feat: add xai video model

RULES.md

@@ -163,7 +163,8 @@
 - `VOICE_PROVIDER`：配音通道，服务端固定使用 `azure_openai`；旧环境若写 `minimax` 会被忽略
 - `AZURE_OPENAI_BASE_URL` / `AZURE_OPENAI_API_KEY`：微软 Azure OpenAI 协议配音网关；本地未单独配置 Key 时回退复用 `LLM_API_KEY`
 - `AZURE_TTS_MODEL` / `AZURE_TTS_VOICE_ID` / `AZURE_TTS_VOICE_POOL` / `AZURE_TTS_PATH` / `AZURE_TTS_PATHS`：Azure OpenAI TTS 模型、默认音色、音色池和 OpenAI 协议语音路径；后端会按 `AZURE_TTS_PATHS` 依次尝试，便于区分路径不对和整条语音服务不可用
-- `POE_API_KEY` / `VIDEO_API_KEY`：视频生成通道 Key，只能放本地环境变量
+- `POE_API_KEY` / `VIDEO_API_KEY`：默认视频生成通道 Key，只能放本地环境变量
+- `XAI_VIDEO_API_BASE_URL` / `XAI_VIDEO_API_KEY` / `VIDEO_MODEL_XAI`：xAI / Grok Imagine Video 独立视频通道；默认 base 为 `https://ai.skg.com/ezlink/xai`，模型为 `grok-imagine-video`，真实 key 只放本地 `api/.env`、本地 Docker `deploy/.env.local` 或服务器 `deploy/.env.production`，不入库。未配置 `XAI_VIDEO_API_KEY` 时 `/health` 会标记 xAI 视频不可用，画布不显示该模型。
 - `PASSWORD_AUTH_ENABLED`：生产密码登录总开关；当前固定为 `false`，只允许飞书免登录。若应急恢复密码入口，必须显式改成 `true` 并重启 API。
 - `WEB_AUTH_USERNAME` / `WEB_AUTH_PASSWORD` / `WEB_AUTH_SESSION_SECRET`：生产备用网页登录和会话签名配置；密码和 session secret 只放服务器环境变量，不入库。当前密码入口被 `PASSWORD_AUTH_ENABLED=false` 禁用；即使只开飞书免登录，也必须配置 `WEB_AUTH_SESSION_SECRET` 用于签名会话 Cookie。
 - `FEISHU_APP_ID` / `FEISHU_APP_SECRET`：飞书免登录 OAuth 应用凭证；只放服务器 `deploy/.env.production` 或本地 `api/.env`，不入库。

api/.env.example

@@ -61,6 +61,7 @@ YTDLP_COOKIES_FILE=
 YTDLP_COOKIES_FROM_BROWSER=
 VIDEO_MODEL=seedance
 VIDEO_MODEL_SEEDANCE=seedance-2-fast
+VIDEO_MODEL_XAI=grok-imagine-video
 VIDEO_MODEL_KLING=kling-omni
 VIDEO_MODEL_VEO3=veo-3.1-fast
 
@@ -96,6 +97,13 @@ POE_API_KEY=
 # VIDEO_STATUS_PATH=/api/v3/contents/generations/tasks/{id}
 # VIDEO_CONTENT_PATH=/api/v3/contents/generations/tasks/{id}/content
 #
+# SKG xAI/Grok Imagine 视频网关。真实 key 只填本地/服务器私有 .env。
+XAI_VIDEO_API_BASE_URL=https://ai.skg.com/ezlink/xai
+XAI_VIDEO_API_KEY=
+XAI_VIDEO_CREATE_PATH=/v1/videos/generations
+XAI_VIDEO_STATUS_PATH=/v1/videos/{id}
+XAI_VIDEO_CONTENT_PATH=
+#
 # 自定义视频网关覆盖；留空时如配置 POE_API_KEY，则走 Poe。
 VIDEO_API_BASE_URL=
 VIDEO_API_KEY=

api/main.py

@@ -350,9 +350,31 @@ VIDEO_MODEL_ALIASES = {
     "veo3": env_video_model("VIDEO_MODEL_VEO3", "veo-3.1-fast"),
     "veo": env_video_model("VIDEO_MODEL_VEO3", "veo-3.1-fast"),
     "voe": env_video_model("VIDEO_MODEL_VEO3", "veo-3.1-fast"),
+    "grok_imagine_video": env_video_model("VIDEO_MODEL_XAI", "grok-imagine-video"),
+    "grok-imagine-video": env_video_model("VIDEO_MODEL_XAI", "grok-imagine-video"),
+    "xai": env_video_model("VIDEO_MODEL_XAI", "grok-imagine-video"),
 }
 VIDEO_API_BASE_URL = os.getenv("VIDEO_API_BASE_URL", "").strip()
 VIDEO_API_KEY = os.getenv("VIDEO_API_KEY", "").strip()
+_VIDEO_XAI_BASE_DEFAULT = (
+    VIDEO_API_BASE_URL
+    if "xai" in VIDEO_API_BASE_URL.lower()
+    else "https://ai.skg.com/ezlink/xai"
+)
+XAI_VIDEO_API_BASE_URL = (
+    os.getenv("XAI_VIDEO_API_BASE_URL")
+    or os.getenv("XAI_GATEWAY_BASE")
+    or _VIDEO_XAI_BASE_DEFAULT
+).strip().rstrip("/")
+XAI_VIDEO_API_KEY = (
+    os.getenv("XAI_VIDEO_API_KEY")
+    or os.getenv("XAI_GATEWAY_KEY")
+    or (VIDEO_API_KEY if "xai" in VIDEO_API_BASE_URL.lower() else "")
+).strip()
+XAI_VIDEO_MODEL = VIDEO_MODEL_ALIASES["xai"]
+XAI_VIDEO_CREATE_PATH = os.getenv("XAI_VIDEO_CREATE_PATH", "/v1/videos/generations").strip() or "/v1/videos/generations"
+XAI_VIDEO_STATUS_PATH = os.getenv("XAI_VIDEO_STATUS_PATH", "/v1/videos/{id}").strip() or "/v1/videos/{id}"
+XAI_VIDEO_CONTENT_PATH = os.getenv("XAI_VIDEO_CONTENT_PATH", "").strip()
 WEB_AUTH_USERNAME = os.getenv("WEB_AUTH_USERNAME", "").strip()
 WEB_AUTH_PASSWORD = os.getenv("WEB_AUTH_PASSWORD", "").strip()
 WEB_AUTH_SESSION_SECRET = os.getenv("WEB_AUTH_SESSION_SECRET", "").strip()
@@ -389,6 +411,12 @@ WEB_AUTH_CONFIGURED = bool(PASSWORD_AUTH_CONFIGURED or FEISHU_AUTH_CONFIGURED)
 
 def default_video_gateway_paths(base_url: str) -> tuple[str, str, str]:
     base = base_url.strip().rstrip("/").lower()
+    if "api.x.ai" in base or "/ezlink/xai" in base:
+        return (
+            "/v1/videos/generations",
+            "/v1/videos/{id}",
+            "",
+        )
     if "ai.skg.com/doubao" in base:
         return (
             "/api/v3/contents/generations/tasks",
@@ -1446,13 +1474,30 @@ def video_uses_poe() -> bool:
     return bool(POE_API_KEY)
 
 
-def video_uses_ark() -> bool:
-    base = video_api_base()
+def is_xai_video_model(model: str | None) -> bool:
+    value = (model or "").strip().lower()
+    if not value:
+        value = (VIDEO_MODEL or "").strip().lower()
+    resolved = VIDEO_MODEL_ALIASES.get(value, value).strip().lower()
+    xai_model = (XAI_VIDEO_MODEL or "grok-imagine-video").strip().lower()
+    return resolved == xai_model or resolved.startswith("grok-imagine-video")
+
+
+def video_uses_xai(model: str | None = None) -> bool:
+    return is_xai_video_model(model) or "api.x.ai" in video_api_base(model).lower() or "/ezlink/xai" in video_api_base(model).lower()
+
+
+def video_uses_ark(model: str | None = None) -> bool:
+    if video_uses_xai(model):
+        return False
+    base = video_api_base(model)
     return "ark.cn-beijing.volces.com" in base or "ai.skg.com/doubao" in base
 
 
-def video_provider_name() -> str:
-    base = video_api_base()
+def video_provider_name(model: str | None = None) -> str:
+    base = video_api_base(model)
+    if video_uses_xai(model):
+        return "xai"
     if video_uses_poe():
         return "poe"
     if "ai.skg.com/doubao" in base:
@@ -1462,7 +1507,9 @@ def video_provider_name() -> str:
     return "custom"
 
 
-def video_api_base() -> str:
+def video_api_base(model: str | None = None) -> str:
+    if is_xai_video_model(model):
+        return XAI_VIDEO_API_BASE_URL.rstrip("/")
     if VIDEO_API_BASE_URL:
         return VIDEO_API_BASE_URL.rstrip("/")
     if POE_API_KEY:
@@ -1470,7 +1517,13 @@ def video_api_base() -> str:
     return (LLM_BASE_URL or "https://api.openai.com/v1").rstrip("/")
 
 
-def video_api_key() -> str:
+def video_api_key(model: str | None = None) -> str:
+    if is_xai_video_model(model):
+        if XAI_VIDEO_API_KEY:
+            return XAI_VIDEO_API_KEY
+        if "xai" in VIDEO_API_BASE_URL.lower() and VIDEO_API_KEY:
+            return VIDEO_API_KEY
+        return ""
     if VIDEO_API_KEY:
         return VIDEO_API_KEY
     if video_uses_poe():
@@ -1478,14 +1531,26 @@ def video_api_key() -> str:
     return LLM_API_KEY
 
 
+def video_create_paths(model: str | None = None) -> list[str]:
+    return [XAI_VIDEO_CREATE_PATH] if video_uses_xai(model) else VIDEO_CREATE_PATHS
+
+
+def video_status_path(model: str | None = None) -> str:
+    return XAI_VIDEO_STATUS_PATH if video_uses_xai(model) else VIDEO_STATUS_PATH
+
+
+def video_content_path(model: str | None = None) -> str:
+    return XAI_VIDEO_CONTENT_PATH if video_uses_xai(model) else VIDEO_CONTENT_PATH
+
+
 def video_path(template: str, **values: str) -> str:
     path = template.format(**values)
     return path if path.startswith("/") else f"/{path}"
 
 
-def ensure_video_api_configured() -> None:
-    if not video_api_key():
-        raise HTTPException(503, "POE_API_KEY、VIDEO_API_KEY 或 LLM_API_KEY 未配置，无法调用生视频 API")
+def ensure_video_api_configured(model: str | None = None) -> None:
+    if not video_api_key(model):
+        raise HTTPException(503, "POE_API_KEY、VIDEO_API_KEY、XAI_VIDEO_API_KEY 或 LLM_API_KEY 未配置，无法调用生视频 API")
 
 
 def storyboard_ref_path(job_id: str, ref: dict | None) -> Path | None:
@@ -4973,13 +5038,16 @@ def _image_size_payload(raw: str | None, model: str | None = None) -> dict:
     return {} if size == "auto" else {"size": size}
 
 
-def video_duration_options() -> list[int]:
-    if video_uses_ark():
+def video_duration_options(model: str | None = None) -> list[int]:
+    if video_uses_ark(model) or video_uses_xai(model):
         return [5, 8, 10, 12, 15]
     return [4, 8, 12]
 
 
-def video_size_options() -> list[dict]:
+def video_size_options(model: str | None = None) -> list[dict]:
+    if video_uses_xai(model):
+        allowed = {"720x1280", "1280x720", "1024x1024"}
+        return [item for item in VIDEO_SIZE_CHOICES if str(item["value"]) in allowed]
     return VIDEO_SIZE_CHOICES
 
 
@@ -4992,7 +5060,9 @@ def _video_resolution_choice(value: str) -> dict:
 
 def _video_resolution_values_for_model(model: str | None) -> list[str]:
     concrete = (model or "").strip().lower()
-    if video_uses_ark():
+    if video_uses_xai(concrete):
+        return ["480p", "720p"]
+    if video_uses_ark(concrete):
         if "seedance-2-0-fast" in concrete:
             return ["480p", "720p"]
         if "seedance-2-0" in concrete or "seedance-1-5-pro" in concrete or "seedance-1-0-pro" in concrete:
@@ -5029,7 +5099,7 @@ def _normalize_video_resolution(raw: str | None, model: str | None = None) -> st
     return value
 
 
-def _normalize_video_size(raw: str | None) -> str:
+def _normalize_video_size(raw: str | None, model: str | None = None) -> str:
     value = (raw or "720x1280").strip().lower().replace(" ", "")
     aliases = {
         "vertical": "720x1280",
@@ -5046,7 +5116,7 @@ def _normalize_video_size(raw: str | None) -> str:
         "3:4": "960x1280",
     }
     value = aliases.get(value, value)
-    allowed = {str(item["value"]) for item in VIDEO_SIZE_CHOICES}
+    allowed = {str(item["value"]) for item in video_size_options(model)}
     if value not in allowed:
         raise HTTPException(400, f"unsupported video size: {raw}")
     return value
@@ -5060,14 +5130,18 @@ def video_model_options() -> list[dict]:
         "veo3": "Veo 3",
         "veo": "Veo",
         "voe": "Veo",
+        "xai": "Grok Imagine Video",
+        "grok_imagine_video": "Grok Imagine Video",
+        "grok-imagine-video": "Grok Imagine Video",
     }
     concrete_label_map = {
         "doubao-seedance-2-0-fast-260128": "Seedance 2.0 Fast",
         "doubao-seedance-2-0-260128": "Seedance 2.0 高清",
+        "grok-imagine-video": "Grok Imagine Video",
     }
     seen_models: set[str] = set()
     options: list[dict] = []
-    for key in ["seedance", "seedance_hd", "kling", "veo3", "veo"]:
+    for key in ["seedance", "seedance_hd", "xai", "kling", "veo3", "veo"]:
         if key not in VIDEO_MODEL_ALIASES:
             continue
         model = VIDEO_MODEL_ALIASES[key]
@@ -5078,13 +5152,14 @@ def video_model_options() -> list[dict]:
             "id": key,
             "label": concrete_label_map.get(model, label_map.get(key, key)),
             "model": model,
-            "description": f"当前视频网关可选模型；单次时长最高 {max(video_duration_options())} 秒",
-            "duration_options": video_duration_options(),
-            "size_options": video_size_options(),
+            "provider": video_provider_name(model),
+            "description": f"当前视频网关可选模型；单次时长最高 {max(video_duration_options(model))} 秒",
+            "duration_options": video_duration_options(model),
+            "size_options": video_size_options(model),
             "resolution_options": video_resolution_options(model),
             "default_resolution": default_video_resolution(model),
-            "max_duration_seconds": max(video_duration_options()),
-            "available": bool(video_api_key()),
+            "max_duration_seconds": max(video_duration_options(model)),
+            "available": bool(video_api_key(model)),
         })
     default_model = resolve_video_model(VIDEO_MODEL)
     if not any(item["id"] == VIDEO_MODEL or item["model"] == default_model for item in options):
@@ -5092,13 +5167,14 @@ def video_model_options() -> list[dict]:
             "id": VIDEO_MODEL,
             "label": label_map.get(VIDEO_MODEL, VIDEO_MODEL),
             "model": default_model,
+            "provider": video_provider_name(default_model),
             "description": "默认视频模型",
-            "duration_options": video_duration_options(),
-            "size_options": video_size_options(),
+            "duration_options": video_duration_options(default_model),
+            "size_options": video_size_options(default_model),
             "resolution_options": video_resolution_options(default_model),
             "default_resolution": default_video_resolution(default_model),
-            "max_duration_seconds": max(video_duration_options()),
-            "available": bool(video_api_key()),
+            "max_duration_seconds": max(video_duration_options(default_model)),
+            "available": bool(video_api_key(default_model)),
         })
     return options
 
@@ -6585,6 +6661,10 @@ def health() -> dict:
             "video_base_url": video_api_base(),
             "video_configured": bool(video_api_key()),
             "video_create_paths": VIDEO_CREATE_PATHS,
+            "xai_video_model": XAI_VIDEO_MODEL,
+            "xai_video_base_url": XAI_VIDEO_API_BASE_URL,
+            "xai_video_configured": bool(video_api_key(XAI_VIDEO_MODEL)),
+            "xai_video_create_path": XAI_VIDEO_CREATE_PATH,
         },
     }
 
@@ -8832,8 +8912,8 @@ class ProductFusionDescriptionReq(BaseModel):
     shots: list[ProductFusionShot] = Field(default_factory=list)
 
 
-def video_seconds(duration: float) -> str:
-    if video_uses_ark():
+def video_seconds(duration: float, model: str | None = None) -> str:
+    if video_uses_ark(model) or video_uses_xai(model):
         if duration <= 0:
             return "5"
         return str(max(4, min(15, round(duration))))
@@ -8848,7 +8928,7 @@ def resolve_video_model(raw: str | None) -> str:
     requested = (raw or VIDEO_MODEL or "seedance").strip()
     lowered = requested.lower()
     if lowered in {"sora", "sora-2", "sora_2"}:
-        raise HTTPException(400, "Sora 已停用，请选择当前已接入的 Seedance")
+        raise HTTPException(400, "Sora 已停用，请选择当前已接入的 Seedance 或 Grok Imagine Video")
     return VIDEO_MODEL_ALIASES.get(lowered, requested)
 
 
@@ -8897,6 +8977,12 @@ def video_url_from_response(data: dict) -> str:
             v = content.get(key)
             if isinstance(v, str) and v:
                 return v
+    video = data.get("video")
+    if isinstance(video, dict):
+        for key in ("url", "video_url", "download_url", "file_url"):
+            v = video.get(key)
+            if isinstance(v, str) and v:
+                return v
     return ""
 
 
@@ -8987,12 +9073,15 @@ def _video_create_failure_message(create_errors: list[str]) -> str:
     return "视频生成失败：视频模型没有接受本次请求。请换一张参考图或简化提示词后重试；如果持续失败，请联系管理员。"
 
 
-def download_generated_video(client, base: str, headers: dict, provider_id: str, direct_url: str, out_mp4: Path) -> None:
+def download_generated_video(client, base: str, headers: dict, provider_id: str, direct_url: str, out_mp4: Path, model: str | None = None) -> None:
     if direct_url:
         url = direct_url if direct_url.startswith("http") else f"{base}{direct_url if direct_url.startswith('/') else '/' + direct_url}"
         r = client.get(url, headers=headers if url.startswith(base) else None)
     else:
-        r = client.get(f"{base}{video_path(VIDEO_CONTENT_PATH, id=provider_id)}", headers=headers)
+        content_path = video_content_path(model)
+        if not content_path:
+            raise RuntimeError("视频生成完成但未返回可下载地址")
+        r = client.get(f"{base}{video_path(content_path, id=provider_id)}", headers=headers)
     r.raise_for_status()
     out_mp4.write_bytes(r.content)
 
@@ -9032,7 +9121,33 @@ def submit_video_create(
     product_imgs: list[Path] | None = None,
     primary_role: str = "first_frame",
 ):
-    if video_uses_ark():
+    model = str(payload.get("model") or "")
+    if video_uses_xai(model):
+        duration = int(float(str(payload.get("duration") or payload.get(VIDEO_DURATION_FIELD) or 8)))
+        data: dict = {
+            "model": model,
+            "prompt": payload["prompt"],
+            "duration": max(1, duration),
+            "aspect_ratio": size_to_video_ratio(str(payload.get("size", ""))),
+            "resolution": _normalize_video_resolution(str(payload.get("resolution") or ""), model),
+        }
+        reference_images: list[dict] = []
+        if ref_img.exists() and primary_role:
+            ref_payload = {"url": ark_reference_data_url(ref_img)}
+            if primary_role == "first_frame":
+                data["image"] = ref_payload
+            else:
+                reference_images.append(ref_payload)
+        if last_img and last_img.exists():
+            reference_images.append({"url": ark_reference_data_url(last_img)})
+        for product_img in (product_imgs or [])[:6]:
+            if product_img.exists():
+                reference_images.append({"url": ark_reference_data_url(product_img)})
+        if reference_images:
+            data["reference_images"] = reference_images[:6]
+        return client.post(url, headers={**headers, "Content-Type": "application/json"}, json=data)
+
+    if video_uses_ark(model):
         content = [{"type": "text", "text": payload["prompt"]}]
         if source_ref and source_ref.kind == "source_video" and source_ref.url:
             content.append(
@@ -9046,7 +9161,7 @@ def submit_video_create(
             {
                 "type": "image_url",
                 "image_url": {"url": ark_reference_data_url(ref_img)},
-                "role": primary_role,
+                "role": primary_role or "reference_image",
             }
         )
         if last_img and last_img.exists():
@@ -9112,8 +9227,8 @@ def render_storyboard_video(
     ref_img = out_dir / "reference.jpg"
     last_img = out_dir / "last_reference.jpg"
     out_mp4 = out_dir / "video.mp4"
-    base = video_api_base()
-    headers = {"Authorization": f"Bearer {video_api_key()}"}
+    base = video_api_base(model)
+    headers = {"Authorization": f"Bearer {video_api_key(model)}"}
 
     try:
         prepare_video_reference(ref_path, ref_img)
@@ -9133,15 +9248,15 @@ def render_storyboard_video(
             payload[VIDEO_DURATION_FIELD] = seconds
             create = None
             create_errors: list[str] = []
-            for create_path in VIDEO_CREATE_PATHS:
+            for create_path in video_create_paths(model):
                 resp = submit_video_create(client, f"{base}{video_path(create_path)}", headers, ref_img, payload, source_ref, prepared_last_img, prepared_product_imgs, primary_role)
-                if video_uses_ark() and source_ref and resp.status_code in {400, 422}:
+                if video_uses_ark(model) and source_ref and resp.status_code in {400, 422}:
                     create_errors.append(f"{video_path(create_path)} + reference_video -> HTTP {resp.status_code}: {resp.text[:700]}")
                     resp = submit_video_create(client, f"{base}{video_path(create_path)}", headers, ref_img, payload, None, prepared_last_img, prepared_product_imgs, primary_role)
-                if video_uses_ark() and prepared_last_img and resp.status_code in {400, 422}:
+                if video_uses_ark(model) and prepared_last_img and resp.status_code in {400, 422}:
                     create_errors.append(f"{video_path(create_path)} + last_frame -> HTTP {resp.status_code}: {resp.text[:700]}")
                     resp = submit_video_create(client, f"{base}{video_path(create_path)}", headers, ref_img, payload, None, None, prepared_product_imgs, primary_role)
-                if video_uses_ark() and prepared_product_imgs and resp.status_code in {400, 422}:
+                if video_uses_ark(model) and prepared_product_imgs and resp.status_code in {400, 422}:
                     create_errors.append(f"{video_path(create_path)} + product_reference -> HTTP {resp.status_code}: {resp.text[:700]}")
                     resp = submit_video_create(client, f"{base}{video_path(create_path)}", headers, ref_img, payload, None, prepared_last_img, None, primary_role)
                 if resp.status_code < 400:
@@ -9154,7 +9269,7 @@ def render_storyboard_video(
                 print(f"[video create failed] job={job_id} video={local_id} errors={' | '.join(create_errors)[:1800]}", flush=True)
                 raise RuntimeError(_video_create_failure_message(create_errors))
             data = create.json()
-            video_api_id = data.get("id") or provider_id or local_id
+            video_api_id = data.get("request_id") or data.get("id") or provider_id or local_id
             status = normalize_video_status(data.get("status"))
             progress = video_progress(data, 5)
             direct_url = video_url_from_response(data)
@@ -9171,7 +9286,7 @@ def render_storyboard_video(
             deadline = time.time() + VIDEO_POLL_TIMEOUT_SECONDS
             while status in {"queued", "in_progress"} and time.time() < deadline:
                 time.sleep(8)
-                poll = client.get(f"{base}{video_path(VIDEO_STATUS_PATH, id=video_api_id)}", headers=headers)
+                poll = client.get(f"{base}{video_path(video_status_path(model), id=video_api_id)}", headers=headers)
                 poll.raise_for_status()
                 pdata = poll.json()
                 status = normalize_video_status(pdata.get("status"))
@@ -9200,7 +9315,7 @@ def render_storyboard_video(
                 update_generated_video(job_id, local_id, status="failed", error=_video_public_error(raw_error or f"video status: {status}"), progress=progress, queue_message="")
                 return
 
-            download_generated_video(client, base, headers, video_api_id, direct_url, out_mp4)
+            download_generated_video(client, base, headers, video_api_id, direct_url, out_mp4, model)
             update_generated_video(
                 job_id,
                 local_id,
@@ -9286,7 +9401,6 @@ def refine_storyboard(job_id: str, idx: int, req: RefineStoryboardReq) -> dict:
 
 
 def _enqueue_storyboard_videos(job: Job, frame: KeyFrame, req: GenerateStoryboardVideoReq, bg: BackgroundTasks | None = None) -> list[str]:
-    ensure_video_api_configured()
     prompt = _ensure_english(req.prompt.strip())
     if not prompt and frame.storyboard:
         prompt = _storyboard_video_prompt(frame.storyboard, req.seed)
@@ -9295,7 +9409,7 @@ def _enqueue_storyboard_videos(job: Job, frame: KeyFrame, req: GenerateStoryboar
     count = max(1, min(12, int(req.count or 1)))
 
     ref = req.first_image or req.subject_image or req.product_image or req.scene_image or req.action_image
-    primary_role = "first_frame" if req.first_image else "reference_image"
+    primary_role = "first_frame" if req.first_image else ("reference_image" if ref else "")
     ref_path = storyboard_ref_path(job.id, ref) or (job_dir(job.id) / "frames" / f"{frame.index:03d}.jpg")
     if not ref_path.exists():
         raise HTTPException(404, "reference image missing")
@@ -9315,13 +9429,23 @@ def _enqueue_storyboard_videos(job: Job, frame: KeyFrame, req: GenerateStoryboar
             seen_ref_paths.add(key)
 
     model = resolve_video_model(req.model)
-    seconds = video_seconds(float(req.duration or 4))
-    video_size = _normalize_video_size(req.size)
+    ensure_video_api_configured(model)
+    seconds = video_seconds(float(req.duration or 4), model)
+    video_size = _normalize_video_size(req.size, model)
     video_resolution = _normalize_video_resolution(req.resolution, model)
     source_ref = req.source_ref
     if source_ref and source_ref.kind == "source_video" and not source_ref.url:
         source_ref = None
-    has_visual_reference = bool(ref_path.exists() or last_ref_path or reference_ref_paths)
+    has_visual_reference = bool(
+        req.first_image
+        or req.subject_image
+        or req.product_image
+        or req.scene_image
+        or req.action_image
+        or req.last_image
+        or raw_product_refs
+        or req.subject_images
+    )
     items: list[GeneratedVideo] = []
     ids: list[str] = []
     queued_tasks: list[tuple[str, tuple]] = []

deploy/.env.local.example

@@ -75,6 +75,7 @@ VIDEO_API_BASE_URL=https://ai.skg.com/doubao
 VIDEO_API_KEY=
 VIDEO_MODEL=seedance
 VIDEO_MODEL_SEEDANCE=doubao-seedance-2-0-fast-260128
+VIDEO_MODEL_XAI=grok-imagine-video
 VIDEO_MODEL_KLING=kling-omni
 VIDEO_MODEL_VEO3=veo-3.1-fast
 VIDEO_CREATE_PATHS=/api/v3/contents/generations/tasks
@@ -82,6 +83,11 @@ VIDEO_STATUS_PATH=/api/v3/contents/generations/tasks/{id}
 VIDEO_CONTENT_PATH=/api/v3/contents/generations/tasks/{id}/content
 VIDEO_DURATION_FIELD=seconds
 VIDEO_POLL_TIMEOUT_SECONDS=900
+XAI_VIDEO_API_BASE_URL=https://ai.skg.com/ezlink/xai
+XAI_VIDEO_API_KEY=
+XAI_VIDEO_CREATE_PATH=/v1/videos/generations
+XAI_VIDEO_STATUS_PATH=/v1/videos/{id}
+XAI_VIDEO_CONTENT_PATH=
 
 # Azure OpenAI TTS. Leave blank unless testing voice locally.
 AUDIO_REWRITE_MODEL=gemini-2.5-pro

deploy/.env.production.example

@@ -107,6 +107,7 @@ VIDEO_API_BASE_URL=https://ai.skg.com/doubao
 VIDEO_API_KEY=
 VIDEO_MODEL=seedance
 VIDEO_MODEL_SEEDANCE=doubao-seedance-2-0-fast-260128
+VIDEO_MODEL_XAI=grok-imagine-video
 VIDEO_MODEL_KLING=kling-omni
 VIDEO_MODEL_VEO3=veo-3.1-fast
 VIDEO_CREATE_PATHS=/api/v3/contents/generations/tasks
@@ -114,3 +115,8 @@ VIDEO_STATUS_PATH=/api/v3/contents/generations/tasks/{id}
 VIDEO_CONTENT_PATH=/api/v3/contents/generations/tasks/{id}/content
 VIDEO_DURATION_FIELD=seconds
 VIDEO_POLL_TIMEOUT_SECONDS=900
+XAI_VIDEO_API_BASE_URL=https://ai.skg.com/ezlink/xai
+XAI_VIDEO_API_KEY=
+XAI_VIDEO_CREATE_PATH=/v1/videos/generations
+XAI_VIDEO_STATUS_PATH=/v1/videos/{id}
+XAI_VIDEO_CONTENT_PATH=

docs/source-analysis.html

@@ -618,7 +618,7 @@
           <p><strong>2026-05-25 三模式版：</strong>默认首页再收敛为一个中央对话框，首页和画布底部输入框只让用户选文生图、文生视频、图生视频，然后手写提示词生成。图生视频只显示“上传图片”，不再把首帧 / 首尾帧这类模型实现概念作为主入口；营销图文不再作为首页默认入口。后端 <code>/health</code> 返回可选图片 / 视频模型、图片尺寸、视频画幅和真实可用视频时长，首页按返回值显示模型和规格选择；当前 Doubao / Seedance 生产链路单条最长 15 秒，不向用户暴露 30 秒按钮。</p>
           <p><strong>2026-05-25 根域名画布版：</strong><code>https://marketing.skg.com</code> 登录后直接进入个人生成画布，不再先进入 React 单对话框首页再点画布；<code>/canvas/</code> 只保留为旧链接兼容跳转。后续优先少改成熟画布结构，只在必要时改模式文案、生成接入和结果/队列显示。</p>
           <p><strong>2026-05-25 上游能力恢复版：</strong>用户明确要求“API 没关系，其他恢复，别削弱”。因此根域名画布恢复 <code>chatfire-AI/huobao-canvas</code> 的成熟节点和工作流结构：推荐词、AI 润色、自动执行、工作流模板、首帧/尾帧/参考图节点、图片/视频/LLM 配置、多角度分镜、故事板、绘本和批量下载都保留；只继续替换品牌、路由和 API 接入。生成请求仍走 SKG 后端 <code>/api</code> 与登录 Cookie，员工不需要个人 API Key。</p>
-          <p><strong>2026-05-25 媒体模型接入收口：</strong>图片和视频模型选择只暴露当前后端真实可用项：图片为 <code>auto</code>、<code>gpt-image-2</code>、<code>gemini-3-pro-image-preview</code>；视频当前只接通 <code>Seedance 2.0 Fast</code>（真实模型 <code>doubao-seedance-2-0-fast-260128</code>）。旧上游的 Nano Banana、Seedream、Kling、Veo 或浏览器本地自定义媒体模型不能进入生成下拉，避免同事选到实际不可用的模型。</p>
+          <p><strong>2026-05-25 媒体模型接入收口：</strong>图片和视频模型选择只暴露当前后端真实可用项：图片为 <code>auto</code>、<code>gpt-image-2</code>、<code>gemini-3-pro-image-preview</code>；视频已接通 <code>Seedance 2.0 Fast</code>（真实模型 <code>doubao-seedance-2-0-fast-260128</code>）和按独立 key 配置的 <code>Grok Imagine Video</code>（真实模型 <code>grok-imagine-video</code>）。旧上游的 Nano Banana、Seedream、Kling、Veo 或浏览器本地自定义媒体模型不能进入生成下拉，避免同事选到实际不可用的模型。</p>
           <p><strong>2026-05-26 公司沉淀版：</strong>画布项目从浏览器本地存储升级为服务端 Postgres 持久化；<code>localStorage</code> 只作为离线缓存和首次导入来源。后端同时建立用户、任务、资源索引和审计表，保留原有 <code>state.json</code> 文件作为任务详情真源，避免一次迁移动到大文件资产结构。</p>
           <p><strong>2026-05-26 AI 润色中性化：</strong>画布 <code>AI 润色</code> 不再复用 SKG 广告文案接口 <code>/creative/copy</code>。后端新增 <code>POST /prompt/polish</code>，前端 <code>useChat</code>、根画布输入框、文本节点和自动执行意图分析改走中性提示词/通用生成接口：只优化用户已经给出的主体、风格、镜头和细节，不主动添加 SKG、按摩产品、TikTok 广告话术或用户没有提到的品牌。当前润色链路会先清理上一次润色遗留的模板尾巴，再判断人物/无人/物体/场景/动物/未知主体；原文明确有人时才声明虚构 AI 角色，原文明确无人时才保留无人物约束，原文没写人时不主动造人但也不追加“必须无人物”的模板尾巴；当输入或参考图已经有人物时，按 AI 生成的虚拟角色继续描述，而不是把人物参考图判定为不可用。</p>
           <p><strong>2026-05-26 我的工作流云端版：</strong>工作流面板从只有公共模板扩展为“公共工作流 / 我的工作流”两类。当前画布可以保存成当前登录用户自己的云端工作流模板，后续在同一账号的其他电脑或浏览器打开后可插回画布；保存时只沉淀节点结构、连线、配置和提示词，主动清掉已生成图片、视频、任务进度、错误和运行态字段，避免把一次性生成结果误当模板复用。</p>
@@ -657,7 +657,7 @@
                 <tr><td><code>web/canvas-app/src/stores/workflows.js</code></td><td>我的工作流 store：调用 <code>GET/POST/DELETE /canvas-workflows</code> 读取、保存和删除当前登录用户自己的云端工作流模板。保存前会清理节点里的 <code>base64</code>、生成 URL、任务进度、错误、视频结果和 LLM 输出等运行态字段，只保留可复用的节点结构、连线、配置和提示词。</td></tr>
                 <tr><td><code>web/canvas-app/src/views/Canvas.vue</code></td><td>画布主交互：恢复上游底部 prompt composer、<code>AI 润色</code>、<code>自动执行</code>、推荐词、节点菜单、工作流面板、API/模型设置入口和批量下载入口。自动执行会调用 <code>useWorkflowOrchestrator</code> 分析提示词，创建文生图、图转视频、故事板、多角度分镜或绘本节点组；手动模式只创建文本节点，用户自行连接节点。工作流面板支持公共模板和我的工作流：公共模板走本地 <code>createNodes()</code>，我的工作流从云端 <code>workflow_data</code> 插回当前画布，并重新生成节点 ID、按视口中心重排、按映射重连边。Vue Flow 开启可见节点渲染，大画布不再把所有节点同时挂载到 DOM；节点数超过 120 时隐藏 MiniMap，减少点击后的同步重绘压力。底部推荐词来自共享短词池，4 个一组单行展示，刷新按钮在 30 组内轮换，不改变输入面板高度。</td></tr>
                 <tr><td><code>web/canvas-app/src/config/suggestions.js</code></td><td>首页和画布共用的推荐词配置：维护 <code>QUICK_SUGGESTION_GROUPS</code>，当前为 30 组 / 120 个短词，每组 4 个，控制刷新按钮的轮换范围；词条保持短小，避免推荐栏换行或顶起 composer。</td></tr>
-                <tr><td><code>web/canvas-app/src/config/models.js</code></td><td>画布媒体模型和规格的前端白名单：图片只内置 <code>auto</code>、<code>gpt-image-2</code>、<code>gemini-3-pro-image-preview</code>，尺寸只内置 <code>auto</code>、<code>1024x1536</code>、<code>1024x1024</code>、<code>1536x1024</code>；视频只内置 <code>seedance</code> / <code>Seedance 2.0 Fast</code>，画幅和时长对齐后端 <code>/health</code> 能力边界。<code>useModelConfig.js</code> 和 Pinia 模型 store 会忽略浏览器本地自定义图片/视频模型，防止旧缓存把不可用模型带回生成下拉。</td></tr>
+                <tr><td><code>web/canvas-app/src/config/models.js</code></td><td>画布媒体模型和规格的前端白名单：图片只内置 <code>auto</code>、<code>gpt-image-2</code>、<code>gemini-3-pro-image-preview</code>，尺寸只内置 <code>auto</code>、<code>1024x1536</code>、<code>1024x1024</code>、<code>1536x1024</code>；视频内置 <code>seedance</code> / <code>Seedance 2.0 Fast</code> 和默认不可用的 <code>xai</code> / <code>Grok Imagine Video</code>，后者只有后端 <code>/health</code> 回传 <code>available=true</code> 时才进入生成下拉。画幅和时长对齐后端 <code>/health</code> 能力边界。<code>useModelConfig.js</code> 和 Pinia 模型 store 会忽略浏览器本地自定义图片/视频模型，防止旧缓存把不可用模型带回生成下拉。</td></tr>
                 <tr><td><code>web/canvas-app/src/hooks/useCachedMediaUrl.js</code></td><td>画布媒体本地缓存 Hook：只缓存同源、登录保护下的 <code>/api/jobs/...</code> 和 <code>/api/agent-runs/...</code> 图片 / 视频 / 音频。图片节点和视频节点先用原始 URL 保证首屏可见，再后台写入浏览器 Cache Storage；下次打开同一素材时返回本机 <code>blob:</code> URL，减少反复从 VPS 下载。</td></tr>
                 <tr><td><code>web/canvas-app/src/hooks/useApi.js</code></td><td>画布到本项目后端的适配层：不再读取浏览器 API Key，而是使用当前登录会话 Cookie 调用 <code>/api</code>。文生图 / 图生图先创建轻量 creative job，再调用 <code>/frames/0/generate</code>；本地上传到图片节点的参考图也会先通过 <code>/creative/jobs/image</code> 写成后端资产，再把 <code>/api/jobs/...</code> URL 保存到节点，避免刷新后丢失。文生视频 / 图生视频调用 <code>/storyboard/video</code> 并轮询 <code>/jobs/{id}</code>，完成后把图片或 mp4 URL 写回画布节点。<code>useChat</code> 已从 SKG 广告文案接口切到 <code>/prompt/polish</code>：AI 润色显式使用 image/video prompt 模式，LLM 节点使用通用 chat 模式，避免自动注入用户没有提到的 SKG、产品、平台或营销语境；后端会清理旧润色模板尾巴、判断人物/无人/物体/场景意图，并在输出后检查“有人却禁止人物、无人却新增人物、未写 SKG 却出现 SKG”等冲突。图生视频实际提交到后端后，后端会对参考图追加 AI 虚拟角色条件说明，不要求前端判断图片里是否有人脸。</td></tr>
                 <tr><td><code>web/scripts/sync-canvas-root.mjs</code></td><td>构建桥接脚本：在 <code>next build</code> 静态导出完成后，把 Vite 画布产物 <code>web/canvas-app/dist</code> 覆盖到 <code>web/out</code> 根目录，使 <code>https://marketing.skg.com</code> 登录后直接进入画布；旧 <code>web/scripts/sync-canvas-dist.mjs</code> 保留但不再由生产构建调用。</td></tr>
@@ -692,7 +692,7 @@
               <tbody>
                 <tr><td><code>api/main.py</code></td><td>FastAPI 单文件后端：登录会话、状态模型、任务恢复、下载、抽帧、Vision、清洗、元素、分镜、原音频转写/翻译、声音与背景音分析、后续口播改写/TTS、文件返回；同时承载全局 <code>prompt_library</code> 和 <code>asset_library</code> 的磁盘索引、CRUD、删除保护和复制到 job API。启动时会初始化 Postgres schema、扫描现有 <code>state.json</code> / 资源库并写入索引；<code>/canvas-projects</code> 系列接口把画布项目按当前登录用户持久化，<code>/canvas-workflows</code> 系列接口把我的工作流按当前登录用户持久化为可复用模板。轻量创作入口 <code>POST /creative/jobs/image</code> 把上传图片或空白底图写成一个只有 0 号关键帧的 <code>Job</code>，让首页直接复用生图/生视频接口；该接口兼容无 body / JSON 空对象 / 正常 multipart 上传，避免无首帧文生图或文生视频时空 multipart 被 FastAPI 在业务前置解析阶段拒绝；<code>POST /prompt/polish</code> 用于中性 AI 润色和通用 LLM 文本生成，只保留用户明确给出的主体、品牌、产品、地点、风格和意图，不默认加入 SKG、按摩产品、平台或短视频广告话术。润色链路会先用 <code>_strip_previous_polish_boilerplate</code> 去掉旧模板尾巴，再用 <code>_classify_prompt_intent</code> 判断人物、无人、物体、场景、动物或未知主体，最后用 <code>_repair_polished_prompt</code> 修掉有人/无人矛盾、未写人却新增人物、未写 SKG 却出现 SKG 等冲突；<code>_append_reference_image_person_guard</code> 会在视频任务最终入队前给参考图请求追加条件提示，声明参考图里若有人物则按 AI 生成的虚拟角色处理；<code>/health</code> 返回 <code>database</code>、<code>image_options</code>、<code>image_size_options</code>、<code>video_options</code>、<code>video_size_options</code>、<code>video_duration_options</code> 和 <code>video_max_duration_seconds</code>；<code>/frames/{idx}/generate</code> 的 <code>model</code> 字段用于图片模型偏好，<code>size</code> 字段用于图片输出尺寸；<code>/storyboard/video</code> 继续使用 <code>model</code> 字段选择视频别名，并先校验画幅与时长能力边界，然后把 <code>GeneratedVideo</code> 写成 <code>queued</code> 占位并进入进程内视频队列。队列默认 <code>VIDEO_QUEUE_MAX_CONCURRENT=2</code>、<code>VIDEO_QUEUE_MAX_CONCURRENT_PER_USER=1</code>，同一用户连续提交不会占满全局并发；排队任务会回写 <code>queue_position</code>、<code>queue_size</code>、<code>queue_message</code>。旧 <code>AgentRun</code> 一键出片状态机、TK 复刻接口和 <code>POST /creative/copy</code> 作为明确的 SKG 营销文案接口继续保留。</td></tr>
                 <tr><td><code>api/db.py</code></td><td>Postgres 适配层：在 <code>DATABASE_URL</code> 存在且 <code>psycopg</code> 可用时启用；负责建表、健康检查、用户 upsert、审计日志、画布项目 CRUD、我的工作流 CRUD，以及把 <code>Job</code>、<code>AgentRun</code>、提示词库和素材库写入索引表。数据库不可用时本地开发会降级为 disabled，生产 <code>verify-prod-docker.sh</code> 会要求 <code>database.connected=true</code>。</td></tr>
-                <tr><td><code>video_model_options()</code></td><td>视频模型能力出口：如果 <code>seedance</code>、<code>kling</code>、<code>veo3</code>、<code>veo</code> 等业务别名实际都映射到同一个真实模型，会按真实模型去重，只给前端返回一个可用选项；当前生产真实模型为 <code>doubao-seedance-2-0-fast-260128</code>，前端显示为 <code>Seedance 2.0 Fast</code>。后续只有在服务器真的配置了不同可用视频模型时，才应把新的模型重新暴露给画布。</td></tr>
+                <tr><td><code>video_model_options()</code></td><td>视频模型能力出口：如果 <code>seedance</code>、<code>kling</code>、<code>veo3</code>、<code>veo</code> 等业务别名实际都映射到同一个真实模型，会按真实模型去重，只给前端返回一个可用选项；当前 Seedance 真实模型为 <code>doubao-seedance-2-0-fast-260128</code>，前端显示为 <code>Seedance 2.0 Fast</code>。新增 <code>xai</code> / <code>grok-imagine-video</code> 独立走 <code>XAI_VIDEO_API_BASE_URL=https://ai.skg.com/ezlink/xai</code>、<code>XAI_VIDEO_API_KEY</code>、<code>/v1/videos/generations</code> 和 <code>/v1/videos/{id}</code>，创建返回 <code>request_id</code>、轮询完成返回 <code>video.url</code>；未配置 xAI key 时 <code>/health</code> 会标记不可用，前端不显示。</td></tr>
                 <tr><td><code>api/product_library/skg-products</code></td><td>内置 SKG 白底产品图库：<code>manifest.json</code> 记录从桌面产品图筛出的 gallery 白底图和桌面 4 张产品角度图，<code>images/</code> 存 45 张参考图。</td></tr>
                 <tr><td><code>api/character_library/skg-characters</code></td><td>内置相似主体形象库：从桌面 5 套策划形象导入，<code>manifest.json</code> 记录运动阳光男、都市型男、优雅白领女、运动辣妹、绅士大叔，每套含 7 张透明骨架参考图和一段 <code>prompt_brief</code>。相似主体生成时优先使用文字 brief 作为创意方向，避免把内置图作为强参考图复制。</td></tr>
                 <tr><td><code>asset_library/</code></td><td>全局素材库目录，和 <code>jobs/</code> 平级，不写入任何 job state。四类目录为 <code>subjects</code>、<code>products</code>、<code>scenes</code>、<code>videos</code>；每个素材自带 <code>manifest.json</code> 和图片/视频文件，<code>index.json</code> 只是启动扫描重建出来的缓存。库素材选用到 job 时必须复制文件到 <code>jobs/&lt;jobId&gt;/assets</code> 或 <code>storyboard-videos</code>，禁止直接保存 library 引用。</td></tr>
@@ -1266,7 +1266,7 @@ ProductRefStateItem {
               <li>ASR：优先走当前 OpenAI-compatible 音频转写入口；如果该网关没有 <code>/audio/transcriptions</code>，自动 fallback 到 <code>ASR_FALLBACK_MODEL</code>（默认 <code>gemini-2.5-flash</code>）的多模态音频识别。</li>
               <li>Voice：当前语音通道固定是 <code>VOICE_PROVIDER=azure_openai</code>，通过 <code>AZURE_OPENAI_BASE_URL=https://ai.skg.com/azure</code> 的 OpenAI 协议生成 TTS；后端按 <code>AZURE_TTS_PATHS</code> 依次尝试路径。第一步暂不默认调用。</li>
               <li>Audio Product Brief：默认是通用 SKG 放松产品卖点；当前第一步只保留配置，后续分镜/新配音阶段再使用。</li>
-              <li>Video Gen：当前视频通道固定优先 Seedance；<code>VIDEO_API_BASE_URL=https://ai.skg.com/doubao</code> 走 content JSON 异步任务，提交后写入候选片段并轮询到完成。</li>
+              <li>Video Gen：当前视频通道默认 Seedance；<code>VIDEO_API_BASE_URL=https://ai.skg.com/doubao</code> 走 content JSON 异步任务。新增 <code>xai</code> / <code>Grok Imagine Video</code> 时，后端按模型分流到 <code>XAI_VIDEO_API_BASE_URL=https://ai.skg.com/ezlink/xai</code> 的 <code>/v1/videos/generations</code>，使用 <code>request_id</code> 轮询 <code>/v1/videos/{id}</code>，完成后下载 <code>video.url</code> 写入候选片段。</li>
               <li>Compose：还没做本地 ffmpeg 字幕/TTS 合成。</li>
             </ul>
           </div>
@@ -1310,6 +1310,19 @@ ProductRefStateItem {
         <h2>变更记录</h2>
         <p>这个记录不是 git log 的替代品。它记录“产品理解发生了什么变化、影响了哪些源码、你以后描述需求时该怎么说”。后续每次改功能都要补一条。</p>
         <div class="changelog">
+          <article class="change">
+            <header>
+              <h3>2026-06-03 · 接入 xAI Grok Imagine Video</h3>
+              <span class="tag blue">API</span>
+              <span class="tag violet">Model</span>
+              <span class="tag green">Canvas</span>
+            </header>
+            <div class="body">
+              <p><strong>问题：</strong>SKG xAI 网关 <code>https://ai.skg.com/ezlink/xai</code> 已确认可用 <code>grok-imagine-video</code> 文生视频，但项目只把 Seedance 暴露给画布，后端也按单一视频网关处理，无法同时保留 Seedance 并新增 xAI。</p>
+              <p><strong>改动：</strong><code>api/main.py</code> 新增 <code>xai</code> / <code>grok-imagine-video</code> 视频模型别名、<code>XAI_VIDEO_API_BASE_URL</code> / <code>XAI_VIDEO_API_KEY</code> / <code>XAI_VIDEO_CREATE_PATH</code> / <code>XAI_VIDEO_STATUS_PATH</code> 配置，按模型分流到 <code>/v1/videos/generations</code> 和 <code>/v1/videos/{id}</code>；创建时识别 xAI 的 <code>request_id</code>，轮询完成时读取 <code>video.url</code> 并下载 MP4。纯文生视频不会把系统空白帧误传为参考图；图生视频会把用户上传首帧作为 <code>image</code> 传入。</p>
+              <p><strong>前端 / 配置：</strong><code>web/canvas-app/src/config/models.js</code> 新增默认不可用的 <code>xai</code> 模型，<code>web/canvas-app/src/stores/pinia/models.js</code> 改为接受后端 <code>/health</code> 返回的可用视频模型，不再硬编码只保留 Seedance。<code>api/.env.example</code>、<code>deploy/.env.local.example</code> 和 <code>deploy/.env.production.example</code> 增加 xAI 私有 key 配置位，真实 key 只填本地或服务器私有 env。</p>
+            </div>
+          </article>
           <article class="change">
             <header>
               <h3>2026-05-30 · 稳定性 / 安全加固（子进程超时、SSRF、并发锁、上传持久化、轮询容错）</h3>

web/canvas-app/src/config/models.js

@@ -127,6 +127,24 @@ export const VIDEO_MODELS = [
         defaultResolution: '720p',
         defaultParams: { ratio: '720x1280', duration: 10, resolution: '720p' }
     },
+    {
+        label: 'Grok Imagine Video',
+        key: 'xai',
+        provider: ['chatfire'],
+        type: 't2v+i2v',
+        ratios: ['720x1280', '1280x720', '1024x1024'],
+        durs: [
+            { label: '5 秒', key: 5 },
+            { label: '8 秒', key: 8 },
+            { label: '10 秒', key: 10 },
+            { label: '12 秒', key: 12 },
+            { label: '15 秒', key: 15 }
+        ],
+        resolutions: ['480p', '720p'],
+        defaultResolution: '720p',
+        defaultParams: { ratio: '720x1280', duration: 8, resolution: '720p' },
+        available: false
+    },
     {
         label: 'Seedance 2.0 高清',
         key: 'seedance_hd',

web/canvas-app/src/stores/pinia/models.js

@@ -460,11 +460,7 @@ export const useModelStore = defineStore('model', () => {
         .filter(Boolean)
       const videoOptions = data?.models?.video_options || []
       runtimeVideoModels.value = videoOptions
-        .filter(item => {
-          const id = String(item?.id || '').toLowerCase()
-          const model = String(item?.model || '').toLowerCase()
-          return id.includes('seedance') || model.includes('seedance')
-        })
+        .filter(item => item?.id && item.available !== false)
         .map(normalizeRuntimeVideoModel)
         .filter(Boolean)
       return true