Files
ubuntu-post-install/paintplus/backend/app/schemas.py
T
Claude 084922afaa paintplus: vendor the app source and rename from EditmaskwithAI
Bring the full EditmaskwithAI application into the repo under paintplus/
(429 files) so the service is self-contained — the installer copies the
vendored source to ~/docker/paintplus/src instead of cloning at runtime.

Rename to PaintPlus (service + branding; app logic untouched):
- services/editmaskwithai.sh -> services/paintplus.sh (register_service
  paintplus, install_paintplus, ~/docker/paintplus, Caddy paintplus:8000,
  Authelia option preserved)
- container names -> paintplus across docker-compose*.yml; dev network
  -> paintplus-network
- browser <title> -> "PaintPlus - AI Image Editor"; README heading ->
  PaintPlus with upstream provenance note
- README utilities table: editmaskwithai -> paintplus

Backend/frontend code (help strings referencing the old container name,
the ai_photo_edit.db filename) is intentionally left as-is to avoid
touching application logic.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Nb2vJ8W7bHKx1JXVvpCraH
2026-06-26 05:48:43 +00:00

139 lines
2.9 KiB
Python

from pydantic import BaseModel, EmailStr
from typing import Optional, List, Dict, Any
from datetime import datetime
# User schemas
class UserCreate(BaseModel):
email: EmailStr
password: str
class UserResponse(BaseModel):
id: int
email: str
created_at: datetime
class Config:
from_attributes = True
# Project schemas
class ProjectCreate(BaseModel):
name: str
class ProjectResponse(BaseModel):
id: int
user_id: int
name: str
created_at: datetime
updated_at: datetime
class Config:
from_attributes = True
# Edit schemas
class EditRequest(BaseModel):
prompt: str
mode: str = "A" # "A" or "B"
selection_type: str # "rectangle", "ellipse", "lasso"
bbox: Dict[str, int] # {x, y, width, height}
feather_px: int = 0
selection_data: Optional[Dict[str, Any]] = None
class EditResponse(BaseModel):
id: int
project_id: int
created_at: datetime
mode: str
prompt: str
selection_type: str
bbox_json: str
feather_px: int
ai_provider: str
status: str
error_message: Optional[str] = None
class Config:
from_attributes = True
# Image upload
class UploadResponse(BaseModel):
project_id: int
original_url: str
current_url: str
# Patch Library schemas
class PatchCreate(BaseModel):
name: str
description: Optional[str] = None
source_type: str # "ai_generated", "manual_selection", "imported"
source_project_id: Optional[int] = None
source_edit_id: Optional[int] = None
category: Optional[str] = None
tags: Optional[str] = None
bbox: Optional[Dict[str, int]] = None
class PatchResponse(BaseModel):
id: int
name: str
description: Optional[str]
created_at: datetime
source_type: str
source_project_id: Optional[int]
source_edit_id: Optional[int]
width: int
height: int
tags: Optional[str]
category: Optional[str]
is_public: bool
file_path: str
thumbnail_path: Optional[str]
class Config:
from_attributes = True
class PatchApply(BaseModel):
project_id: int
patch_id: int
bbox: Dict[str, int]
feather_px: int = 5
# Text-to-Image schemas
class TextToImageRequest(BaseModel):
prompt: str
width: int = 1024
height: int = 1024
negative_prompt: Optional[str] = None
ai_provider: Optional[str] = None
ai_model: Optional[str] = None
create_project: bool = True
project_name: Optional[str] = None
class TextToImageResponse(BaseModel):
status: str
prompt: str
width: int
height: int
project_id: Optional[int] = None
image_url: Optional[str] = None
layer_position: Optional[Dict[str, int]] = None
ai_provider: str
ai_model: Optional[str] = None
# Generic responses
class StatusResponse(BaseModel):
status: str
message: Optional[str] = None
data: Optional[Any] = None