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05ae98abdb
reflect()/think() can now run on a different model than memory consolidation: INTROSPECTION_BACKEND / INTROSPECTION_MODEL (default to SUMMARY_BACKEND, so unset = unchanged). Consolidation (summaries/profile/narrative) keeps the capable model; her *voice* (reflections, thoughts) can run a steerable tune. dream.py lets reflect()/think() self-resolve to the introspection backend; both now thread a `model` override into llm.complete. Trial live: introspection -> dolphin3:8b on the 3090; consolidation -> Qwen-32B on the MI50. Suite 73 green, ruff clean. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
81 lines
4.2 KiB
Python
81 lines
4.2 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 # min thought salience to push (eager = ~0.7)
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ping_cooldown_min: int # min minutes between pushes (eager = 0)
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ping_quiet_hours: str # local "start-end" 24h window to stay silent, e.g. "1-9"
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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_cooldown_min=int(os.getenv("PING_COOLDOWN_MIN", "0")),
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ping_quiet_hours=os.getenv("PING_QUIET_HOURS", "1-9"),
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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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