feat: add key-free demo mode replaying recorded fixtures

backend/Dockerfile

@@ -6,11 +6,15 @@ RUN npm ci
 COPY frontend/ ./
 RUN npm run build
 
-FROM ghcr.io/astral-sh/uv:python3.13-bookworm-slim
-WORKDIR /srv
+FROM ghcr.io/astral-sh/uv:python3.13-bookworm-slim AS live
+WORKDIR /srv/backend
 COPY backend/pyproject.toml backend/uv.lock ./
 RUN uv sync --frozen --no-dev --no-install-project
 COPY backend/app ./app
+COPY eval/scenarios.yaml ../eval/scenarios.yaml
 COPY --from=frontend /build/dist ./app/static
 EXPOSE 8000
 CMD ["uv", "run", "--no-sync", "uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "8000"]
+
+FROM live AS demo
+COPY eval/fixtures ../eval/fixtures

backend/app/adapters/anthropic/llm.py

@@ -112,7 +112,7 @@ class AnthropicRecommender:
         if parsed is None:
             raise RecommenderOutputError("Intent response contained no structured output")
         validated = IntentOutput.model_validate(parsed.model_dump())
-        return _to_intent(validated)
+        return to_intent(validated)
 
     async def stream_rerank(
         self,
@@ -125,7 +125,7 @@ class AnthropicRecommender:
     ) -> AsyncGenerator[RerankSelection]:
         """Yield each complete valid selection while the JSON is streaming."""
         schema = transform_schema(RerankOutput.model_json_schema())
-        parser = _RecommendationObjectParser()
+        parser = RecommendationObjectParser()
         async with self.client.messages.stream(
             model=self.settings.llm_model,
             max_tokens=self.settings.rerank_max_tokens,
@@ -166,8 +166,11 @@ class AnthropicRecommender:
             raise RecommenderOutputError("Rerank response returned too many selections")
 
 
-class _RecommendationObjectParser:
+class RecommendationObjectParser:
+    """Incrementally extract complete recommendation objects from JSON text."""
+
     def __init__(self) -> None:
+        """Create an empty parser for one rerank response."""
         self.complete_text = ""
         self._scan_index = 0
         self._object_start: int | None = None
@@ -177,6 +180,7 @@ class _RecommendationObjectParser:
         self._has_found_array = False
 
     def feed(self, text_delta: str) -> list[RerankSelectionOutput]:
+        """Consume a text delta and return newly completed selections."""
         self.complete_text += text_delta
         if not self._has_found_array:
             match = _RECOMMENDATION_ARRAY.search(self.complete_text)
@@ -231,7 +235,8 @@ class _RecommendationObjectParser:
             raise RecommenderOutputError("Rerank item failed validation") from error
 
 
-def _to_intent(output: IntentOutput) -> Intent:
+def to_intent(output: IntentOutput) -> Intent:
+    """Map validated intent output to the application domain."""
     return Intent(
         mood=tuple(output.mood),
         activity=output.activity,

backend/app/adapters/demo/cassette.py

@@ -0,0 +1,128 @@
+"""Decode recorded Spotify and Anthropic responses for demo replay."""
+
+import base64
+import json
+from dataclasses import dataclass
+from functools import cache
+from pathlib import Path
+
+from app.adapters.demo.scenario import FIXTURE_ROOT
+
+
+@dataclass(frozen=True)
+class RecordedResponse:
+    """One decoded response retained from a recorded HTTP interaction."""
+
+    method: str
+    url: str
+    status: int
+    response_body: bytes
+    response_chunks: tuple[bytes, ...]
+
+    def json_body(self) -> object:
+        """Parse the decoded response body as JSON."""
+        return json.loads(self.response_body)
+
+
+@dataclass(frozen=True)
+class DemoCassette:
+    """The recorded service responses needed by one demo scenario."""
+
+    key: str
+    spotify_responses: tuple[RecordedResponse, ...]
+    intent_response_bodies: tuple[bytes, ...]
+    rerank_response_chunks: tuple[bytes, ...]
+
+    @property
+    def intent_response_body(self) -> bytes:
+        """Return the final intent response recorded for this scenario."""
+        return self.intent_response_bodies[-1]
+
+    @property
+    def spotify_search_responses(self) -> tuple[RecordedResponse, ...]:
+        """Return recorded Spotify search responses in capture order."""
+        return tuple(response for response in self.spotify_responses if "/search?" in response.url)
+
+    @property
+    def spotify_taste_responses(self) -> tuple[RecordedResponse, ...]:
+        """Return recorded Spotify taste responses in capture order."""
+        return tuple(
+            response
+            for response in self.spotify_responses
+            if any(
+                endpoint in response.url
+                for endpoint in ("/me/top/artists", "/me/top/tracks", "/me/tracks?")
+            )
+        )
+
+
+@cache
+def load_cassette(scenario_key: str) -> DemoCassette:
+    """Load and decode both service cassettes for one scenario."""
+    scenario_root = FIXTURE_ROOT / scenario_key
+    spotify = _load_responses(scenario_root / "spotify.json")
+    anthropic = _load_responses(scenario_root / "anthropic.json")
+    intent_responses = tuple(
+        response for response in anthropic if _is_anthropic_message(response.response_body)
+    )
+    rerank_responses = tuple(
+        response for response in anthropic if not _is_anthropic_message(response.response_body)
+    )
+    if not spotify or not intent_responses or not rerank_responses:
+        raise ValueError(f"Scenario cassette is incomplete: {scenario_key}")
+    return DemoCassette(
+        key=scenario_key,
+        spotify_responses=spotify,
+        intent_response_bodies=tuple(response.response_body for response in intent_responses),
+        rerank_response_chunks=rerank_responses[-1].response_chunks,
+    )
+
+
+def _load_responses(path: Path) -> tuple[RecordedResponse, ...]:
+    payload = json.loads(path.read_text(encoding="ascii"))
+    if not isinstance(payload, list):
+        raise ValueError(f"Cassette must contain a response list: {path}")
+    return tuple(_decode_response(entry) for entry in payload)
+
+
+def _decode_response(payload: object) -> RecordedResponse:
+    if not isinstance(payload, dict):
+        raise ValueError("Cassette response must be a mapping")
+    try:
+        chunks_value = payload["response_chunks_base64"]
+        if not isinstance(chunks_value, list):
+            raise TypeError
+        chunks = tuple(_decode_base64(value) for value in chunks_value)
+        return RecordedResponse(
+            method=_string(payload["method"]),
+            url=_string(payload["url"]),
+            status=_integer(payload["status"]),
+            response_body=_decode_base64(payload["response_body_base64"]),
+            response_chunks=chunks,
+        )
+    except (KeyError, TypeError, ValueError) as error:
+        raise ValueError("Cassette response is invalid") from error
+
+
+def _decode_base64(value: object) -> bytes:
+    return base64.b64decode(_string(value), validate=True)
+
+
+def _string(value: object) -> str:
+    if not isinstance(value, str):
+        raise TypeError
+    return value
+
+
+def _integer(value: object) -> int:
+    if not isinstance(value, int):
+        raise TypeError
+    return value
+
+
+def _is_anthropic_message(body: bytes) -> bool:
+    try:
+        payload = json.loads(body)
+    except (json.JSONDecodeError, UnicodeDecodeError):
+        return False
+    return isinstance(payload, dict) and payload.get("type") == "message"

backend/app/adapters/demo/catalog.py

@@ -0,0 +1,89 @@
+"""Spotify catalog adapter backed by one recorded demo cassette."""
+
+from collections import defaultdict
+from urllib.parse import parse_qs, urlparse
+
+from app.adapters.demo.cassette import DemoCassette, RecordedResponse
+from app.adapters.demo.scenario import normalize_text
+from app.adapters.spotify.mapping import (
+    parse_saved_track_page,
+    parse_search_tracks,
+    parse_top_artists,
+    parse_track_page,
+)
+from app.domain.models import Track
+from app.ports.protocols import TimeRange
+
+
+class DemoCatalog:
+    """Replay recorded Spotify search and taste responses without HTTP."""
+
+    def __init__(self, cassette: DemoCassette) -> None:
+        """Index one scenario cassette for deterministic request replay."""
+        self.cassette = cassette
+        self._search_pages = _index_search_pages(cassette.spotify_search_responses)
+        self._search_cursors: dict[str, int] = defaultdict(int)
+
+    async def search_tracks(self, query: str, limit: int = 10) -> list[Track]:
+        """Return the next recorded search page for a normalized query."""
+        normalized_query = normalize_text(query)
+        pages = self._search_pages.get(normalized_query, ())
+        cursor = self._search_cursors[normalized_query]
+        if cursor >= len(pages):
+            return []
+        self._search_cursors[normalized_query] += 1
+        return parse_search_tracks(pages[cursor].json_body())[:limit]
+
+    async def fetch_top_artists(self, time_range: TimeRange, limit: int) -> list[str]:
+        """Return the recorded synthetic top artists for a time range."""
+        response = self._taste_response("/me/top/artists", time_range)
+        return parse_top_artists(response.json_body())[:limit]
+
+    async def fetch_top_tracks(self, time_range: TimeRange, limit: int) -> list[Track]:
+        """Return the recorded synthetic top tracks for a time range."""
+        response = self._taste_response("/me/top/tracks", time_range)
+        return parse_track_page(response.json_body())[:limit]
+
+    async def fetch_saved_tracks(self, limit: int) -> list[Track]:
+        """Return recorded synthetic saved-track pages in offset order."""
+        responses = sorted(
+            (
+                response
+                for response in self.cassette.spotify_taste_responses
+                if urlparse(response.url).path.endswith("/me/tracks")
+            ),
+            key=_saved_track_offset,
+        )
+        tracks: list[Track] = []
+        for response in responses:
+            tracks.extend(parse_saved_track_page(response.json_body()))
+            if len(tracks) >= limit:
+                break
+        return tracks[:limit]
+
+    def _taste_response(self, endpoint: str, time_range: TimeRange) -> RecordedResponse:
+        for response in self.cassette.spotify_taste_responses:
+            parsed_url = urlparse(response.url)
+            query = parse_qs(parsed_url.query)
+            if parsed_url.path.endswith(endpoint) and query.get("time_range") == [time_range]:
+                return response
+        raise ValueError(f"Cassette lacks {endpoint} for {time_range}")
+
+
+def _index_search_pages(
+    responses: tuple[RecordedResponse, ...],
+) -> dict[str, tuple[RecordedResponse, ...]]:
+    pages: dict[str, list[RecordedResponse]] = defaultdict(list)
+    for response in responses:
+        query = parse_qs(urlparse(response.url).query).get("q")
+        if query:
+            pages[normalize_text(query[0])].append(response)
+    return {key: tuple(value) for key, value in pages.items()}
+
+
+def _saved_track_offset(response: RecordedResponse) -> int:
+    value = parse_qs(urlparse(response.url).query).get("offset", ["0"])[0]
+    try:
+        return int(value)
+    except ValueError:
+        return 0

backend/app/adapters/demo/pipeline.py

@@ -0,0 +1,78 @@
+"""Demo-only pipeline decorator for honest fuzzy replay disclosure."""
+
+import time
+from collections.abc import AsyncGenerator
+from contextlib import aclosing
+
+from app.adapters.demo.catalog import DemoCatalog
+from app.adapters.demo.recommender import DemoRecommender, parse_recorded_intent
+from app.adapters.demo.scenario import select_replay_scenario
+from app.config import Settings
+from app.domain.models import ConversationTurn, PreviousRecommendation, Track
+from app.pipeline.event import PipelineEvent, PipelineMetadataEvent, PipelineWarningEvent
+from app.pipeline.grounding import Grounder
+from app.pipeline.orchestrator import RecommendationPipeline
+from app.ports.protocols import MusicCatalog
+
+DEMO_REPLAY_CODE = "demo_replay"
+
+
+class DemoReplayPipeline:
+    """Decorate the real pipeline with a fuzzy-replay warning event."""
+
+    def __init__(self, settings: Settings) -> None:
+        """Create one cache-preserving pipeline with a replay recommender."""
+        self.settings = settings
+        self.pipeline = RecommendationPipeline(DemoRecommender(settings), settings)
+
+    async def stream(
+        self,
+        session_id: str,
+        request_id: str,
+        catalog: MusicCatalog,
+        query: str,
+        history: tuple[ConversationTurn, ...],
+        previous_recommendations: tuple[PreviousRecommendation, ...],
+    ) -> AsyncGenerator[PipelineEvent]:
+        """Stream the selected fixture and disclose non-exact selection."""
+        match = select_replay_scenario(query, bool(previous_recommendations))
+        seeded_pool = await self._prepare_refinement_pool(catalog)
+        event_stream = self.pipeline.stream(
+            session_id,
+            request_id,
+            catalog,
+            query,
+            history,
+            previous_recommendations,
+            seeded_pool=seeded_pool,
+        )
+        async with aclosing(event_stream) as events:
+            async for event in events:
+                yield event
+                if isinstance(event, PipelineMetadataEvent) and not match.is_exact:
+                    yield PipelineWarningEvent(
+                        code=DEMO_REPLAY_CODE,
+                        message=f'Demo replay is showing the recorded "{match.chip}" scenario.',
+                    )
+
+    async def _prepare_refinement_pool(
+        self,
+        catalog: MusicCatalog,
+    ) -> tuple[Track, ...] | None:
+        if not isinstance(catalog, DemoCatalog):
+            return None
+        intent_bodies = catalog.cassette.intent_response_bodies
+        if len(intent_bodies) < 2:
+            return None
+        # Refinement cassettes record the parent intent first and refinement intent last.
+        parent_intent = parse_recorded_intent(intent_bodies[0])
+        result = await Grounder(self.settings).ground(
+            catalog,
+            parent_intent.candidates,
+            # The recorded parent pool is listener-neutral, so replay has no known-track exclusions.
+            frozenset(),
+            parent_intent.familiarity,
+            self.settings.rerank_count + self.settings.rerank_pool_buffer,
+            time.monotonic() + self.settings.request_deadline_seconds,
+        )
+        return result.tracks

backend/app/adapters/demo/playlist.py

@@ -0,0 +1,28 @@
+"""Playlist writer that makes demo saves explicit and network-free."""
+
+import hashlib
+
+import structlog
+
+from app.domain.models import CreatedPlaylist
+
+
+class DemoPlaylistWriter:
+    """Simulate playlist writes with stable Spotify-shaped URLs."""
+
+    async def create_playlist(self, name: str, description: str) -> CreatedPlaylist:
+        """Return a deterministic fake playlist without an external write."""
+        digest = hashlib.sha256(f"{name}\n{description}".encode()).hexdigest()[:12]
+        playlist_id = f"demo-{digest}"
+        return CreatedPlaylist(
+            id=playlist_id,
+            url=f"https://open.spotify.com/playlist/{playlist_id}",
+        )
+
+    async def add_tracks_to_playlist(self, playlist_id: str, track_uris: list[str]) -> None:
+        """Log the simulated track addition without writing to Spotify."""
+        structlog.get_logger().info(
+            "demo_playlist_simulated",
+            playlist_id=playlist_id,
+            track_count=len(track_uris),
+        )

backend/app/adapters/demo/recommender.py

@@ -0,0 +1,128 @@
+"""Anthropic recommender adapter backed by recorded response chunks."""
+
+import asyncio
+import json
+from collections.abc import AsyncGenerator
+from contextvars import ContextVar
+
+from app.adapters.anthropic.llm import (
+    IntentOutput,
+    RecommendationObjectParser,
+    RerankOutput,
+    to_intent,
+)
+from app.adapters.demo.cassette import DemoCassette, load_cassette
+from app.adapters.demo.scenario import select_replay_scenario
+from app.config import Settings
+from app.domain.models import (
+    ConversationTurn,
+    Intent,
+    PreviousRecommendation,
+    RerankSelection,
+    Track,
+)
+from app.ports.protocols import RecommenderOutputError
+
+
+class DemoRecommender:
+    """Replay recorded intent and rerank output through live validation."""
+
+    def __init__(self, settings: Settings) -> None:
+        """Bind replay pacing and task-local scenario state."""
+        self.settings = settings
+        self._cassette: ContextVar[DemoCassette | None] = ContextVar(
+            "demo_recommender_cassette",
+            default=None,
+        )
+
+    async def create_intent(
+        self,
+        query: str,
+        history: tuple[ConversationTurn, ...],
+        previous_recommendations: tuple[PreviousRecommendation, ...],
+        taste_summary: str,
+        candidate_count: int,
+    ) -> Intent:
+        """Parse the selected scenario's recorded structured intent."""
+        match = select_replay_scenario(query, bool(previous_recommendations))
+        cassette = load_cassette(match.key)
+        self._cassette.set(cassette)
+        return parse_recorded_intent(cassette.intent_response_body)
+
+    async def stream_rerank(
+        self,
+        intent: Intent,
+        grounded_tracks: tuple[Track, ...],
+        taste_summary: str,
+        history: tuple[ConversationTurn, ...],
+        selection_count: int,
+        correction: str | None = None,
+    ) -> AsyncGenerator[RerankSelection]:
+        """Replay recorded SSE chunks through the live incremental parser."""
+        cassette = self._cassette.get()
+        if cassette is None:
+            raise RecommenderOutputError("Demo rerank has no selected scenario")
+        parser = RecommendationObjectParser()
+        async for text_delta in _text_deltas(
+            cassette.rerank_response_chunks,
+            self.settings.demo_chunk_delay_seconds,
+        ):
+            for selection in parser.feed(text_delta):
+                yield RerankSelection(selection.track_id, selection.justification)
+        try:
+            validated = RerankOutput.model_validate_json(parser.complete_text)
+        except ValueError as error:
+            raise RecommenderOutputError("Recorded rerank response is invalid") from error
+        if len(validated.recommendations) > selection_count:
+            raise RecommenderOutputError("Recorded rerank returned too many selections")
+
+
+def parse_recorded_intent(response_body: bytes) -> Intent:
+    """Parse an Anthropic message body through the live intent output model."""
+    try:
+        response = json.loads(response_body)
+        content = response["content"]
+        text = content[0]["text"]
+        if not isinstance(text, str):
+            raise TypeError
+        return to_intent(IntentOutput.model_validate_json(text))
+    except (IndexError, KeyError, TypeError, ValueError) as error:
+        raise RecommenderOutputError("Recorded intent response is invalid") from error
+
+
+async def _text_deltas(
+    chunks: tuple[bytes, ...],
+    delay_seconds: float,
+) -> AsyncGenerator[str]:
+    buffer = b""
+    for chunk_index, chunk in enumerate(chunks):
+        if chunk_index and delay_seconds > 0:
+            await asyncio.sleep(delay_seconds)
+        buffer += chunk
+        buffer = buffer.replace(b"\r\n", b"\n")
+        while b"\n\n" in buffer:
+            event, buffer = buffer.split(b"\n\n", 1)
+            text_delta = _event_text_delta(event)
+            if text_delta is not None:
+                yield text_delta
+    if buffer:
+        text_delta = _event_text_delta(buffer)
+        if text_delta is not None:
+            yield text_delta
+
+
+def _event_text_delta(event: bytes) -> str | None:
+    data_lines = [line[5:].strip() for line in event.splitlines() if line.startswith(b"data:")]
+    if not data_lines:
+        return None
+    try:
+        payload = json.loads(b"\n".join(data_lines))
+    except (json.JSONDecodeError, UnicodeDecodeError):
+        return None
+    if not isinstance(payload, dict) or payload.get("type") != "content_block_delta":
+        return None
+    delta = payload.get("delta")
+    if not isinstance(delta, dict) or delta.get("type") != "text_delta":
+        return None
+    text = delta.get("text")
+    return text if isinstance(text, str) else None

backend/app/adapters/demo/scenario.py

@@ -0,0 +1,151 @@
+"""Select replayable demo scenarios from the shared scenario catalog."""
+
+import re
+import unicodedata
+from dataclasses import dataclass
+from difflib import SequenceMatcher
+from functools import lru_cache
+from pathlib import Path
+
+import yaml
+
+_REPOSITORY_ROOT = Path(__file__).parents[4]
+SCENARIO_PATH = _REPOSITORY_ROOT / "eval" / "scenarios.yaml"
+FIXTURE_ROOT = _REPOSITORY_ROOT / "eval" / "fixtures"
+_WORD_PATTERN = re.compile(r"[a-z0-9]+")
+
+
+@dataclass(frozen=True)
+class Scenario:
+    """One shared suggestion and its optional parent scenario."""
+
+    key: str
+    chip: str
+    query: str
+    after: str | None = None
+
+    @property
+    def is_refinement(self) -> bool:
+        """Return whether this scenario refines an earlier result."""
+        return self.after is not None
+
+
+@dataclass(frozen=True)
+class ScenarioMatch:
+    """Describe which recorded scenario will answer a demo request."""
+
+    key: str
+    is_exact: bool
+    scenario_query: str
+    chip: str
+
+
+@lru_cache(maxsize=1)
+def load_scenarios() -> tuple[Scenario, ...]:
+    """Load and validate the shared scenario catalog once."""
+    payload = yaml.safe_load(SCENARIO_PATH.read_text(encoding="ascii"))
+    if not isinstance(payload, dict) or payload.get("version") != 1:
+        raise ValueError("Scenario catalog must have version 1")
+    entries = payload.get("scenarios")
+    if not isinstance(entries, list) or not entries:
+        raise ValueError("Scenario catalog must contain scenarios")
+    scenarios = tuple(_parse_scenario(entry) for entry in entries)
+    keys = {scenario.key for scenario in scenarios}
+    if len(keys) != len(scenarios):
+        raise ValueError("Scenario keys must be unique")
+    if any(scenario.after not in keys for scenario in scenarios if scenario.after is not None):
+        raise ValueError("Scenario catalog contains an unknown parent")
+    return scenarios
+
+
+def select_scenario(query: str) -> ScenarioMatch:
+    """Select an exact scenario or the nearest available recorded fixture."""
+    scenarios = _replayable_scenarios()
+    normalized_query = normalize_text(query)
+    for scenario in scenarios:
+        if normalized_query in {normalize_text(scenario.query), normalize_text(scenario.chip)}:
+            return _to_match(scenario, is_exact=True)
+
+    selected = max(
+        scenarios,
+        key=lambda scenario: max(
+            SequenceMatcher(None, normalized_query, normalize_text(scenario.query)).ratio(),
+            SequenceMatcher(None, normalized_query, normalize_text(scenario.chip)).ratio(),
+        ),
+    )
+    return _to_match(selected, is_exact=False)
+
+
+def select_replay_scenario(
+    query: str,
+    has_previous_recommendations: bool,
+) -> ScenarioMatch:
+    """Map a request with prior results to its recorded refinement when available."""
+    selected = select_scenario(query)
+    scenarios = _replayable_scenarios()
+    selected_scenario = next(scenario for scenario in scenarios if scenario.key == selected.key)
+    if selected_scenario.is_refinement or not has_previous_recommendations:
+        return selected
+    refinement = next(
+        (scenario for scenario in scenarios if scenario.after == selected_scenario.key),
+        None,
+    )
+    return _to_match(refinement, is_exact=False) if refinement is not None else selected
+
+
+def suggestion_items() -> list[dict[str, str]]:
+    """Return chip and query pairs for non-refinement scenarios."""
+    return [
+        {"chip": scenario.chip, "query": scenario.query}
+        for scenario in load_scenarios()
+        if not scenario.is_refinement
+    ]
+
+
+def normalize_text(value: str) -> str:
+    """Normalize text for exact and similarity matching."""
+    decomposed = unicodedata.normalize("NFKD", value.casefold())
+    ascii_text = decomposed.encode("ascii", errors="ignore").decode("ascii")
+    return " ".join(_WORD_PATTERN.findall(ascii_text))
+
+
+@lru_cache(maxsize=1)
+def _replayable_scenarios() -> tuple[Scenario, ...]:
+    fixture_keys = {path.name for path in FIXTURE_ROOT.iterdir() if path.is_dir()}
+    scenarios = tuple(scenario for scenario in load_scenarios() if scenario.key in fixture_keys)
+    if not scenarios:
+        raise ValueError("Demo mode requires at least one scenario fixture")
+    return scenarios
+
+
+def _parse_scenario(payload: object) -> Scenario:
+    if not isinstance(payload, dict):
+        raise ValueError("Each scenario must be a mapping")
+    required = {"key", "chip", "query", "facets"}
+    if not required <= set(payload):
+        raise ValueError("Scenario is missing a required field")
+    after = payload.get("after")
+    if after is not None and not isinstance(after, str):
+        raise ValueError("Scenario parent must be a key")
+    return Scenario(
+        key=_required_string(payload, "key"),
+        chip=_required_string(payload, "chip"),
+        query=_required_string(payload, "query"),
+        after=after,
+    )
+
+
+def _required_string(payload: dict[object, object], key: str) -> str:
+    value = payload.get(key)
+    if not isinstance(value, str) or not value:
+        raise ValueError(f"Scenario {key} must be a non-empty string")
+    return value
+
+
+def _to_match(scenario: Scenario, is_exact: bool) -> ScenarioMatch:
+    return ScenarioMatch(
+        key=scenario.key,
+        is_exact=is_exact,
+        scenario_query=scenario.query,
+        chip=scenario.chip,
+    )

backend/app/api/recommendations.py

@@ -1,4 +1,4 @@
-"""Authenticated recommendation streaming and playlist creation routes."""
+"""Recommendation streaming and playlist creation routes."""
 
 import asyncio
 from collections.abc import AsyncIterator, Callable
@@ -38,6 +38,10 @@ from app.pipeline.orchestrator import RecommendationPipeline
 from app.ports.protocols import MusicCatalog, PlaylistWriter
 
 SpotifyClientFactory = Callable[[SpotifySession], MusicCatalog | PlaylistWriter]
+MusicCatalogFactory = Callable[
+    [SpotifySession, str, tuple[PreviousRecommendation, ...]],
+    MusicCatalog,
+]
 
 router = APIRouter()
 
@@ -47,14 +51,12 @@ async def recommendations(
     request: Request,
     payload: RecommendationRequest,
 ) -> StreamingResponse:
-    """Stream one authenticated discovery response as NDJSON."""
+    """Stream one session-resolved discovery response as NDJSON."""
     resolved = resolve_session(request)
     if resolved is None:
         raise HTTPException(status_code=401, detail="Not authenticated")
 
     pipeline = cast(RecommendationPipeline, request.app.state.recommendation_pipeline)
-    factory = cast(SpotifyClientFactory, request.app.state.spotify_client_factory)
-    catalog = cast(MusicCatalog, factory(resolved.session))
     request_id = cast(str, request.state.request_id)
     history = tuple(ConversationTurn(turn.role, turn.content) for turn in payload.history)
     previous = tuple(
@@ -66,6 +68,8 @@ async def recommendations(
         )
         for item in payload.prior_recommendations
     )
+    factory = cast(MusicCatalogFactory, request.app.state.music_catalog_factory)
+    catalog = factory(resolved.session, payload.query, previous)
 
     return StreamingResponse(
         _stream_lines(
@@ -86,7 +90,7 @@ async def create_playlist(
     request: Request,
     payload: PlaylistCreateRequest,
 ) -> PlaylistCreateResponse:
-    """Create and fill one authenticated Spotify playlist."""
+    """Create and fill one live or simulated playlist."""
     resolved = resolve_session(request)
     if resolved is None:
         raise HTTPException(status_code=401, detail="Not authenticated")

backend/app/api/routes.py

@@ -1,4 +1,4 @@
-"""HTTP routes for Spotify login and session management."""
+"""HTTP routes for login and session management."""
 
 from dataclasses import dataclass
 from typing import cast
@@ -9,7 +9,7 @@ from fastapi.responses import JSONResponse, RedirectResponse, Response
 
 from app.adapters.spotify.login import begin_login, complete_login
 from app.adapters.spotify.session import PendingLogins, SessionStore, SpotifySession
-from app.config import Settings
+from app.config import AppMode, Settings
 
 SESSION_COOKIE_NAME = "discovery_session"
 
@@ -26,8 +26,10 @@ class ResolvedSession:
 
 @router.get("/api/auth/login")
 def login(request: Request) -> RedirectResponse:
-    """Start Spotify Authorization Code with PKCE login."""
+    """Start the configured live or demo login flow."""
     application_settings = cast(Settings, request.app.state.settings)
+    if application_settings.app_mode is AppMode.DEMO:
+        return RedirectResponse("/?login=demo", status_code=307)
     pending_logins = cast(PendingLogins, request.app.state.pending_logins)
     authorize_url = begin_login(application_settings, pending_logins)
     return RedirectResponse(authorize_url, status_code=307)
@@ -40,11 +42,13 @@ async def callback(
     state: str | None = None,
     error: str | None = None,
 ) -> RedirectResponse:
-    """Complete Spotify login and establish an opaque cookie session."""
+    """Complete live login and establish an opaque cookie session."""
+    application_settings = cast(Settings, request.app.state.settings)
+    if application_settings.app_mode is AppMode.DEMO:
+        return RedirectResponse("/?login=demo", status_code=307)
     if error is not None or code is None or state is None:
         return _login_error_redirect()
 
-    application_settings = cast(Settings, request.app.state.settings)
     http = cast(httpx2.AsyncClient, request.app.state.http)
     pending_logins = cast(PendingLogins, request.app.state.pending_logins)
     session_store = cast(SessionStore, request.app.state.session_store)
@@ -80,6 +84,12 @@ def current_session(request: Request) -> JSONResponse:
     return JSONResponse({"display_name": resolved.session.display_name})
 
 
+@router.get("/api/suggestions")
+def suggestions(request: Request) -> list[dict[str, str]]:
+    """Return shared non-refinement suggestion chips and queries."""
+    return cast(list[dict[str, str]], request.app.state.suggestions)
+
+
 @router.post("/api/auth/logout", status_code=204)
 def logout(request: Request) -> Response:
     """Remove the current application session and clear its cookie."""
@@ -105,7 +115,11 @@ def _login_error_redirect() -> RedirectResponse:
 
 
 def resolve_session(request: Request) -> ResolvedSession | None:
-    """Resolve the cookie session or the installed live seed session."""
+    """Resolve the stable demo identity, cookie, or live seed session."""
+    application_settings = cast(Settings, request.app.state.settings)
+    if application_settings.app_mode is AppMode.DEMO:
+        demo_session = cast(SpotifySession, request.app.state.demo_session)
+        return ResolvedSession("demo", demo_session)
     session_store = cast(SessionStore, request.app.state.session_store)
     cookie_session_id = request.cookies.get(SESSION_COOKIE_NAME)
     if cookie_session_id is not None:

backend/app/config.py

@@ -73,6 +73,9 @@ class Settings(BaseSettings):
     resolution_cache_max_entries: int = 2048
     taste_profile_ttl_seconds: float = 900.0
 
+    # Demo replay paces recorded stream chunks so cards appear as they did live.
+    demo_chunk_delay_seconds: float = 0.05
+
     # Taste profile fetch bounds: enough signal to describe a listener
     # without paging through an entire library on session start.
     top_items_limit: int = 50

backend/app/main.py

@@ -12,6 +12,11 @@ from fastapi import FastAPI
 from fastapi.staticfiles import StaticFiles
 
 from app.adapters.anthropic.llm import AnthropicRecommender
+from app.adapters.demo.cassette import load_cassette
+from app.adapters.demo.catalog import DemoCatalog
+from app.adapters.demo.pipeline import DemoReplayPipeline
+from app.adapters.demo.playlist import DemoPlaylistWriter
+from app.adapters.demo.scenario import select_replay_scenario, suggestion_items
 from app.adapters.spotify.auth import TokenSet, refresh_access_token
 from app.adapters.spotify.client import SpotifyClient
 from app.adapters.spotify.errors import SpotifyError
@@ -19,6 +24,7 @@ from app.adapters.spotify.session import PendingLogins, SessionStore, SpotifySes
 from app.api.recommendations import router as recommendations_router
 from app.api.routes import router
 from app.config import AppMode, Settings, settings
+from app.domain.models import PreviousRecommendation
 from app.observability.logging import configure_logging
 from app.observability.timing import RequestTimingMiddleware
 from app.pipeline.orchestrator import RecommendationPipeline
@@ -38,17 +44,35 @@ def create_app(
     @asynccontextmanager
     async def lifespan(application: FastAPI) -> AsyncIterator[None]:
         _validate_live_settings(active_settings)
+        application.state.session_store = SessionStore()
+        application.state.pending_logins = PendingLogins()
+        application.state.settings = active_settings
+        application.state.seed_session_id = None
+        application.state.suggestions = suggestion_items()
+        if active_settings.app_mode is AppMode.DEMO:
+            application.state.demo_session = _demo_session()
+            application.state.recommendation_pipeline = DemoReplayPipeline(active_settings)
+
+            def demo_catalog_factory(
+                session: SpotifySession,
+                query: str,
+                previous_recommendations: tuple[PreviousRecommendation, ...],
+            ) -> DemoCatalog:
+                match = select_replay_scenario(query, bool(previous_recommendations))
+                return DemoCatalog(load_cassette(match.key))
+
+            application.state.music_catalog_factory = demo_catalog_factory
+            application.state.spotify_client_factory = lambda session: DemoPlaylistWriter()
+            yield
+            return
+
         async with httpx2.AsyncClient(
             timeout=active_settings.spotify_timeout_seconds,
             transport=http_transport,
         ) as http:
             application.state.http = http
-            application.state.session_store = SessionStore()
-            application.state.pending_logins = PendingLogins()
-            application.state.settings = active_settings
-            application.state.seed_session_id = None
             anthropic_client = AsyncAnthropic(
-                api_key=active_settings.anthropic_api_key or "unused-demo-key",
+                api_key=active_settings.anthropic_api_key,
                 timeout=active_settings.llm_timeout_seconds,
                 http_client=anthropic_http_client,
             )
@@ -61,7 +85,15 @@ def create_app(
             def spotify_client_factory(session: SpotifySession) -> SpotifyClient:
                 return SpotifyClient(http, session, active_settings)
 
+            def music_catalog_factory(
+                session: SpotifySession,
+                query: str,
+                previous_recommendations: tuple[PreviousRecommendation, ...],
+            ) -> SpotifyClient:
+                return spotify_client_factory(session)
+
             application.state.spotify_client_factory = spotify_client_factory
+            application.state.music_catalog_factory = music_catalog_factory
             if (
                 active_settings.app_mode is AppMode.LIVE
                 and active_settings.spotify_seed_refresh_token
@@ -141,3 +173,11 @@ async def _install_seed_session(
             display_name=current_user.display_name,
         )
     )
+
+
+def _demo_session() -> SpotifySession:
+    return SpotifySession(
+        tokens=TokenSet(access_token="demo", refresh_token="demo", expires_at=float("inf")),
+        account_id="demo-listener",
+        display_name="Demo Listener",
+    )

backend/app/pipeline/orchestrator.py

@@ -118,6 +118,7 @@ class RecommendationPipeline:
         query: str,
         history: tuple[ConversationTurn, ...],
         previous_recommendations: tuple[PreviousRecommendation, ...],
+        seeded_pool: tuple[Track, ...] | None = None,
     ) -> AsyncGenerator[PipelineEvent]:
         """Yield ordered events for one recommendation request."""
         started_at = time.monotonic()
@@ -157,7 +158,9 @@ class RecommendationPipeline:
             candidate_count=len(intent.candidates),
         )
 
-        pool = await self._grounded_pool(session_id, catalog, intent, taste, deadline_at)
+        pool = await self._grounded_pool(
+            session_id, catalog, intent, taste, deadline_at, seeded_pool
+        )
         if not pool:
             yield PipelineErrorEvent(
                 code="no_grounded_results",
@@ -189,10 +192,13 @@ class RecommendationPipeline:
         intent: Intent,
         taste: CompressedTasteProfile,
         deadline_at: float,
+        seeded_pool: tuple[Track, ...] | None,
     ) -> tuple[Track, ...]:
-        """Reuse the session's pool on refinement, otherwise ground anew."""
+        """Reuse the seeded or session pool on refinement, otherwise ground anew."""
         if intent.is_refinement:
-            cached_pool = self.last_pools.get(session_id)
+            cached_pool = (
+                seeded_pool if seeded_pool is not None else self.last_pools.get(session_id)
+            )
             if cached_pool:
                 return cached_pool
         result = await self.grounder.ground(

backend/tests/test_anthropic_llm.py

@@ -2,12 +2,12 @@
 
 import pytest
 
-from app.adapters.anthropic.llm import _RecommendationObjectParser
+from app.adapters.anthropic.llm import RecommendationObjectParser
 from app.ports.protocols import RecommenderOutputError
 
 
 def test_parser_missing_object_start_raises_typed_output_error() -> None:
-    parser = _RecommendationObjectParser()
+    parser = RecommendationObjectParser()
 
     with pytest.raises(RecommenderOutputError, match="object start position"):
         parser._finish_object()

backend/tests/test_demo_adapters.py

@@ -0,0 +1,68 @@
+"""Offline replay tests for demo service adapters."""
+
+import asyncio
+
+from app.adapters.demo.cassette import load_cassette
+from app.adapters.demo.catalog import DemoCatalog
+from app.adapters.demo.recommender import DemoRecommender
+from app.config import Settings
+
+
+def test_cassette_decodes_bodies_and_preserves_rerank_chunks() -> None:
+    cassette = load_cassette("focus-coding")
+
+    assert cassette.intent_response_body.startswith(b'{"model"')
+    assert len(cassette.spotify_search_responses) > 20
+    assert len(cassette.spotify_taste_responses) == 6
+    assert len(cassette.rerank_response_chunks) > 1
+    assert b"event: content_block_delta" in b"".join(cassette.rerank_response_chunks)
+
+
+def test_demo_catalog_replays_search_and_synthetic_taste_pages() -> None:
+    async def run() -> None:
+        catalog = DemoCatalog(load_cassette("focus-coding"))
+
+        tracks = await catalog.search_tracks('track:"Stay" artist:"Hybrid Minds"')
+        artists = await catalog.fetch_top_artists("short_term", 50)
+        top_tracks = await catalog.fetch_top_tracks("long_term", 50)
+        saved_tracks = await catalog.fetch_saved_tracks(100)
+
+        assert tracks[0].title == "Stay"
+        assert artists[0] == "Synthetic Focus Artist"
+        assert {track.title for track in top_tracks} >= {
+            "Synthetic Focus Track",
+            "Synthetic Jazz Track",
+        }
+        assert saved_tracks[0].title == "Synthetic Saved Track"
+
+    asyncio.run(run())
+
+
+def test_demo_recommender_parses_intent_and_streams_recorded_rerank() -> None:
+    async def run() -> None:
+        recommender = DemoRecommender(Settings(demo_chunk_delay_seconds=0))
+        intent = await recommender.create_intent(
+            "Focus while coding",
+            (),
+            (),
+            "Synthetic taste",
+            35,
+        )
+        selections = [
+            selection
+            async for selection in recommender.stream_rerank(
+                intent,
+                (),
+                "Synthetic taste",
+                (),
+                15,
+            )
+        ]
+
+        assert intent.activity == "programming"
+        assert len(intent.candidates) == 35
+        assert len(selections) == 15
+        assert selections[0].track_id == "2nIixNuuV5eHCJydG5aYIB"
+        assert all(selection.justification for selection in selections)
+
+    asyncio.run(run())

backend/tests/test_demo_app.py

@@ -0,0 +1,208 @@
+"""Full HTTP contract tests for key-free demo mode."""
+
+import asyncio
+
+import httpx
+from fastapi.testclient import TestClient
+from pydantic import TypeAdapter
+from starlette.types import ASGIApp, Message, Receive, Scope, Send
+
+from app.adapters.demo.scenario import load_scenarios
+from app.api.schemas import StreamEvent
+from app.config import Settings
+from app.main import create_app
+
+
+class _MetadataBarrier:
+    """Pause one marked ASGI response immediately after its metadata event."""
+
+    def __init__(self, app: ASGIApp) -> None:
+        self.app = app
+        self.metadata_sent = asyncio.Event()
+        self.resume_response = asyncio.Event()
+
+    async def __call__(self, scope: Scope, receive: Receive, send: Send) -> None:
+        is_refinement = dict(scope.get("headers", ())).get(b"x-demo-request") == b"refinement"
+
+        async def send_with_barrier(message: Message) -> None:
+            await send(message)
+            if message["type"] == "http.response.body" and b'"type":"metadata"' in message.get(
+                "body", b""
+            ):
+                self.metadata_sent.set()
+                await self.resume_response.wait()
+
+        await self.app(scope, receive, send_with_barrier if is_refinement else send)
+
+
+def test_demo_request_streams_valid_events_without_a_session() -> None:
+    app = create_app(Settings(demo_chunk_delay_seconds=0))
+    with TestClient(app) as client:
+        response = client.post(
+            "/api/recommendations",
+            json={"schema_version": 1, "query": "Focus while coding"},
+        )
+
+    adapter: TypeAdapter[StreamEvent] = TypeAdapter(StreamEvent)
+    events = [adapter.validate_json(line) for line in response.text.splitlines()]
+    assert response.status_code == 200
+    assert events[0].type == "metadata"
+    assert events[-1].type == "done"
+    assert sum(event.type == "track" for event in events) == 15
+
+
+def test_unknown_demo_query_discloses_the_replayed_scenario_before_tracks() -> None:
+    app = create_app(Settings(demo_chunk_delay_seconds=0))
+    with TestClient(app) as client:
+        response = client.post(
+            "/api/recommendations",
+            json={"schema_version": 1, "query": "Focus while codign"},
+        )
+
+    adapter: TypeAdapter[StreamEvent] = TypeAdapter(StreamEvent)
+    events = [adapter.validate_json(line) for line in response.text.splitlines()]
+    warning_index = next(
+        index
+        for index, event in enumerate(events)
+        if event.type == "warning" and event.code == "demo_replay"
+    )
+    first_track_index = next(index for index, event in enumerate(events) if event.type == "track")
+    warning = events[warning_index]
+    assert warning_index < first_track_index
+    assert warning.type == "warning"
+    assert "Focus while coding" in warning.message
+
+
+def test_demo_refinement_reconstructs_the_pool_recorded_with_its_cassette() -> None:
+    app = create_app(Settings(demo_chunk_delay_seconds=0))
+    with TestClient(app) as client:
+        initial_response = client.post(
+            "/api/recommendations",
+            json={"schema_version": 1, "query": "Focus while coding"},
+        )
+        initial_adapter: TypeAdapter[StreamEvent] = TypeAdapter(StreamEvent)
+        initial_events: list[StreamEvent] = [
+            initial_adapter.validate_json(line) for line in initial_response.text.splitlines()
+        ]
+        prior_recommendations = [
+            {
+                "rank": event.rank,
+                "track_id": event.track.id,
+                "title": event.track.title,
+                "artists": event.track.artists,
+            }
+            for event in initial_events
+            if event.type == "track"
+        ]
+        response = client.post(
+            "/api/recommendations",
+            json={
+                "schema_version": 1,
+                "query": "More electronic",
+                "prior_recommendations": prior_recommendations,
+            },
+        )
+
+    adapter: TypeAdapter[StreamEvent] = TypeAdapter(StreamEvent)
+    events = [adapter.validate_json(line) for line in response.text.splitlines()]
+    warning_codes = [event.code for event in events if event.type == "warning"]
+    assert "rerank_fallback" not in warning_codes
+    assert sum(event.type == "track" for event in events) == 15
+
+
+def test_concurrent_demo_refinement_uses_its_request_local_recorded_pool() -> None:
+    async def run() -> None:
+        settings = Settings(demo_chunk_delay_seconds=0)
+        previous = [
+            {
+                "rank": 1,
+                "track_id": "previous",
+                "title": "Previous track",
+                "artists": ["Previous artist"],
+            }
+        ]
+        payload = {
+            "schema_version": 1,
+            "query": "More electronic",
+            "prior_recommendations": previous,
+        }
+
+        baseline_app = create_app(settings)
+        baseline_transport = httpx.ASGITransport(app=baseline_app)
+        async with (
+            baseline_app.router.lifespan_context(baseline_app),
+            httpx.AsyncClient(
+                transport=baseline_transport,
+                base_url="http://test",
+            ) as client,
+        ):
+            baseline_response = await client.post("/api/recommendations", json=payload)
+        baseline_events = _stream_events(baseline_response)
+        expected_track_ids = [event.track.id for event in baseline_events if event.type == "track"]
+
+        concurrent_app = create_app(settings)
+        barrier = _MetadataBarrier(concurrent_app)
+        transport = httpx.ASGITransport(app=barrier)
+        async with (
+            concurrent_app.router.lifespan_context(concurrent_app),
+            httpx.AsyncClient(transport=transport, base_url="http://test") as client,
+        ):
+            refinement_task = asyncio.create_task(
+                client.post(
+                    "/api/recommendations",
+                    json=payload,
+                    headers={"x-demo-request": "refinement"},
+                )
+            )
+            try:
+                await asyncio.wait_for(barrier.metadata_sent.wait(), timeout=2)
+                unrelated_response = await client.post(
+                    "/api/recommendations",
+                    json={"schema_version": 1, "query": "Energy for the gym"},
+                )
+            finally:
+                barrier.resume_response.set()
+            refinement_response = await refinement_task
+
+        events = _stream_events(refinement_response)
+        warning_codes = [event.code for event in events if event.type == "warning"]
+        track_ids = [event.track.id for event in events if event.type == "track"]
+        assert unrelated_response.status_code == 200
+        assert refinement_response.status_code == 200
+        assert "rerank_fallback" not in warning_codes
+        assert track_ids == expected_track_ids
+
+    asyncio.run(run())
+
+
+def test_demo_auth_playlist_and_suggestions_are_explicitly_simulated() -> None:
+    app = create_app(Settings(demo_chunk_delay_seconds=0))
+    with TestClient(app, follow_redirects=False) as client:
+        current_user = client.get("/api/auth/me")
+        login = client.get("/api/auth/login")
+        playlist = client.post(
+            "/api/playlists",
+            json={
+                "schema_version": 1,
+                "name": "Night drive",
+                "track_uris": ["spotify:track:demo"],
+            },
+        )
+        suggestions = client.get("/api/suggestions")
+
+    expected_suggestions = [
+        {"chip": scenario.chip, "query": scenario.query}
+        for scenario in load_scenarios()
+        if not scenario.is_refinement
+    ]
+    assert current_user.json() == {"display_name": "Demo Listener"}
+    assert login.headers["location"] == "/?login=demo"
+    assert playlist.json()["url"].startswith("https://open.spotify.com/playlist/demo-")
+    assert suggestions.json() == expected_suggestions
+    assert not hasattr(app.state, "http")
+    assert not hasattr(app.state, "anthropic")
+
+
+def _stream_events(response: httpx.Response) -> list[StreamEvent]:
+    adapter: TypeAdapter[StreamEvent] = TypeAdapter(StreamEvent)
+    return [adapter.validate_json(line) for line in response.text.splitlines()]

backend/tests/test_demo_scenario.py

@@ -0,0 +1,32 @@
+"""Tests for deterministic demo scenario selection."""
+
+from app.adapters.demo.scenario import select_replay_scenario, select_scenario
+
+
+def test_scenario_selection_prefers_normalized_exact_query_or_chip() -> None:
+    query_match = select_scenario("something calm for while I am programming, but not boring")
+    chip_match = select_scenario("  FOCUS, while CODING!  ")
+
+    assert query_match.key == "focus-coding"
+    assert query_match.is_exact
+    assert chip_match.key == "focus-coding"
+    assert chip_match.is_exact
+
+
+def test_scenario_selection_falls_back_to_nearest_fixture() -> None:
+    match = select_scenario("Focus while codign")
+
+    assert match.key == "focus-coding"
+    assert not match.is_exact
+
+
+def test_prior_results_select_a_matching_refinement_or_same_scenario() -> None:
+    refinement = select_replay_scenario("Focus while coding", True)
+    direct_refinement = select_replay_scenario("More electronic", False)
+    same_scenario = select_replay_scenario("Rainy Sunday", True)
+
+    assert refinement.key == "focus-coding-refine"
+    assert not refinement.is_exact
+    assert direct_refinement.key == "focus-coding-refine"
+    assert direct_refinement.is_exact
+    assert same_scenario.key == "rainy-sunday"

backend/tests/test_health.py

@@ -22,8 +22,14 @@ def test_anthropic_client_uses_configured_timeout(monkeypatch: pytest.MonkeyPatc
     constructor = Mock(return_value=anthropic_client)
     monkeypatch.setattr("app.main.AsyncAnthropic", constructor)
 
-    with TestClient(create_app(Settings(llm_timeout_seconds=42.0))) as client:
+    live_settings = Settings(
+        app_mode="live",
+        spotify_client_id="client-id",
+        anthropic_api_key="api-key",
+        llm_timeout_seconds=42.0,
+    )
+    with TestClient(create_app(live_settings)) as client:
         response = client.get("/api/health")
 
     assert response.status_code == 200
-    constructor.assert_called_once_with(api_key="unused-demo-key", timeout=42.0, http_client=None)
+    constructor.assert_called_once_with(api_key="api-key", timeout=42.0, http_client=None)

backend/tests/test_recommendation_api.py

@@ -12,6 +12,7 @@ from app.adapters.spotify.errors import SpotifyAuthenticationError
 from app.adapters.spotify.session import SessionStore, SpotifySession
 from app.api.routes import SESSION_COOKIE_NAME
 from app.api.schemas import StreamEvent
+from app.config import AppMode, Settings
 from app.domain.models import ConversationTurn, CreatedPlaylist, PreviousRecommendation, Track
 from app.main import create_app
 from app.pipeline.event import PipelineDoneEvent, PipelineMetadataEvent, PipelineTrackEvent
@@ -81,8 +82,13 @@ def test_recommendations_stream_lines_validate_against_frozen_schemas(
     assert [event.type for event in events] == ["metadata", "track", "done"]
 
 
-def test_recommendations_require_a_valid_session_without_seed() -> None:
-    with TestClient(create_app()) as client:
+def test_live_recommendations_require_a_valid_session_without_seed() -> None:
+    application_settings = Settings(
+        app_mode=AppMode.LIVE,
+        spotify_client_id="client-id",
+        anthropic_api_key="test-key",
+    )
+    with TestClient(create_app(application_settings)) as client:
         response = client.post(
             "/api/recommendations",
             json={"schema_version": 1, "query": "focused electronic music"},