331 lines
24 KiB
Python
331 lines
24 KiB
Python
"""Separate authenticated OpenAI-compatible API; only explicitly enabled Deck profiles."""
|
|
import base64
|
|
import hashlib
|
|
import json
|
|
import os
|
|
from pathlib import Path
|
|
import secrets
|
|
import re
|
|
import socket
|
|
import threading
|
|
import time
|
|
from http.server import BaseHTTPRequestHandler,ThreadingHTTPServer
|
|
from api_compat import normalize_chat,CompatibilityError
|
|
from inference import InferenceError
|
|
from stt import read_upload
|
|
|
|
class APIError(ValueError):
|
|
def __init__(self,message,status=400,code='invalid_request_error'):
|
|
super().__init__(message);self.status=status;self.code=code
|
|
|
|
class Endpoint:
|
|
def __init__(self,root,profiles,worker,scheduler,images,credentials,management_port):
|
|
self.root=Path(root);self.profiles=profiles;self.worker=worker;self.scheduler=scheduler;self.images=images;self.tts=None;self.stt=None;self.video=None;self.credentials=credentials
|
|
self.management_port=management_port;self.lock=threading.RLock();self.http=None;self.thread=None;self.state='stopped';self.error=None;self.inflight=0
|
|
self.allowed_ports=[int(p) for p in os.environ.get('DECK_API_PORTS','').split(',') if p]
|
|
self.config=dict(port=self.allowed_ports[0] if self.allowed_ports else 8120,enabled_profiles=[],autostart=False)
|
|
path=self.root/'endpoint.json'
|
|
if path.exists():self.config.update(json.loads(path.read_text()))
|
|
image_ids={p['id'] for p in self.profiles.status()['profiles'] if p['kind']=='image'}
|
|
selected=[i for i in self.config['enabled_profiles'] if i in image_ids]
|
|
if len(selected)>1:
|
|
self.config['enabled_profiles']=[i for i in self.config['enabled_profiles'] if i not in image_ids or i==selected[0]];self.persist()
|
|
def persist(self):
|
|
self.root.mkdir(parents=True,exist_ok=True,mode=0o700)
|
|
path=self.root/'endpoint.tmp';path.write_text(json.dumps(self.config));path.replace(self.root/'endpoint.json')
|
|
def rows(self):
|
|
rows=self.profiles.status()['profiles']
|
|
with self.lock:enabled=set(self.config['enabled_profiles'])
|
|
return [dict(p,enabled=(p['id']==self.video.selected if self.video else False) if p['kind']=='video' else p['id'] in enabled) for p in rows]
|
|
def status(self):
|
|
rows=self.rows();worker=self.worker.status();job=self.images.status()['job'];counts={}
|
|
for key,kind in [('llm','chat'),('image','image'),('tts','audio'),('stt','stt')]:
|
|
subset=[p for p in rows if p['kind']==kind]
|
|
counts[key]=dict(enabled=sum(p['enabled'] for p in subset),available=sum(p['enabled'] and p['runnable'] for p in subset),loaded=bool(worker['state']=='ready' and kind=='chat') if kind=='chat' else bool(self.tts and self.tts.status()['job'] and self.tts.status()['job']['state']=='running') if kind=='audio' else bool(self.stt and self.stt.status()['job'] and self.stt.status()['job']['state']=='running') if kind=='stt' else bool(kind=='image' and job and job['state']=='running'),supported=kind in ('chat','image') or (kind=='audio' and self.tts is not None) or (kind=='stt' and self.stt is not None))
|
|
scheduler_status=self.scheduler.status()
|
|
with self.lock:return dict(video=self.video.status() if self.video else None,state=self.state,reachable=bool(self.thread and self.thread.is_alive() and self.state=='running'),port=self.config['port'],bind=os.environ.get('DECK_API_BIND','127.0.0.1'),base_url=f"http://127.0.0.1:{self.config['port']}/v1",allowed_ports=self.allowed_ports,error=self.error,counts=counts,worker=worker,scheduler=scheduler_status,profiles=[dict(id=p['id'],name=p['name'],kind=p['kind'],enabled=p['enabled'],runnable=p['runnable'],blockers=p['blockers']) for p in rows],active_requests=self.inflight)
|
|
def configure(self,data):
|
|
if set(data)!={'port'} or type(data['port']) is not int or not 1024<=data['port']<=65535:raise ValueError('Port zwischen 1024 und 65535 erforderlich.')
|
|
port=data['port']
|
|
with self.lock:
|
|
if self.state!='stopped':raise ValueError('Endpunkt zuerst vollständig stoppen.')
|
|
if port==self.management_port:raise ValueError('Der Verwaltungsport ist bereits belegt.')
|
|
if self.allowed_ports and port not in self.allowed_ports:raise ValueError('Dieser Port ist im Docker-Installer nicht freigegeben.')
|
|
try:
|
|
with socket.socket() as sock:sock.bind((os.environ.get('DECK_API_BIND','127.0.0.1'),port))
|
|
except OSError:raise ValueError('Port ist bereits belegt.') from None
|
|
self.config['port']=port;self.persist()
|
|
return self.status()
|
|
def enable(self,data):
|
|
if set(data)!={'id','enabled'} or type(data['enabled']) is not bool:raise ValueError('Profil-ID und Aktivierung erforderlich.')
|
|
rows=self.rows()
|
|
row=next((p for p in rows if p['id']==data['id']),None)
|
|
if not row:raise ValueError('Profil nicht gefunden.')
|
|
if data['enabled'] and not row['runnable']:raise ValueError('Profil nicht ausführbar: '+' '.join(row['blockers']))
|
|
if row['kind']=='video':
|
|
if not self.video:raise ValueError('Video-Verwaltung nicht eingerichtet.')
|
|
if data['enabled']:self.video.select(row['id'])
|
|
elif self.video.selected==row['id']:self.video.select(None)
|
|
return self.status()
|
|
with self.lock:
|
|
enabled=set(self.config['enabled_profiles'])
|
|
if data['enabled']:
|
|
if row['kind']=='image':enabled.difference_update(p['id'] for p in rows if p['kind']=='image')
|
|
enabled.add(data['id'])
|
|
else:enabled.discard(data['id'])
|
|
self.config['enabled_profiles']=sorted(enabled);self.persist()
|
|
return self.status()
|
|
def start(self):
|
|
with self.lock:
|
|
if self.state=='running':return {'state':'running','port':self.config['port']}
|
|
if self.state!='stopped':raise ValueError('Endpunkt wird noch gestoppt.')
|
|
record=self.credentials.read()
|
|
if not record or not record.get('api_token_hash'):raise ValueError('Zuerst unter Zugang & API einen API-Token einrichten.')
|
|
if self.allowed_ports and self.config['port'] not in self.allowed_ports:raise ValueError('Gespeicherter Port ist nicht im Docker-Installer freigegeben.')
|
|
if self.config['port']==self.management_port:raise ValueError('Verwaltungsport kann nicht als API-Port verwendet werden.')
|
|
try:http=APIHTTPServer((os.environ.get('DECK_API_BIND','127.0.0.1'),self.config['port']),APIHandler)
|
|
except OSError:raise ValueError('API-Port bereits belegt; kein anderer Dienst wurde verändert.') from None
|
|
http.endpoint=self;self.http=http;self.state='running';self.error=None
|
|
self.thread=threading.Thread(target=http.serve_forever,daemon=True);self.thread.start()
|
|
self.config['autostart']=True;self.persist()
|
|
return self.status()
|
|
def stop(self):
|
|
with self.lock:
|
|
self.config['autostart']=False;self.persist()
|
|
if self.state=='running':
|
|
self.state='stopping';threading.Thread(target=self._drain,daemon=True).start()
|
|
return self.status()
|
|
def _drain(self):
|
|
http=self.http
|
|
if http:http.shutdown();http.server_close()
|
|
while True:
|
|
if self.video:
|
|
vs=self.video.status()
|
|
if vs['state']=='switching':time.sleep(.1);continue
|
|
if vs['mode']=='video':self.video.switch('llm');time.sleep(.1);continue
|
|
with self.lock:pending=self.inflight
|
|
if not pending and self.scheduler.unload_idle():break
|
|
time.sleep(.1)
|
|
with self.lock:self.http=None;self.thread=None;self.state='stopped'
|
|
def close(self):
|
|
# Process shutdown does not change the user's autostart preference.
|
|
with self.lock:self.state='stopping';http=self.http
|
|
if http:http.shutdown();http.server_close()
|
|
if self.tts:self.tts.stop()
|
|
if self.stt:self.stt.stop()
|
|
self.images.stop();self.worker.stop()
|
|
def allowed(self):
|
|
with self.lock:return self.state=='running'
|
|
def authenticate(self,header):
|
|
if not header.startswith('Bearer ') or len(header)>300:return False
|
|
record=self.credentials.read()
|
|
return bool(record and record.get('api_token_hash') and secrets.compare_digest(hashlib.sha256(header[7:].encode()).hexdigest(),record['api_token_hash']))
|
|
def find_profile(self,name,kind):
|
|
if not isinstance(name,str):raise APIError('model muss den API-Namen eines aktivierten Profils enthalten.')
|
|
row=next((p for p in self.rows() if (p['name']==name or (kind=='image' and name=='athena-image')) and p['kind']==kind and p['enabled']),None)
|
|
if not row:raise APIError('Modellprofil nicht aktiviert oder unbekannt.',404,'model_not_found')
|
|
if not row['runnable']:raise APIError('Profil derzeit nicht ausführbar: '+' '.join(row['blockers']),503,'model_unavailable')
|
|
return row
|
|
def model_list(self,kind="chat"):
|
|
return dict(object='list',data=[dict(id='athena-image' if kind=='image' else p['name'],object='model',created=int(p['updated_at']),owned_by='athena-deck') for p in self.rows() if p['enabled'] and p['runnable'] and p['kind']==kind])
|
|
|
|
class APIHTTPServer(ThreadingHTTPServer):
|
|
daemon_threads=True
|
|
def __init__(self,*args,**kwargs):
|
|
self.admission=threading.BoundedSemaphore(32);super().__init__(*args,**kwargs)
|
|
def process_request(self,request,address):
|
|
if not self.admission.acquire(blocking=False):self.shutdown_request(request);return
|
|
try:super().process_request(request,address)
|
|
except Exception:self.admission.release();raise
|
|
def process_request_thread(self,*args):
|
|
try:super().process_request_thread(*args)
|
|
finally:self.admission.release()
|
|
def handle_error(self,*args):pass # No request bodies, prompts, or traces in logs.
|
|
|
|
class APIHandler(BaseHTTPRequestHandler):
|
|
protocol_version='HTTP/1.1'
|
|
def setup(self):super().setup();self.connection.settimeout(15);self.sent=False
|
|
def log_message(self,*args):pass
|
|
def compatibility_headers(self):
|
|
info=getattr(self,'compatibility',{})
|
|
if info:
|
|
self.send_header('X-Athena-Reasoning-Requested',info['requested'])
|
|
self.send_header('X-Athena-Reasoning-Effective',info['effective'])
|
|
self.send_header('X-Athena-Reasoning-Semantics',info['semantics'])
|
|
def send(self,payload,status=200):
|
|
body=json.dumps(payload).encode();self.sent=True
|
|
self.send_response(status);self.compatibility_headers();self.send_header('Content-Type','application/json');self.send_header('Content-Length',str(len(body)));self.send_header('Cache-Control','no-store');self.send_header('Connection','close');self.end_headers();self.wfile.write(body);self.close_connection=True
|
|
def failure(self,exc):
|
|
if self.sent:return
|
|
self.send({'error':{'message':str(exc),'type':getattr(exc,'code','server_error'),'param':None,'code':getattr(exc,'code','worker_unavailable')}},getattr(exc,'status',503))
|
|
def video_route(self,ep):
|
|
if not self.path.startswith('/v1/videos'):return False
|
|
if not ep.video:raise APIError('Video-Worker nicht eingerichtet.',503)
|
|
if self.command=='GET' and self.path=='/v1/videos/models':
|
|
ident=ep.video.selected
|
|
self.send({'object':'list','data':[{'id':'athena-video','object':'model','owned_by':'athena-deck'}] if any(p['id']==ident and p['runnable'] for p in ep.rows()) else []});return True
|
|
if self.command=='POST' and self.path=='/v1/videos':
|
|
if self.headers.get('Transfer-Encoding'):raise APIError('Chunked Upload nicht unterstützt.')
|
|
try:length=int(self.headers.get('Content-Length','0'))
|
|
except ValueError:raise APIError('Ungültige Länge.')
|
|
if not 0<length<=65536 or self.headers.get('Content-Type','').split(';')[0]!='application/json':raise APIError('JSON bis 64 KiB erforderlich.',413)
|
|
try:
|
|
data=json.loads(self.rfile.read(length))
|
|
if not isinstance(data,dict):raise ValueError('JSON-Objekt erforderlich.')
|
|
job=ep.video.generate(data)
|
|
except ValueError as exc:raise APIError(str(exc),409,'video_not_ready') from None
|
|
self.send(job,202);return True
|
|
parts=self.path.split('/')
|
|
if self.command=='GET' and len(parts) in (4,5) and re.fullmatch('[a-f0-9]{32}',parts[3]):
|
|
job=ep.video.status()['job']
|
|
if not job or job['id']!=parts[3]:raise APIError('Video-Auftrag nicht gefunden.',404)
|
|
if len(parts)==4:self.send(job);return True
|
|
if parts[4]=='content':
|
|
try:path=ep.video.result(parts[3])
|
|
except ValueError as exc:raise APIError(str(exc),409) from None
|
|
self.sent=True;self.send_response(200);self.send_header('Content-Type','video/mp4');self.send_header('Content-Length',str(path.stat().st_size));self.send_header('Cache-Control','no-store');self.send_header('Connection','close');self.end_headers()
|
|
with path.open('rb') as source:
|
|
while chunk:=source.read(1024*1024):self.wfile.write(chunk)
|
|
self.close_connection=True;return True
|
|
raise APIError('Video-Route nicht gefunden.',404)
|
|
def do_GET(self):self.route()
|
|
def do_POST(self):self.route()
|
|
def route(self):
|
|
ep=self.server.endpoint;admitted=False
|
|
try:
|
|
if not ep.authenticate(self.headers.get('Authorization','')):raise APIError('Gültiger API-Bearer-Token erforderlich.',401,'invalid_api_key')
|
|
if self.headers.get('Origin'):raise APIError('Browserzugriff erfolgt über die Deck-Verwaltung; keine Cross-Origin-API-Freigabe.',403)
|
|
with ep.lock:
|
|
if not ep.allowed():raise APIError('Endpunkt wird gestoppt.',503,'endpoint_stopping')
|
|
ep.inflight+=1;admitted=True
|
|
model_routes={'/v1/models':'chat','/v1/images/models':'image','/v1/audio/speech/models':'audio','/v1/audio/transcriptions/models':'stt'}
|
|
if self.command=='GET' and self.path in model_routes:return self.send(ep.model_list(model_routes[self.path]))
|
|
if self.command=='GET' and self.path=='/health':return self.send({'status':'ok','service':'athena-deck-api'})
|
|
if self.video_route(ep):return
|
|
if self.command!='POST':raise APIError('Route nicht gefunden.',404)
|
|
if ep.video and ep.scheduler.gpu_mode!='llm' and self.path!='/v1/audio/transcriptions':raise APIError('Video-Modus aktiv; Chat-, Bild- und TTS-Aufträge sind gesperrt. Auf LLM zurückschalten.',503,'video_mode_active')
|
|
if self.path=='/v1/audio/transcriptions':return self.transcription(ep)
|
|
if self.path not in ('/v1/chat/completions','/v1/images/generations','/v1/audio/speech'):raise APIError('Route nicht implementiert.',404)
|
|
if self.headers.get('Transfer-Encoding'):raise APIError('Chunked Upload wird nicht unterstützt.')
|
|
try:length=int(self.headers.get('Content-Length','0'))
|
|
except ValueError:raise APIError('Ungültige Content-Length.') from None
|
|
if not 0<length<=1024*1024 or self.headers.get('Content-Type','').split(';')[0]!='application/json':raise APIError('JSON-Anfrage bis 1 MiB erforderlich.',413)
|
|
try:data=json.loads(self.rfile.read(length),parse_constant=lambda _:(_ for _ in ()).throw(ValueError()))
|
|
except (ValueError,UnicodeError):raise APIError('Ungültiges JSON.') from None
|
|
if not isinstance(data,dict):raise APIError('JSON-Objekt erforderlich.')
|
|
if self.path=='/v1/chat/completions':return self.chat(ep,data)
|
|
if self.path=='/v1/audio/speech':return self.speech(ep,data)
|
|
return self.image(ep,data)
|
|
except (APIError,InferenceError) as exc:
|
|
if isinstance(exc,InferenceError):
|
|
with ep.lock:ep.error=str(exc)
|
|
self.failure(exc)
|
|
except (BrokenPipeError,ConnectionResetError):pass
|
|
except Exception:self.failure(APIError('Worker nicht erreichbar oder Zeitlimit überschritten.',503,'worker_unavailable'))
|
|
finally:
|
|
self.close_connection=True
|
|
if admitted:
|
|
with ep.lock:ep.inflight-=1
|
|
def transcription(self,ep):
|
|
if not ep.stt:raise APIError('STT-Laufzeit nicht eingerichtet.',501,'not_implemented')
|
|
try:
|
|
fields,audio=read_upload(self)
|
|
if 'profile_id' in fields:raise ValueError('API-Profilname als model erforderlich.')
|
|
profile=ep.find_profile(fields.get('model'),'stt')
|
|
job=ep.stt.start(profile['id'],audio,fields.get('language','de'))
|
|
except APIError:raise
|
|
except ValueError as exc:raise APIError(str(exc)) from None
|
|
deadline=time.monotonic()+280
|
|
while time.monotonic()<deadline:
|
|
current=ep.stt.status()['job']
|
|
if not current or current['id']!=job['id']:raise APIError('STT-Ergebnis nicht mehr verfügbar.',409)
|
|
if current['state']=='complete':return self.send({'text':current['text']})
|
|
if current['state']!='running':raise APIError(current['phase'],503)
|
|
time.sleep(.2)
|
|
ep.stt.stop();raise APIError('STT-Zeitlimit überschritten.',504)
|
|
def speech(self,ep,data):
|
|
if not ep.tts:raise APIError('TTS-Laufzeit nicht eingerichtet.',501)
|
|
if set(data)-{'model','input','voice','response_format','speed','language'}:raise APIError('Nicht unterstützte TTS-Felder.')
|
|
if data.get('response_format','wav')!='wav':raise APIError('Derzeit wird nur WAV unterstützt; response_format=wav setzen.')
|
|
profile=ep.find_profile(data.get('model'),'audio')
|
|
try:job=ep.tts.start(profile['id'],data.get('input'),speaker=data.get('voice','Ryan'),language=data.get('language','Auto'),speed=data.get('speed'),wait=True)
|
|
except ValueError as exc:raise APIError(str(exc)) from None
|
|
end=time.monotonic()+620
|
|
while time.monotonic()<end:
|
|
current=ep.tts.status()['job']
|
|
if current and current['id']==job['id'] and current['state'] in ('failed','cancelled'):raise APIError(current['phase'],503)
|
|
try:body=ep.tts.audio(job['id'])
|
|
except (ValueError,OSError):time.sleep(.25);continue
|
|
self.sent=True;self.send_response(200);self.send_header('Content-Type','audio/wav');self.send_header('Content-Length',str(len(body)));self.send_header('Cache-Control','no-store');self.send_header('Connection','close');self.end_headers();self.wfile.write(body);return
|
|
raise APIError('TTS-Zeitlimit überschritten.',504)
|
|
def chat(self,ep,data):
|
|
try:data,self.compatibility=normalize_chat(data)
|
|
except CompatibilityError as exc:raise APIError(str(exc)) from None
|
|
if type(data.get('stream',False)) is not bool:raise APIError('stream muss true oder false sein.')
|
|
if data.get('n',1)!=1:raise APIError('Zunächst wird n=1 unterstützt.')
|
|
messages=data.get('messages')
|
|
if not isinstance(messages,list) or not messages or any(not isinstance(m,dict) for m in messages):raise APIError('messages muss eine nichtleere Liste sein.')
|
|
profile=ep.find_profile(data.get('model'),'chat')
|
|
images=0
|
|
for message in messages:
|
|
content=message.get('content')
|
|
if isinstance(content,list):
|
|
for part in content:
|
|
if not isinstance(part,dict):raise APIError('Ungültiger Nachrichteninhalt.')
|
|
if part.get('type')=='text':continue
|
|
if part.get('type')!='image_url' or not profile['parameters'].get('vision_projector'):raise APIError('Für Bildeingaben einen Vision-Projektor im Profil aktivieren.')
|
|
value=part.get('image_url')
|
|
url=value.get('url') if isinstance(value,dict) else None
|
|
if not isinstance(url,str) or not url.startswith(('data:image/png;base64,','data:image/jpeg;base64,','data:image/webp;base64,')):raise APIError('Nur eingebettete PNG/JPEG/WebP-Bilder; keine externen URLs.')
|
|
import base64,binascii
|
|
try:raw=base64.b64decode(url.split(',',1)[1],validate=True)
|
|
except (ValueError,binascii.Error):raise APIError('Ungültige Bildkodierung.') from None
|
|
if not raw:raise APIError('Leeres Bild.')
|
|
images+=1
|
|
if images>1:raise APIError('Zunächst ein Bild pro Anfrage unterstützt.')
|
|
# Re-resolve after waiting so edits/disable cannot silently launch a stale profile.
|
|
key=('chat',profile['id'],profile['revision'])
|
|
def allowed():return ep.allowed() and any(p['id']==profile['id'] and p['revision']==profile['revision'] and p['enabled'] for p in ep.rows())
|
|
with ep.scheduler.lease(key,profile['parameters']['slots'],lambda:ep.worker.ensure(profile),allowed=allowed):
|
|
body=dict(data)
|
|
for field in ('temperature','top_p','top_k'):body.setdefault(field,profile['parameters'][field])
|
|
conn,key=ep.worker.connect()
|
|
try:
|
|
conn.request('POST','/v1/chat/completions',body=json.dumps(body).encode(),headers={'Content-Type':'application/json','Authorization':'Bearer '+key})
|
|
response=conn.getresponse()
|
|
if response.status!=200:
|
|
response.read(65536);raise APIError('llama.cpp hat die Anfrage abgelehnt. Kontext und Anfrageparameter prüfen.',response.status if 400<=response.status<600 else 502,'upstream_error')
|
|
if not data.get('stream'):
|
|
raw=response.read(16*1024*1024+1)
|
|
if len(raw)>16*1024*1024:raise InferenceError('Modellantwort überschreitet 16 MiB.')
|
|
return self.send(json.loads(raw))
|
|
self.sent=True;self.connection.settimeout(30)
|
|
self.send_response(200);self.compatibility_headers();self.send_header('Content-Type','text/event-stream');self.send_header('Cache-Control','no-store');self.send_header('Connection','close');self.end_headers()
|
|
deadline=time.monotonic()+600
|
|
while time.monotonic()<deadline:
|
|
chunk=response.read1(8192)
|
|
if not chunk:return
|
|
self.wfile.write(chunk);self.wfile.flush()
|
|
raise InferenceError('Zeitlimit der Streaming-Antwort überschritten.')
|
|
finally:conn.close()
|
|
def image(self,ep,data):
|
|
if set(data)-{'model','prompt','n','size','response_format','user'}:raise APIError('Nicht unterstützte Bildparameter. Schritte/Guidance/Seed stehen im Profil.')
|
|
if data.get('n',1)!=1 or data.get('response_format','b64_json')!='b64_json':raise APIError('Unterstützt werden n=1 und response_format=b64_json.')
|
|
profile=ep.find_profile(data.get('model'),'image');params=profile['parameters']
|
|
size=data.get('size')
|
|
if size is not None and (not isinstance(size,str) or (size!='auto' and not re.fullmatch(r'[1-9][0-9]{1,4}x[1-9][0-9]{1,4}',size))):raise APIError('size muss auto oder eine Auflösung wie 1024x1024 sein.')
|
|
# The selected profile owns resource limits; client size is only a preference.
|
|
def allowed():return ep.allowed() and any(p['id']==profile['id'] and p['revision']==profile['revision'] and p['enabled'] for p in ep.rows())
|
|
with ep.scheduler.lease(('image',),allowed=allowed):
|
|
return self.generate_image(ep,profile,data)
|
|
def generate_image(self,ep,profile,data):
|
|
job=ep.images.start(profile['id'],data.get('prompt'),reserved=True)
|
|
deadline=time.monotonic()+2100
|
|
while time.monotonic()<deadline:
|
|
current=ep.images.status()['job']
|
|
if not current or current['id']!=job['id']:raise InferenceError('Bildauftrag nicht mehr verfügbar.')
|
|
if current['state']=='complete':return self.send({'created':int(time.time()),'data':[{'b64_json':base64.b64encode(ep.images.image(job['id'])).decode()}],'athena_deck':{'model':'athena-image','size':f"{profile['parameters']['width']}x{profile['parameters']['height']}",'requested_size':data.get('size'),'size_policy':'profile'}})
|
|
if current['state']!='running':raise InferenceError(current['phase'])
|
|
time.sleep(.25)
|
|
ep.images.stop();raise InferenceError('Zeitlimit der Bildgenerierung überschritten.')
|