fix bugs

Author: longgui0318

py/wavespeed_api/requests/dia_tts.py

@@ -13,10 +13,6 @@ class DiaTts(BaseRequest):
         ...,
         description="The text to be converted to speech.")
 
-    def __init__(self, prompt: str, **kwargs):
-        super().__init__(**kwargs)
-        self.prompt = prompt
-
     def build_payload(self) -> dict:
         """Builds the request payload dictionary."""
         payload = {

py/wavespeed_api/requests/flux_control_lora_canny.py

@@ -26,34 +26,6 @@ class FluxControlLoraCanny(BaseRequest):
     width: Optional[int] = Field(864, description="The width of the generated image.", ge=512, le=1536)
     height: Optional[int] = Field(1536, description="The height of the generated image.", ge=512, le=1536)
 
-    def __init__(
-            self,
-            prompt: str,
-            control_image: Optional[str] = None,
-            control_scale: Optional[float] = 1,
-            enable_safety_checker: Optional[bool] = True,
-            guidance_scale: Optional[float] = 3.5,
-            loras: Optional[List[Union[LoraWeightItem, Dict[str, Any]]]] = None,  # Allow dicts for easier init
-            num_images: Optional[int] = 1,
-            num_inference_steps: Optional[int] = 28,
-            seed: Optional[int] = -1,
-            width: Optional[int] = 864,
-            height: Optional[int] = 1536,
-            **kwargs):
-        super().__init__(**kwargs)
-        self.prompt = prompt
-        self.control_image = control_image
-        self.control_scale = control_scale
-        self.enable_safety_checker = enable_safety_checker
-        self.guidance_scale = guidance_scale
-        if loras is not None:
-            self.loras = [LoraWeightItem(**lora) if isinstance(lora, dict) else lora for lora in loras]
-        self.num_images = num_images
-        self.num_inference_steps = num_inference_steps
-        self.seed = seed
-        self.width = width
-        self.height = height
-
     def build_payload(self) -> dict:
         """Builds the request payload dictionary."""
         payload = {

py/wavespeed_api/requests/flux_control_lora_depth.py

@@ -32,34 +32,6 @@ class FluxControlLoraDepth(BaseRequest):
     width: Optional[int] = Field(864, description="The width of the generated image.", ge=512, le=1536)
     height: Optional[int] = Field(1536, description="The height of the generated image.", ge=512, le=1536)
 
-    def __init__(
-            self,
-            prompt: str,
-            control_image: Optional[str] = None,
-            control_scale: Optional[float] = 1,
-            enable_safety_checker: Optional[bool] = True,
-            guidance_scale: Optional[float] = 3.5,
-            loras: Optional[List[Union[LoraWeightItem, Dict[str, Any]]]] = None,  # Allow dicts for easier init
-            num_images: Optional[int] = 1,
-            num_inference_steps: Optional[int] = 28,
-            seed: Optional[int] = -1,
-            width: Optional[int] = 864,
-            height: Optional[int] = 1536,
-            **kwargs):
-        super().__init__(**kwargs)
-        self.prompt = prompt
-        self.control_image = control_image
-        self.control_scale = control_scale
-        self.enable_safety_checker = enable_safety_checker
-        self.guidance_scale = guidance_scale
-        if loras is not None:
-            self.loras = [LoraWeightItem(**lora) if isinstance(lora, dict) else lora for lora in loras]
-        self.num_images = num_images
-        self.num_inference_steps = num_inference_steps
-        self.seed = seed
-        self.width = width
-        self.height = height
-
     def build_payload(self) -> dict:
         """Builds the request payload dictionary."""
         payload = {

py/wavespeed_api/requests/flux_dev.py

@@ -21,33 +21,6 @@ class FluxDev(BaseRequest):
     height: Optional[int] = Field(default=1024, description="The height of the generated image." , ge=512, le=1536)
     strength: Optional[float] = Field(default=0.8, description="Strength indicates extent to transform the reference image", ge=0, le=1)
 
-    def __init__(
-            self,
-            prompt: str,
-            enable_safety_checker: Optional[bool] = True,
-            guidance_scale: Optional[float] = 3.5,
-            image: Optional[str] = None,
-            mask_image: Optional[str] = None,
-            num_images: Optional[int] = 1,
-            num_inference_steps: Optional[int] = 28,
-            seed: Optional[int] = -1,
-            width: Optional[int] = 1024,
-            height: Optional[int] = 1024,
-            strength: Optional[float] = 0.8,
-            **kwargs):
-        super().__init__(**kwargs)
-        
-        self.prompt = prompt
-        self.enable_safety_checker = enable_safety_checker
-        self.guidance_scale = guidance_scale
-        self.image = image
-        self.mask_image = mask_image
-        self.num_images = num_images
-        self.num_inference_steps = num_inference_steps
-        self.seed = seed
-        self.width = width
-        self.height = height
-        self.strength = strength
 
     def build_payload(self) -> dict:
         """Builds the request payload dictionary."""

py/wavespeed_api/requests/flux_dev_fill.py

@@ -25,35 +25,6 @@ class FluxDevFill(BaseRequest):
     width: Optional[int] = Field(default=864, description="The width of the generated image.", ge=512, le=1536)
     height: Optional[int] = Field(default=1536, description="The height of the generated image.", ge=512, le=1536)
 
-    def __init__(
-            self,
-            image: str,
-            mask_image: Optional[str] = None,
-            prompt: Optional[str] = None,
-            num_inference_steps: Optional[int] = 28,
-            seed: Optional[int] = -1,
-            guidance_scale: Optional[float] = 30,
-            num_images: Optional[int] = 1,
-            loras: Optional[List[Union[LoraWeightItem, Dict[str, Any]]]] = None,  # Allow dicts for easier init
-            enable_safety_checker: Optional[bool] = True,
-            width: Optional[int] = 864,
-            height: Optional[int] = 1536,
-            **kwargs):
-        super().__init__(**kwargs)
-        
-        self.image = image
-        self.mask_image = mask_image
-        self.prompt = prompt
-        self.num_inference_steps = num_inference_steps
-        self.seed = seed
-        self.guidance_scale = guidance_scale
-        self.num_images = num_images
-        self.width = width
-        self.height = height
-        if loras is not None:
-            self.loras = [LoraWeightItem(**lora) if isinstance(lora, dict) else lora for lora in loras]
-        self.enable_safety_checker = enable_safety_checker
-
     def build_payload(self) -> dict:
         """Builds the request payload dictionary."""
         payload = {

py/wavespeed_api/requests/flux_dev_lora.py

@@ -24,36 +24,6 @@ class FluxDevLora(BaseRequest):
     height: Optional[int] = Field(default=1024, description="The height of the generated image.", ge=512, le=1536)
     strength: Optional[float] = Field(default=0.8, description="Strength indicates extent to transform the reference image", maximum=1, minimum=0)
 
-    def __init__(
-            self,
-            prompt: str,
-            enable_safety_checker: Optional[bool] = True,
-            guidance_scale: Optional[float] = 3.5,
-            image: Optional[str] = None,
-            loras: Optional[List[Union[LoraWeightItem, Dict[str, Any]]]] = None,  # Allow dicts for easier init
-            mask_image: Optional[str] = None,
-            num_images: Optional[int] = 1,
-            num_inference_steps: Optional[int] = 28,
-            seed: Optional[int] = -1,
-            width: Optional[int] = 1024,
-            height: Optional[int] = 1024,
-            strength: Optional[float] = 0.8,
-            **kwargs):
-        super().__init__(**kwargs)
-        self.prompt = prompt
-        self.enable_safety_checker = enable_safety_checker
-        self.guidance_scale = guidance_scale
-        self.image = image
-        if loras is not None:
-            self.loras = [LoraWeightItem(**lora) if isinstance(lora, dict) else lora for lora in loras]
-        self.mask_image = mask_image
-        self.num_images = num_images
-        self.num_inference_steps = num_inference_steps
-        self.seed = seed
-        self.width = width
-        self.height = height
-        self.strength = strength
-
     def build_payload(self) -> dict:
         """Builds the request payload dictionary."""
         payload = {

py/wavespeed_api/requests/flux_dev_lora_ultra_fast.py

@@ -32,36 +32,6 @@ class FluxDevLoraUltraFast(BaseRequest):
     seed: Optional[int] = Field(default=-1, description="Random seed (-1 for random)") 
     enable_safety_checker: Optional[bool] = Field(default=True, description="Enable safety checker") 
 
-    def __init__(
-            self,
-            prompt: str,
-            image: Optional[str] = "",
-            mask_image: Optional[str] = None,
-            strength: Optional[float] = 0.8,
-            loras: Optional[List[Union[LoraWeightItem, Dict[str, Any]]]] = None,  # Allow dicts for easier init
-            width: Optional[int] = 1024,
-            height: Optional[int] = 1024,
-            num_inference_steps: Optional[int] = 28,
-            guidance_scale: Optional[float] = 3.5,
-            num_images: Optional[int] = 1,
-            seed: Optional[int] = -1,
-            enable_safety_checker: Optional[bool] = True,
-            **kwargs):
-        super().__init__(**kwargs)
-        self.prompt = prompt
-        self.image = image
-        self.mask_image = mask_image
-        self.strength = strength
-        if loras is not None:
-            self.loras = [LoraWeightItem(**lora) if isinstance(lora, dict) else lora for lora in loras]
-        self.width = width
-        self.height = height
-        self.num_inference_steps = num_inference_steps
-        self.guidance_scale = guidance_scale
-        self.num_images = num_images
-        self.seed = seed
-        self.enable_safety_checker = enable_safety_checker
-
     def build_payload(self) -> dict:
         """Builds the request payload dictionary."""
         payload = {

py/wavespeed_api/requests/flux_dev_ultra_fast.py

@@ -28,33 +28,6 @@ class FluxDevUltraFast(BaseRequest):
     height: Optional[int] = Field(default=1024, description="The height of the generated image.", ge=512, le=1536)
     strength: Optional[float] = Field(default=0.8, description="Strength indicates extent to transform the reference image", maximum=1, minimum=0, step=0.1, title="Strength")
 
-    def __init__(
-            self,
-            prompt: str,
-            enable_safety_checker: Optional[bool] = True,
-            guidance_scale: Optional[float] = 3.5,
-            image: Optional[str] = None,
-            mask_image: Optional[str] = None,
-            num_images: Optional[int] = 1,
-            num_inference_steps: Optional[int] = 28,
-            seed: Optional[int] = -1,
-            width: Optional[int] = 1024,
-            height: Optional[int] = 1024,
-            strength: Optional[float] = 0.8,
-            **kwargs: Any):
-        super().__init__(**kwargs)
-        self.enable_safety_checker = enable_safety_checker
-        self.guidance_scale = guidance_scale
-        self.image = image
-        self.mask_image = mask_image
-        self.num_images = num_images
-        self.num_inference_steps = num_inference_steps
-        self.prompt = prompt
-        self.seed = seed
-        self.width = width
-        self.height = height
-        self.strength = strength
-
     def build_payload(self) -> dict:
         """Builds the request payload dictionary."""
         payload = {

py/wavespeed_api/requests/flux_pro_redux.py

@@ -20,29 +20,6 @@ class FluxProRedux(BaseRequest):
     num_images: int = Field(default=1, description="The number of images to generate.", title="Num Images")
     enable_safety_checker: bool = Field(default=True, description="If set to true, the safety checker will be enabled.", title="Enable Safety Checker")
 
-    def __init__(
-            self,
-            image: str,
-            prompt: str = "",
-            width: int = 1024,
-            height: int = 1024,
-            seed: int = 0,
-            num_inference_steps: int = 28,
-            guidance_scale: float = 3.5,
-            num_images: int = 1,
-            enable_safety_checker: bool = True,
-            **kwargs):
-        super().__init__(**kwargs)
-        self.image = image
-        self.prompt = prompt
-        self.width = width
-        self.height = height
-        self.seed = seed
-        self.num_inference_steps = num_inference_steps
-        self.guidance_scale = guidance_scale
-        self.num_images = num_images
-        self.enable_safety_checker = enable_safety_checker
-
     def build_payload(self) -> dict:
         """Builds the request payload dictionary."""
         payload = {

py/wavespeed_api/requests/flux_redux_dev.py

@@ -21,27 +21,6 @@ class FluxReduxDev(BaseRequest):
     width: Optional[int] = Field(default=1024, description="The width of the generated image.", ge=512, le=1536)
     height: Optional[int] = Field(default=1024, description="The height of the generated image.", ge=512, le=1536)
 
-    def __init__(
-            self,
-            image: str,
-            enable_safety_checker: Optional[bool] = True,
-            guidance_scale: Optional[float] = 3.5,
-            num_images: Optional[int] = 1,
-            num_inference_steps: Optional[int] = 28,
-            seed: Optional[int] = -1,
-            width: Optional[int] = 1024,
-            height: Optional[int] = 1024,
-            **kwargs):
-        super().__init__(**kwargs)
-        self.enable_safety_checker = enable_safety_checker
-        self.guidance_scale = guidance_scale
-        self.image = image
-        self.num_images = num_images
-        self.num_inference_steps = num_inference_steps
-        self.seed = seed
-        self.width = width
-        self.height = height
-
     def build_payload(self) -> dict:
         """Builds the request payload dictionary."""
         payload = {