diff --git a/main.py b/main.py
index 74321e993..c5311cbd3 100644
--- a/main.py
+++ b/main.py
@@ -263,9 +263,17 @@ async def websocket_endpoint(websocket: WebSocket, client_id: str = None):
}
PROVIDER_ID_RE = re.compile(r"^[a-zA-Z0-9_-]{2,40}$")
-SUPPORTED_PROVIDER_PROTOCOLS = {"openai", "apimart", "gemini", "volcengine", "runninghub", "jimeng"}
+SUPPORTED_PROVIDER_PROTOCOLS = {"openai", "apimart", "gemini", "volcengine", "runninghub", "jimeng", "fal"}
SUPPORTED_IMAGE_REQUEST_MODES = {"openai", "openai-json"}
RUNNINGHUB_DEFAULT_BASE_URL = "https://www.runninghub.cn"
+FAL_DEFAULT_BASE_URL = "https://queue.fal.run"
+FAL_MODELS_API_URL = "https://api.fal.ai/v1/models"
+FAL_DEFAULT_IMAGE_MODELS = [
+ "fal-ai/flux/schnell",
+ "fal-ai/flux/dev",
+ "fal-ai/flux-pro",
+ "fal-ai/nano-banana",
+]
RUNNINGHUB_OPENAPI_BASE_URL = "https://www.runninghub.cn/openapi/v2"
RUNNINGHUB_MODEL_REGISTRY_URL = "https://raw.githubusercontent.com/HM-RunningHub/ComfyUI_RH_OpenAPI/main/models_registry.json"
RUNNINGHUB_LLM_BASE_URL = "https://llm.runninghub.cn/v1"
@@ -771,6 +779,22 @@ def default_api_providers():
"ms_loras": [],
"ms_defaults_version": 0,
},
+ {
+ "id": "fal",
+ "name": "fal.ai",
+ "base_url": FAL_DEFAULT_BASE_URL,
+ "protocol": "fal",
+ "image_request_mode": "openai",
+ "image_generation_endpoint": "",
+ "image_edit_endpoint": "",
+ "enabled": True,
+ "primary": False,
+ "image_models": FAL_DEFAULT_IMAGE_MODELS,
+ "chat_models": [],
+ "video_models": [],
+ "ms_loras": [],
+ "ms_defaults_version": 0,
+ },
]
def merge_default_api_providers(providers):
@@ -850,6 +874,19 @@ def merge_default_api_providers(providers):
protocols.update(normalize_model_protocols(lingjing_default.get("model_protocols")))
current["model_protocols"] = protocols
# 即梦 CLI 不再是强制保留的默认平台：仅在用户已添加了即梦协议的平台时，规范化其默认模型/地址。
+ fal_default = next((d for d in default_api_providers() if d["id"] == "fal"), None)
+ if fal_default:
+ current = next((item for item in merged if item.get("id") == "fal"), None)
+ if not current:
+ merged.append(fal_default)
+ else:
+ if not current.get("base_url"):
+ current["base_url"] = fal_default["base_url"]
+ current["protocol"] = "fal"
+ current["image_request_mode"] = normalize_image_request_mode(current.get("image_request_mode"))
+ current["image_models"] = model_list_from_values(current.get("image_models") or [])
+ current["chat_models"] = model_list_from_values(current.get("chat_models") or [])
+ current["video_models"] = []
for current in merged:
if not is_jimeng_provider(current):
continue
@@ -1170,6 +1207,9 @@ def normalize_provider(item):
if provider_id == "runninghub":
protocol = "runninghub"
base_url = base_url or RUNNINGHUB_DEFAULT_BASE_URL
+ if provider_id == "fal":
+ protocol = "fal"
+ base_url = base_url or FAL_DEFAULT_BASE_URL
return {
"id": provider_id,
"name": name,
@@ -3779,7 +3819,7 @@ def provider_protocol(provider):
# 单模型可覆盖的协议（仅 OpenAI / Gemini，二者可共用同一站点的 Base URL + Key）
PER_MODEL_PROTOCOL_OPTIONS = {"openai", "gemini"}
# 协议固定、不支持单模型覆盖的内置平台
-FIXED_PROTOCOL_PROVIDER_IDS = {"modelscope", "volcengine", "jimeng", "runninghub"}
+FIXED_PROTOCOL_PROVIDER_IDS = {"modelscope", "volcengine", "jimeng", "runninghub", "fal"}
def normalize_model_protocols(value):
"""规整 {模型名: 协议} 覆盖表，仅保留 openai/gemini。"""
@@ -3836,6 +3876,9 @@ def is_runninghub_provider(provider):
def is_jimeng_provider(provider):
return provider_protocol(provider) == "jimeng" or str((provider or {}).get("id") or "").strip().lower() == "jimeng"
+def is_fal_provider(provider):
+ return provider_protocol(provider) == "fal" or str((provider or {}).get("id") or "").strip().lower() == "fal"
+
def is_yuli_provider(provider):
# 玉玉API（yuli.host）的视频接口走自有格式（/v1/video/create + /v1/video/query），
# 与通用 OpenAI /v1/videos/generations 不同，需单独识别。
@@ -8625,6 +8668,176 @@ async def generate_runninghub_video(payload, provider):
local_urls = [await save_remote_video_to_output(url, prefix="rh_video_") for url in urls]
return {"videos": local_urls, "task_id": task_id, "raw": result}
+def fal_api_key(provider=None):
+ provider_id = str((provider or {}).get("id") or "fal").strip().lower() or "fal"
+ api_key = str((provider or {}).get("api_key") or "").strip() or provider_env_key_value(provider_id)
+ if not api_key:
+ raise HTTPException(status_code=400, detail="未配置 fal.ai API Key，请在 API 设置中填写。")
+ return strip_auth_scheme(api_key, "Key")
+
+def fal_headers(provider=None, json_body=True):
+ headers = {
+ "Authorization": f"Key {fal_api_key(provider)}",
+ "Accept": "application/json",
+ }
+ if json_body:
+ headers["Content-Type"] = "application/json"
+ return headers
+
+def fal_queue_base_url(provider=None):
+ base_url = str((provider or {}).get("base_url") or FAL_DEFAULT_BASE_URL).strip().rstrip("/")
+ return base_url or FAL_DEFAULT_BASE_URL
+
+def fal_queue_url(provider, model):
+ model_id = selected_model(model, FAL_DEFAULT_IMAGE_MODELS[0]).strip().strip("/")
+ if not model_id:
+ raise HTTPException(status_code=400, detail="fal.ai 模型名称不能为空")
+ if model_id.startswith(("http://", "https://")):
+ return model_id
+ return f"{fal_queue_base_url(provider)}/{model_id}"
+
+def fal_image_size(size):
+ width, height = parse_size_pair(size)
+ if not width or not height:
+ return "square_hd"
+ ratio = width / max(1, height)
+ if abs(ratio - 1.0) < 0.08:
+ return "square_hd"
+ if abs(ratio - (4 / 3)) < 0.08:
+ return "landscape_4_3"
+ if abs(ratio - (3 / 4)) < 0.08:
+ return "portrait_4_3"
+ if abs(ratio - (16 / 9)) < 0.08:
+ return "landscape_16_9"
+ if abs(ratio - (9 / 16)) < 0.08:
+ return "portrait_16_9"
+ return {"width": width, "height": height}
+
+FAL_KREA_ASPECT_RATIOS = (
+ ("1:1", 1 / 1),
+ ("4:3", 4 / 3),
+ ("3:2", 3 / 2),
+ ("16:9", 16 / 9),
+ ("2.35:1", 2.35 / 1),
+ ("4:5", 4 / 5),
+ ("2:3", 2 / 3),
+ ("9:16", 9 / 16),
+)
+
+def fal_krea_aspect_ratio(width, height):
+ try:
+ width = float(width)
+ height = float(height)
+ except (TypeError, ValueError):
+ return "1:1"
+ if width <= 0 or height <= 0:
+ return "1:1"
+ ratio = width / height
+ return min(FAL_KREA_ASPECT_RATIOS, key=lambda item: abs(math.log(ratio / item[1])))[0]
+
+def build_fal_model_input(model, prompt, size, quality=None):
+ model_id = selected_model(model, FAL_DEFAULT_IMAGE_MODELS[0]).strip().strip("/")
+ model_lc = model_id.lower()
+ width, height = parse_size_pair(size)
+ body = {
+ "prompt": prompt,
+ "image_size": fal_image_size(size),
+ }
+ if model_lc.startswith("krea/v2/"):
+ body = {
+ "prompt": prompt,
+ "aspect_ratio": fal_krea_aspect_ratio(width, height),
+ }
+ quality_value = str(quality or "").strip().lower()
+ if quality_value in {"low", "medium", "high"}:
+ body["creativity"] = quality_value
+ for key in ("image_size", "width", "height", "negative_prompt", "num_inference_steps", "guidance_scale"):
+ body.pop(key, None)
+ elif model_lc == "fal-ai/flux-2-max":
+ if width and height:
+ body["image_size"] = {"width": width, "height": height}
+ for key in ("aspect_ratio", "creativity", "negative_prompt", "num_inference_steps", "guidance_scale"):
+ body.pop(key, None)
+ return body
+
+def fal_reference_url(ref):
+ return reference_to_data_url(ref, max_size=1536)
+
+def fal_submit_payload(prompt, size, model, reference_images=None, quality=None):
+ body = build_fal_model_input(model, prompt, size, quality)
+ refs = [fal_reference_url(ref) for ref in (reference_images or [])[:ONLINE_IMAGE_REFERENCE_MAX]]
+ refs = [url for url in refs if url]
+ if refs:
+ model_lc = str(model or "").lower()
+ if len(refs) > 1 or "nano-banana" in model_lc:
+ body["image_urls"] = refs
+ else:
+ body["image_url"] = refs[0]
+ return body
+
+def fal_response_url(provider, model, request_id):
+ model_id = selected_model(model, FAL_DEFAULT_IMAGE_MODELS[0]).strip().strip("/")
+ base = fal_queue_base_url(provider)
+ return f"{base}/{model_id}/requests/{urllib.parse.quote(str(request_id), safe='')}"
+
+def fal_status_value(raw):
+ if not isinstance(raw, dict):
+ return ""
+ return str(raw.get("status") or raw.get("state") or "").strip().upper()
+
+def fal_failure_message(raw):
+ if not isinstance(raw, dict):
+ return str(raw or "")
+ error = raw.get("error") or raw.get("detail") or raw.get("message") or raw.get("logs")
+ if isinstance(error, str):
+ return error
+ if isinstance(error, (dict, list)):
+ return json.dumps(error, ensure_ascii=False)[:800]
+ return ""
+
+async def wait_for_fal_result(client, provider, model, submit_raw):
+ request_id = str((submit_raw or {}).get("request_id") or "").strip()
+ status_url = str((submit_raw or {}).get("status_url") or "").strip()
+ response_url = str((submit_raw or {}).get("response_url") or "").strip()
+ if not response_url and request_id:
+ response_url = fal_response_url(provider, model, request_id)
+ if not status_url and response_url:
+ status_url = response_url
+ if not response_url:
+ raise HTTPException(status_code=502, detail=f"fal.ai 未返回 response_url/request_id：{submit_raw}")
+
+ deadline = time.monotonic() + IMAGE_TASK_TIMEOUT
+ last_payload = submit_raw
+ headers = fal_headers(provider, json_body=False)
+ while status_url and time.monotonic() < deadline:
+ await asyncio.sleep(IMAGE_POLL_INTERVAL)
+ status_response = await client.get(status_url, headers=headers)
+ status_response.raise_for_status()
+ last_payload = status_response.json() if status_response.text else {}
+ status = fal_status_value(last_payload)
+ if status in {"COMPLETED", "SUCCEEDED", "SUCCESS", "DONE"}:
+ break
+ if status in {"FAILED", "ERROR", "CANCELED", "CANCELLED"}:
+ raise HTTPException(status_code=502, detail=f"fal.ai 任务失败：{fal_failure_message(last_payload) or last_payload}")
+ else:
+ raise HTTPException(status_code=504, detail=f"fal.ai 生图任务超时：request_id={request_id or response_url}，最后响应：{last_payload}")
+
+ result_response = await client.get(response_url, headers=headers)
+ result_response.raise_for_status()
+ return result_response.json() if result_response.text else {}
+
+async def generate_fal_provider_image(prompt, size, model, reference_images=None, provider=None, quality=None):
+ provider = provider or get_api_provider_exact("fal")
+ body = fal_submit_payload(prompt, size, model, reference_images, quality)
+ async with httpx.AsyncClient(timeout=httpx.Timeout(connect=20.0, read=1800.0, write=120.0, pool=20.0)) as client:
+ response = await client.post(fal_queue_url(provider, model), headers=fal_headers(provider), json=body)
+ response.raise_for_status()
+ submit_raw = response.json() if response.text else {}
+ raw = await wait_for_fal_result(client, provider, model, submit_raw)
+ if isinstance(raw, dict):
+ raw.setdefault("_fal_request", submit_raw)
+ return extract_image(raw), raw
+
async def generate_ai_image(prompt, size, quality, model, reference_images=None, provider_id="comfly"):
provider = get_api_provider(provider_id)
if provider["id"] == "modelscope":
@@ -8637,6 +8850,8 @@ async def generate_ai_image(prompt, size, quality, model, reference_images=None,
return await generate_gemini_provider_image(prompt, size, model, reference_images, provider)
if is_volcengine_provider(provider):
return await generate_volcengine_provider_image(prompt, size, model, reference_images, provider)
+ if is_fal_provider(provider):
+ return await generate_fal_provider_image(prompt, size, model, reference_images, provider, quality)
is_gpt2 = is_gpt_image_2_model(model)
is_apimart = is_apimart_provider(provider)
# 不对 GPT 尺寸做任何缩小/拦截：用户选什么尺寸就原样发给上游；
@@ -10368,6 +10583,8 @@ async def save_providers(payload: List[ApiProviderPayload]):
provider["protocol"] = "runninghub"
if provider["id"] == "volcengine":
provider["protocol"] = "volcengine"
+ if provider["id"] == "fal":
+ provider["protocol"] = "fal"
if not providers:
raise HTTPException(status_code=400, detail="至少保留一个 API 平台")
# 强制最多一个 primary（取最后被标记的；都没标记则保持原样不强制）
@@ -10416,9 +10633,13 @@ def protocol_from_payload(payload):
return "runninghub"
if provider_id == "jimeng":
return "jimeng"
+ if provider_id == "fal":
+ return "fal"
base_url = str(getattr(payload, "base_url", "") or "").strip().lower()
if "runninghub.cn" in base_url or "runninghub.ai" in base_url:
return "runninghub"
+ if "fal.ai" in base_url or "fal.run" in base_url:
+ return "fal"
protocol = str(getattr(payload, "protocol", "") or "openai").strip().lower()
return protocol if protocol in SUPPORTED_PROVIDER_PROTOCOLS else "openai"
@@ -10438,6 +10659,8 @@ def api_key_from_payload(payload, protocol: str = ""):
return value
if protocol == "volcengine":
return volcengine_provider_api_key("")
+ if protocol == "fal":
+ return provider_env_key_value("fal")
return ""
def upstream_models_url(base_url: str, protocol: str):
@@ -10452,10 +10675,87 @@ def upstream_models_url(base_url: str, protocol: str):
def upstream_model_headers(api_key: str, protocol: str):
if protocol == "gemini":
return {"x-goog-api-key": api_key, "Accept": "application/json"}
+ if protocol == "fal":
+ return {"Authorization": f"Key {strip_auth_scheme(api_key, 'Key')}", "Accept": "application/json"}
if protocol == "runninghub":
return {"Authorization": bearer_auth_value(api_key), "Accept": "application/json"}
return {"Authorization": bearer_auth_value(api_key), "Accept": "application/json"}
+def fal_model_id(item):
+ if isinstance(item, str):
+ return item.strip()
+ if not isinstance(item, dict):
+ return ""
+ return str(
+ item.get("id")
+ or item.get("endpoint_id")
+ or item.get("endpointId")
+ or item.get("model_id")
+ or item.get("modelId")
+ or item.get("slug")
+ or item.get("name")
+ or ""
+ ).strip()
+
+def fal_is_image_model(item):
+ if not isinstance(item, dict):
+ return True
+ text = " ".join(
+ str(item.get(key) or "")
+ for key in ("category", "type", "tags", "description", "id", "endpoint_id", "name")
+ ).lower()
+ if any(word in text for word in ("video", "audio", "speech", "voice", "music", "llm", "chat", "embedding", "3d")):
+ return False
+ return any(word in text for word in ("image", "flux", "stable-diffusion", "sdxl", "text-to-image", "image-to-image", "nano-banana"))
+
+async def fetch_fal_models_payload(api_key: str):
+ if not api_key:
+ raise HTTPException(status_code=400, detail="请先填写或保存 fal.ai API Key")
+ headers = upstream_model_headers(api_key, "fal")
+ categories = ["text-to-image", "image-to-image", "image-editing"]
+ ids = []
+ raw_items = []
+ async with httpx.AsyncClient(timeout=30) as client:
+ for category in categories:
+ cursor = ""
+ for _page in range(5):
+ params = {"category": category, "limit": 100}
+ if cursor:
+ params["cursor"] = cursor
+ response = await client.get(FAL_MODELS_API_URL, headers=headers, params=params)
+ if response.status_code >= 400 and category != categories[0]:
+ break
+ response.raise_for_status()
+ raw = response.json() if response.text else {}
+ items = []
+ if isinstance(raw, dict):
+ for key in ("data", "models", "items", "results"):
+ if isinstance(raw.get(key), list):
+ items = raw[key]
+ break
+ cursor = str(raw.get("next_cursor") or raw.get("nextCursor") or raw.get("cursor") or "").strip()
+ elif isinstance(raw, list):
+ items = raw
+ cursor = ""
+ raw_items.extend(items)
+ for item in items:
+ model_id = fal_model_id(item)
+ if model_id and fal_is_image_model(item) and model_id not in ids:
+ ids.append(model_id)
+ if not cursor:
+ break
+ if not ids:
+ ids = list(FAL_DEFAULT_IMAGE_MODELS)
+ return {
+ "total": len(ids),
+ "protocol": "fal",
+ "image_models": ids,
+ "chat_models": [],
+ "video_models": [],
+ "all": ids,
+ "raw": {"models": raw_items[:200]},
+ }
+
def volcengine_default_model_payload(status=200, message="", raw=None):
return {
"ok": True,
@@ -10557,16 +10857,21 @@ async def probe_openai_models_endpoint(client, base_url: str, api_key: str):
return False, {"status": response.status_code, "message": f"OpenAI /v1/models 不可用 (HTTP {response.status_code})", "raw": raw}
return False, {"status": response.status_code, "message": f"OpenAI /v1/models 服务端错误 {response.status_code}", "raw": raw}
-async def probe_volcengine_auto_detect(client, base_url: str, api_key: str):
+def is_likely_volcengine_base_url(base_url: str):
+ host = urllib.parse.urlparse(str(base_url or "").strip()).netloc.lower()
+ return any(key in host for key in ("volces.com", "volcengine", "byteplusapi.com"))
+
+async def probe_volcengine_auto_detect(client, base_url: str, api_key: str, force: bool = False):
+ likely_volcengine = force or is_likely_volcengine_base_url(base_url)
task_ok, task_probe = await probe_volcengine_task_endpoint(client, base_url, api_key)
- if task_ok:
+ if task_ok and likely_volcengine and task_probe.get("status") != 404:
return True, {
"status": task_probe.get("status") or 200,
"message": "检测到方舟/Ark 任务协议",
"raw": {"task_probe": task_probe.get("raw")},
}
compat_ok, compat_probe = await probe_openai_compat_bearer_endpoint(client, base_url, api_key)
- if compat_ok:
+ if compat_ok and likely_volcengine:
return True, {
"status": compat_probe.get("status") or 200,
"message": "检测到方舟/Ark Bearer 鉴权入口（OpenAI 兼容透传）",
@@ -10659,6 +10964,21 @@ async def test_provider_connection(payload: TestConnectionPayload):
"protocol": "runninghub",
"raw": payload_models.get("raw"),
}
+ if protocol == "fal":
+ api_key = api_key_from_payload(payload, protocol)
+ payload_models = await fetch_fal_models_payload(api_key)
+ return {
+ "ok": True,
+ "status": 200,
+ "message": "fal.ai API 可用，已拉取图像生成模型。",
+ "model_count": payload_models["total"],
+ "image_models": payload_models["image_models"],
+ "chat_models": [],
+ "video_models": [],
+ "all": payload_models["all"],
+ "protocol": "fal",
+ "raw": payload_models.get("raw"),
+ }
base_url = (payload.base_url or "").strip().rstrip("/")
if not base_url:
raise HTTPException(status_code=400, detail="请先填写请求地址")
@@ -10682,7 +11002,7 @@ async def test_provider_connection(payload: TestConnectionPayload):
return {"ok": False, "status": resp.status_code, "message": f"上游 {endpoint_label} 返回网页 HTML，请检查请求地址是否为 API Base URL"}
if resp.status_code >= 400:
if protocol == "volcengine":
- detected, probe = await probe_volcengine_auto_detect(client, base_url, api_key)
+ detected, probe = await probe_volcengine_auto_detect(client, base_url, api_key, force=True)
if detected:
message = f"{probe.get('message') or '方舟任务接口可达'}；但 /api/v3/models 不可用。请按实际方舟控制台模型名称手动填写视频模型。"
return volcengine_default_model_payload(status=probe.get("status") or resp.status_code, message=message, raw={"models_error": resp.text[:300], **(probe.get("raw") or {})})
@@ -10696,7 +11016,7 @@ async def test_provider_connection(payload: TestConnectionPayload):
grouped, ids = parse_upstream_models(data, protocol)
grouped, ids = apply_agnes_model_defaults(base_url, grouped, ids)
if protocol == "volcengine" and not ids:
- detected, probe = await probe_volcengine_auto_detect(client, base_url, api_key)
+ detected, probe = await probe_volcengine_auto_detect(client, base_url, api_key, force=True)
if detected:
return volcengine_default_model_payload(status=resp.status_code, raw=data)
return {
@@ -10713,7 +11033,7 @@ async def test_provider_connection(payload: TestConnectionPayload):
if protocol == "volcengine":
try:
async with httpx.AsyncClient(timeout=15) as client:
- detected, probe = await probe_volcengine_auto_detect(client, base_url, api_key)
+ detected, probe = await probe_volcengine_auto_detect(client, base_url, api_key, force=True)
if detected:
message = f"{probe.get('message') or '方舟任务接口可达'}；但模型列表请求失败。请按实际方舟控制台模型名称手动填写视频模型。"
return volcengine_default_model_payload(status=probe.get("status") or 0, message=message, raw={"models_error": str(e)[:300], **(probe.get("raw") or {})})
@@ -10732,6 +11052,20 @@ async def probe_async_endpoint(payload: TestConnectionPayload):
api_key = api_key_from_payload(payload, protocol)
if not api_key:
raise HTTPException(status_code=400, detail="请先填写或保存 API Key")
+ if protocol == "fal":
+ payload_models = await fetch_fal_models_payload(api_key)
+ return {
+ "ok": True,
+ "protocol": "fal",
+ "status_code": 200,
+ "message": "fal.ai API 可用，已拉取图像生成模型。",
+ "raw": payload_models.get("raw"),
+ "model_count": payload_models["total"],
+ "image_models": payload_models["image_models"],
+ "chat_models": [],
+ "video_models": [],
+ "all": payload_models["all"],
+ }
if protocol == "volcengine":
try:
async with httpx.AsyncClient(timeout=15) as client:
@@ -10863,6 +11197,8 @@ async def fetch_models_from_upstream(base_url: str, api_key: str, protocol: str
if protocol == "runninghub":
provider = {"id": "runninghub", "name": "RunningHub", "base_url": base_url or RUNNINGHUB_DEFAULT_BASE_URL, "protocol": "runninghub", "api_key": api_key}
return await runninghub_models_payload(provider)
+ if protocol == "fal":
+ return await fetch_fal_models_payload(api_key)
base_url = (base_url or "").strip().rstrip("/")
if not base_url:
raise HTTPException(status_code=400, detail="请先填写请求地址")
@@ -10885,7 +11221,7 @@ async def fetch_models_from_upstream(base_url: str, api_key: str, protocol: str
raise HTTPException(status_code=400, detail=f"上游 {endpoint_label} 返回网页 HTML，请检查请求地址是否为 API Base URL")
if resp.status_code >= 400:
if protocol == "volcengine":
- detected, probe = await probe_volcengine_auto_detect(client, base_url, api_key)
+ detected, probe = await probe_volcengine_auto_detect(client, base_url, api_key, force=True)
if detected:
payload = volcengine_default_model_payload(
status=probe.get("status") or resp.status_code,
@@ -10926,7 +11262,7 @@ async def fetch_models_from_upstream(base_url: str, api_key: str, protocol: str
if protocol == "volcengine":
try:
async with httpx.AsyncClient(timeout=15) as client:
- detected, probe = await probe_volcengine_auto_detect(client, base_url, api_key)
+ detected, probe = await probe_volcengine_auto_detect(client, base_url, api_key, force=True)
if detected:
payload = volcengine_default_model_payload(
status=probe.get("status") or 0,
diff --git a/static/api-settings.html b/static/api-settings.html
index 3c9b6d145..e316c06f1 100644
--- a/static/api-settings.html
+++ b/static/api-settings.html
@@ -15,12 +15,12 @@
} catch(e) {}
})();
-
-
-
-
-
-
+
+
+
+
+
+
@@ -228,6 +228,7 @@
+
@@ -471,6 +472,6 @@
-
+