89 lines
3.6 KiB
Python
89 lines
3.6 KiB
Python
"""Typed application settings: the only reader of environment variables."""
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from enum import StrEnum
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from pydantic_settings import BaseSettings, SettingsConfigDict
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class AppMode(StrEnum):
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"""Runtime mode: live Spotify + Anthropic, or fixture-replay demo."""
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LIVE = "live"
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DEMO = "demo"
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class Settings(BaseSettings):
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"""Application settings, loaded from the environment or a .env file."""
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model_config = SettingsConfigDict(env_file=".env", extra="ignore")
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app_mode: AppMode = AppMode.DEMO
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# Spotify application and OAuth. The redirect URI must exactly match a
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# URI registered in the Spotify developer dashboard, port included.
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spotify_client_id: str = ""
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spotify_redirect_uri: str = "http://127.0.0.1:8888/callback"
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spotify_api_base_url: str = "https://api.spotify.com/v1"
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# Set behind TLS so the session cookie is never sent over plain HTTP.
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session_cookie_secure: bool = False
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# A pre-authorized refresh token installs a session at startup, so a
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# hosted instance works without an interactive login.
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spotify_seed_refresh_token: str = ""
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# Spotify transport. A Retry-After above the cap fails the request
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# instead of silently holding it open for seconds.
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spotify_timeout_seconds: float = 10.0
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spotify_retry_after_cap_seconds: float = 5.0
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# LLM provider. Effort steers reasoning depth per call: intent is a
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# recall task, reranking benefits from more deliberation.
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anthropic_api_key: str = ""
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llm_model: str = "claude-sonnet-5"
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intent_effort: str = "low"
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rerank_effort: str = "medium"
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# Bound provider calls independently from the grounding deadline.
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llm_timeout_seconds: float = 120.0
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# Ceilings include adaptive thinking tokens, which is why they sit far
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# above the size of the structured output itself.
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intent_max_tokens: int = 16384
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rerank_max_tokens: int = 16384
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# Pipeline shape. candidate_count is the main call-1 latency lever and
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# the hallucination budget: at "new to you" familiarity a large share of
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# proposed tracks fails verification, so breadth keeps the pool filled.
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# The buffer gives the reranker real choices beyond the shown count.
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candidate_count: int = 35
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rerank_count: int = 15
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rerank_pool_buffer: int = 5
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# Grounding. Search is capped at 10 results per call, so resolving is a
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# fan-out; concurrency 6 stays far under the limiter (40 wide drew no
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# 429s when measured). Below the floor the response is an honest error
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# instead of a thin list. The similarity threshold rejects wrong tracks
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# while tolerating punctuation and edition noise.
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grounding_concurrency: int = 6
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grounding_floor: int = 8
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title_similarity_threshold: float = 0.82
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request_deadline_seconds: float = 25.0
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# In-process caches, single instance by design; a shared store is the
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# first production step. Resolution entries are small, so the bound is
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# generous; taste rarely shifts within a session.
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resolution_cache_ttl_seconds: float = 3600.0
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resolution_cache_max_entries: int = 2048
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taste_profile_ttl_seconds: float = 900.0
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# Demo replay paces recorded stream chunks so cards appear as they did live.
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demo_chunk_delay_seconds: float = 0.05
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# Taste profile fetch bounds: enough signal to describe a listener
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# without paging through an entire library on session start.
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top_items_limit: int = 50
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saved_tracks_limit: int = 100
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# Created playlists carry a fixed prefix so they can be found and
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# removed in bulk afterwards.
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playlist_name_prefix: str = "discovery-by-llm"
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settings = Settings()
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