API

app/models.py

@@ -0,0 +1,368 @@
+from datetime import datetime
+from uuid import UUID
+
+from pydantic import BaseModel, EmailStr, Field
+
+
+# ── Auth ──
+
+
+class RegisterRequest(BaseModel):
+    email: EmailStr
+    password: str = Field(min_length=8)
+    display_name: str | None = None
+    timezone: str = "America/Chicago"
+
+
+class LoginRequest(BaseModel):
+    email: EmailStr
+    password: str
+
+
+class AppleAuthRequest(BaseModel):
+    identity_token: str
+    authorization_code: str
+    full_name: str | None = None
+
+
+class RefreshRequest(BaseModel):
+    refresh_token: str
+
+
+class AuthResponse(BaseModel):
+    access_token: str
+    refresh_token: str
+    expires_in: int
+    user: "UserOut"
+
+
+class UserOut(BaseModel):
+    id: UUID
+    email: str | None
+    display_name: str | None
+    timezone: str
+    created_at: datetime
+
+
+# ── Tasks ──
+
+
+class TaskCreate(BaseModel):
+    title: str
+    description: str | None = None
+    priority: int = Field(0, ge=0, le=4)
+    deadline: datetime | None = None
+    estimated_minutes: int | None = None
+    tags: list[str] = []
+
+
+class TaskUpdate(BaseModel):
+    title: str | None = None
+    description: str | None = None
+    priority: int | None = Field(None, ge=0, le=4)
+    status: str | None = None
+    deadline: datetime | None = None
+    estimated_minutes: int | None = None
+    tags: list[str] | None = None
+
+
+class TaskOut(BaseModel):
+    id: UUID
+    user_id: UUID
+    title: str
+    description: str | None
+    priority: int
+    status: str
+    deadline: datetime | None
+    estimated_minutes: int | None
+    source: str
+    tags: list[str]
+    plan_type: str | None
+    brain_dump_raw: str | None
+    created_at: datetime
+    updated_at: datetime
+
+
+class BrainDumpRequest(BaseModel):
+    raw_text: str
+    source: str = "manual"
+    timezone: str = "America/Chicago"
+
+
+class ParsedSubtask(BaseModel):
+    title: str
+    description: str | None = None
+    deadline: datetime | None = None
+    estimated_minutes: int | None = None
+    suggested: bool = False
+
+
+class ParsedTask(BaseModel):
+    task_id: str | None = None
+    title: str
+    description: str | None = None
+    priority: int = 0
+    deadline: datetime | None = None
+    estimated_minutes: int | None = None
+    tags: list[str] = []
+    subtasks: list[ParsedSubtask] = []
+
+class BrainDumpResponse(BaseModel):
+    parsed_tasks: list[ParsedTask]
+    unparseable_fragments: list[str] = []
+    ask_for_plans: bool = True
+
+
+class PlanRequest(BaseModel):
+    plan_type: str = "llm_generated"
+
+
+# ── Steps ──
+
+
+class StepOut(BaseModel):
+    id: UUID
+    task_id: UUID
+    sort_order: int
+    title: str
+    description: str | None
+    estimated_minutes: int | None
+    status: str
+    checkpoint_note: str | None
+    last_checked_at: datetime | None
+    completed_at: datetime | None
+    created_at: datetime
+
+
+class StepUpdate(BaseModel):
+    title: str | None = None
+    description: str | None = None
+    estimated_minutes: int | None = None
+    sort_order: int | None = None
+    status: str | None = None
+    checkpoint_note: str | None = None
+
+
+class PlanResponse(BaseModel):
+    task_id: UUID
+    plan_type: str
+    steps: list[StepOut]
+
+
+# ── Sessions ──
+
+
+class SessionStartRequest(BaseModel):
+    task_id: UUID | None = None
+    platform: str = "mac"
+    work_app_bundle_ids: list[str] | None = None
+
+
+class SessionCheckpointRequest(BaseModel):
+    current_step_id: UUID | None = None
+    last_action_summary: str | None = None
+    next_up: str | None = None
+    goal: str | None = None
+    active_app: str | None = None
+    last_screenshot_analysis: str | None = None
+    attention_score: int | None = None
+    distraction_count: int | None = None
+
+
+class SessionEndRequest(BaseModel):
+    status: str = "completed"
+
+
+class OpenSessionOut(BaseModel):
+    id: UUID
+    task_id: UUID | None
+    task: dict | None
+    status: str
+    platform: str
+    started_at: datetime
+    ended_at: datetime | None
+    checkpoint: dict
+
+
+class SessionJoinRequest(BaseModel):
+    platform: str = "ipad"
+    work_app_bundle_ids: list[str] | None = None
+
+
+class SessionJoinResponse(BaseModel):
+    session_id: UUID
+    joined: bool
+    task: dict | None
+    current_step: dict | None
+    all_steps: list[StepOut]
+    suggested_app_scheme: str | None
+    suggested_app_name: str | None
+
+
+class SessionOut(BaseModel):
+    id: UUID
+    user_id: UUID
+    task_id: UUID | None
+    platform: str
+    started_at: datetime
+    ended_at: datetime | None
+    status: str
+    checkpoint: dict
+    created_at: datetime
+
+
+class ResumeCard(BaseModel):
+    welcome_back: str
+    you_were_doing: str
+    next_step: str
+    motivation: str
+
+
+class SessionResumeResponse(BaseModel):
+    session_id: UUID
+    task: dict | None
+    current_step: dict | None
+    progress: dict
+    resume_card: ResumeCard
+
+
+# ── Distractions ──
+
+
+class ScreenshotAnalysisResponse(BaseModel):
+    on_task: bool
+    current_step_id: UUID | None
+    checkpoint_note_update: str | None
+    steps_completed: list[UUID] = []
+    distraction_type: str | None
+    app_name: str | None
+    confidence: float
+    gentle_nudge: str | None
+    vlm_summary: str | None
+
+
+class AppActivityRequest(BaseModel):
+    session_id: UUID
+    app_bundle_id: str
+    app_name: str
+    duration_seconds: int
+    returned_to_task: bool = False
+
+
+class AppActivityResponse(BaseModel):
+    distraction_logged: bool
+    session_distraction_count: int
+    gentle_nudge: str | None
+
+
+class AppCheckRequest(BaseModel):
+    app_bundle_id: str
+
+
+class AppCheckResponse(BaseModel):
+    is_distraction_app: bool
+    pending_task_count: int
+    most_urgent_task: dict | None
+    nudge: str | None
+
+
+# ── Analyze Result (Device-Side VLM) ──
+
+
+class ProposedAction(BaseModel):
+    label: str
+    action_type: str
+    details: str | None = None
+
+
+class FrictionDetection(BaseModel):
+    type: str = "none"
+    confidence: float = 0.0
+    description: str | None = None
+    proposed_actions: list[ProposedAction] = []
+    source_context: str | None = None
+    target_context: str | None = None
+
+
+class SessionAction(BaseModel):
+    type: str = "none"  # resume | switch | complete | start_new | none
+    session_id: UUID | None = None
+    reason: str | None = None
+
+
+class AnalyzeResultRequest(BaseModel):
+    session_id: UUID | None = None  # optional — VLM can run without an active session
+    on_task: bool
+    current_step_id: UUID | None = None
+    inferred_task: str | None = None
+    checkpoint_note_update: str | None = None
+    steps_completed: list[UUID] = []
+    friction: FrictionDetection = FrictionDetection()
+    session_action: SessionAction = SessionAction()
+    intent: str | None = None
+    distraction_type: str | None = None
+    app_name: str | None = None
+    confidence: float = 0.0
+    gentle_nudge: str | None = None
+    vlm_summary: str | None = None
+
+
+class AnalyzeResultResponse(BaseModel):
+    side_effects_applied: bool
+    steps_updated: int
+    distraction_logged: bool
+    proactive_action_id: UUID | None = None
+
+
+# ── Proactive Actions ──
+
+
+class ProactiveRespondRequest(BaseModel):
+    proactive_action_id: UUID
+    user_choice: str  # accepted | declined | alternative_chosen
+    chosen_action: str | None = None
+
+
+class ProactiveRespondResponse(BaseModel):
+    logged: bool
+    should_execute: bool
+
+
+class ProactiveExecuteRequest(BaseModel):
+    proactive_action_id: UUID
+    action_type: str
+    execution_params: dict = {}
+
+
+class ProactiveExecuteResponse(BaseModel):
+    executed: bool
+    result: str | None = None
+
+
+class ProactivePreference(BaseModel):
+    preferred_action: str | None
+    total_choices: int
+    acceptance_rate: float
+
+
+class ProactivePreferencesResponse(BaseModel):
+    preferences: dict[str, ProactivePreference]
+
+
+# ── Device Token ──
+
+
+class DeviceTokenRequest(BaseModel):
+    platform: str
+    token: str
+
+
+# ── Analytics ──
+
+
+class AnalyticsSummary(BaseModel):
+    total_focus_minutes: float
+    sessions_completed: int
+    tasks_completed: int
+    top_distractors: list[dict]
+    avg_attention_score: float | None