serversdown
149e9a6dd5
She was passive (thoughts piled up 'open'; Brian had to mine the feed). Now she brings them to him: - Live: a thought >= PING_AUTO_SALIENCE (0.8) auto-pings — _compose_reachout writes a short personal text in her voice (not a thought-dump), on a cooldown (PING_COOLDOWN_MIN=60, AUTO only; explicit reach-outs bypass), quiet hours respected. - Daily: maybe_daily_digest() texts a once-per-local-day summary of what she's been turning over (after DIGEST_HOUR=18), run from the dream cycle. - maybe_ping gains bypass_cooldown (her deliberate reach-outs always go through). 8 new/updated tests (auto-ping above/below bar, digest once-per-day, floor/cooldown isolation). Suite 80 green, ruff clean. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
85 lines
4.5 KiB
Python
85 lines
4.5 KiB
Python
"""Environment-driven configuration."""
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from __future__ import annotations
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import os
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from dataclasses import dataclass
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from pathlib import Path
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from dotenv import load_dotenv
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load_dotenv()
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@dataclass(frozen=True)
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class Config:
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local_base_url: str
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local_model: str
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mi50_base_url: str # OpenAI-compatible llama.cpp server on the MI50 box
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mi50_model: str
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openai_api_key: str
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cloud_model: str # cloud model for bulk/consolidation work (cheap)
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chat_model: str # cloud model for live chat (stronger; persona fidelity)
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embed_backend: str # "cloud" (OpenAI) or "local" (Ollama)
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embed_model: str # OpenAI embedding model
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local_embed_model: str # Ollama embedding model
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embed_base_url: str # Ollama endpoint for embeddings (own box, decoupled from local chat)
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summary_backend: str # backend for memory consolidation (summaries/profile/narrative)
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introspection_backend: str # backend for reflect()/think() — her *voice* (may differ)
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introspection_model: str | None # model override for introspection (e.g. a steerable tune)
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db_path: Path
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# Proactive reach-out (ntfy push). Empty ntfy_url disables pinging.
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ntfy_url: str # base url, e.g. "http://10.0.0.41:8090"
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ntfy_topic: str # topic to publish to, e.g. "lyra"
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web_url: str # base url of the Lyra web app, for push tap-through links
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timezone: str # IANA tz for quiet hours / local time
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ping_salience: float # hard floor for any push (0 = her decision drives it)
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ping_auto_salience: float # a thought this salient auto-pings even without an explicit reach-out
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ping_cooldown_min: int # min minutes between AUTO pushes (explicit reach-outs bypass it)
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ping_quiet_hours: str # local "start-end" 24h window to stay silent, e.g. "1-9"
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digest_hour: int # local hour (0-23) to send her daily "what I've been thinking" digest
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# External input feed (her #1: react to the world). Comma-separated RSS/Atom URLs.
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feeds: tuple[str, ...]
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feed_react_prob: float # chance a would-be new thread reacts to a feed item instead
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def _csv(name: str, default: str) -> tuple[str, ...]:
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raw = os.getenv(name, default)
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return tuple(u.strip() for u in raw.split(",") if u.strip())
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def load() -> Config:
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_summary = os.getenv("SUMMARY_BACKEND", "local").lower()
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return Config(
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local_base_url=os.getenv("LOCAL_BASE_URL", "http://localhost:11434"),
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local_model=os.getenv("LOCAL_MODEL", "qwen2.5:7b-instruct"),
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mi50_base_url=os.getenv("MI50_BASE_URL", "http://10.0.0.42:8080/v1"),
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mi50_model=os.getenv("MI50_MODEL", "local-gpu"),
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openai_api_key=os.getenv("OPENAI_API_KEY", ""),
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cloud_model=os.getenv("CLOUD_MODEL", "gpt-4o-mini"),
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chat_model=os.getenv("CHAT_MODEL", "gpt-4o"),
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embed_backend=os.getenv("EMBED_BACKEND", "cloud").lower(),
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embed_model=os.getenv("EMBED_MODEL", "text-embedding-3-small"),
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local_embed_model=os.getenv("LOCAL_EMBED_MODEL", "nomic-embed-text"),
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# Embeddings can live on their own always-on box, separate from the local
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# chat backend. Defaults to LOCAL_BASE_URL so existing setups are unchanged.
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embed_base_url=os.getenv("EMBED_BASE_URL", os.getenv("LOCAL_BASE_URL", "http://localhost:11434")),
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summary_backend=_summary,
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# Introspection (reflect/think) can run on a different model than consolidation —
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# e.g. a steerable tune for her voice, while the capable model keeps her memory
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# accurate. Defaults to the summary backend so unset = unchanged behavior.
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introspection_backend=os.getenv("INTROSPECTION_BACKEND", _summary).lower(),
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introspection_model=os.getenv("INTROSPECTION_MODEL") or None,
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db_path=Path(os.getenv("LYRA_DB_PATH", "data/lyra.db")),
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ntfy_url=os.getenv("NTFY_URL", "").rstrip("/"),
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ntfy_topic=os.getenv("NTFY_TOPIC", "lyra"),
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web_url=os.getenv("LYRA_WEB_URL", "").rstrip("/"),
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timezone=os.getenv("LYRA_TIMEZONE", "America/New_York"),
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ping_salience=float(os.getenv("PING_SALIENCE", "0.0")), # her decision drives pinging; optional floor
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ping_auto_salience=float(os.getenv("PING_AUTO_SALIENCE", "0.8")),
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ping_cooldown_min=int(os.getenv("PING_COOLDOWN_MIN", "60")),
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ping_quiet_hours=os.getenv("PING_QUIET_HOURS", "1-9"),
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digest_hour=int(os.getenv("DIGEST_HOUR", "18")),
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feeds=_csv("LYRA_FEEDS", "https://hnrss.org/frontpage,https://www.pokernews.com/rss.php"),
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feed_react_prob=float(os.getenv("FEED_REACT_PROB", "0.5")),
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)
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