2b721d182b
Backend:
- New UserRole.PROJECT_MANAGER with pm_client_ids[] on User model
- New models: Client (slug-based), Team (member_user_ids[]), Project (client-scoped)
- Job model gains project_id field
- New GET/POST/PATCH/DELETE /clients, /clients/{id}/teams, /clients/{id}/projects,
/clients/{id}/pm routes (admin-only client CRUD; PM or admin for teams/projects)
- get_accessible_project_ids() helper: staff→all, PM→their clients' projects,
CLIENT→projects from teams they belong to (with legacy owner fallback)
- list_jobs, get_job, bulk_download, get_vtt_content, delete_job all use new isolation
Frontend:
- UserRole type gains 'project_manager'
- Job, JobCreateRequest gain project_id field
- Client, Team, Project, PMUser types added
- ApiClient: full client/team/project/PM CRUD methods
- useClients hook with all query/mutation hooks
- Admin pages: ClientList + ClientDetail (teams, members, projects, PM assignment)
- NewJob form: client + project picker (shown when clients exist)
- Sidebar: Clients nav item for admin and project_manager roles
- Routes: /admin/clients and /admin/clients/:clientId behind RoleGate
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
195 lines
8.6 KiB
Python
195 lines
8.6 KiB
Python
from datetime import datetime
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from enum import Enum
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from typing import Any, Literal, Optional
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from pydantic import BaseModel, Field, constr
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class JobStatus(str, Enum):
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CREATED = "created"
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INGESTING = "ingesting"
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AI_PROCESSING = "ai_processing"
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PENDING_QC = "pending_qc"
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APPROVED_ENGLISH = "approved_english" # For English source videos
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APPROVED_SOURCE = "approved_source" # For non-English source videos
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REJECTED = "rejected"
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QC_FEEDBACK = "qc_feedback"
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TRANSLATING = "translating"
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TTS_GENERATING = "tts_generating"
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TTS_FAILED = "tts_failed" # TTS synthesis failed after retries, requires reprocessing
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RENDERING_VIDEO = "rendering_video" # Accessible video rendering in progress
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RENDER_FAILED = "render_failed" # Accessible video rendering failed, requires reprocessing
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RENDERING_QC = "rendering_qc" # Re-rendering accessible video during QC review
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PENDING_FINAL_REVIEW = "pending_final_review"
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COMPLETED = "completed"
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@classmethod
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def is_approved(cls, status: str) -> bool:
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"""Check if status indicates source approval (any language)"""
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return status in [cls.APPROVED_ENGLISH.value, cls.APPROVED_SOURCE.value]
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class Source(BaseModel):
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filename: str
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original_filename: Optional[str] = None
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gcs_uri: str
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duration_s: Optional[float] = None
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language: constr(min_length=2, max_length=10) = "en" # Final source language (from detection or explicit)
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language_hint: Optional[str] = None # User-provided hint for non-English videos
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detected_language: Optional[str] = None # AI-detected language from Gemini
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class TTSPreferences(BaseModel):
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"""TTS voice preferences for audio description generation"""
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provider: Literal["gemini", "google", "elevenlabs"] = "gemini"
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default_voice: str = "Kore" # Default Gemini voice
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voices_per_language: dict[str, str] = {} # {"en": "Kore", "es": "Aoede"}
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# TTS quality and style settings
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model: Literal["flash", "pro"] = "flash" # flash = fast/cheap, pro = higher quality
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speed: float = Field(default=1.0, ge=0.5, le=2.0) # Speech rate multiplier
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style_preset: Literal[
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"neutral", "calm", "energetic", "professional", "warm", "documentary", "custom"
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] = "neutral"
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custom_style_prompt: Optional[str] = None # Used when style_preset is "custom"
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# ElevenLabs-specific settings
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stability: Optional[float] = None # 0.0-1.0, default 0.5 when used
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similarity_boost: Optional[float] = None # 0.0-1.0, default 0.5 when used
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class RequestedOutputs(BaseModel):
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captions_vtt: bool = True
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audio_description_vtt: bool = True
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audio_description_mp3: bool = True
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accessible_video_mp4: bool = False # Rendered video with embedded audio descriptions
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accessible_video_method: Optional[Literal["overlay", "pause_insert"]] = None # User-selected method
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sdh_vtt: bool = False # SDH (Subtitles for Deaf and Hard of Hearing) captions with speaker labels, sound effects, music notation
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languages: list[str] = []
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transcreation: list[str] = []
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tts_preferences: Optional[TTSPreferences] = None
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translation_mode: Literal["traditional", "video_native"] = "video_native"
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class PausePointData(BaseModel):
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"""Pause point timing data for accessible video editing during QC."""
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cue_index: int # AD cue index this pause point belongs to
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original_ms: float # Rendered timeline position (ms) - for UI display
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source_ms: Optional[float] = None # Source video cut point (ms) - for re-rendering (None = use original_ms)
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adjusted_ms: Optional[float] = None # User-adjusted timestamp (ms), None = use original
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min_bound_ms: float # Minimum allowed value (end of previous AD segment)
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max_bound_ms: float # Maximum allowed value (start of next AD segment)
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class VideoSegmentMetadata(BaseModel):
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"""Metadata for a video segment between pause points."""
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segment_index: int # 0-based segment index
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start_ms: float # Start timestamp in source video (ms)
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end_ms: float # End timestamp in source video (ms)
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gcs_uri: str # GCS path to segment MP4
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duration_ms: float # Actual segment duration (ms)
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is_freeze_frame: bool = False # True if this is a freeze frame segment with AD audio
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cue_index: Optional[int] = None # AD cue index (only for freeze frame segments)
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class TTSRegenerationRequest(BaseModel):
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"""Request to regenerate TTS for a specific cue during QC."""
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cue_index: int
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requested_at: datetime
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new_text: Optional[str] = None # If provided, use this text instead of current VTT
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status: Literal["pending", "processing", "completed", "failed"] = "pending"
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error_message: Optional[str] = None
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class AccessibleVideoEditState(BaseModel):
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"""Editable state for accessible video during QC review."""
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pause_points: list[PausePointData] = []
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video_segments: list[VideoSegmentMetadata] = []
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tts_regeneration_queue: list[TTSRegenerationRequest] = []
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last_render_at: Optional[datetime] = None
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whisper_refine_enabled: bool = False # Default: off (user enables if cue positions changed)
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class LangOutput(BaseModel):
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captions_vtt_gcs: Optional[str] = None
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sdh_captions_vtt_gcs: Optional[str] = None # SDH-format captions (speaker labels, sound effects, music)
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ad_vtt_gcs: Optional[str] = None
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ad_mp3_gcs: Optional[str] = None
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# Accessible video outputs
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accessible_video_gcs: Optional[str] = None # Rendered accessible MP4
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accessible_video_method: Optional[Literal["overlay", "pause_insert"]] = None
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retimed_captions_vtt_gcs: Optional[str] = None # Re-timed captions for pause-insert method
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ad_cues_gcs_prefix: Optional[str] = None # GCS path prefix for per-cue MP3 segments
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ad_cue_manifest: Optional[list[dict]] = None # Per-cue manifest: [{cue_index, gcs_uri, text, duration_s}]
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# QC editing state for accessible video
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video_segments_gcs_prefix: Optional[str] = None # GCS prefix for persisted video segments
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accessible_video_edit_state: Optional[AccessibleVideoEditState] = None
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origin: Optional[Literal["translate", "transcreate", "gemini_translate", "video_native"]] = None
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qa_notes: Optional[str] = None
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descriptive_transcript_gcs: Optional[str] = None # WCAG-compliant combined speech+description transcript
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class ReviewHistoryItem(BaseModel):
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at: datetime
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status: str
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by: Optional[str] = None
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notes: Optional[str] = None
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class Review(BaseModel):
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notes: Optional[str] = ""
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reviewer_id: Optional[str] = None
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history: list[ReviewHistoryItem] = []
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class AISection(BaseModel):
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ingestion_json: Optional[dict[str, Any]] = None
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confidence: Optional[float] = None
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class AccessibleVideoProgressItem(BaseModel):
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"""Progress tracking for accessible video rendering per language."""
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status: Literal["pending", "rendering", "completed", "failed"] = "pending"
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method: Optional[Literal["overlay", "pause_insert"]] = None
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error_message: Optional[str] = None
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started_at: Optional[datetime] = None
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completed_at: Optional[datetime] = None
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class Job(BaseModel):
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id: Optional[str] = Field(None, alias="_id")
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client_id: str
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title: str
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source: Source
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requested_outputs: RequestedOutputs
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status: JobStatus = JobStatus.CREATED
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review: Review = Review()
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outputs: Optional[dict[str, LangOutput]] = None
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accessible_video_progress: Optional[dict[str, AccessibleVideoProgressItem]] = None
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ai: Optional[AISection] = None
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error: Optional[dict[str, Any]] = None
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tts_rewrites: Optional[list[dict[str, Any]]] = None # Track auto-rewritten TTS cues
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project_id: Optional[str] = None # Platform project this job belongs to (Client → Project → Job)
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brand_context: Optional[str] = None # Brand names present in the video for accurate product identification
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cost_tracker_project_id: Optional[str] = None # External project ID for AI cost attribution
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created_at: Optional[datetime] = None
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updated_at: Optional[datetime] = None
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class Config:
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populate_by_name = True
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use_enum_values = True
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class JobCreate(BaseModel):
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title: str
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source_is_english: bool = True # True = English source, False = other language (auto-detect)
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language_hint: Optional[str] = None # Optional hint when source_is_english=False
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requested_outputs: RequestedOutputs
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brand_context: Optional[str] = None # Comma-separated brand names present in the video (e.g. "Sellotape, Coca-Cola")
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class JobUpdate(BaseModel):
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title: Optional[str] = None
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status: Optional[JobStatus] = None
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review: Optional[Review] = None
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outputs: Optional[dict[str, LangOutput]] = None
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ai: Optional[AISection] = None
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error: Optional[dict[str, Any]] = None
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