
-
-      <div>
-        <label className="block text-sm font-medium text-zinc-700 dark:text-zinc-300">
-          market mode
-        </label>
-        <select
-          value={form.xp_market_mode}
-          onChange={(e) => setForm({ ...form, xp_market_mode: e.target.value as 'hotel' | 'airline' })}
-          className="mt-1 w-full rounded-lg border border-zinc-300 bg-white px-3 py-2 text-sm text-zinc-900 focus:border-zinc-900 focus:outline-none dark:border-zinc-700 dark:bg-zinc-900 dark:text-zinc-100 dark:focus:border-zinc-100"
-        >
-          <option value="hotel">hotel</option>
-          <option value="airline">airline</option>
-        </select>
-      </div>
-
-      <div className="flex items-center gap-2">
-        <input
-          type="checkbox"
-          id="human-only"
-          checked={form.xp_human_only}
-          onChange={(e) => setForm({ ...form, xp_human_only: e.target.checked })}
-          className="h-4 w-4 rounded border-zinc-300 text-zinc-900 focus:ring-zinc-900 dark:border-zinc-700 dark:bg-zinc-900"
-        />
-        <label htmlFor="human-only" className="text-sm text-zinc-700 dark:text-zinc-300">
-          human participants only
-        </label>
-      </div>
-
-      {selectedTaskId && (
-        <div className="rounded-lg bg-zinc-50 p-3 dark:bg-zinc-900">
-          <p className="text-sm text-zinc-600 dark:text-zinc-400">
-            task selected: <span className="font-mono text-xs">{selectedTaskId.slice(0, 8)}...</span>
-          </p>
-        </div>
-      )}
-
-      <button
-        type="submit"
-        disabled={loading}
-        className="w-full rounded-lg bg-black px-4 py-2 text-sm font-medium text-white transition-colors hover:bg-zinc-800 disabled:opacity-50 dark:bg-zinc-50 dark:text-black dark:hover:bg-zinc-200"
-      >
-        {loading ? 'creating experiment...' : 'create experiment'}
-      </button>
-    </form>
-  );
-};

web/src/components/admin/TaskManager.tsx

@@ -1,178 +0,0 @@
-'use client';
-
-import { useState, useEffect } from 'react';
-
-type Task = {
-  id: string;
-  task_name: string;
-  task_description: string;
-  task_def_of_done: string;
-  created_at: string;
-};
-
-type TaskManagerProps = {
-  onTaskSelect?: (taskId: string) => void;
-  selectedTaskId?: string;
-};
-
-export const TaskManager = ({ onTaskSelect, selectedTaskId }: TaskManagerProps) => {
-  const [tasks, setTasks] = useState<Task[]>([]);
-  const [loading, setLoading] = useState(false);
-  const [showForm, setShowForm] = useState(false);
-  const [form, setForm] = useState({
-    task_name: '',
-    task_description: '',
-    task_def_of_done: '',
-  });
-  const [error, setError] = useState<string | null>(null);
-
-  const fetchTasks = async () => {
-    try {
-      const res = await fetch('/api/admin/tasks');
-      if (!res.ok) throw new Error(`fetch failed: ${res.status}`);
-      const data = await res.json();
-      setTasks(data.tasks || []);
-    } catch (err: any) {
-      setError(err.message);
-    }
-  };
-
-  useEffect(() => {
-    fetchTasks();
-  }, []);
-
-  const handleSubmit = async (e: React.FormEvent) => {
-    e.preventDefault();
-    setLoading(true);
-    setError(null);
-
-    try {
-      const res = await fetch('/api/admin/tasks', {
-        method: 'POST',
-        headers: { 'Content-Type': 'application/json' },
-        body: JSON.stringify(form),
-      });
-
-      if (!res.ok) {
-        const data = await res.json();
-        throw new Error(data.error || 'creation failed');
-      }
-
-      setForm({ task_name: '', task_description: '', task_def_of_done: '' });
-      setShowForm(false);
-      await fetchTasks();
-    } catch (err: any) {
-      setError(err.message);
-    } finally {
-      setLoading(false);
-    }
-  };
-
-  return (
-    <div className="space-y-4">
-      <div className="flex items-center justify-between">
-        <h2 className="text-lg font-semibold text-zinc-900 dark:text-zinc-100">
-          Tasks
-        </h2>
-        <button
-          onClick={() => setShowForm(!showForm)}
-          className="rounded-lg bg-zinc-900 px-3 py-1.5 text-sm font-medium text-white transition-colors hover:bg-zinc-700 dark:bg-zinc-100 dark:text-black dark:hover:bg-zinc-300"
-        >
-          {showForm ? 'cancel' : 'new task'}
-        </button>
-      </div>
-
-      {error && (
-        <div className="rounded-lg bg-red-50 p-3 text-sm text-red-800 dark:bg-red-950 dark:text-red-200">
-          {error}
-        </div>
-      )}
-
-      {showForm && (
-        <form onSubmit={handleSubmit} className="space-y-3 rounded-lg border border-zinc-200 bg-white p-4 dark:border-zinc-800 dark:bg-zinc-950">
-          <div>
-            <label className="block text-sm font-medium text-zinc-700 dark:text-zinc-300">
-              task name
-            </label>
-            <input
-              type="text"
-              value={form.task_name}
-              onChange={(e) => setForm({ ...form, task_name: e.target.value })}
-              className="mt-1 w-full rounded-lg border border-zinc-300 bg-white px-3 py-2 text-sm text-zinc-900 focus:border-zinc-900 focus:outline-none dark:border-zinc-700 dark:bg-zinc-900 dark:text-zinc-100 dark:focus:border-zinc-100"
-              placeholder="e.g., Book cheapest flight to Paris"
-              required
-            />
-          </div>
-
-          <div>
-            <label className="block text-sm font-medium text-zinc-700 dark:text-zinc-300">
-              description
-            </label>
-            <textarea
-              value={form.task_description}
-              onChange={(e) => setForm({ ...form, task_description: e.target.value })}
-              className="mt-1 w-full rounded-lg border border-zinc-300 bg-white px-3 py-2 text-sm text-zinc-900 focus:border-zinc-900 focus:outline-none dark:border-zinc-700 dark:bg-zinc-900 dark:text-zinc-100 dark:focus:border-zinc-100"
-              placeholder="User should find and book the cheapest available flight..."
-              rows={3}
-            />
-          </div>
-
-          <div>
-            <label className="block text-sm font-medium text-zinc-700 dark:text-zinc-300">
-              definition of done
-            </label>
-            <textarea
-              value={form.task_def_of_done}
-              onChange={(e) => setForm({ ...form, task_def_of_done: e.target.value })}
-              className="mt-1 w-full rounded-lg border border-zinc-300 bg-white px-3 py-2 text-sm text-zinc-900 focus:border-zinc-900 focus:outline-none dark:border-zinc-700 dark:bg-zinc-900 dark:text-zinc-100 dark:focus:border-zinc-100"
-              placeholder="Booking is completed and confirmation page is shown"
-              rows={2}
-            />
-          </div>
-
-          <button
-            type="submit"
-            disabled={loading}
-            className="w-full rounded-lg bg-black px-4 py-2 text-sm font-medium text-white transition-colors hover:bg-zinc-800 disabled:opacity-50 dark:bg-zinc-50 dark:text-black dark:hover:bg-zinc-200"
-          >
-            {loading ? 'creating...' : 'create task'}
-          </button>
-        </form>
-      )}
-
-      <div className="space-y-2">
-        {tasks.length === 0 ? (
-          <p className="py-8 text-center text-sm text-zinc-500 dark:text-zinc-400">
-            no tasks yet
-          </p>
-        ) : (
-          tasks.map((task) => (
-            <div
-              key={task.id}
-              onClick={() => onTaskSelect?.(task.id)}
-              className={`cursor-pointer rounded-lg border p-3 transition-colors ${
-                selectedTaskId === task.id
-                  ? 'border-zinc-900 bg-zinc-50 dark:border-zinc-100 dark:bg-zinc-900'
-                  : 'border-zinc-200 bg-white hover:border-zinc-300 dark:border-zinc-800 dark:bg-zinc-950 dark:hover:border-zinc-700'
-              }`}
-            >
-              <h3 className="font-medium text-zinc-900 dark:text-zinc-100">
-                {task.task_name}
-              </h3>
-              {task.task_description && (
-                <p className="mt-1 text-sm text-zinc-600 dark:text-zinc-400">
-                  {task.task_description}
-                </p>
-              )}
-              {task.task_def_of_done && (
-                <p className="mt-1 text-xs text-zinc-500 dark:text-zinc-500">
-                  done: {task.task_def_of_done}
-                </p>
-              )}
-            </div>
-          ))
-        )}
-      </div>
-    </div>
-  );
-};

web/src/components/feats/airline/AirlineCard.tsx

@@ -1,7 +1,6 @@
 'use client';
 
 import type { EventName } from '@/lib/events';
-import type { Flight } from '@/lib/airline-utils';
 import { useHoverTracking } from '@/hooks/useHoverTracking';
 import PriceDisplay from '@/components/ui/PriceDisplay';
 
@@ -12,17 +11,32 @@ const dispatchInteraction = (eventName: EventName, productId?: string, metadata?
     document.dispatchEvent(e);
 };
 
+type CabinClass = 'economy' | 'premium' | 'business' | 'first';
+type FareRule = 'flexible' | 'standard' | 'basic';
+
+interface Flight {
+    id: string;
+    departure: { time: string; airport: string };
+    arrival: { time: string; airport: string };
+    duration: string;
+    stops: number;
+    cabinClass: CabinClass;
+    fareRule: FareRule;
+    refundable: boolean;
+    basePrice: number;
+}
+
 export default function AirlineCard({ flight }: { flight: Flight }) {
     const durationRef = useHoverTracking({
         eventName: 'hover_over_title',
         productId: flight.id,
-        metadata: { elementText: flight.duration, dateIndex: flight.dateIndex },
+        metadata: { elementText: flight.duration },
     });
 
     const priceRef = useHoverTracking({
         eventName: 'hover_over_paragraph',
         productId: flight.id,
-        metadata: { elementText: 'price', dateIndex: flight.dateIndex },
+        metadata: { elementText: 'price' },
     });
 
     const handleCardClick = () => {
@@ -30,9 +44,7 @@ export default function AirlineCard({ flight }: { flight: Flight }) {
             cabinClass: flight.cabinClass,
             fareRule: flight.fareRule,
             price: flight.basePrice,
-            dateIndex: flight.dateIndex,
         });
-        window.location.href = `/airline/products/${flight.id}`;
     };
 
     return (

web/src/components/feats/airline/AirlineDetails.tsx

@@ -1,75 +0,0 @@
-'use client';
-
-import type { Flight } from '@/lib/airline-utils';
-
-interface AirlineDetailsProps {
-  product: Flight;
-  onAddToCart: () => void;
-  addedToCart: boolean;
-}
-
-export default function AirlineDetails({ product, onAddToCart, addedToCart }: AirlineDetailsProps) {
-  return (
-    <div className="w-full flex flex-col lg:flex-row gap-12 py-8">
-      {/* Image Section */}
-      <div className="w-full lg:w-1/3 bg-gray-100 rounded-lg aspect-square flex items-center justify-center shrink-0">
-        <span className="text-gray-400 text-lg font-medium">Flight Image</span>
-      </div>
-
-      {/* Details Section */}
-      <div className="flex-1 flex flex-col">
-        <div className="flex justify-between items-start border-b pb-6 mb-6">
-          <div>
-            <h1 className="text-3xl font-bold text-gray-900 mb-1">{product.flightType}</h1>
-            <p className="text-lg text-gray-500">{product.cabinClass} Class</p>
-          </div>
-          <div className="text-right">
-            <p className="text-4xl font-bold text-gray-900">${product.basePrice}</p>
-            {product.refundable && (
-              <span className="inline-block mt-2 px-3 py-1 bg-green-50 text-green-700 rounded-full text-xs font-medium">
-                Refundable
-              </span>
-            )}
-          </div>
-        </div>
-
-        <div className="flex items-center justify-between mb-10">
-          <div className="text-center min-w-[100px]">
-            <p className="text-3xl font-bold text-gray-900">{product.departure.time}</p>
-            <p className="text-sm text-gray-500 font-medium mt-1">{product.departure.airport}</p>
-          </div>
-
-          <div className="flex-1 px-8 flex flex-col items-center">
-            <p className="text-sm text-gray-500 mb-2">{product.duration}</p>
-            <div className="w-full h-0.5 bg-gray-200 relative flex items-center justify-center">
-              <div className="absolute w-3 h-3 bg-gray-400 rounded-full"></div>
-            </div>
-            <p className="text-sm text-gray-500 mt-2">
-              {product.stops === 0 ? 'Nonstop' : `${product.stops} stop${product.stops > 1 ? 's' : ''}`}
-            </p>
-          </div>
-
-          <div className="text-center min-w-[100px]">
-            <p className="text-3xl font-bold text-gray-900">{product.arrival.time}</p>
-            <p className="text-sm text-gray-500 font-medium mt-1">{product.arrival.airport}</p>
-          </div>
-        </div>
-
-        <div className="mt-auto flex items-center justify-between pt-6 border-t">
-          <div className="text-gray-600">
-            <span className="font-bold text-gray-900">{product.availability}</span> seats remaining
-            <span className="mx-2">•</span>
-            {product.fareRule}
-          </div>
-          <button
-            onClick={onAddToCart}
-            disabled={addedToCart}
-            className="px-8 py-4 bg-black hover:bg-gray-800 disabled:bg-green-600 text-white rounded-lg text-lg font-medium transition-all min-w-[200px]"
-          >
-            {addedToCart ? 'In Cart' : 'Add to Cart'}
-          </button>
-        </div>
-      </div>
-    </div>
-  );
-}

web/src/components/feats/airline/AirlineHero.tsx

@@ -1,9 +1,7 @@
 'use client';
 
 import { useState, FormEvent } from 'react';
-import { useRouter } from 'next/navigation';
 import { Button, Label, Input, DateInput, RadioGroup, Dropdown, DropdownCounter } from '@/components/ui';
-import { dateToDaysFromToday } from '@/lib/airline-utils';
 
 type TripType = 'roundtrip' | 'oneway' | 'multicity';
 
@@ -21,7 +19,6 @@ const LocationIcon = () => (
 );
 
 export default function AirlineHero() {
-  const router = useRouter();
   const [tripType, setTripType] = useState<TripType>('roundtrip');
   const [origin, setOrigin] = useState('');
   const [destination, setDestination] = useState('');
@@ -31,23 +28,7 @@ export default function AirlineHero() {
 
   const handleSearch = (e: FormEvent) => {
     e.preventDefault();
-    const params = new URLSearchParams();
+    console.log({ tripType, origin, destination, departDate, returnDate, passengers });
-
-    if (departDate) {
-      const daysOffset = dateToDaysFromToday(departDate);
-      params.set('dateIndex', daysOffset.toString());
-    }
-
-    if (origin) params.set('origin', origin);
-    if (destination) params.set('destination', destination);
-    if (tripType !== 'roundtrip') params.set('tripType', tripType);
-    if (returnDate && tripType === 'roundtrip') params.set('returnDate', returnDate);
-
-    params.set('adults', passengers.adults.toString());
-    params.set('children', passengers.children.toString());
-    params.set('infants', passengers.infants.toString());
-
-    router.push(`/airline/products?${params.toString()}`);
   };
 
   const totalPax = passengers.adults + passengers.children + passengers.infants;

web/src/components/feats/hotel/HotelCard.tsx

@@ -1,7 +1,6 @@
 'use client';
 
 import type { EventName } from '@/lib/events';
-import type { Hotel } from '@/lib/hotel-utils';
 import { useHoverTracking } from '@/hooks/useHoverTracking';
 import PriceDisplay from '@/components/ui/PriceDisplay';
 
@@ -12,6 +11,18 @@ const dispatchInteraction = (eventName: EventName, productId?: string, metadata?
     document.dispatchEvent(e);
 };
 
+interface Hotel {
+    id: string;
+    name: string;
+    roomType: string;
+    checkIn: string;
+    checkOut: string;
+    amenities: string[];
+    refundable: boolean;
+    pricePerNight: number;
+    nights: number;
+}
+
 const AmenityIcon = ({ name }: { name: string }) => {
     const iconMap: Record<string, string> = {
         wifi: 'Wi-Fi',
@@ -28,13 +39,13 @@ export default function HotelCard({ hotel }: { hotel: Hotel }) {
     const titleRef = useHoverTracking({
         eventName: 'hover_over_title',
         productId: hotel.id,
-        metadata: { elementText: hotel.name, dateIndex: hotel.dateIndex },
+        metadata: { elementText: hotel.name },
     });
 
     const priceRef = useHoverTracking({
         eventName: 'hover_over_paragraph',
         productId: hotel.id,
-        metadata: { elementText: 'price', dateIndex: hotel.dateIndex },
+        metadata: { elementText: 'price' },
     });
 
     const handleCardClick = () => {
@@ -42,9 +53,7 @@ export default function HotelCard({ hotel }: { hotel: Hotel }) {
             roomType: hotel.roomType,
             price: hotel.pricePerNight,
             nights: hotel.nights,
-            dateIndex: hotel.dateIndex,
         });
-        window.location.href = `/hotel/products/${hotel.id}`;
     };
 
     return (

web/src/components/feats/hotel/HotelDetails.tsx

@@ -1,74 +0,0 @@
-'use client';
-
-import type { Hotel } from '@/lib/hotel-utils';
-
-interface HotelDetailsProps {
-  product: Hotel;
-  onAddToCart: () => void;
-  addedToCart: boolean;
-}
-
-export default function HotelDetails({ product, onAddToCart, addedToCart }: HotelDetailsProps) {
-  return (
-    <div className="w-full flex flex-col lg:flex-row gap-12 py-8">
-      {/* Image Section - Larger and cleaner */}
-      <div className="w-full lg:w-1/2 bg-gray-100 rounded-lg aspect-[4/3] flex items-center justify-center shrink-0">
-        <span className="text-gray-400 text-lg font-medium">Hotel Image</span>
-      </div>
-
-      {/* Details Section - Full height/width usage */}
-      <div className="flex-1 flex flex-col">
-        <div className="border-b pb-6 mb-6">
-          <h1 className="text-4xl font-bold text-gray-900 mb-2">{product.name}</h1>
-          <p className="text-xl text-gray-500">{product.roomType}</p>
-        </div>
-
-        <div className="grid grid-cols-2 gap-8 mb-8">
-          <div>
-            <h3 className="text-sm font-semibold text-gray-900 uppercase tracking-wider mb-2">Check-in</h3>
-            <p className="text-lg text-gray-700">{product.checkIn}</p>
-          </div>
-          <div>
-            <h3 className="text-sm font-semibold text-gray-900 uppercase tracking-wider mb-2">Check-out</h3>
-            <p className="text-lg text-gray-700">{product.checkOut}</p>
-          </div>
-        </div>
-
-        <div className="mb-8">
-          <h3 className="text-sm font-semibold text-gray-900 uppercase tracking-wider mb-3">Amenities</h3>
-          <div className="flex flex-wrap gap-3">
-            {product.amenities.map(a => (
-              <span key={a} className="px-3 py-1.5 bg-gray-100 text-gray-700 rounded-md text-sm font-medium">
-                {a}
-              </span>
-            ))}
-          </div>
-        </div>
-
-        {product.refundable && (
-          <div className="mb-8 p-4 bg-green-50 text-green-800 rounded-md inline-block">
-            <span className="font-medium">Free cancellation available</span>
-          </div>
-        )}
-
-        <div className="mt-auto pt-6 border-t flex items-center justify-between">
-          <div>
-            <p className="text-sm text-gray-500 mb-1">Total for {product.nights} night{product.nights > 1 ? 's' : ''}</p>
-            <div className="flex items-baseline gap-2">
-              <span className="text-4xl font-bold text-gray-900">${product.pricePerNight * product.nights}</span>
-              <span className="text-gray-500">/ {product.nights} nights</span>
-            </div>
-          </div>
-
-          <button
-            onClick={onAddToCart}
-            disabled={addedToCart}
-            className="px-8 py-4 bg-black hover:bg-gray-800 disabled:bg-green-600 text-white rounded-lg text-lg font-medium transition-all min-w-[200px]"
-          >
-            {addedToCart ? 'In Cart' : 'Add to Cart'}
-          </button>
-        </div>
-      </div>
-    </div>
-  );
-}

web/src/components/feats/hotel/HotelHero.tsx

@@ -1,9 +1,7 @@
 'use client';
 
 import { useState, FormEvent } from 'react';
-import { useRouter } from 'next/navigation';
 import { Button, Label, Input, DateInput, Dropdown, DropdownCounter } from '@/components/ui';
-import { dateToDaysFromToday } from '@/lib/hotel-utils';
 
 const LocationIcon = () => (
   <svg className="w-5 h-5" fill="none" stroke="currentColor" viewBox="0 0 24 24">
@@ -13,25 +11,14 @@ const LocationIcon = () => (
 );
 
 export default function HotelHero() {
-  const router = useRouter();
   const [destination, setDestination] = useState('');
   const [checkIn, setCheckIn] = useState('');
+  const [checkOut, setCheckOut] = useState('');
   const [guests, setGuests] = useState({ adults: 2, rooms: 1 });
 
   const handleSearch = (e: FormEvent) => {
     e.preventDefault();
-    const params = new URLSearchParams();
+    console.log({ destination, checkIn, checkOut, guests });
-
-    if (checkIn) {
-      const daysOffset = dateToDaysFromToday(checkIn);
-      params.set('dateIndex', daysOffset.toString());
-    }
-
-    if (destination) params.set('destination', destination);
-    params.set('adults', guests.adults.toString());
-    params.set('rooms', guests.rooms.toString());
-
-    router.push(`/hotel/products?${params.toString()}`);
   };
 
   return (
@@ -39,16 +26,16 @@ export default function HotelHero() {
       <div className="w-full max-w-4xl px-4">
         <div className="text-center mb-8">
           <h1 className="text-4xl md:text-5xl font-bold mb-4">
-            Find your perfect room
+            Find your perfect stay
           </h1>
           <p className="text-lg">
-            Search rooms, compare prices, and book with confidence
+            Search hotels, compare prices, and book with confidence
           </p>
         </div>
 
         <form onSubmit={handleSearch} className="search-form">
-          <div className="grid grid-cols-1 sm:grid-cols-2 lg:grid-cols-3 gap-4">
+          <div className="grid grid-cols-1 sm:grid-cols-2 lg:grid-cols-4 gap-4">
-            <div>
+            <div className="sm:col-span-2">
               <Label htmlFor="destination">Where to?</Label>
               <Input
                 type="text"
@@ -62,7 +49,7 @@ export default function HotelHero() {
             </div>
 
             <div>
-              <Label htmlFor="checkIn">Date (1 night stay)</Label>
+              <Label htmlFor="checkIn">Check-in</Label>
               <DateInput
                 id="checkIn"
                 value={checkIn}
@@ -72,27 +59,43 @@ export default function HotelHero() {
             </div>
 
             <div>
-              <Label htmlFor="guests">Guests</Label>
+              <Label htmlFor="checkOut">Check-out</Label>
-              <Dropdown label={`${guests.adults} ${guests.adults === 1 ? 'adult' : 'adults'}`}>
+              <DateInput
+                id="checkOut"
+                value={checkOut}
+                onChange={(e) => setCheckOut(e.target.value)}
+                required
+              />
+            </div>
+
+            <div className="sm:col-span-2 lg:col-span-4">
+              <Label htmlFor="guests">Guests & Rooms</Label>
+              <Dropdown label={`${guests.adults} ${guests.adults === 1 ? 'adult' : 'adults'}, ${guests.rooms} ${guests.rooms === 1 ? 'room' : 'rooms'}`}>
                 <DropdownCounter
                   label="Adults"
                   value={guests.adults}
                   min={1}
                   onChange={(v) => setGuests({ ...guests, adults: v })}
                 />
+                <DropdownCounter
+                  label="Rooms"
+                  value={guests.rooms}
+                  min={1}
+                  onChange={(v) => setGuests({ ...guests, rooms: v })}
+                />
               </Dropdown>
             </div>
 
-            <div className="sm:col-span-2 lg:col-span-3">
+            <div className="sm:col-span-2 lg:col-span-4">
               <Button type="submit" fullWidth>
-                Search Rooms
+                Search Hotels
               </Button>
             </div>
           </div>
         </form>
 
         <div className="mt-6 text-center text-sm">
-          <p>Over 2 million rooms worldwide · Best price guarantee · Free cancellation on most bookings</p>
+          <p>Over 2 million hotels worldwide · Best price guarantee · Free cancellation on most bookings</p>
         </div>
       </div>
     </div>

web/src/contexts/CartContext.tsx

@@ -1,76 +0,0 @@
-'use client';
-
-import { createContext, useContext, useState, useEffect, ReactNode } from 'react';
-
-export interface CartItem {
-  id: string;
-  type: 'hotel' | 'airline';
-  name: string;
-  price: number;
-  metadata: Record<string, unknown>;
-  dateIndex: number;
-}
-
-interface CartContextType {
-  items: CartItem[];
-  addItem: (item: CartItem) => void;
-  removeItem: (id: string) => void;
-  clearCart: () => void;
-  itemCount: number;
-}
-
-const CartContext = createContext<CartContextType | undefined>(undefined);
-
-const CART_KEY = 'phantom_cart';
-
-export const CartProvider = ({ children }: { children: ReactNode }) => {
-  const [items, setItems] = useState<CartItem[]>([]);
-  const [loaded, setLoaded] = useState(false);
-
-  // load cart from sessionStorage on mount
-  useEffect(() => {
-    const stored = sessionStorage.getItem(CART_KEY);
-    if (stored) {
-      try {
-        setItems(JSON.parse(stored));
-      } catch (e) {
-        console.error('[CART_LOAD]', e);
-      }
-    }
-    setLoaded(true);
-  }, []);
-
-  // persist to sessionStorage whenever cart changes
-  useEffect(() => {
-    if (!loaded) return;
-    sessionStorage.setItem(CART_KEY, JSON.stringify(items));
-  }, [items, loaded]);
-
-  const addItem = (item: CartItem) => {
-    setItems(prev => {
-      // prevent duplicates
-      if (prev.find(i => i.id === item.id)) return prev;
-      return [...prev, item];
-    });
-  };
-
-  const removeItem = (id: string) => {
-    setItems(prev => prev.filter(i => i.id !== id));
-  };
-
-  const clearCart = () => {
-    setItems([]);
-  };
-
-  return (
-    <CartContext.Provider value={{ items, addItem, removeItem, clearCart, itemCount: items.length }}>
-      {children}
-    </CartContext.Provider>
-  );
-};
-
-export const useCart = () => {
-  const ctx = useContext(CartContext);
-  if (!ctx) throw new Error('useCart must be used within CartProvider');
-  return ctx;
-};

web/src/hooks/useInteractionTracking.ts

@@ -1,5 +1,5 @@
 import { useEffect, useRef, useState } from 'react';
-import '@/lib/experiments'
+import '@/lib/experiments' // ensure experiments lib is loaded
 import type { EventName } from '@/lib/events';
 
 const fetchSessionId = async (): Promise<string> => {
@@ -21,14 +21,10 @@ const track = async (ev: {
   metadata?: Record<string, unknown>;
 }) => {
   try {
-    const experimentId = localStorage.getItem('phantom_experiment_id');
     await fetch('/api/ingest', {
       method: 'POST',
       headers: { 'Content-Type': 'application/json' },
-      body: JSON.stringify({
+      body: JSON.stringify(ev),
-        ...ev,
-        experimentId: experimentId || undefined,
-      }),
     });
   } catch (err) {
     console.error('track failed:', err);

web/src/lib/airline-utils.ts

@@ -1,75 +0,0 @@
-export interface AirlineProduct {
-  id: string;
-  flight_type: string;
-  date_index: number;
-  metadata: {
-    departure: { time: string; airport: string };
-    arrival: { time: string; airport: string };
-    duration: string;
-    stops: number;
-    cabin_class: string;
-    fare_rule: string;
-    refundable: boolean;
-    total?: number;
-    base_price: number;
-  };
-  availability: number;
-}
-
-export interface Flight {
-  id: string;
-  flightType: string;
-  departure: { time: string; airport: string };
-  arrival: { time: string; airport: string };
-  duration: string;
-  stops: number;
-  cabinClass: string;
-  fareRule: string;
-  refundable: boolean;
-  basePrice: number;
-  dateIndex: number;
-  availability: number;
-}
-
-const EPOCH = new Date(0);
-
-export const transformProduct = (p: AirlineProduct): Flight => {
-  const { id, flight_type, date_index, metadata, availability } = p;
-
-  return {
-    id,
-    flightType: flight_type,
-    departure: metadata.departure,
-    arrival: metadata.arrival,
-    duration: metadata.duration,
-    stops: metadata.stops,
-    cabinClass: metadata.cabin_class,
-    fareRule: metadata.fare_rule,
-    refundable: metadata.refundable,
-    basePrice: metadata.base_price,
-    dateIndex: date_index,
-    availability,
-  };
-};
-
-// convert date string to days from today
-export const dateToDaysFromToday = (dateStr: string): number => {
-  const target = new Date(dateStr);
-  target.setHours(0, 0, 0, 0);
-  const today = new Date();
-  today.setHours(0, 0, 0, 0);
-  return Math.floor((target.getTime() - today.getTime()) / 86400000);
-};
-
-// convert date string to date_index (days since epoch)
-export const dateToIndex = (dateStr: string): number => {
-  const d = new Date(dateStr);
-  return Math.floor((d.getTime() - EPOCH.getTime()) / 86400000);
-};
-
-// get current date_index
-export const todayIndex = (): number => {
-  const now = new Date();
-  now.setHours(0, 0, 0, 0);
-  return Math.floor((now.getTime() - EPOCH.getTime()) / 86400000);
-};

web/src/lib/hotel-utils.ts

@@ -1,71 +0,0 @@
-export interface HotelProduct {
-  id: string;
-  room_type: string;
-  date_index: number;
-  metadata: {
-    amenities?: string[];
-    total?: number;
-    image_url?: string;
-    base_price?: number;
-    name?: string;
-    refundable?: boolean;
-  };
-  availability: number;
-}
-
-export interface Hotel {
-  id: string;
-  name: string;
-  roomType: string;
-  checkIn: string;
-  checkOut: string;
-  dateIndex: number;
-  amenities: string[];
-  refundable: boolean;
-  pricePerNight: number;
-  nights: number;
-}
-
-const EPOCH = new Date(0);
-
-export const transformProduct = (p: HotelProduct): Hotel => {
-  const { id, room_type, date_index, metadata } = p;
-  const checkIn = new Date(EPOCH.getTime() + date_index * 86400000);
-  const nights = 1;
-  const checkOut = new Date(checkIn.getTime() + nights * 86400000);
-
-  return {
-    id,
-    name: metadata?.name || room_type,
-    roomType: room_type,
-    checkIn: checkIn.toLocaleDateString('en-US', { month: 'short', day: 'numeric' }),
-    checkOut: checkOut.toLocaleDateString('en-US', { month: 'short', day: 'numeric' }),
-    dateIndex: date_index,
-    amenities: metadata?.amenities || [],
-    refundable: metadata?.refundable || false,
-    pricePerNight: metadata?.base_price || 100,
-    nights,
-  };
-};
-
-// convert date string to days from today
-export const dateToDaysFromToday = (dateStr: string): number => {
-  const target = new Date(dateStr);
-  target.setHours(0, 0, 0, 0);
-  const today = new Date();
-  today.setHours(0, 0, 0, 0);
-  return Math.floor((target.getTime() - today.getTime()) / 86400000);
-};
-
-// convert date string to date_index (days since epoch)
-export const dateToIndex = (dateStr: string): number => {
-  const d = new Date(dateStr);
-  return Math.floor((d.getTime() - EPOCH.getTime()) / 86400000);
-};
-
-// get current date_index
-export const todayIndex = (): number => {
-  const now = new Date();
-  now.setHours(0, 0, 0, 0);
-  return Math.floor((now.getTime() - EPOCH.getTime()) / 86400000);
-};

web/src/lib/product-utils.ts

@@ -1,25 +0,0 @@
-import { HotelProduct, Hotel, transformProduct as transformHotel } from './hotel-utils';
-import { AirlineProduct, Flight, transformProduct as transformFlight } from './airline-utils';
-
-export type Product = Hotel | Flight;
-export type ProductRaw = HotelProduct | AirlineProduct;
-
-export const isHotelProduct = (p: ProductRaw): p is HotelProduct => {
-  return 'room_type' in p;
-};
-
-export const isAirlineProduct = (p: ProductRaw): p is AirlineProduct => {
-  return 'flight_type' in p;
-};
-
-export const transformProduct = (p: ProductRaw): Product => {
-  if (isHotelProduct(p)) {
-    return transformHotel(p);
-  }
-  return transformFlight(p);
-};
-
-export const getProductType = (p: Product): 'hotel' | 'airline' => {
-  if ('roomType' in p) return 'hotel';
-  return 'airline';
-};

web/src/proxy.ts

@@ -10,8 +10,6 @@ export function proxy(req: NextRequest) {
         pathname.startsWith('/admin') ||
         pathname.startsWith('/_next') ||
         pathname.startsWith('/static') ||
-        pathname.startsWith('/start-task') ||
-        pathname.startsWith('/cart') ||
         pathname.includes('.')
         // TODO: add robots.txt and sitemap.xml if needed here
     ) {

web/src/utils/supabase/client.ts

@@ -1,10 +0,0 @@
-import { createBrowserClient } from "@supabase/ssr";
-
-const supabaseUrl = process.env.NEXT_PUBLIC_SUPABASE_URL;
-const supabaseKey = process.env.NEXT_PUBLIC_SUPABASE_ANON_KEY;
-
-export const createClient = () =>
-    createBrowserClient(
-        supabaseUrl!,
-        supabaseKey!,
-    );

web/src/utils/supabase/middleware.ts

@@ -1,37 +0,0 @@
-import { createServerClient, type CookieOptions } from "@supabase/ssr";
-import { type NextRequest, NextResponse } from "next/server";
-
-const supabaseUrl = process.env.NEXT_PUBLIC_SUPABASE_URL;
-const supabaseKey = process.env.NEXT_PUBLIC_SUPABASE_ANON_KEY;
-
-export const createClient = (request: NextRequest) => {
-  // Create an unmodified response
-  let supabaseResponse = NextResponse.next({
-    request: {
-      headers: request.headers,
-    },
-  });
-
-  const supabase = createServerClient(
-    supabaseUrl!,
-    supabaseKey!,
-    {
-      cookies: {
-        getAll() {
-          return request.cookies.getAll()
-        },
-        setAll(cookiesToSet) {
-          cookiesToSet.forEach(({ name, value, options }) => request.cookies.set(name, value))
-          supabaseResponse = NextResponse.next({
-            request,
-          })
-          cookiesToSet.forEach(({ name, value, options }) =>
-            supabaseResponse.cookies.set(name, value, options)
-          )
-        },
-      },
-    },
-  );
-
-  return supabaseResponse
-};

web/src/utils/supabase/server.ts

@@ -1,27 +0,0 @@
-import { createServerClient, type CookieOptions } from "@supabase/ssr";
-import { cookies } from "next/headers";
-import { ReadonlyRequestCookies } from "next/dist/server/web/spec-extension/adapters/request-cookies";
-
-const supabaseUrl = process.env.NEXT_PUBLIC_SUPABASE_URL;
-const supabaseKey = process.env.NEXT_PUBLIC_SUPABASE_ANON_KEY;
-
-export const createClient = (cookieStore: ReadonlyRequestCookies) => {
-    return createServerClient(
-        supabaseUrl!,
-        supabaseKey!,
-        {
-            cookies: {
-                getAll() {
-                    return cookieStore.getAll()
-                },
-                setAll(cookiesToSet) {
-                    try {
-                        cookiesToSet.forEach(({ name, value, options }) => cookieStore.set(name, value, options))
-                    } catch {
-                        // `setAll` called from Server Component - ignored if middleware handles session refresh
-                    }
-                },
-            },
-        },
-    );
-};