feat: 普号增加25s普通视频、增加pro系列高清模型、统一模型名字、过载不再计入错误禁用计数

src/services/generation_handler.py

@@ -19,52 +19,139 @@ from ..core.logger import debug_logger
 
 # Model configuration
 MODEL_CONFIG = {
-    "sora-image": {
+    "gpt-image": {
         "type": "image",
         "width": 360,
         "height": 360
     },
-    "sora-image-landscape": {
+    "gpt-image-landscape": {
         "type": "image",
         "width": 540,
         "height": 360
     },
-    "sora-image-portrait": {
+    "gpt-image-portrait": {
         "type": "image",
         "width": 360,
         "height": 540
     },
     # Video models with 10s duration (300 frames)
-    "sora-video-10s": {
+    "sora2-landscape-10s": {
         "type": "video",
         "orientation": "landscape",
         "n_frames": 300
     },
-    "sora-video-landscape-10s": {
-        "type": "video",
-        "orientation": "landscape",
-        "n_frames": 300
-    },
-    "sora-video-portrait-10s": {
+    "sora2-portrait-10s": {
         "type": "video",
         "orientation": "portrait",
         "n_frames": 300
     },
     # Video models with 15s duration (450 frames)
-    "sora-video-15s": {
+    "sora2-landscape-15s": {
         "type": "video",
         "orientation": "landscape",
         "n_frames": 450
     },
-    "sora-video-landscape-15s": {
-        "type": "video",
-        "orientation": "landscape",
-        "n_frames": 450
-    },
-    "sora-video-portrait-15s": {
+    "sora2-portrait-15s": {
         "type": "video",
         "orientation": "portrait",
         "n_frames": 450
+    },
+    # Video models with 25s duration (750 frames)
+    "sora2-landscape-25s": {
+        "type": "video",
+        "orientation": "landscape",
+        "n_frames": 750,
+        "model": "sy_8",
+        "size": "small"
+    },
+    "sora2-portrait-25s": {
+        "type": "video",
+        "orientation": "portrait",
+        "n_frames": 750,
+        "model": "sy_8",
+        "size": "small"
+    },
+    # Pro video models (require Pro subscription)
+    "sora2pro-landscape-10s": {
+        "type": "video",
+        "orientation": "landscape",
+        "n_frames": 300,
+        "model": "sy_ore",
+        "size": "small",
+        "require_pro": True
+    },
+    "sora2pro-portrait-10s": {
+        "type": "video",
+        "orientation": "portrait",
+        "n_frames": 300,
+        "model": "sy_ore",
+        "size": "small",
+        "require_pro": True
+    },
+    "sora2pro-landscape-15s": {
+        "type": "video",
+        "orientation": "landscape",
+        "n_frames": 450,
+        "model": "sy_ore",
+        "size": "small",
+        "require_pro": True
+    },
+    "sora2pro-portrait-15s": {
+        "type": "video",
+        "orientation": "portrait",
+        "n_frames": 450,
+        "model": "sy_ore",
+        "size": "small",
+        "require_pro": True
+    },
+    "sora2pro-landscape-25s": {
+        "type": "video",
+        "orientation": "landscape",
+        "n_frames": 750,
+        "model": "sy_ore",
+        "size": "small",
+        "require_pro": True
+    },
+    "sora2pro-portrait-25s": {
+        "type": "video",
+        "orientation": "portrait",
+        "n_frames": 750,
+        "model": "sy_ore",
+        "size": "small",
+        "require_pro": True
+    },
+    # Pro HD video models (require Pro subscription, high quality)
+    "sora2pro-hd-landscape-10s": {
+        "type": "video",
+        "orientation": "landscape",
+        "n_frames": 300,
+        "model": "sy_ore",
+        "size": "large",
+        "require_pro": True
+    },
+    "sora2pro-hd-portrait-10s": {
+        "type": "video",
+        "orientation": "portrait",
+        "n_frames": 300,
+        "model": "sy_ore",
+        "size": "large",
+        "require_pro": True
+    },
+    "sora2pro-hd-landscape-15s": {
+        "type": "video",
+        "orientation": "landscape",
+        "n_frames": 450,
+        "model": "sy_ore",
+        "size": "large",
+        "require_pro": True
+    },
+    "sora2pro-hd-portrait-15s": {
+        "type": "video",
+        "orientation": "portrait",
+        "n_frames": 450,
+        "model": "sy_ore",
+        "size": "large",
+        "require_pro": True
     }
 }
 
@@ -294,10 +381,20 @@ class GenerationHandler:
                     return
 
         # Streaming mode: proceed with actual generation
+        # Check if model requires Pro subscription
+        require_pro = model_config.get("require_pro", False)
+
         # Select token (with lock for image generation, Sora2 quota check for video generation)
-        token_obj = await self.load_balancer.select_token(for_image_generation=is_image, for_video_generation=is_video)
+        # If Pro is required, filter for Pro tokens only
+        token_obj = await self.load_balancer.select_token(
+            for_image_generation=is_image,
+            for_video_generation=is_video,
+            require_pro=require_pro
+        )
         if not token_obj:
-            if is_image:
+            if require_pro:
+                raise Exception("No available Pro tokens. Pro models require a ChatGPT Pro subscription.")
+            elif is_image:
                 raise Exception("No available tokens for image generation. All tokens are either disabled, cooling down, locked, or expired.")
             else:
                 raise Exception("No available tokens for video generation. All tokens are either disabled, cooling down, Sora2 quota exhausted, don't support Sora2, or expired.")
@@ -383,12 +480,18 @@ class GenerationHandler:
                     )
                 else:
                     # Normal video generation
+                    # Get model and size from config (default to sy_8 and small for backward compatibility)
+                    sora_model = model_config.get("model", "sy_8")
+                    video_size = model_config.get("size", "small")
+
                     task_id = await self.sora_client.generate_video(
                         clean_prompt, token_obj.token,
                         orientation=model_config["orientation"],
                         media_id=media_id,
                         n_frames=n_frames,
-                        style_id=style_id
+                        style_id=style_id,
+                        model=sora_model,
+                        size=video_size
                     )
             else:
                 task_id = await self.sora_client.generate_image(
@@ -1271,10 +1374,16 @@ class GenerationHandler:
             # Get n_frames from model configuration
             n_frames = model_config.get("n_frames", 300)  # Default to 300 frames (10s)
 
+            # Get model and size from config (default to sy_8 and small for backward compatibility)
+            sora_model = model_config.get("model", "sy_8")
+            video_size = model_config.get("size", "small")
+
             task_id = await self.sora_client.generate_video(
                 full_prompt, token_obj.token,
                 orientation=model_config["orientation"],
-                n_frames=n_frames
+                n_frames=n_frames,
+                model=sora_model,
+                size=video_size
             )
             debug_logger.log_info(f"Video generation started, task_id: {task_id}")
 
@@ -1282,7 +1391,7 @@ class GenerationHandler:
             task = Task(
                 task_id=task_id,
                 token_id=token_obj.id,
-                model=f"sora-video-{model_config['orientation']}",
+                model=f"sora2-video-{model_config['orientation']}",
                 prompt=full_prompt,
                 status="processing",
                 progress=0.0
@@ -1375,7 +1484,7 @@ class GenerationHandler:
             task = Task(
                 task_id=task_id,
                 token_id=token_obj.id,
-                model=f"sora-video-{model_config['orientation']}",
+                model=f"sora2-video-{model_config['orientation']}",
                 prompt=f"remix:{remix_target_id} {clean_prompt}",
                 status="processing",
                 progress=0.0

src/services/load_balancer.py

@@ -17,13 +17,14 @@ class LoadBalancer:
         # Use image timeout from config as lock timeout
         self.token_lock = TokenLock(lock_timeout=config.image_timeout)
 
-    async def select_token(self, for_image_generation: bool = False, for_video_generation: bool = False) -> Optional[Token]:
+    async def select_token(self, for_image_generation: bool = False, for_video_generation: bool = False, require_pro: bool = False) -> Optional[Token]:
         """
         Select a token using random load balancing
 
         Args:
             for_image_generation: If True, only select tokens that are not locked for image generation and have image_enabled=True
             for_video_generation: If True, filter out tokens with Sora2 quota exhausted (sora2_cooldown_until not expired), tokens that don't support Sora2, and tokens with video_enabled=False
+            require_pro: If True, only select tokens with ChatGPT Pro subscription (plan_type="chatgpt_pro")
 
         Returns:
             Selected token or None if no available tokens
@@ -56,6 +57,13 @@ class LoadBalancer:
         if not active_tokens:
             return None
 
+        # Filter for Pro tokens if required
+        if require_pro:
+            pro_tokens = [token for token in active_tokens if token.plan_type == "chatgpt_pro"]
+            if not pro_tokens:
+                return None
+            active_tokens = pro_tokens
+
         # If for video generation, filter out tokens with Sora2 quota exhausted and tokens without Sora2 support
         if for_video_generation:
             from datetime import datetime

src/services/sora_client.py

@@ -254,8 +254,20 @@ class SoraClient:
         return result["id"]
     
     async def generate_video(self, prompt: str, token: str, orientation: str = "landscape",
-                            media_id: Optional[str] = None, n_frames: int = 450, style_id: Optional[str] = None) -> str:
-        """Generate video (text-to-video or image-to-video)"""
+                            media_id: Optional[str] = None, n_frames: int = 450, style_id: Optional[str] = None,
+                            model: str = "sy_8", size: str = "small") -> str:
+        """Generate video (text-to-video or image-to-video)
+
+        Args:
+            prompt: Video generation prompt
+            token: Access token
+            orientation: Video orientation (landscape/portrait)
+            media_id: Optional image media_id for image-to-video
+            n_frames: Number of frames (300/450/750)
+            style_id: Optional style ID
+            model: Model to use (sy_8 for standard, sy_ore for pro)
+            size: Video size (small for standard, large for HD)
+        """
         inpaint_items = []
         if media_id:
             inpaint_items = [{
@@ -267,9 +279,9 @@ class SoraClient:
             "kind": "video",
             "prompt": prompt,
             "orientation": orientation,
-            "size": "small",
+            "size": size,
             "n_frames": n_frames,
-            "model": "sy_8",
+            "model": model,
             "inpaint_items": inpaint_items,
             "style_id": style_id
         }