Files
spark-control/image/app/server.py
T
Keysat 7e0759846f v0.27.0:0 - in-app settings gear + swap-lock route fix
Move the ~20 optional cluster knobs out of the StartOS "Configure Sparks"
action (now just the 4 required fields) and into a dashboard ⚙ Settings gear,
backed by a /data/app_settings.json overlay keyed by env-var names. One shared
mutable Settings instance + Settings.reload() applies edits live without a
restart; existing installs' values migrate automatically on first boot.

Also: support-service ports (parakeet/kokoro/embed/qdrant + vllm) are now
configurable, and GET /api/swap/lock no longer 404s (it was shadowed by the
/api/swap/{job_id} catch-all). WebhookNotifier is re-pointed on save so its
url/secret reload live too.
2026-06-18 13:41:28 -05:00

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from __future__ import annotations
import asyncio
import json
import os
from pathlib import Path
from fastapi import FastAPI, HTTPException, Query, Request
from fastapi.responses import FileResponse, JSONResponse, StreamingResponse
from fastapi.staticfiles import StaticFiles
from pydantic import BaseModel, ValidationError
from typing import Literal
from . import app_settings
from .config import Settings
from .connectivity import get_mac, record_report, record_state, summary as connectivity_summary
from .coordination import LockHeld, ScheduleRegistry, SwapLockManager, WebhookNotifier, valid_schedule_id
from .custom_services import add_custom_service, delete_custom_service
from .audio_proxy import build_router as build_audio_router
from .deep_health import DeepHealth
from .discovery import build_menu, infer_recipe, repo_to_key
from .disk import delete_from_disk, probe_host, read_model_config
from .download import DownloadManager
from .llm_proxy import build_router as build_llm_router
from .embeddings_proxy import build_router as build_embeddings_router
from .redaction_gateway import build_router as build_redaction_router, MapStore
from .hardware import HardwareProbe
from .health import check_kokoro, check_parakeet, check_vllm, check_embeddings, check_qdrant, probe_vllm_endpoint
from .matrix_bridge import MatrixBridgeManager
from .models import ModelDef, load_catalog
from .nim import SUGGESTED_NIMS, CATALOG_URL, NimManager
from .overrides import add_custom, delete_custom, load_overrides, set_knobs
from .services import docker_state, run_action, services_from_settings
from .shellsafe import validate_container, validate_image, validate_repo
from .speech_models import SpeechModelsManager
from .ssh import ssh_run
from .swap import SwapManager
from .updates import UpdateManager, get_update_status
from .validate import validate_launch
from .wol import send_local_broadcast, send_via_peer
# One-time migration: seed the in-app settings overlay from env (values set via
# the StartOS action on a pre-gear install) before building Settings, so nothing
# is lost on upgrade. No-op once the overlay exists. See app_settings.
app_settings.seed_from_env(os.environ)
settings = Settings.from_env()
catalog = load_catalog(settings.models_yaml)
# Coordination layer (GPU arbiter): swap-lifecycle webhook, the swap reservation
# lock, and the read-only schedule registry. See coordination.py.
swap_webhook = WebhookNotifier(settings.swap_webhook_url, settings.swap_webhook_secret)
swap_lock = SwapLockManager()
schedule_registry = ScheduleRegistry()
swap_manager = SwapManager(settings, catalog, notifier=swap_webhook)
download_manager = DownloadManager(settings)
update_manager = UpdateManager(settings)
hardware_probe = HardwareProbe(settings)
nim_manager = NimManager(settings)
deep_health = DeepHealth(settings)
speech_models = SpeechModelsManager(settings)
matrix_bridge = MatrixBridgeManager(settings)
app = FastAPI(title="spark-control", version="0.1.0")
# ---- Same-origin (CSRF) guard on state-mutating control endpoints ----
# The app ships no API auth by design (LAN/VPN-only, no public interface). That
# makes the realistic remote threat a *browser-driven CSRF*: a malicious page open
# in the operator's browser silently POSTing to the control endpoints (swap, NIM
# install, service stop, disk delete, …) while they're on the trusted network.
# Browsers attach an Origin (and Referer) header to every cross-site state-changing
# request, so we reject mutating requests whose Origin/Referer hostname doesn't
# match the host the dashboard was served from. Programmatic consumers (Recap Relay,
# CRM, Open WebUI, …) hit the proxy/data surface below and send no browser Origin,
# so they're unaffected; the exempt prefixes are the cross-origin-by-design API.
_CSRF_SAFE_METHODS = {"GET", "HEAD", "OPTIONS", "TRACE"}
_CSRF_EXEMPT_PREFIXES = (
"/v1/", # OpenAI-compatible chat/audio/embeddings/rerank proxies
"/scrub", "/rehydrate", # redaction gateway (used by downstream apps)
"/api/search", # retrieval proxy
"/api/audio/", # diarize-chunk / label-merge / transcribe-with-speakers
"/api/health-event", # health reports posted by consumer apps
)
# Note: the coordination endpoints (/api/swap/lock, /api/schedule) are
# intentionally NOT exempt. External schedulers are non-browser clients (no
# Origin header) so they pass the guard already — same as /api/swap — while a
# malicious page can't drive them from the operator's browser. Don't add them.
@app.middleware("http")
async def csrf_guard(request, call_next):
if request.method not in _CSRF_SAFE_METHODS and not request.url.path.startswith(_CSRF_EXEMPT_PREFIXES):
origin = request.headers.get("origin") or request.headers.get("referer")
if origin:
from urllib.parse import urlparse
origin_host = urlparse(origin).hostname
req_host = (request.headers.get("host") or "").rsplit(":", 1)[0]
# Only block when we can positively identify a mismatch; absence of a
# header (non-browser client) or an unparseable Host falls through.
if origin_host and req_host and origin_host != req_host:
return JSONResponse(
status_code=403,
content={"detail": "cross-origin request to a control endpoint was blocked"},
)
return await call_next(request)
@app.on_event("startup")
async def _start_deep_health() -> None:
# Fire-and-forget; the loop catches its own exceptions.
asyncio.create_task(deep_health.run_periodic())
@app.on_event("shutdown")
async def _stop_deep_health() -> None:
deep_health.stop()
_STATIC_DIR = Path(__file__).resolve().parent / "static"
app.mount("/static", StaticFiles(directory=_STATIC_DIR), name="static")
# OpenAI-compatible audio proxy: /v1/audio/speech, /v1/audio/transcriptions, /v1/models.
# Lets Open WebUI, Home Assistant, and any other OpenAI-shaped client talk to
# Parakeet (STT) and Kokoro (TTS) through a single spark-control URL.
# Passing deep_health lets the proxy fire an immediate wedge-detect + auto-restart
# when Parakeet returns 500, instead of waiting up to 5 min for the periodic probe.
app.include_router(build_audio_router(settings, deep_health=deep_health))
# OpenAI-compatible LLM proxy: /v1/chat/completions, /v1/completions.
# Forwards to whatever vLLM is currently running on Spark 1 (per the LLM swap
# state). Supports SSE streaming when stream=true. Same trusted-host model
# as the audio proxy — clients only need one URL for everything.
app.include_router(build_llm_router(settings))
# OpenAI-compatible embeddings + rerank + hybrid search proxy:
# /v1/embeddings -> spark-embed (bge-m3 dense), /v1/rerank -> spark-embed
# (bge-reranker-v2-m3), /api/search -> orchestrated dense(+sparse) retrieval
# from Qdrant with optional cross-encoder rerank. Same single-trusted-host
# model as the LLM and audio proxies.
app.include_router(build_embeddings_router(settings))
# Redaction gateway: /scrub + /rehydrate. The privacy boundary between sovereign
# LP data and the Claude API — de-identify context before it leaves the box,
# re-identify Claude's response locally. The pseudonym map (the de-anon key) is
# held server-side in a TTL-swept store on /data and never leaves this host.
redaction_map_store = MapStore(settings.redaction_map_db, settings.redaction_map_ttl)
app.include_router(build_redaction_router(settings, redaction_map_store))
@app.get("/", include_in_schema=False)
async def index() -> FileResponse:
return FileResponse(_STATIC_DIR / "index.html")
@app.get("/api/config")
async def get_config() -> dict:
return {
"configured": settings.configured,
"spark1_host": settings.spark1_host,
"spark2_host": settings.spark2_host,
"vllm_port": settings.vllm_port,
"open_webui_url": settings.open_webui_url or None,
}
# ---- In-app settings ('gear') ----
# The optional cluster knobs (ports, container names, support-service hosts,
# integrations) live in an app-owned overlay on /data, edited here instead of in
# the StartOS action — which keeps to just the four required setup fields. See
# app_settings. Writes apply live: we rewrite the overlay then reload the shared
# Settings instance in place, so every router/manager holding the reference picks
# up the change with no container restart.
@app.get("/api/settings")
async def get_settings() -> dict:
return app_settings.public_view()
class SettingsUpdate(BaseModel):
values: dict[str, str]
@app.post("/api/settings")
async def post_settings(req: SettingsUpdate) -> dict:
try:
app_settings.apply(req.values)
except app_settings.SettingsError as e:
raise HTTPException(422, str(e))
settings.reload()
# WebhookNotifier snapshots url/secret (not the Settings object), so reload()
# can't reach it — re-point it explicitly so a webhook edit applies live too.
swap_webhook.update(settings.swap_webhook_url, settings.swap_webhook_secret)
return app_settings.public_view()
def _reload_catalog() -> None:
global catalog
catalog = load_catalog(settings.models_yaml)
swap_manager.reload_catalog(catalog)
def _recipe_summaries() -> list[dict]:
"""Known launch recipes (bundled + saved), for the download panel's autocomplete.
These are NOT the menu — the menu is what's on disk. This is just the set of
repos Spark Control already knows how to launch, so the download box can
suggest them by name without putting phantom cards on the dashboard."""
out = []
for m in catalog.models.values():
if m.repo:
out.append({"repo": m.repo, "display_name": m.display_name, "mode": m.mode})
return out
@app.get("/api/models")
async def get_models() -> dict:
"""The model menu = what's actually downloaded on the Sparks (one scan per
Spark), each annotated with its launch recipe or flagged `needs_setup`.
Does SSH, so it's the slower of the model endpoints; the front-end calls it on
load, after a swap/download/delete, and on a slow timer — not every poll."""
if not settings.configured:
return {"configured": False, "defaults": catalog.defaults.model_dump(), "models": {}, "recipes": []}
menu = await build_menu(settings, catalog)
return {
"configured": True,
"defaults": catalog.defaults.model_dump(),
"models": menu,
"recipes": _recipe_summaries(),
}
@app.get("/api/models/suggest")
async def suggest_model(repo: str = Query(...)) -> dict:
"""Read a downloaded model's config.json + size and propose a launch recipe.
Prefills the 'set up this model' form for an on-disk model that has no recipe
yet. The operator confirms/edits, then POSTs it to /api/models to save."""
if not settings.configured:
raise HTTPException(503, "spark1 not configured")
try:
validate_repo(repo)
except ValueError as e:
raise HTTPException(400, str(e))
hosts = [(settings.spark1_host, settings.spark1_user)]
if settings.spark2_host:
hosts.append((settings.spark2_host, settings.spark2_user))
# Config from whichever Spark has it; size summed across the Sparks that do.
sizes = await asyncio.gather(*(probe_host(h, u, repo, settings) for h, u in hosts))
total = sum(r.size_bytes for r in sizes if r.on_disk)
on_hosts = sum(1 for r in sizes if r.on_disk)
config = None
for (h, u), r in zip(hosts, sizes):
if r.on_disk:
config = await read_model_config(h, u, repo, settings)
if config is not None:
break
return infer_recipe(repo, config or {}, total, on_hosts)
class KnobsBody(BaseModel):
knobs: dict
@app.put("/api/models/{key}/knobs")
async def put_model_knobs(key: str, body: KnobsBody) -> dict:
if key not in catalog.models:
raise HTTPException(404, f"unknown model: {key}")
# Strip empty/None values
clean = {k: v for k, v in body.knobs.items() if v not in (None, "")}
set_knobs(key, clean)
_reload_catalog()
return {"ok": True, "key": key, "knobs": clean}
class CustomModelBody(BaseModel):
key: str
display_name: str
repo: str = ""
local_path: str | None = None
size_gb: float = 0
mode: Literal["solo", "cluster"] = "solo"
description: str | None = None
capabilities: list[str] = []
vllm_args: list[str] = []
knobs: dict | None = None
@app.post("/api/models")
async def post_model(body: CustomModelBody) -> dict:
if not body.key or not body.key.replace("-", "").replace("_", "").isalnum():
raise HTTPException(400, "key must be alphanumeric/-/_ only")
# Validate the full entry BEFORE persisting (exactly-one source, local-path
# whitelist, chat-template location). Doing it via ModelDef means the API and
# the YAML-override path share one set of rules, and a bad entry can't be
# written to /data and then break catalog load.
try:
ModelDef.model_validate(body.model_dump())
if body.repo:
validate_repo(body.repo) # HF charset (the model only validates local paths)
except ValidationError as e:
msg = e.errors()[0]["msg"] if e.errors() else str(e)
raise HTTPException(400, msg.removeprefix("Value error, "))
except ValueError as e:
raise HTTPException(400, str(e))
if body.key in catalog.models and not catalog.models[body.key].custom:
raise HTTPException(409, f"'{body.key}' is a bundled model — pick a different key")
add_custom(body.model_dump())
_reload_catalog()
return {"ok": True, "key": body.key}
@app.delete("/api/models/{key}")
async def del_model(key: str) -> dict:
if key not in catalog.models:
raise HTTPException(404, f"unknown model: {key}")
if not catalog.models[key].custom:
raise HTTPException(400, "cannot delete a bundled model; you may override its knobs instead")
delete_custom(key)
_reload_catalog()
return {"ok": True, "key": key}
@app.delete("/api/models/{key}/disk")
async def del_model_disk(key: str) -> dict:
"""Remove a model's weights from the Sparks — and thus from the menu, since the
menu IS the disk. Resolves the key against the live menu, so a discovered
model (no saved recipe) is deletable too.
Safety rails:
- Refuses a local/fine-tuned directory (hand-placed, not re-downloadable).
- Refuses if the model is currently loaded on vLLM.
- Refuses if a swap or this model's own download is in flight.
- Idempotent across both Sparks: an already-absent cache dir frees 0 bytes.
"""
if not settings.configured:
raise HTTPException(503, "spark1 not configured")
menu = await build_menu(settings, catalog)
entry = menu.get(key)
if entry is None:
raise HTTPException(404, f"unknown model: {key}")
# Never rm a local fine-tune directory from the dashboard — it's irreplaceable
# training output the user placed by hand, not a re-downloadable HF cache.
if entry.get("local_path"):
raise HTTPException(
400,
"this is a local model; its directory must be managed on the Spark, not deleted from here",
)
repo = entry["repo"]
# Refuse if currently loaded
try:
vllm = await check_vllm(settings)
except Exception:
vllm = {}
if vllm.get("ok") and vllm.get("current_model") == repo:
raise HTTPException(
409,
f"'{entry['display_name']}' is the currently loaded model. Switch to a different model first, then try again."
)
# Refuse if a swap is in flight
if swap_manager.current_job_id:
raise HTTPException(409, "a model swap is in progress; wait for it to finish")
# Refuse if a download is in flight for this same repo (a different model's download is fine)
if download_manager.current_job_id:
job = download_manager.get(download_manager.current_job_id)
if job and job.repo == repo:
raise HTTPException(409, "this model is currently downloading; cancel or wait for it to finish")
status = await delete_from_disk(repo, settings)
# Audit log
record_report(
f"disk:{key}",
ok=True,
source="disk-delete",
detail=f"freed {status.total_bytes} bytes across {len(status.per_host)} host(s)",
)
return {
"ok": True,
"key": key,
"repo": repo,
"bytes_freed": status.total_bytes,
"per_host": [
{"host": r.host, "size_bytes": r.size_bytes, **({"error": r.error} if r.error else {})}
for r in status.per_host
],
}
@app.get("/api/hardware")
async def get_hardware() -> dict:
"""Per-Spark hardware snapshot — RAM, disk, GPU mem + util, CPU load, uptime."""
return await hardware_probe.fetch()
@app.get("/api/connectivity")
async def get_connectivity() -> dict:
"""Up/down transition log per Spark + cached MACs."""
return connectivity_summary()
@app.get("/api/deep-health")
async def get_deep_health() -> dict:
"""Last result + auto-restart counters for each service's synthetic probe."""
return deep_health.summary()
@app.post("/api/deep-health/{service}/run")
async def run_deep_health(service: str) -> dict:
"""Manually run a single service's deep-health probe right now."""
if service not in deep_health.PROBES:
raise HTTPException(404, f"unknown service: {service}")
result = await deep_health.run_one(service)
return {
"ok": result.ok,
"at": result.at,
"latency_ms": result.latency_ms,
"error": result.error,
"note": result.note,
}
class HealthEventBody(BaseModel):
service: str # e.g. "parakeet", "kokoro", "vllm"
ok: bool # true on success, false on failure
source: str | None = None # what app reported (e.g. "open-webui")
error: str | None = None # optional detail
ms: int | None = None # optional latency
@app.post("/api/health-event")
async def post_health_event(body: HealthEventBody) -> dict:
"""Passive endpoint: any LAN app can POST here when its call to one of our
services succeeds or (more usefully) fails. We log the report into the
connectivity history so a brief blip that polling misses still surfaces.
Example:
curl -X POST http://<dashboard>/api/health-event \\
-H 'content-type: application/json' \\
-d '{"service":"parakeet","ok":false,"error":"503","source":"open-webui","ms":420}'
"""
if not body.service.strip():
raise HTTPException(400, "service is required")
event = record_report(
body.service.strip(),
ok=body.ok,
source=(body.source or "external").strip(),
detail=(body.error or "").strip(),
latency_ms=body.ms,
)
return {"ok": True, "recorded": event}
@app.post("/api/spark/{name}/wake")
async def wake_spark(name: str) -> dict:
"""Send a Wake-on-LAN magic packet for the named Spark.
Tries the OTHER Spark (if reachable) first because the packet has to
originate on the target's LAN segment to be reliable. Falls back to a
direct UDP broadcast from this container.
"""
if name not in ("spark1", "spark2"):
raise HTTPException(404, f"unknown spark: {name}")
mac = get_mac(name)
if not mac:
raise HTTPException(400, f"MAC for {name} not yet known; bring it up once so we can probe it, then this will work next time it sleeps")
# Find the peer's connectivity to decide the path.
other = "spark2" if name == "spark1" else "spark1"
other_host = settings.spark1_host if other == "spark1" else settings.spark2_host
other_user = settings.spark1_user if other == "spark1" else settings.spark2_user
delivered_via = None
via_peer_ok = False
via_peer_err = ""
if other_host and other_user:
via_peer_ok, via_peer_err = await send_via_peer(other_host, other_user, mac, settings)
if via_peer_ok:
delivered_via = other
if not via_peer_ok:
# Fall back to direct from this container
try:
send_local_broadcast(mac)
delivered_via = "container"
except Exception as e:
raise HTTPException(500, f"WoL failed: peer={via_peer_err!r} container={e!r}")
return {"ok": True, "spark": name, "mac": mac, "delivered_via": delivered_via}
@app.post("/api/spark/{name}/ssh-key")
async def spark_ssh_key(name: str) -> dict:
"""Ensure the named Spark has an ed25519 keypair and return its PUBLIC key.
This is the Spark's *outbound* identity — the key it uses to log in to other
machines (e.g. the operator's Mac). It is the opposite direction from, and
distinct from, the package's own key shown by the StartOS "Show Public Key"
action (which grants this dashboard SSH access to the Sparks).
Non-destructive: generates the key only if absent, never overwrites an
existing one (which may already be an identity the Spark uses elsewhere).
Public keys are not secret, so returning it is safe. No request-supplied
value reaches the command — `name` is constrained to a fixed set and
host/user come from operator config — so there is nothing to shell-quote.
"""
if name not in ("spark1", "spark2"):
raise HTTPException(404, f"unknown spark: {name}")
host = settings.spark1_host if name == "spark1" else settings.spark2_host
user = settings.spark1_user if name == "spark1" else settings.spark2_user
if not host or not user:
raise HTTPException(400, f"{name} is not configured")
# Empty passphrase so the key is usable unattended; comment carries the
# remote hostname so it's identifiable in an authorized_keys file later.
cmd = (
"set -e; "
"mkdir -p ~/.ssh && chmod 700 ~/.ssh; "
"if [ ! -f ~/.ssh/id_ed25519 ]; then "
'ssh-keygen -t ed25519 -N "" -C "spark-control@$(hostname)" -f ~/.ssh/id_ed25519 >/dev/null 2>&1; '
"echo CREATED=1; else echo CREATED=0; fi; "
"[ -f ~/.ssh/id_ed25519.pub ] || ssh-keygen -y -f ~/.ssh/id_ed25519 > ~/.ssh/id_ed25519.pub; "
"echo PUBKEY=$(cat ~/.ssh/id_ed25519.pub)"
)
rc, out, err = await ssh_run(host, user, cmd, settings, timeout=15)
if rc != 0:
raise HTTPException(502, f"couldn't read/create the SSH key on {name}: {err.strip() or out.strip() or f'rc={rc}'}")
created = False
pubkey = ""
for line in out.splitlines():
if line.startswith("CREATED="):
created = line.strip() == "CREATED=1"
elif line.startswith("PUBKEY="):
pubkey = line[len("PUBKEY="):].strip()
if not pubkey:
raise HTTPException(502, f"no public key returned from {name}")
return {"ok": True, "spark": name, "host": host, "user": user, "pubkey": pubkey, "created": created}
@app.get("/api/services")
async def get_services() -> dict:
"""Lifecycle state of always-on support services (Parakeet, Kokoro, …).
Each entry includes:
- host/port/container/user (configured)
- state: docker container status (running | exited | restarting | missing | unconfigured)
- http_ready: whether the service's /health endpoint responded
- base_url
- model (if reported by the service)
- restart_count
"""
services = services_from_settings(settings)
out: dict[str, dict] = {}
async def one(name: str):
svc = services[name]
docker = await docker_state(settings, svc)
if name == "parakeet":
http = await check_parakeet(settings)
elif name == "kokoro":
http = await check_kokoro(settings)
elif name == "embeddings":
http = await check_embeddings(settings)
elif name == "qdrant":
http = await check_qdrant(settings)
elif svc.kind == "vllm":
# An extra vLLM monitored on another Spark (registered as a custom
# service). Probe its own host/port, not the primary Spark 1 one.
http = await probe_vllm_endpoint(svc.host, svc.port)
elif svc.kind == "bot":
# No HTTP health endpoint (host networking, no port) — judged purely
# by docker state. http_ready stays None so the badge isn't pinned
# to a "Starting…" verdict that can never clear.
http = {"ok": None, "base_url": None}
else:
# Custom services expose a /health endpoint by convention.
http = await check_kokoro(settings) if svc.kind == "tts" else {"ok": None, "base_url": svc.host and f"http://{svc.host}:{svc.port}"}
return name, {
"host": svc.host,
"user": svc.user,
"port": svc.port,
"container": svc.container,
"kind": svc.kind,
"base_url": http.get("base_url"),
# None (not False) for services with no HTTP surface (the bot), so
# the UI judges them by docker state alone instead of "Starting…".
"http_ready": None if svc.kind == "bot" else bool(http.get("ok")),
# Prefer the check fn's own top-level model key (embeddings reports
# it there); fall back to a model field inside detail for services
# whose /health embeds it (parakeet).
"model": http.get("model") or http.get("current_model") or ((http.get("detail") or {}).get("model") if isinstance(http.get("detail"), dict) else None),
"docker_state": docker.get("state"),
"restart_count": docker.get("restart_count"),
"started_at": docker.get("started_at"),
"exit_code": docker.get("exit_code"),
"error": docker.get("error"),
"detail": http.get("detail"),
}
results = await asyncio.gather(*[one(n) for n in services.keys()])
for name, info in results:
out[name] = info
# Feed http reachability into the connectivity log (transition-only).
# Skip services with no HTTP surface (http_ready is None) — they'd
# otherwise register as perpetually "down".
if info.get("http_ready") is not None:
record_state(name, bool(info.get("http_ready")))
return out
@app.get("/api/nim/catalog")
async def get_nim_catalog() -> dict:
return {
"catalog_url": CATALOG_URL,
"ngc_key_configured": bool(settings.ngc_api_key),
"suggested": SUGGESTED_NIMS,
}
class NimInstallBody(BaseModel):
image: str
container: str
port: int
host: Literal["spark1", "spark2"] = "spark2"
kind: str = ""
register: bool = True # write to custom services overrides after install
@app.post("/api/nim/install")
async def post_nim_install(body: NimInstallBody) -> dict:
try:
validate_image(body.image)
validate_container(body.container)
except ValueError as e:
raise HTTPException(400, str(e))
target_host = settings.spark1_host if body.host == "spark1" else settings.spark2_host
target_user = settings.spark1_user if body.host == "spark1" else settings.spark2_user
try:
job = await nim_manager.trigger(
image=body.image,
container=body.container,
port=body.port,
host=target_host,
user=target_user,
)
except RuntimeError as e:
raise HTTPException(409 if "in progress" in str(e) else 400, str(e))
if body.register:
# Persist in custom services so the panel shows it after install.
add_custom_service({
"key": body.container,
"kind": body.kind or "nim",
"host": target_host,
"user": target_user,
"container": body.container,
"port": body.port,
"image": body.image,
})
return {"job_id": job.id, "image": job.image, "container": job.container, "state": job.state}
@app.get("/api/nim/install/{job_id}")
async def get_nim_install(job_id: str) -> dict:
job = nim_manager.get(job_id)
if job is None:
raise HTTPException(404, "no such job")
return {
"id": job.id,
"image": job.image,
"container": job.container,
"port": job.port,
"host": job.host,
"state": job.state,
"phase": job.phase,
"started_at": job.started_at,
"finished_at": job.finished_at,
"returncode": job.returncode,
"lines": job.lines,
}
@app.get("/api/nim/install/{job_id}/stream")
async def stream_nim_install(job_id: str):
job = nim_manager.get(job_id)
if job is None:
raise HTTPException(404, "no such job")
async def gen():
sent = 0
last_phase = None
while True:
n = len(job.lines)
if n > sent:
for line in job.lines[sent:n]:
yield f"data: {json.dumps({'line': line})}\n\n"
sent = n
if job.phase != last_phase:
yield f"event: phase\ndata: {json.dumps({'state': job.state, 'phase': job.phase})}\n\n"
last_phase = job.phase
if job.returncode is not None and sent >= len(job.lines):
yield f"event: done\ndata: {json.dumps({'state': job.state, 'returncode': job.returncode})}\n\n"
return
await asyncio.sleep(0.5)
return StreamingResponse(gen(), media_type="text/event-stream")
@app.delete("/api/services/{name}")
async def del_service(name: str) -> dict:
# Only allow deleting custom services (not the bundled built-in keys)
if name in ("parakeet", "kokoro", "embeddings", "qdrant", "matrix-bridge"):
raise HTTPException(400, "built-in service; cannot delete (use Configure Sparks to point at a different host)")
delete_custom_service(name)
return {"ok": True, "name": name}
@app.post("/api/services/{name}/{action}")
async def service_action(name: str, action: str) -> dict:
services = services_from_settings(settings)
if name not in services:
raise HTTPException(404, f"unknown service: {name}")
if action not in ("start", "stop", "restart"):
raise HTTPException(400, f"unknown action: {action}")
result = await run_action(settings, services[name], action) # type: ignore[arg-type]
if not result["ok"]:
raise HTTPException(500, result.get("stderr") or result.get("error") or "action failed")
return {"name": name, "action": action, **result}
# ---- matrix-bridge bot: update (git pull + rebuild) + logs ----
# Status badge + start/stop/restart ride the generic /api/services machinery
# above (the bot is a registered ServiceDef). Only the long-running Update and
# the logs view need bespoke endpoints.
def _serialize_mb_update(job) -> dict:
return {
"id": job.id,
"state": job.state,
"phase": job.phase,
"started_at": job.started_at,
"finished_at": job.finished_at,
"returncode": job.returncode,
"lines": job.lines,
}
@app.post("/api/matrix-bridge/update")
async def post_matrix_bridge_update() -> dict:
"""Pull latest code, rebuild, and recreate the bot container. Long-running
(docker build) — returns a job id to stream."""
try:
job = await matrix_bridge.trigger_update()
except RuntimeError as e:
raise HTTPException(409 if "in progress" in str(e) else 503, str(e))
return {"job_id": job.id, "state": job.state}
@app.get("/api/matrix-bridge/update/{job_id}")
async def get_matrix_bridge_update(job_id: str) -> dict:
job = matrix_bridge.get(job_id)
if job is None:
raise HTTPException(404, "no such job")
return _serialize_mb_update(job)
@app.get("/api/matrix-bridge/update/{job_id}/stream")
async def stream_matrix_bridge_update(job_id: str, request: Request):
job = matrix_bridge.get(job_id)
if job is None:
raise HTTPException(404, "no such job")
async def gen():
sent = 0
last_phase = None
while True:
# An update can run for minutes; bail promptly if the client is gone
# rather than spinning the poll loop until the job's 25-min ceiling.
if await request.is_disconnected():
return
n = len(job.lines)
if n > sent:
for line in job.lines[sent:n]:
yield f"data: {json.dumps({'line': line})}\n\n"
sent = n
if job.phase != last_phase:
yield f"event: phase\ndata: {json.dumps({'state': job.state, 'phase': job.phase})}\n\n"
last_phase = job.phase
if job.returncode is not None and sent >= len(job.lines):
yield f"event: done\ndata: {json.dumps({'state': job.state, 'returncode': job.returncode})}\n\n"
return
await asyncio.sleep(0.5)
return StreamingResponse(gen(), media_type="text/event-stream")
@app.get("/api/matrix-bridge/logs")
async def get_matrix_bridge_logs(tail: int = Query(100, ge=1, le=1000)) -> dict:
"""Last N lines of `docker logs` for the bot container (stderr merged)."""
result = await matrix_bridge.fetch_logs(tail=tail)
if not result.get("ok"):
raise HTTPException(502, result.get("output") or result.get("error") or "could not read logs")
return result
# ---- Speech model patch management ----
@app.get("/api/speech-models")
async def get_speech_models() -> dict:
"""Status of the parakeet-asr container + the spark-control overlay patches
(diarizer.py + main.py). Drift between local shipped patches and what's
inside the container is surfaced so the UI can prompt for reapply."""
return await speech_models.status()
@app.post("/api/speech-models/reapply")
async def post_speech_models_reapply() -> dict:
"""Copy spark-control's shipped diarizer.py + patched main.py into the
parakeet-asr container, verify Python syntax, restart the container, and
wait for both models (Parakeet ASR + Sortformer) to reload. ~60120 seconds."""
try:
result = await speech_models.reapply_patches()
except RuntimeError as e:
raise HTTPException(409, str(e))
if not result.get("ok"):
# Bubble up which step failed for client-side error rendering.
raise HTTPException(500, {"detail": "patch reapply failed", "result": result})
return result
@app.post("/api/speech-models/restart")
async def post_speech_models_restart() -> dict:
"""`docker restart parakeet-asr` only — no file changes. Useful when the
container's models look wedged but patches are already current."""
try:
result = await speech_models.restart_container()
except RuntimeError as e:
raise HTTPException(409, str(e))
if not result.get("ok"):
raise HTTPException(500, {"detail": "container restart failed", "result": result})
return result
# NOTE: a WhisperX-on-Spark-2 install action lived here briefly in v0.12.0:04
# but was reverted in v0.13.0:0. NGC's custom-versioned torch on ARM64 made
# building torchaudio (which WhisperX needs via pyannote) unworkable. The
# existing Parakeet + Sortformer pipeline stays as the audio path.
@app.get("/api/endpoints")
async def get_endpoints() -> dict:
"""Service-discovery summary. Stable shape; other apps on the LAN can poll this
to learn the OpenAI-compatible vLLM endpoint, the Parakeet STT endpoint, the
Kokoro TTS endpoint, and the embeddings + Qdrant retrieval endpoints without
needing to know the individual Spark IPs."""
vllm, parakeet, kokoro, embeddings, qdrant = await asyncio.gather(
check_vllm(settings),
check_parakeet(settings),
check_kokoro(settings),
check_embeddings(settings),
check_qdrant(settings),
)
return {
"vllm": {
"ready": bool(vllm.get("ok")),
"base_url": vllm.get("base_url"),
"model": vllm.get("current_model"),
"openai_compat": True,
"disabled": bool(vllm.get("disabled")),
},
"parakeet": {
"ready": bool(parakeet.get("ok")),
"base_url": parakeet.get("base_url"),
"kind": "stt",
"model": (parakeet.get("detail") or {}).get("model") if isinstance(parakeet.get("detail"), dict) else None,
"disabled": bool(parakeet.get("disabled")),
},
"kokoro": {
"ready": bool(kokoro.get("ok")),
"base_url": kokoro.get("base_url"),
"kind": "tts",
"disabled": bool(kokoro.get("disabled")),
},
"embeddings": {
"ready": bool(embeddings.get("ok")),
"base_url": embeddings.get("base_url"),
"kind": "embedding",
"model": embeddings.get("model"),
# The proxied OpenAI-compatible endpoints live on Spark Control itself.
"openai_endpoints": ["/v1/embeddings", "/v1/rerank", "/api/search"],
"disabled": bool(embeddings.get("disabled")),
},
"qdrant": {
"ready": bool(qdrant.get("ok")),
"base_url": qdrant.get("base_url"),
"kind": "vectordb",
"collection": settings.qdrant_collection or None,
"disabled": bool(qdrant.get("disabled")),
},
}
@app.get("/api/status")
async def get_status() -> dict:
vllm, parakeet, kokoro, embeddings, qdrant = await asyncio.gather(
check_vllm(settings),
check_parakeet(settings),
check_kokoro(settings),
check_embeddings(settings),
check_qdrant(settings),
)
# Feed health into the connectivity log (deduped — only logs on transition).
# Skip services switched off via DISABLED_SERVICES — they'd otherwise log as
# perpetually down.
for _name, _r in (
("vllm", vllm), ("parakeet", parakeet), ("kokoro", kokoro),
("embeddings", embeddings), ("qdrant", qdrant),
):
if not _r.get("disabled"):
record_state(_name, bool(_r.get("ok")))
current_key = _identify_current_model(vllm.get("current_model"))
return {
"configured": settings.configured,
"vllm": vllm,
"parakeet": parakeet,
"kokoro": kokoro,
"embeddings": embeddings,
"qdrant": qdrant,
"current_model_key": current_key,
"current_swap_job": swap_manager.current_job_id,
}
def _identify_current_model(repo: str | None) -> str | None:
if not repo:
return None
# A recipe-backed model keys by its recipe key; a discovered model (loaded but
# not yet set up) keys by the same slug build_menu uses, so it still
# highlights as the active card.
for key, m in catalog.models.items():
if m.repo == repo:
return key
return repo_to_key(repo)
class SwapRequest(BaseModel):
model_key: str
dry_run: bool = False
@app.post("/api/swap/{key}/validate")
async def validate_swap(key: str) -> dict:
"""Pre-flight check: run vLLM's argparse layer against the proposed launch
command WITHOUT starting an engine. Cheap (~5 s) and doesn't disturb the
currently-loaded model.
"""
return await validate_launch(key, catalog, settings)
@app.post("/api/swap")
async def post_swap(req: SwapRequest, request: Request) -> dict:
if not settings.configured and not req.dry_run:
raise HTTPException(503, "spark1 not configured")
# Enforce the swap reservation lock (the GPU arbiter). A held lock blocks any
# real swap that doesn't present the holder's token in X-Swap-Lock-Token — so
# an external scheduler that holds the lock can swap, but the dashboard (no
# token) is refused while someone else holds it. Dry runs don't touch the
# cluster, so they're exempt.
if not req.dry_run:
blocked = swap_lock.is_blocked_by(request.headers.get("x-swap-lock-token"))
if blocked is not None:
raise HTTPException(status_code=423, detail={
"error": "the GPU swap path is reserved by another holder",
"lock": blocked,
})
try:
job = await swap_manager.trigger(req.model_key, dry_run=req.dry_run)
except KeyError:
raise HTTPException(404, f"unknown model: {req.model_key}")
except RuntimeError as e:
raise HTTPException(409, str(e))
return {"job_id": job.id, "model_key": job.model_key, "state": job.state}
# ---- Swap reservation lock (the GPU arbiter) ----
# ROUTE ORDER IS LOAD-BEARING: these static `/api/swap/lock` routes MUST be
# registered before the parametric `/api/swap/{job_id}` below. FastAPI matches in
# registration order, so if `{job_id}` came first, GET /api/swap/lock would bind
# job_id="lock", look up a (non-existent) swap job, and 404 — which is exactly
# the bug this ordering fixes. Keep these above the {job_id} routes.
# CSRF: these are control-surface, not browser-exempt — an external scheduler is
# a non-browser client (no Origin header) so it passes the guard already, the
# same way it calls /api/swap; the dashboard is same-origin.
class LockAcquireRequest(BaseModel):
holder: str
ttl_seconds: int | None = None
note: str = ""
token: str | None = None # present only to extend an existing hold
@app.post("/api/swap/lock")
async def acquire_swap_lock(req: LockAcquireRequest) -> dict:
"""Reserve the GPU swap path. Returns a secret token used to swap (header
X-Swap-Lock-Token) and to release. 409 if held by another holder."""
try:
lock = swap_lock.acquire(req.holder, req.ttl_seconds, req.note, token=req.token)
except ValueError as e:
raise HTTPException(422, str(e))
except LockHeld as e:
raise HTTPException(status_code=409, detail={
"error": "swap lock is held by another holder",
"lock": e.state,
})
return {**swap_lock.status(), "token": lock.token}
@app.get("/api/swap/lock")
async def get_swap_lock() -> dict:
"""Public, token-free view of the reservation: held? who? until when?"""
return swap_lock.status()
@app.delete("/api/swap/lock")
async def release_swap_lock(request: Request, force: bool = Query(False)) -> dict:
"""Release the reservation. Needs the matching X-Swap-Lock-Token unless
?force=true (the human override from the dashboard)."""
token = request.headers.get("x-swap-lock-token") or request.query_params.get("token")
try:
released = swap_lock.release(token, force=force)
except PermissionError as e:
raise HTTPException(403, str(e))
return {"released": released, **swap_lock.status()}
@app.get("/api/swap/{job_id}")
async def get_swap(job_id: str) -> dict:
job = swap_manager.get(job_id)
if job is None:
raise HTTPException(404, "no such job")
return {
"id": job.id,
"model_key": job.model_key,
"state": job.state,
"started_at": job.started_at,
"finished_at": job.finished_at,
"returncode": job.returncode,
"dry_run": job.dry_run,
"lines": job.lines,
}
@app.get("/api/swap/{job_id}/stream")
async def stream_swap(job_id: str):
job = swap_manager.get(job_id)
if job is None:
raise HTTPException(404, "no such job")
async def gen():
sent = 0
while True:
n = len(job.lines)
if n > sent:
for line in job.lines[sent:n]:
payload = json.dumps({"line": line, "state": job.state})
yield f"data: {payload}\n\n"
sent = n
if job.returncode is not None and sent >= len(job.lines):
payload = json.dumps({
"state": job.state,
"returncode": job.returncode,
"finished_at": job.finished_at,
})
yield f"event: done\ndata: {payload}\n\n"
return
await asyncio.sleep(0.4)
return StreamingResponse(gen(), media_type="text/event-stream")
# ---- Coordination layer: read-only schedule registry ----
# (The swap reservation lock lives above, next to the swap routes.) Same CSRF
# posture: control-surface, not browser-exempt — external schedulers send no
# Origin header so they pass the guard; the dashboard is same-origin.
class ScheduleRequest(BaseModel):
name: str
id: str | None = None
owner: str = ""
cron: str = ""
next_run: str = ""
description: str = ""
@app.get("/api/schedule")
async def list_schedules() -> dict:
return {"schedules": schedule_registry.list()}
@app.post("/api/schedule")
async def register_schedule(req: ScheduleRequest) -> dict:
"""Register (or update, by id) a schedule an external scheduler owns. Spark
Control only stores it for the dashboard — it never executes it."""
try:
entry = schedule_registry.register(
name=req.name, id=req.id, owner=req.owner,
cron=req.cron, next_run=req.next_run, description=req.description,
)
except ValueError as e:
raise HTTPException(422, str(e))
return entry.public()
@app.delete("/api/schedule/{schedule_id}")
async def delete_schedule(schedule_id: str) -> dict:
# Whitelist the path segment at the boundary (repo convention), even though
# it's only ever a dict key — keeps it from being reflected or logged raw.
if not valid_schedule_id(schedule_id):
raise HTTPException(422, "invalid schedule id")
return {"deleted": schedule_registry.delete(schedule_id)}
class DownloadRequest(BaseModel):
repo: str
mode: Literal["spark1", "spark2", "cluster"] = "spark1"
@app.post("/api/download")
async def post_download(req: DownloadRequest) -> dict:
if not settings.configured:
raise HTTPException(503, "spark1 not configured")
try:
job = await download_manager.trigger(req.repo, req.mode)
except ValueError as e:
raise HTTPException(400, str(e))
except RuntimeError as e:
raise HTTPException(409, str(e))
return {"job_id": job.id, "repo": job.repo, "mode": job.mode, "state": job.state}
@app.get("/api/download/{job_id}")
async def get_download(job_id: str) -> dict:
job = download_manager.get(job_id)
if job is None:
raise HTTPException(404, "no such job")
return _serialize_download(job)
def _serialize_download(job) -> dict:
return {
"id": job.id,
"repo": job.repo,
"mode": job.mode,
"state": job.state,
"started_at": job.started_at,
"finished_at": job.finished_at,
"returncode": job.returncode,
"progress": {
"percent": job.progress.percent,
"downloaded": job.progress.downloaded,
"total": job.progress.total,
"elapsed": job.progress.elapsed,
"eta": job.progress.eta,
"rate": job.progress.rate,
"phase": job.progress.phase,
},
"lines": job.lines,
}
@app.get("/api/download/{job_id}/stream")
async def stream_download(job_id: str):
job = download_manager.get(job_id)
if job is None:
raise HTTPException(404, "no such job")
async def gen():
sent = 0
last_progress = None
while True:
n = len(job.lines)
if n > sent:
for line in job.lines[sent:n]:
yield f"data: {json.dumps({'line': line})}\n\n"
sent = n
# progress is small; emit on change
prog = (job.progress.percent, job.progress.phase, job.progress.downloaded, job.progress.eta, job.progress.rate)
if prog != last_progress:
yield f"event: progress\ndata: {json.dumps({'state': job.state, **_serialize_download(job)['progress']})}\n\n"
last_progress = prog
if job.returncode is not None and sent >= len(job.lines):
yield f"event: done\ndata: {json.dumps({'state': job.state, 'returncode': job.returncode, 'finished_at': job.finished_at})}\n\n"
return
await asyncio.sleep(0.5)
return StreamingResponse(gen(), media_type="text/event-stream")
@app.get("/api/updates")
async def get_updates() -> dict:
return await get_update_status(settings)
@app.get("/api/explain-updates")
async def explain_updates():
"""Stream a layman's explanation of the pending commits from the currently-loaded vLLM model."""
import httpx
info = await get_update_status(settings)
if not info.get("ok"):
async def err_gen():
yield f"event: done\ndata: {json.dumps({'error': info.get('error', 'unknown')})}\n\n"
return StreamingResponse(err_gen(), media_type="text/event-stream")
vllm = await check_vllm(settings)
if not vllm.get("ok") or not vllm.get("current_model"):
async def err_gen():
yield f"event: done\ndata: {json.dumps({'error': 'no vLLM model loaded — swap to a model first'})}\n\n"
return StreamingResponse(err_gen(), media_type="text/event-stream")
commits = "\n".join(info.get("log", []))
if not commits.strip():
async def empty_gen():
yield f"event: done\ndata: {json.dumps({'error': 'no pending commits'})}\n\n"
return StreamingResponse(empty_gen(), media_type="text/event-stream")
prompt = (
"You are reviewing pending git commits to `eugr/spark-vllm-docker`, an upstream community project that "
"orchestrates vLLM on dual NVIDIA DGX Spark hardware (Blackwell GPUs, cluster via Ray, recipes per model). "
"The reader has a setup running models like Qwen3.6-35B-A3B-NVFP4 (daily driver, solo), Qwen3-VL 235B (cluster), "
"and Gemma 4 31B. The reader is technically literate but is NOT a vLLM expert.\n\n"
"For the commit list below: give a short overall verdict (Apply / Optional / Skip and why), then a brief "
"bullet per commit grouping similar ones. Call out anything that would break a working setup or that "
"requires re-downloading models. Avoid jargon. ~250 words max.\n\n"
f"Pending commits:\n{commits}"
)
async def gen():
try:
async with httpx.AsyncClient(timeout=httpx.Timeout(300.0, connect=5.0)) as c:
async with c.stream(
"POST",
f"{vllm['base_url']}/chat/completions",
json={
"model": vllm["current_model"],
"stream": True,
"messages": [{"role": "user", "content": prompt}],
"max_tokens": 600,
"temperature": 0.4,
},
) as r:
r.raise_for_status()
async for line in r.aiter_lines():
if not line.startswith("data: "):
continue
data = line[6:].strip()
if data == "[DONE]":
break
try:
chunk = json.loads(data)
choices = chunk.get("choices") or []
if not choices:
continue
delta = choices[0].get("delta") or {}
text = delta.get("content")
reasoning = delta.get("reasoning")
if text:
yield f"data: {json.dumps({'content': text})}\n\n"
elif reasoning:
yield f"data: {json.dumps({'reasoning': reasoning})}\n\n"
except json.JSONDecodeError:
continue
except Exception as e:
yield f"data: {json.dumps({'error': f'{type(e).__name__}: {e}'})}\n\n"
yield f"event: done\ndata: {json.dumps({'ok': True})}\n\n"
return StreamingResponse(gen(), media_type="text/event-stream")
class UpdateRequest(BaseModel):
mode: Literal["solo", "cluster"] = "cluster"
@app.post("/api/updates/apply")
async def post_update_apply(req: UpdateRequest) -> dict:
if not settings.configured:
raise HTTPException(503, "spark1 not configured")
try:
job = await update_manager.trigger(req.mode)
except RuntimeError as e:
raise HTTPException(409, str(e))
return {"job_id": job.id, "mode": job.mode, "state": job.state}
@app.get("/api/updates/{job_id}")
async def get_update_job(job_id: str) -> dict:
job = update_manager.get(job_id)
if job is None:
raise HTTPException(404, "no such job")
return {
"id": job.id,
"mode": job.mode,
"state": job.state,
"phase": job.phase,
"started_at": job.started_at,
"finished_at": job.finished_at,
"returncode": job.returncode,
"lines": job.lines,
}
@app.get("/api/updates/{job_id}/stream")
async def stream_update(job_id: str):
job = update_manager.get(job_id)
if job is None:
raise HTTPException(404, "no such job")
async def gen():
sent = 0
last_phase = None
while True:
n = len(job.lines)
if n > sent:
for line in job.lines[sent:n]:
yield f"data: {json.dumps({'line': line})}\n\n"
sent = n
if job.phase != last_phase:
yield f"event: phase\ndata: {json.dumps({'state': job.state, 'phase': job.phase})}\n\n"
last_phase = job.phase
if job.returncode is not None and sent >= len(job.lines):
yield f"event: done\ndata: {json.dumps({'state': job.state, 'returncode': job.returncode})}\n\n"
return
await asyncio.sleep(0.5)
return StreamingResponse(gen(), media_type="text/event-stream")
@app.post("/api/test-connection")
async def test_connection() -> dict:
"""Probe both Sparks with a `hostname` command. Useful for the StartOS setup flow."""
results: dict[str, dict] = {}
if settings.spark1_host:
rc, out, err = await ssh_run(settings.spark1_host, settings.spark1_user, "hostname && docker ps --format '{{.Names}}'", settings, timeout=10)
results["spark1"] = {"ok": rc == 0, "rc": rc, "stdout": out.strip(), "stderr": err.strip()}
else:
results["spark1"] = {"ok": False, "error": "not configured"}
if settings.spark2_host:
rc, out, err = await ssh_run(settings.spark2_host, settings.spark2_user, "hostname && docker ps --format '{{.Names}}'", settings, timeout=10)
results["spark2"] = {"ok": rc == 0, "rc": rc, "stdout": out.strip(), "stderr": err.strip()}
else:
results["spark2"] = {"ok": False, "error": "not configured"}
return results