Files
spark-control/image/app/config.py
T
Keysat 8d839e3714 v0.13.0:4 - redaction gateway, embeddings proxy, expanded audio API
- Add redaction gateway (redaction_gateway.py, redaction/ scrub + tests)
- Add embeddings proxy and spark_embed service (Dockerfile + main.py)
- Expand audio_proxy with speaker-aware handling; deep_health/health/server updates
- Package: configureSparks action + sparkConfig model updates, manifest/main wiring
- Docs: AUDIO_API, EMBEDDINGS, REDACTION_GATEWAY; HANDOFF and runbook/known-issues refresh
2026-06-11 17:45:57 -05:00

103 lines
3.7 KiB
Python

from __future__ import annotations
import os
from dataclasses import dataclass
from pathlib import Path
def _env(name: str, default: str = "") -> str:
return os.environ.get(name, default)
def _resolve_models_yaml() -> str:
if env := os.environ.get("MODELS_YAML"):
return env
here = Path(__file__).resolve().parent # app/
candidates = [
here.parent / "models.yaml", # image/models.yaml (Docker)
here.parent.parent / "models.yaml", # <repo>/models.yaml (dev)
Path("/app/models.yaml"), # explicit container path
]
for p in candidates:
if p.exists():
return str(p)
return str(candidates[0]) # let load fail with a clear path
@dataclass(frozen=True)
class Settings:
spark1_host: str
spark1_user: str
spark2_host: str
spark2_user: str
parakeet_host: str
parakeet_user: str
parakeet_container: str
kokoro_host: str
kokoro_user: str
kokoro_container: str
embed_host: str
embed_user: str
embed_container: str
qdrant_host: str
qdrant_user: str
qdrant_container: str
qdrant_collection: str
redaction_map_db: str
redaction_map_ttl: int
ssh_key_path: str
ssh_known_hosts: str
models_yaml: str
vllm_port: int
parakeet_port: int
kokoro_port: int
embed_port: int
qdrant_port: int
bind_port: int
open_webui_url: str
ngc_api_key: str
@classmethod
def from_env(cls) -> "Settings":
spark2_host = _env("SPARK2_HOST")
spark2_user = _env("SPARK2_USER")
# Parakeet (STT) and Kokoro (TTS) default to Spark 2 unless overridden.
return cls(
spark1_host=_env("SPARK1_HOST"),
spark1_user=_env("SPARK1_USER"),
spark2_host=spark2_host,
spark2_user=spark2_user,
parakeet_host=_env("PARAKEET_HOST") or spark2_host,
parakeet_user=_env("PARAKEET_USER") or spark2_user,
parakeet_container=_env("PARAKEET_CONTAINER") or "parakeet-asr",
kokoro_host=_env("KOKORO_HOST") or spark2_host,
kokoro_user=_env("KOKORO_USER") or spark2_user,
kokoro_container=_env("KOKORO_CONTAINER") or "kokoro-tts",
# Embeddings (spark-embed: bge-m3 dense + reranker) and Qdrant
# (vector storage) default to Spark 2 unless overridden.
embed_host=_env("EMBED_HOST") or spark2_host,
embed_user=_env("EMBED_USER") or spark2_user,
embed_container=_env("EMBED_CONTAINER") or "spark-embed",
qdrant_host=_env("QDRANT_HOST") or spark2_host,
qdrant_user=_env("QDRANT_USER") or spark2_user,
qdrant_container=_env("QDRANT_CONTAINER") or "qdrant",
qdrant_collection=_env("QDRANT_COLLECTION", ""),
# Redaction gateway pseudonym-map store (server-held de-anon key).
redaction_map_db=_env("REDACTION_MAP_DB", "/data/redaction_maps.db"),
redaction_map_ttl=int(_env("REDACTION_MAP_TTL", "7200")),
ssh_key_path=_env("SSH_KEY_PATH"),
ssh_known_hosts=_env("SSH_KNOWN_HOSTS"),
models_yaml=_resolve_models_yaml(),
vllm_port=int(_env("VLLM_PORT", "8888")),
parakeet_port=int(_env("PARAKEET_PORT", "8000")),
kokoro_port=int(_env("KOKORO_PORT", "8880")),
embed_port=int(_env("EMBED_PORT", "8088")),
qdrant_port=int(_env("QDRANT_PORT", "6333")),
bind_port=int(_env("BIND_PORT", "9999")),
open_webui_url=_env("OPEN_WEBUI_URL", ""),
ngc_api_key=_env("NGC_API_KEY", ""),
)
@property
def configured(self) -> bool:
return bool(self.spark1_host)