Files
FabledCurator/agent/fc_agent/client.py
T
bvandeusen 95d2ae1d58 feat(agent): global bandwidth cap — the agent can't saturate the desktop's network
One shared TokenBucket (default 8 MB/s; BANDWIDTH_LIMIT_MB_S, 0 = unlimited;
live MB/s dial + net readout in the control UI) is charged by every still
download (streamed chunk reads) and every ffmpeg video stream (metered from
outside via /proc/<pid>/io and SIGSTOP/SIGCONTed into budget).

Why: D1 re-measurement 2026-07-02 — the idle link moves ~38 MB/s, but 8
unthrottled downloaders bufferbloated it to ~1-1.5 MB/s PER STREAM (operator's
browser included). Capping the aggregate keeps the desktop usable and still
beats the collapsed sweep throughput it replaces. Agent build 2026-07-02.4.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01CDgx8bQS5YrGRK76v8HUnM
2026-07-02 11:20:45 -04:00

141 lines
6.4 KiB
Python

"""HTTP client for the FabledCurator GPU-job API.
The agent's ONLY contact with FC — lease/submit/heartbeat/fail + fetch image
bytes, all over HTTP with the bearer token. No DB/Redis.
"""
import requests
from requests.adapters import HTTPAdapter
from urllib3.util.retry import Retry
class FcClient:
def __init__(self, base_url: str, token: str, agent_id: str):
self.base = base_url.rstrip("/")
self.agent_id = agent_id
# Main session: NO in-request retry — lease/fetch are cheap to redo and
# the worker loop already backs off + re-leases on failure. (Auto-retrying
# a lease could double-claim a batch if a response is lost.)
self.s = self._session(token)
# Submit session: retry in-place, because by submit time the GPU work is
# already DONE — a momentary blip (dropped connection, gateway 5xx during
# a curator redeploy) must not throw that work away and force a full
# re-download + recompute on another agent. A duplicate submit after a
# lost response is harmless: the job is already closed, so it just returns
# 409 lease_invalid (a no-op). Idempotent enough to retry POST safely.
retry = Retry(
total=3, connect=3, read=3, status=3,
backoff_factor=0.5, # ~0.5s, 1s, 2s between tries
status_forcelist=(500, 502, 503, 504), # transient server/gateway
allowed_methods=frozenset({"POST"}),
raise_on_status=False, # let raise_for_status decide
)
self._submit_s = self._session(token, retry)
@staticmethod
def _session(token: str, retry: Retry | None = None) -> requests.Session:
s = requests.Session()
s.headers["Authorization"] = f"Bearer {token}"
# Many worker threads share a Session; the default pool (10) would
# throttle them + spam "connection pool is full". Size it for the cap.
adapter = HTTPAdapter(
pool_connections=64, pool_maxsize=64, max_retries=retry or 0
)
s.mount("http://", adapter)
s.mount("https://", adapter)
return s
def _submit(self, path: str, payload: dict) -> dict:
"""POST to a submit endpoint on the RETRYING session (by submit time the
GPU work is done — a blip must not throw it away), raise on a hard error,
and return the parsed JSON. `agent_id` is added to every body."""
r = self._submit_s.post(
f"{self.base}{path}",
json={"agent_id": self.agent_id, **payload},
timeout=120,
)
r.raise_for_status()
return r.json()
def _post_quiet(self, path: str, payload: dict) -> None:
"""Fire-and-forget POST on the main session — heartbeat/fail/release are
best-effort, so a transport error is swallowed (the worker's own retry and
the server's orphan-recovery cover a lost call). `agent_id` is added."""
try:
self.s.post(
f"{self.base}{path}",
json={"agent_id": self.agent_id, **payload},
timeout=30,
)
except requests.RequestException:
pass
def lease(self, batch_size: int) -> list[dict]:
r = self.s.post(
f"{self.base}/api/gpu/jobs/lease",
json={"agent_id": self.agent_id, "batch_size": batch_size},
timeout=30,
)
r.raise_for_status()
return r.json().get("jobs", [])
def submit(self, job_id: int, regions: list[dict], replace_kinds: list[str]) -> dict:
return self._submit("/api/gpu/jobs/submit", {
"job_id": job_id, "regions": regions, "replace_kinds": replace_kinds,
})
def submit_embedding(self, job_id: int, embedding: list, version: str) -> dict:
"""Post a whole-image SigLIP embedding (the 'embed' task) → image_record."""
return self._submit("/api/gpu/jobs/submit_embedding", {
"job_id": job_id, "embedding": embedding, "embedding_version": version,
})
def heartbeat(self, job_ids: list[int]) -> None:
self._post_quiet("/api/gpu/jobs/heartbeat", {"job_ids": job_ids})
def fail(self, job_id: int, error: str) -> None:
self._post_quiet("/api/gpu/jobs/fail", {"job_id": job_id, "error": error})
def release(self, job_ids: list[int]) -> None:
# Graceful hand-back on stop so orphaned work is re-leased at once.
if not job_ids:
return
self._post_quiet("/api/gpu/jobs/release", {"job_ids": job_ids})
def fetch_image(self, image_url: str, throttle=None) -> bytes:
# image_url is a server-relative path ("/images/...").
# timeout=(connect, read): the read timeout is BETWEEN-BYTES, not total,
# so a large-but-flowing download still completes — but a stuck/dead
# connection (curator overloaded) fails in 60s instead of hanging a
# downloader for 180s and piling up concurrent stuck requests on curator.
# With a throttle (the worker's shared TokenBucket), the body is streamed
# in chunks and each chunk is charged to the global bandwidth budget —
# pausing between reads lets TCP flow control pace curator's send side.
with self.s.get(
f"{self.base}{image_url}", timeout=(10, 60), stream=throttle is not None
) as r:
r.raise_for_status()
if throttle is None:
return r.content
buf = bytearray()
for chunk in r.iter_content(chunk_size=262_144):
throttle.take(len(chunk))
buf.extend(chunk)
return bytes(buf)
def is_reachable(self) -> bool:
"""Cheap 'is curator responding at all right now?' check. Used to decide,
when a video can't be sampled, between a transient outage (keep retrying —
survives a redeploy) and an unprocessable file (fail it, don't loop)."""
try:
r = self.s.get(f"{self.base}/api/gpu/status", timeout=5)
return r.status_code < 500
except requests.RequestException:
return False
def queue_status(self) -> dict:
# Short timeout: this backs the UI /status poll, so a busy curator must
# not hang the page for long (the GPU meters poll /gpu separately).
r = self.s.get(f"{self.base}/api/gpu/status", timeout=5)
r.raise_for_status()
return r.json()