AI Image Studio, AI podcast Maker, AI product Marketing
This commit is contained in:
ajaysi
@@ -4,18 +4,20 @@ Each module focuses on a related set of routes to keep the primary
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`router.py` concise and easier to maintain.
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"""
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from . import story_setup
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from . import story_content
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from . import story_tasks
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from . import media_generation
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from . import video_generation
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from . import cache_routes
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from . import media_generation
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from . import scene_animation
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from . import story_content
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from . import story_setup
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from . import story_tasks
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from . import video_generation
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__all__ = [
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"story_setup",
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"story_content",
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"story_tasks",
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"media_generation",
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"video_generation",
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"cache_routes",
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"media_generation",
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"scene_animation",
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"story_content",
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"story_setup",
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"story_tasks",
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"video_generation",
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]
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@@ -1,8 +1,10 @@
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from typing import Any, Dict, List
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from typing import Any, Dict, List, Optional
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from fastapi import APIRouter, Depends, HTTPException
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from fastapi.responses import FileResponse
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from loguru import logger
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from pydantic import BaseModel, Field
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from sqlalchemy.orm import Session
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from middleware.auth_middleware import get_current_user, get_current_user_with_query_token
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from models.story_models import (
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@@ -18,8 +20,10 @@ from models.story_models import (
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GenerateAIAudioResponse,
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StoryScene,
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)
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from services.database import get_db
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from services.story_writer.image_generation_service import StoryImageGenerationService
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from services.story_writer.audio_generation_service import StoryAudioGenerationService
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from utils.asset_tracker import save_asset_to_library
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from ..utils.auth import require_authenticated_user
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from ..utils.media_utils import resolve_media_file
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@@ -34,6 +38,7 @@ audio_service = StoryAudioGenerationService()
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async def generate_scene_images(
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request: StoryImageGenerationRequest,
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current_user: Dict[str, Any] = Depends(get_current_user),
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db: Session = Depends(get_db),
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) -> StoryImageGenerationResponse:
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"""Generate images for story scenes."""
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try:
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@@ -70,6 +75,37 @@ async def generate_scene_images(
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for result in image_results
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]
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# Save assets to library
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for result in image_results:
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if not result.get("error") and result.get("image_url"):
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try:
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scene_number = result.get("scene_number", 0)
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# Safely get prompt from scenes_data with bounds checking
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prompt = None
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if scene_number > 0 and scene_number <= len(scenes_data):
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prompt = scenes_data[scene_number - 1].get("image_prompt")
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save_asset_to_library(
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db=db,
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user_id=user_id,
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asset_type="image",
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source_module="story_writer",
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filename=result.get("image_filename", ""),
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file_url=result.get("image_url", ""),
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file_path=result.get("image_path"),
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file_size=result.get("file_size"),
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mime_type="image/png",
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title=f"Scene {scene_number}: {result.get('scene_title', 'Untitled')}",
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description=f"Story scene image for scene {scene_number}",
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prompt=prompt,
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tags=["story_writer", "scene", f"scene_{scene_number}"],
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provider=result.get("provider"),
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model=result.get("model"),
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asset_metadata={"scene_number": scene_number, "scene_title": result.get("scene_title"), "status": "completed"}
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)
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except Exception as e:
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logger.warning(f"[StoryWriter] Failed to save image asset to library: {e}")
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return StoryImageGenerationResponse(images=image_models, success=True)
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except HTTPException:
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@@ -163,6 +199,7 @@ async def serve_scene_image(
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async def generate_scene_audio(
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request: StoryAudioGenerationRequest,
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current_user: Dict[str, Any] = Depends(get_current_user),
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db: Session = Depends(get_db),
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) -> StoryAudioGenerationResponse:
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"""Generate audio narration for story scenes."""
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try:
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@@ -185,18 +222,52 @@ async def generate_scene_audio(
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audio_models: List[StoryAudioResult] = []
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for result in audio_results:
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audio_url = result.get("audio_url") or ""
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audio_filename = result.get("audio_filename") or ""
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audio_models.append(
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StoryAudioResult(
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scene_number=result.get("scene_number", 0),
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scene_title=result.get("scene_title", "Untitled"),
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audio_filename=result.get("audio_filename") or "",
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audio_url=result.get("audio_url") or "",
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audio_filename=audio_filename,
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audio_url=audio_url,
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provider=result.get("provider", "unknown"),
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file_size=result.get("file_size", 0),
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error=result.get("error"),
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)
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)
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# Save assets to library
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if not result.get("error") and audio_url:
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try:
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scene_number = result.get("scene_number", 0)
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# Safely get prompt from scenes_data with bounds checking
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prompt = None
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if scene_number > 0 and scene_number <= len(scenes_data):
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prompt = scenes_data[scene_number - 1].get("text")
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save_asset_to_library(
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db=db,
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user_id=user_id,
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asset_type="audio",
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source_module="story_writer",
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filename=audio_filename,
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file_url=audio_url,
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file_path=result.get("audio_path"),
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file_size=result.get("file_size"),
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mime_type="audio/mpeg",
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title=f"Scene {scene_number}: {result.get('scene_title', 'Untitled')}",
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description=f"Story scene audio narration for scene {scene_number}",
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prompt=prompt,
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tags=["story_writer", "audio", "narration", f"scene_{scene_number}"],
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provider=result.get("provider"),
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model=result.get("model"),
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cost=result.get("cost"),
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asset_metadata={"scene_number": scene_number, "scene_title": result.get("scene_title"), "status": "completed"}
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)
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except Exception as e:
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logger.warning(f"[StoryWriter] Failed to save audio asset to library: {e}")
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return StoryAudioGenerationResponse(audio_files=audio_models, success=True)
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except HTTPException:
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@@ -287,3 +358,59 @@ async def serve_scene_audio(
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raise HTTPException(status_code=500, detail=str(exc))
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class PromptOptimizeRequest(BaseModel):
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text: str = Field(..., description="The prompt text to optimize")
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mode: Optional[str] = Field(default="image", pattern="^(image|video)$", description="Optimization mode: 'image' or 'video'")
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style: Optional[str] = Field(
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default="default",
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pattern="^(default|artistic|photographic|technical|anime|realistic)$",
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description="Style: 'default', 'artistic', 'photographic', 'technical', 'anime', or 'realistic'"
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)
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image: Optional[str] = Field(None, description="Base64-encoded image for context (optional)")
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class PromptOptimizeResponse(BaseModel):
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optimized_prompt: str
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success: bool
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@router.post("/optimize-prompt", response_model=PromptOptimizeResponse)
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async def optimize_prompt(
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request: PromptOptimizeRequest,
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current_user: Dict[str, Any] = Depends(get_current_user),
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) -> PromptOptimizeResponse:
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"""Optimize an image prompt using WaveSpeed prompt optimizer."""
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try:
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user_id = require_authenticated_user(current_user)
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if not request.text or not request.text.strip():
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raise HTTPException(status_code=400, detail="Prompt text is required")
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logger.info(f"[StoryWriter] Optimizing prompt for user {user_id} (mode={request.mode}, style={request.style})")
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from services.wavespeed.client import WaveSpeedClient
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client = WaveSpeedClient()
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optimized_prompt = client.optimize_prompt(
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text=request.text.strip(),
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mode=request.mode or "image",
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style=request.style or "default",
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image=request.image, # Optional base64 image
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enable_sync_mode=True,
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timeout=30
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)
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logger.info(f"[StoryWriter] Prompt optimized successfully for user {user_id}")
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return PromptOptimizeResponse(
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optimized_prompt=optimized_prompt,
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success=True
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)
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except HTTPException:
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raise
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except Exception as exc:
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logger.error(f"[StoryWriter] Failed to optimize prompt: {exc}")
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raise HTTPException(status_code=500, detail=str(exc))
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484
backend/api/story_writer/routes/scene_animation.py
Normal file
484
backend/api/story_writer/routes/scene_animation.py
Normal file
@@ -0,0 +1,484 @@
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"""
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Scene Animation Routes
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Handles scene animation endpoints using WaveSpeed Kling and InfiniteTalk.
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"""
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import mimetypes
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from pathlib import Path
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from typing import Any, Dict, Optional
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from urllib.parse import quote
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from fastapi import APIRouter, BackgroundTasks, Depends, HTTPException, Request
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from loguru import logger
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from sqlalchemy.orm import Session
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from middleware.auth_middleware import get_current_user
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from models.story_models import (
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AnimateSceneRequest,
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AnimateSceneResponse,
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AnimateSceneVoiceoverRequest,
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ResumeSceneAnimationRequest,
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)
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from services.database import get_db
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from services.llm_providers.main_video_generation import track_video_usage
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from services.story_writer.video_generation_service import StoryVideoGenerationService
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from services.subscription import PricingService
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from services.subscription.preflight_validator import validate_scene_animation_operation
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from services.wavespeed.infinitetalk import animate_scene_with_voiceover
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from services.wavespeed.kling_animation import animate_scene_image, resume_scene_animation
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from utils.asset_tracker import save_asset_to_library
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from utils.logger_utils import get_service_logger
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from ..task_manager import task_manager
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from ..utils.auth import require_authenticated_user
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from ..utils.media_utils import load_story_audio_bytes, load_story_image_bytes
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router = APIRouter()
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scene_logger = get_service_logger("api.story_writer.scene_animation")
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AI_VIDEO_SUBDIR = Path("AI_Videos")
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def _build_authenticated_media_url(request: Request, path: str) -> str:
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"""Append the caller's auth token to a media URL so <video>/<img> tags can access it."""
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if not path:
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return path
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token: Optional[str] = None
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auth_header = request.headers.get("Authorization")
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if auth_header and auth_header.startswith("Bearer "):
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token = auth_header.replace("Bearer ", "").strip()
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elif "token" in request.query_params:
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token = request.query_params["token"]
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if token:
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separator = "&" if "?" in path else "?"
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path = f"{path}{separator}token={quote(token)}"
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return path
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def _guess_mime_from_url(url: str, fallback: str) -> str:
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"""Guess MIME type from URL."""
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if not url:
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return fallback
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mime, _ = mimetypes.guess_type(url)
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return mime or fallback
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@router.post("/animate-scene-preview", response_model=AnimateSceneResponse)
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async def animate_scene_preview(
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request_obj: Request,
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request: AnimateSceneRequest,
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current_user: Dict[str, Any] = Depends(get_current_user),
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) -> AnimateSceneResponse:
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"""
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Animate a single scene image using WaveSpeed Kling v2.5 Turbo Std.
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"""
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if not current_user:
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raise HTTPException(status_code=401, detail="Authentication required")
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user_id = str(current_user.get("id", ""))
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if not user_id:
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raise HTTPException(status_code=401, detail="Invalid user ID in authentication token")
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duration = request.duration or 5
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if duration not in (5, 10):
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raise HTTPException(status_code=400, detail="Duration must be 5 or 10 seconds.")
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scene_logger.info(
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"[AnimateScene] User=%s scene=%s duration=%s image_url=%s",
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user_id,
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request.scene_number,
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duration,
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request.image_url,
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)
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image_bytes = load_story_image_bytes(request.image_url)
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if not image_bytes:
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scene_logger.warning("[AnimateScene] Missing image bytes for user=%s scene=%s", user_id, request.scene_number)
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raise HTTPException(status_code=404, detail="Scene image not found. Generate images first.")
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db = next(get_db())
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try:
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pricing_service = PricingService(db)
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validate_scene_animation_operation(pricing_service=pricing_service, user_id=user_id)
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finally:
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db.close()
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animation_result = animate_scene_image(
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image_bytes=image_bytes,
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scene_data=request.scene_data,
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story_context=request.story_context,
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user_id=user_id,
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duration=duration,
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)
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base_dir = Path(__file__).parent.parent.parent.parent
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ai_video_dir = base_dir / "story_videos" / AI_VIDEO_SUBDIR
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ai_video_dir.mkdir(parents=True, exist_ok=True)
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video_service = StoryVideoGenerationService(output_dir=str(ai_video_dir))
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save_result = video_service.save_scene_video(
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video_bytes=animation_result["video_bytes"],
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scene_number=request.scene_number,
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user_id=user_id,
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)
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video_filename = save_result["video_filename"]
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video_url = _build_authenticated_media_url(
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request_obj, f"/api/story/videos/ai/{video_filename}"
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)
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usage_info = track_video_usage(
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user_id=user_id,
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provider=animation_result["provider"],
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model_name=animation_result["model_name"],
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prompt=animation_result["prompt"],
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video_bytes=animation_result["video_bytes"],
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cost_override=animation_result["cost"],
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)
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if usage_info:
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scene_logger.warning(
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"[AnimateScene] Video usage tracked user=%s: %s → %s / %s (cost +$%.2f, total=$%.2f)",
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user_id,
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usage_info.get("previous_calls"),
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usage_info.get("current_calls"),
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usage_info.get("video_limit_display"),
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usage_info.get("cost_per_video", 0.0),
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usage_info.get("total_video_cost", 0.0),
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)
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scene_logger.info(
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"[AnimateScene] ✅ Completed user=%s scene=%s duration=%s cost=$%.2f video=%s",
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user_id,
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request.scene_number,
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animation_result["duration"],
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animation_result["cost"],
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video_url,
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)
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# Save video asset to library
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db = next(get_db())
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try:
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save_asset_to_library(
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db=db,
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user_id=user_id,
|
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asset_type="video",
|
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source_module="story_writer",
|
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filename=video_filename,
|
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file_url=video_url,
|
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file_path=str(ai_video_dir / video_filename),
|
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file_size=len(animation_result["video_bytes"]),
|
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mime_type="video/mp4",
|
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title=f"Scene {request.scene_number} Animation",
|
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description=f"Animated scene {request.scene_number} from story",
|
||||
prompt=animation_result["prompt"],
|
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tags=["story_writer", "video", "animation", f"scene_{request.scene_number}"],
|
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provider=animation_result["provider"],
|
||||
model=animation_result.get("model_name"),
|
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cost=animation_result["cost"],
|
||||
asset_metadata={"scene_number": request.scene_number, "duration": animation_result["duration"], "status": "completed"}
|
||||
)
|
||||
except Exception as e:
|
||||
logger.warning(f"[StoryWriter] Failed to save video asset to library: {e}")
|
||||
finally:
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db.close()
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||||
|
||||
return AnimateSceneResponse(
|
||||
success=True,
|
||||
scene_number=request.scene_number,
|
||||
video_filename=video_filename,
|
||||
video_url=video_url,
|
||||
duration=animation_result["duration"],
|
||||
cost=animation_result["cost"],
|
||||
prompt_used=animation_result["prompt"],
|
||||
provider=animation_result["provider"],
|
||||
prediction_id=animation_result.get("prediction_id"),
|
||||
)
|
||||
|
||||
|
||||
@router.post("/animate-scene-resume", response_model=AnimateSceneResponse)
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||||
async def resume_scene_animation_endpoint(
|
||||
request_obj: Request,
|
||||
request: ResumeSceneAnimationRequest,
|
||||
current_user: Dict[str, Any] = Depends(get_current_user),
|
||||
) -> AnimateSceneResponse:
|
||||
"""Resume downloading a WaveSpeed animation when the initial call timed out."""
|
||||
if not current_user:
|
||||
raise HTTPException(status_code=401, detail="Authentication required")
|
||||
|
||||
user_id = str(current_user.get("id", ""))
|
||||
if not user_id:
|
||||
raise HTTPException(status_code=401, detail="Invalid user ID in authentication token")
|
||||
|
||||
scene_logger.info(
|
||||
"[AnimateScene] Resume requested user=%s scene=%s prediction=%s",
|
||||
user_id,
|
||||
request.scene_number,
|
||||
request.prediction_id,
|
||||
)
|
||||
|
||||
animation_result = resume_scene_animation(
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prediction_id=request.prediction_id,
|
||||
duration=request.duration or 5,
|
||||
user_id=user_id,
|
||||
)
|
||||
|
||||
base_dir = Path(__file__).parent.parent.parent.parent
|
||||
ai_video_dir = base_dir / "story_videos" / AI_VIDEO_SUBDIR
|
||||
ai_video_dir.mkdir(parents=True, exist_ok=True)
|
||||
video_service = StoryVideoGenerationService(output_dir=str(ai_video_dir))
|
||||
|
||||
save_result = video_service.save_scene_video(
|
||||
video_bytes=animation_result["video_bytes"],
|
||||
scene_number=request.scene_number,
|
||||
user_id=user_id,
|
||||
)
|
||||
video_filename = save_result["video_filename"]
|
||||
video_url = _build_authenticated_media_url(
|
||||
request_obj, f"/api/story/videos/ai/{video_filename}"
|
||||
)
|
||||
|
||||
usage_info = track_video_usage(
|
||||
user_id=user_id,
|
||||
provider=animation_result["provider"],
|
||||
model_name=animation_result["model_name"],
|
||||
prompt=animation_result["prompt"],
|
||||
video_bytes=animation_result["video_bytes"],
|
||||
cost_override=animation_result["cost"],
|
||||
)
|
||||
if usage_info:
|
||||
scene_logger.warning(
|
||||
"[AnimateScene] (Resume) Video usage tracked user=%s: %s → %s / %s (cost +$%.2f, total=$%.2f)",
|
||||
user_id,
|
||||
usage_info.get("previous_calls"),
|
||||
usage_info.get("current_calls"),
|
||||
usage_info.get("video_limit_display"),
|
||||
usage_info.get("cost_per_video", 0.0),
|
||||
usage_info.get("total_video_cost", 0.0),
|
||||
)
|
||||
|
||||
scene_logger.info(
|
||||
"[AnimateScene] ✅ Resume completed user=%s scene=%s prediction=%s video=%s",
|
||||
user_id,
|
||||
request.scene_number,
|
||||
request.prediction_id,
|
||||
video_url,
|
||||
)
|
||||
|
||||
return AnimateSceneResponse(
|
||||
success=True,
|
||||
scene_number=request.scene_number,
|
||||
video_filename=video_filename,
|
||||
video_url=video_url,
|
||||
duration=animation_result["duration"],
|
||||
cost=animation_result["cost"],
|
||||
prompt_used=animation_result["prompt"],
|
||||
provider=animation_result["provider"],
|
||||
prediction_id=animation_result.get("prediction_id"),
|
||||
)
|
||||
|
||||
|
||||
@router.post("/animate-scene-voiceover", response_model=Dict[str, Any])
|
||||
async def animate_scene_voiceover_endpoint(
|
||||
request_obj: Request,
|
||||
request: AnimateSceneVoiceoverRequest,
|
||||
background_tasks: BackgroundTasks,
|
||||
current_user: Dict[str, Any] = Depends(get_current_user),
|
||||
) -> Dict[str, Any]:
|
||||
"""
|
||||
Animate a scene using WaveSpeed InfiniteTalk (image + audio) asynchronously.
|
||||
Returns task_id for polling since InfiniteTalk can take up to 10 minutes.
|
||||
"""
|
||||
if not current_user:
|
||||
raise HTTPException(status_code=401, detail="Authentication required")
|
||||
|
||||
user_id = str(current_user.get("id", ""))
|
||||
if not user_id:
|
||||
raise HTTPException(status_code=401, detail="Invalid user ID in authentication token")
|
||||
|
||||
scene_logger.info(
|
||||
"[AnimateSceneVoiceover] User=%s scene=%s resolution=%s (async)",
|
||||
user_id,
|
||||
request.scene_number,
|
||||
request.resolution or "720p",
|
||||
)
|
||||
|
||||
image_bytes = load_story_image_bytes(request.image_url)
|
||||
if not image_bytes:
|
||||
raise HTTPException(status_code=404, detail="Scene image not found. Generate images first.")
|
||||
|
||||
audio_bytes = load_story_audio_bytes(request.audio_url)
|
||||
if not audio_bytes:
|
||||
raise HTTPException(status_code=404, detail="Scene audio not found. Generate audio first.")
|
||||
|
||||
db = next(get_db())
|
||||
try:
|
||||
pricing_service = PricingService(db)
|
||||
validate_scene_animation_operation(pricing_service=pricing_service, user_id=user_id)
|
||||
finally:
|
||||
db.close()
|
||||
|
||||
# Extract token for authenticated URL building (if needed)
|
||||
auth_token = None
|
||||
auth_header = request_obj.headers.get("Authorization")
|
||||
if auth_header and auth_header.startswith("Bearer "):
|
||||
auth_token = auth_header.replace("Bearer ", "").strip()
|
||||
|
||||
# Create async task
|
||||
task_id = task_manager.create_task("scene_voiceover_animation")
|
||||
background_tasks.add_task(
|
||||
_execute_voiceover_animation_task,
|
||||
task_id=task_id,
|
||||
request=request,
|
||||
user_id=user_id,
|
||||
image_bytes=image_bytes,
|
||||
audio_bytes=audio_bytes,
|
||||
auth_token=auth_token,
|
||||
)
|
||||
|
||||
return {
|
||||
"task_id": task_id,
|
||||
"status": "pending",
|
||||
"message": "InfiniteTalk animation started. This may take up to 10 minutes.",
|
||||
}
|
||||
|
||||
|
||||
def _execute_voiceover_animation_task(
|
||||
task_id: str,
|
||||
request: AnimateSceneVoiceoverRequest,
|
||||
user_id: str,
|
||||
image_bytes: bytes,
|
||||
audio_bytes: bytes,
|
||||
auth_token: Optional[str] = None,
|
||||
):
|
||||
"""Background task to generate InfiniteTalk video with progress updates."""
|
||||
try:
|
||||
task_manager.update_task_status(
|
||||
task_id, "processing", progress=5.0, message="Submitting to WaveSpeed InfiniteTalk..."
|
||||
)
|
||||
|
||||
animation_result = animate_scene_with_voiceover(
|
||||
image_bytes=image_bytes,
|
||||
audio_bytes=audio_bytes,
|
||||
scene_data=request.scene_data,
|
||||
story_context=request.story_context,
|
||||
user_id=user_id,
|
||||
resolution=request.resolution or "720p",
|
||||
prompt_override=request.prompt,
|
||||
image_mime=_guess_mime_from_url(request.image_url, "image/png"),
|
||||
audio_mime=_guess_mime_from_url(request.audio_url, "audio/mpeg"),
|
||||
)
|
||||
|
||||
task_manager.update_task_status(
|
||||
task_id, "processing", progress=80.0, message="Saving video file..."
|
||||
)
|
||||
|
||||
base_dir = Path(__file__).parent.parent.parent.parent
|
||||
ai_video_dir = base_dir / "story_videos" / AI_VIDEO_SUBDIR
|
||||
ai_video_dir.mkdir(parents=True, exist_ok=True)
|
||||
video_service = StoryVideoGenerationService(output_dir=str(ai_video_dir))
|
||||
|
||||
save_result = video_service.save_scene_video(
|
||||
video_bytes=animation_result["video_bytes"],
|
||||
scene_number=request.scene_number,
|
||||
user_id=user_id,
|
||||
)
|
||||
video_filename = save_result["video_filename"]
|
||||
# Build authenticated URL if token provided, otherwise return plain URL
|
||||
video_url = f"/api/story/videos/ai/{video_filename}"
|
||||
if auth_token:
|
||||
video_url = f"{video_url}?token={quote(auth_token)}"
|
||||
|
||||
usage_info = track_video_usage(
|
||||
user_id=user_id,
|
||||
provider=animation_result["provider"],
|
||||
model_name=animation_result["model_name"],
|
||||
prompt=animation_result["prompt"],
|
||||
video_bytes=animation_result["video_bytes"],
|
||||
cost_override=animation_result["cost"],
|
||||
)
|
||||
if usage_info:
|
||||
scene_logger.warning(
|
||||
"[AnimateSceneVoiceover] Video usage tracked user=%s: %s → %s / %s (cost +$%.2f, total=$%.2f)",
|
||||
user_id,
|
||||
usage_info.get("previous_calls"),
|
||||
usage_info.get("current_calls"),
|
||||
usage_info.get("video_limit_display"),
|
||||
usage_info.get("cost_per_video", 0.0),
|
||||
usage_info.get("total_video_cost", 0.0),
|
||||
)
|
||||
|
||||
scene_logger.info(
|
||||
"[AnimateSceneVoiceover] ✅ Completed user=%s scene=%s cost=$%.2f video=%s",
|
||||
user_id,
|
||||
request.scene_number,
|
||||
animation_result["cost"],
|
||||
video_url,
|
||||
)
|
||||
|
||||
# Save video asset to library
|
||||
db = next(get_db())
|
||||
try:
|
||||
save_asset_to_library(
|
||||
db=db,
|
||||
user_id=user_id,
|
||||
asset_type="video",
|
||||
source_module="story_writer",
|
||||
filename=video_filename,
|
||||
file_url=video_url,
|
||||
file_path=str(ai_video_dir / video_filename),
|
||||
file_size=len(animation_result["video_bytes"]),
|
||||
mime_type="video/mp4",
|
||||
title=f"Scene {request.scene_number} Animation (Voiceover)",
|
||||
description=f"Animated scene {request.scene_number} with voiceover from story",
|
||||
prompt=animation_result["prompt"],
|
||||
tags=["story_writer", "video", "animation", "voiceover", f"scene_{request.scene_number}"],
|
||||
provider=animation_result["provider"],
|
||||
model=animation_result.get("model_name"),
|
||||
cost=animation_result["cost"],
|
||||
asset_metadata={"scene_number": request.scene_number, "duration": animation_result["duration"], "status": "completed"}
|
||||
)
|
||||
except Exception as e:
|
||||
logger.warning(f"[StoryWriter] Failed to save video asset to library: {e}")
|
||||
finally:
|
||||
db.close()
|
||||
|
||||
result = AnimateSceneResponse(
|
||||
success=True,
|
||||
scene_number=request.scene_number,
|
||||
video_filename=video_filename,
|
||||
video_url=video_url,
|
||||
duration=animation_result["duration"],
|
||||
cost=animation_result["cost"],
|
||||
prompt_used=animation_result["prompt"],
|
||||
provider=animation_result["provider"],
|
||||
prediction_id=animation_result.get("prediction_id"),
|
||||
)
|
||||
|
||||
task_manager.update_task_status(
|
||||
task_id,
|
||||
"completed",
|
||||
progress=100.0,
|
||||
message="InfiniteTalk animation complete!",
|
||||
result=result.dict(),
|
||||
)
|
||||
except HTTPException as exc:
|
||||
error_msg = str(exc.detail) if isinstance(exc.detail, str) else exc.detail.get("error", "Animation failed") if isinstance(exc.detail, dict) else "Animation failed"
|
||||
scene_logger.error(f"[AnimateSceneVoiceover] Failed: {error_msg}")
|
||||
task_manager.update_task_status(
|
||||
task_id,
|
||||
"failed",
|
||||
error=error_msg,
|
||||
message=f"InfiniteTalk animation failed: {error_msg}",
|
||||
)
|
||||
except Exception as exc:
|
||||
error_msg = str(exc)
|
||||
scene_logger.error(f"[AnimateSceneVoiceover] Error: {error_msg}", exc_info=True)
|
||||
task_manager.update_task_status(
|
||||
task_id,
|
||||
"failed",
|
||||
error=error_msg,
|
||||
message=f"InfiniteTalk animation error: {error_msg}",
|
||||
)
|
||||
|
||||
@@ -1,7 +1,9 @@
|
||||
from typing import Any, Dict, List
|
||||
from datetime import datetime
|
||||
from typing import Any, Dict, List, Optional
|
||||
|
||||
from fastapi import APIRouter, Depends, HTTPException
|
||||
from loguru import logger
|
||||
from pydantic import BaseModel
|
||||
|
||||
from middleware.auth_middleware import get_current_user
|
||||
from models.story_models import (
|
||||
@@ -18,6 +20,7 @@ from ..utils.auth import require_authenticated_user
|
||||
|
||||
router = APIRouter()
|
||||
story_service = StoryWriterService()
|
||||
scene_approval_store: Dict[str, Dict[str, Any]] = {}
|
||||
|
||||
|
||||
@router.post("/generate-start", response_model=StoryContentResponse)
|
||||
@@ -193,3 +196,45 @@ async def continue_story(
|
||||
raise HTTPException(status_code=500, detail=str(exc))
|
||||
|
||||
|
||||
class SceneApprovalRequest(BaseModel):
|
||||
project_id: str
|
||||
scene_id: str
|
||||
approved: bool = True
|
||||
notes: Optional[str] = None
|
||||
|
||||
|
||||
@router.post("/script/approve")
|
||||
async def approve_script_scene(
|
||||
request: SceneApprovalRequest,
|
||||
current_user: Dict[str, Any] = Depends(get_current_user),
|
||||
) -> Dict[str, Any]:
|
||||
"""Persist scene approval metadata for auditing."""
|
||||
try:
|
||||
user_id = require_authenticated_user(current_user)
|
||||
approvals = scene_approval_store.setdefault(request.project_id, {})
|
||||
approvals[request.scene_id] = {
|
||||
"approved": request.approved,
|
||||
"notes": request.notes,
|
||||
"user_id": user_id,
|
||||
"timestamp": datetime.utcnow().isoformat(),
|
||||
}
|
||||
logger.info(
|
||||
"[StoryWriter] Scene approval recorded user=%s project=%s scene=%s approved=%s",
|
||||
user_id,
|
||||
request.project_id,
|
||||
request.scene_id,
|
||||
request.approved,
|
||||
)
|
||||
return {
|
||||
"success": True,
|
||||
"project_id": request.project_id,
|
||||
"scene_id": request.scene_id,
|
||||
"approved": request.approved,
|
||||
}
|
||||
except HTTPException:
|
||||
raise
|
||||
except Exception as exc:
|
||||
logger.error(f"[StoryWriter] Failed to approve scene: {exc}")
|
||||
raise HTTPException(status_code=500, detail=str(exc))
|
||||
|
||||
|
||||
|
||||
@@ -509,3 +509,30 @@ async def serve_story_video(
|
||||
raise HTTPException(status_code=500, detail=str(exc))
|
||||
|
||||
|
||||
@router.get("/videos/ai/{video_filename}")
|
||||
async def serve_ai_story_video(
|
||||
video_filename: str,
|
||||
current_user: Dict[str, Any] = Depends(get_current_user),
|
||||
):
|
||||
"""Serve a generated AI scene animation video."""
|
||||
try:
|
||||
require_authenticated_user(current_user)
|
||||
|
||||
base_dir = Path(__file__).parent.parent.parent.parent
|
||||
ai_video_dir = (base_dir / "story_videos" / "AI_Videos").resolve()
|
||||
video_service_ai = StoryVideoGenerationService(output_dir=str(ai_video_dir))
|
||||
video_path = resolve_media_file(video_service_ai.output_dir, video_filename)
|
||||
|
||||
return FileResponse(
|
||||
path=str(video_path),
|
||||
media_type="video/mp4",
|
||||
filename=video_filename
|
||||
)
|
||||
|
||||
except HTTPException:
|
||||
raise
|
||||
except Exception as exc:
|
||||
logger.error(f"[StoryWriter] Failed to serve AI video: {exc}")
|
||||
raise HTTPException(status_code=500, detail=str(exc))
|
||||
|
||||
|
||||
|
||||
Reference in New Issue
Block a user