fix: align Freepik API paths with OpenAPI spec

The original implementation used guessed endpoint paths that don't match
the actual Freepik API. Key fixes based on their OpenAPI spec:

- Task polling is per-endpoint (e.g. GET /v1/ai/text-to-image/flux-dev/{task-id})
  not a generic /v1/ai/tasks/{id}. freepik_client now returns TaskResult
  with status_path, and task_tracker polls using that path.
- Fixed endpoint paths: flux-pro -> flux-pro-v1-1, upscale -> image-upscaler,
  relight -> image-relight, style-transfer -> image-style-transfer,
  expand -> image-expand/flux-pro, inpaint -> ideogram-image-edit,
  remove-background -> beta/remove-background, classifier -> classifier/image,
  audio-isolate -> audio-isolation, icon -> text-to-icon
- Fixed video paths: kling -> kling-o1-pro with kling-o1 status path,
  minimax -> minimax-hailuo-02-1080p, seedance -> seedance-pro-1080p
- Fixed request schemas to match actual API params (e.g. scale_factor
  not scale, reference_image not style_reference, image_url for bg removal)
- Fixed response parsing: status is uppercase (COMPLETED not completed),
  results in data.generated[] array, classifier returns [{class_name, probability}]

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

app/schemas/image_editing.py

@@ -6,36 +6,43 @@ from pydantic import BaseModel, Field
 class UpscaleCreativeRequest(BaseModel):
     image: str = Field(..., description='Base64-encoded image')
     prompt: Optional[str] = None
-    scale: Optional[int] = Field(None, ge=2, le=4)
-    creativity: Optional[float] = Field(None, ge=0.0, le=1.0)
-    resemblance: Optional[float] = Field(None, ge=0.0, le=1.0)
+    scale_factor: Optional[str] = Field(None, description='2x, 4x, 8x, or 16x')
+    creativity: Optional[int] = Field(None, ge=-10, le=10)
+    resemblance: Optional[int] = Field(None, ge=-10, le=10)
+    optimized_for: Optional[str] = Field(
+        None,
+        description='standard, soft_portraits, hard_portraits, art_n_illustration, etc.',
+    )
 
 
 class UpscalePrecisionRequest(BaseModel):
     image: str = Field(..., description='Base64-encoded image')
-    scale: Optional[int] = Field(None, ge=2, le=4)
+    scale_factor: Optional[str] = Field(None, description='2x or 4x')
 
 
 class RelightRequest(BaseModel):
-    image: str = Field(..., description='Base64-encoded image')
+    image: str = Field(..., description='Base64 or URL of image')
     prompt: Optional[str] = None
-    light_source: Optional[str] = None
-    intensity: Optional[float] = Field(None, ge=0.0, le=1.0)
+    transfer_light_from_reference_image: Optional[str] = Field(
+        None, description='Base64 or URL of reference image for light transfer',
+    )
+    light_transfer_strength: Optional[int] = Field(None, ge=0, le=100)
 
 
 class StyleTransferRequest(BaseModel):
-    image: str = Field(..., description='Base64-encoded image')
-    style_reference: str = Field(..., description='Base64-encoded style reference image')
-    strength: Optional[float] = Field(None, ge=0.0, le=1.0)
+    image: str = Field(..., description='Base64 or URL of image')
+    reference_image: str = Field(..., description='Base64 or URL of style reference image')
+    prompt: Optional[str] = None
+    style_strength: Optional[int] = Field(None, ge=0, le=100)
+    structure_strength: Optional[int] = Field(None, ge=0, le=100)
 
 
 class ExpandRequest(BaseModel):
-    image: str = Field(..., description='Base64-encoded image')
+    image: str = Field(..., description='Base64 or URL of image')
     prompt: Optional[str] = None
-    direction: Optional[str] = Field(None, description='Expansion direction')
 
 
 class InpaintRequest(BaseModel):
-    image: str = Field(..., description='Base64-encoded image')
-    mask: str = Field(..., description='Base64-encoded mask image')
+    image: str = Field(..., description='Base64 or URL of image')
+    mask: str = Field(..., description='Base64 or URL of mask image')
     prompt: str = Field(..., min_length=1)

app/schemas/image_generation.py

@@ -5,31 +5,30 @@ from pydantic import BaseModel, Field
 
 class MysticRequest(BaseModel):
     prompt: str = Field(..., min_length=1, max_length=4000)
-    negative_prompt: Optional[str] = None
-    resolution: Optional[str] = None
+    resolution: Optional[str] = Field(None, description='1k, 2k, or 4k')
+    aspect_ratio: Optional[str] = Field(None, description='e.g. square_1_1, widescreen_16_9')
+    model: Optional[str] = Field(None, description='realism, fluid, zen, flexible, super_real, editorial_portraits')
+    seed: Optional[int] = Field(None, ge=1, le=4294967295)
     styling: Optional[dict] = None
-    seed: Optional[int] = None
-    num_images: Optional[int] = Field(None, ge=1, le=4)
+    structure_reference: Optional[str] = Field(None, description='Base64 image for structure reference')
+    style_reference: Optional[str] = Field(None, description='Base64 image for style reference')
 
 
 class FluxDevRequest(BaseModel):
     prompt: str = Field(..., min_length=1, max_length=4000)
-    image: Optional[str] = Field(None, description='Base64-encoded image for img2img')
-    guidance_scale: Optional[float] = Field(None, ge=1.0, le=20.0)
-    num_images: Optional[int] = Field(None, ge=1, le=4)
-    seed: Optional[int] = None
+    aspect_ratio: Optional[str] = Field(None, description='e.g. square_1_1, widescreen_16_9')
+    styling: Optional[dict] = None
+    seed: Optional[int] = Field(None, ge=1, le=4294967295)
 
 
 class FluxProRequest(BaseModel):
     prompt: str = Field(..., min_length=1, max_length=4000)
-    image: Optional[str] = Field(None, description='Base64-encoded image for img2img')
-    guidance_scale: Optional[float] = Field(None, ge=1.0, le=20.0)
-    seed: Optional[int] = None
+    aspect_ratio: Optional[str] = Field(None, description='e.g. square_1_1, widescreen_16_9')
+    styling: Optional[dict] = None
+    seed: Optional[int] = Field(None, ge=1, le=4294967295)
 
 
 class SeedreamRequest(BaseModel):
     prompt: str = Field(..., min_length=1, max_length=4000)
-    image: Optional[str] = Field(None, description='Base64-encoded image for img2img')
-    aspect_ratio: Optional[str] = None
-    num_images: Optional[int] = Field(None, ge=1, le=4)
-    seed: Optional[int] = None
+    aspect_ratio: Optional[str] = Field(None, description='e.g. square_1_1, widescreen_16_9')
+    seed: Optional[int] = Field(None, ge=1, le=4294967295)

app/schemas/utilities.py

@@ -3,10 +3,24 @@ from typing import Optional
 from pydantic import BaseModel, Field
 
 
+class ClassificationResult(BaseModel):
+    class_name: str
+    probability: float
+
+
 class ClassificationResponse(BaseModel):
-    is_ai_generated: bool
-    ai_probability: float
-    human_probability: float
+    data: list[ClassificationResult]
+
+
+class RemoveBackgroundRequest(BaseModel):
+    image_url: str = Field(..., description='URL of image to remove background from')
+
+
+class RemoveBackgroundResponse(BaseModel):
+    original: Optional[str] = None
+    high_resolution: Optional[str] = None
+    preview: Optional[str] = None
+    url: Optional[str] = None
 
 
 class IconRequest(BaseModel):

app/schemas/video_generation.py

@@ -4,20 +4,20 @@ from pydantic import BaseModel, Field
 
 
 class KlingRequest(BaseModel):
-    image: str = Field(..., description='Base64-encoded image')
-    prompt: Optional[str] = None
-    duration: Optional[str] = Field(None, description='5 or 10 seconds')
-    aspect_ratio: Optional[str] = None
+    first_frame: Optional[str] = Field(None, description='Base64 or URL of first frame image')
+    last_frame: Optional[str] = Field(None, description='Base64 or URL of last frame image')
+    prompt: Optional[str] = Field(None, max_length=2500)
+    duration: Optional[int] = Field(None, description='5 or 10 seconds')
+    aspect_ratio: Optional[str] = Field(None, description='16:9, 9:16, or 1:1')
 
 
 class MinimaxRequest(BaseModel):
     prompt: str = Field(..., min_length=1, max_length=4000)
-    first_frame_image: Optional[str] = Field(None, description='Base64-encoded image')
-    subject_reference: Optional[str] = Field(None, description='Base64-encoded reference image')
+    first_frame_image: Optional[str] = Field(None, description='Base64 or URL of first frame')
+    last_frame_image: Optional[str] = Field(None, description='Base64 or URL of last frame')
 
 
 class SeedanceRequest(BaseModel):
-    prompt: str = Field(..., min_length=1, max_length=4000)
-    image: Optional[str] = Field(None, description='Base64-encoded image')
-    duration: Optional[str] = None
-    resolution: Optional[str] = None
+    prompt: str = Field(..., min_length=1, max_length=2000)
+    image: Optional[str] = Field(None, description='Base64 or URL of input image')
+    duration: Optional[str] = Field(None, description='5 or 10 seconds')