Files
project-lyra/lyra/config.py
T
serversdown 03aceec6fa feat(P3): mind/mouth split — separate voice model for the final reply (seam, default off)
The mind (chat backend/model) decides, reasons, and runs tools → a draft; the mouth
re-voices that draft in her character. Default: no mouth configured → the mind's
draft IS the reply, bit-for-bit the old behavior (and old streaming path untouched).

- config: MOUTH_BACKEND / MOUTH_MODEL. The slot for an eventual fine-tuned voice.
- chat: _mind_loop (tool/generation loop, non-stream, returns draft + tools_run),
  _voice_pass / mind.voice_messages (re-voice the draft, keep every fact/number),
  _mouth_target (active only when configured AND != mind). respond + respond_stream
  branch: mouth off = stream the mind directly (unchanged); mouth on = mind decides
  + runs tools, then the mouth streams the re-voiced reply. Falls back to the draft
  on any mouth failure (chat never breaks).
- Key payoff: the mouth needs no tool support (the mind handles tools), so it can be
  a non-tool character model (Dolphin / Claude / fine-tune). Makes the fine-tune
  easy: teach a small model to *sound* like Lyra, not to be smart.
- tests: mouth target on/off, voice_messages shape, voice_pass revoice+fallback.
  Suite 96 green, ruff clean.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-24 06:08:06 +00:00

94 lines
5.1 KiB
Python

"""Environment-driven configuration."""
from __future__ import annotations
import os
from dataclasses import dataclass
from pathlib import Path
from dotenv import load_dotenv
load_dotenv()
@dataclass(frozen=True)
class Config:
local_base_url: str
local_model: str
mi50_base_url: str # OpenAI-compatible llama.cpp server on the MI50 box
mi50_model: str
openai_api_key: str
cloud_model: str # cloud model for bulk/consolidation work (cheap)
chat_model: str # cloud model for live chat (stronger; persona fidelity)
embed_backend: str # "cloud" (OpenAI) or "local" (Ollama)
embed_model: str # OpenAI embedding model
local_embed_model: str # Ollama embedding model
embed_base_url: str # Ollama endpoint for embeddings (own box, decoupled from local chat)
summary_backend: str # backend for memory consolidation (summaries/profile/narrative)
introspection_backend: str # backend for reflect()/think() — her *voice* (may differ)
introspection_model: str | None # model override for introspection (e.g. a steerable tune)
db_path: Path
# Proactive reach-out (ntfy push). Empty ntfy_url disables pinging.
ntfy_url: str # base url, e.g. "http://10.0.0.41:8090"
ntfy_topic: str # topic to publish to, e.g. "lyra"
web_url: str # base url of the Lyra web app, for push tap-through links
timezone: str # IANA tz for quiet hours / local time
ping_salience: float # hard floor for any push (0 = her decision drives it)
ping_auto_salience: float # a thought this salient auto-pings even without an explicit reach-out
ping_cooldown_min: int # min minutes between AUTO pushes (explicit reach-outs bypass it)
ping_quiet_hours: str # local "start-end" 24h window to stay silent, e.g. "1-9"
digest_hour: int # local hour (0-23) to send her daily "what I've been thinking" digest
chat_deliberate: bool # think privately before answering substantive chat turns
# Mind/mouth split: the mind (the chat backend/model above) decides, reasons, and
# runs tools; the mouth re-voices the final reply in her character. Empty = mouth
# is the mind (no separate pass) — the slot for an eventual fine-tuned voice.
mouth_backend: str
mouth_model: str | None
# External input feed (her #1: react to the world). Comma-separated RSS/Atom URLs.
feeds: tuple[str, ...]
feed_react_prob: float # chance a would-be new thread reacts to a feed item instead
def _csv(name: str, default: str) -> tuple[str, ...]:
raw = os.getenv(name, default)
return tuple(u.strip() for u in raw.split(",") if u.strip())
def load() -> Config:
_summary = os.getenv("SUMMARY_BACKEND", "local").lower()
return Config(
local_base_url=os.getenv("LOCAL_BASE_URL", "http://localhost:11434"),
local_model=os.getenv("LOCAL_MODEL", "qwen2.5:7b-instruct"),
mi50_base_url=os.getenv("MI50_BASE_URL", "http://10.0.0.42:8080/v1"),
mi50_model=os.getenv("MI50_MODEL", "local-gpu"),
openai_api_key=os.getenv("OPENAI_API_KEY", ""),
cloud_model=os.getenv("CLOUD_MODEL", "gpt-4o-mini"),
chat_model=os.getenv("CHAT_MODEL", "gpt-4o"),
embed_backend=os.getenv("EMBED_BACKEND", "cloud").lower(),
embed_model=os.getenv("EMBED_MODEL", "text-embedding-3-small"),
local_embed_model=os.getenv("LOCAL_EMBED_MODEL", "nomic-embed-text"),
# Embeddings can live on their own always-on box, separate from the local
# chat backend. Defaults to LOCAL_BASE_URL so existing setups are unchanged.
embed_base_url=os.getenv("EMBED_BASE_URL", os.getenv("LOCAL_BASE_URL", "http://localhost:11434")),
summary_backend=_summary,
# Introspection (reflect/think) can run on a different model than consolidation —
# e.g. a steerable tune for her voice, while the capable model keeps her memory
# accurate. Defaults to the summary backend so unset = unchanged behavior.
introspection_backend=os.getenv("INTROSPECTION_BACKEND", _summary).lower(),
introspection_model=os.getenv("INTROSPECTION_MODEL") or None,
db_path=Path(os.getenv("LYRA_DB_PATH", "data/lyra.db")),
ntfy_url=os.getenv("NTFY_URL", "").rstrip("/"),
ntfy_topic=os.getenv("NTFY_TOPIC", "lyra"),
web_url=os.getenv("LYRA_WEB_URL", "").rstrip("/"),
timezone=os.getenv("LYRA_TIMEZONE", "America/New_York"),
ping_salience=float(os.getenv("PING_SALIENCE", "0.0")), # her decision drives pinging; optional floor
ping_auto_salience=float(os.getenv("PING_AUTO_SALIENCE", "0.8")),
ping_cooldown_min=int(os.getenv("PING_COOLDOWN_MIN", "60")),
ping_quiet_hours=os.getenv("PING_QUIET_HOURS", "1-9"),
digest_hour=int(os.getenv("DIGEST_HOUR", "18")),
chat_deliberate=os.getenv("CHAT_DELIBERATE", "true").lower() not in ("0", "false", "no"),
mouth_backend=os.getenv("MOUTH_BACKEND", "").lower(),
mouth_model=os.getenv("MOUTH_MODEL") or None,
feeds=_csv("LYRA_FEEDS", "https://hnrss.org/frontpage,https://www.pokernews.com/rss.php"),
feed_react_prob=float(os.getenv("FEED_REACT_PROB", "0.5")),
)