o2o-infinith-backend/app/integrations/llm/schemas/report.py

from __future__ import annotations
from pydantic import BaseModel
from models.status import Severity, ChannelStatus, DataSource, Language, VideoType, AnnotationType


class ScreenshotAnnotation(BaseModel):
    type: AnnotationType
    x: float
    y: float
    width: float | None = None
    height: float | None = None
    label: str | None = None
    color: str | None = None


class ScreenshotEvidence(BaseModel):
    id: str
    url: str
    channel: str
    captured_at: str
    caption: str
    source_url: str | None = None
    annotations: list[ScreenshotAnnotation] | None = None


class DiagnosisItem(BaseModel):
    category: str
    detail: str
    severity: Severity
    evidence_ids: list[str] | None = None


# --- ClinicSnapshot ---

class LeadDoctor(BaseModel):
    name: str
    credentials: str
    rating: float
    review_count: int


class PriceRange(BaseModel):
    min: str
    max: str
    currency: str


class LogoImages(BaseModel):
    circle: str | None = None
    horizontal: str | None = None
    korean: str | None = None


class BrandColors(BaseModel):
    primary: str
    accent: str
    text: str


class RegistryData(BaseModel):
    district: str | None = None
    branches: str | None = None
    brand_group: str | None = None
    website_en: str | None = None
    naver_place_url: str | None = None
    gangnam_unni_url: str | None = None
    google_maps_url: str | None = None


class ClinicSnapshot(BaseModel):
    name: str
    name_en: str
    staff_count: int
    lead_doctor: LeadDoctor
    overall_rating: float
    total_reviews: int
    certifications: list[str]
    location: str
    phone: str
    domain: str
    logo_images: LogoImages | None = None
    brand_colors: BrandColors | None = None
    source: DataSource | None = None
    registry_data: RegistryData | None = None


# --- ChannelScore ---

class ChannelScore(BaseModel):
    channel: str
    icon: str
    score: int
    max_score: int
    status: Severity
    headline: str


# --- YouTube ---

class WeeklyViewGrowth(BaseModel):
    absolute: int
    percentage: float


class EstimatedRevenue(BaseModel):
    min: int
    max: int


class LinkedUrl(BaseModel):
    label: str
    url: str


class TopVideo(BaseModel):
    title: str
    views: int
    uploaded_ago: str
    type: VideoType
    duration: str | None = None


class YouTubeAudit(BaseModel):
    channel_name: str
    handle: str
    subscribers: int
    total_videos: int
    total_views: int
    weekly_view_growth: WeeklyViewGrowth
    estimated_monthly_revenue: EstimatedRevenue
    avg_video_length: str
    upload_frequency: str
    channel_created_date: str
    channel_description: str
    linked_urls: list[LinkedUrl]
    playlists: list[str]
    top_videos: list[TopVideo]
    diagnosis: list[DiagnosisItem]


# --- Instagram ---

class InstagramAccount(BaseModel):
    handle: str
    language: Language
    label: str
    posts: int
    followers: int
    following: int
    category: str
    profile_link: str
    highlights: list[str]
    reels_count: int
    content_format: str
    profile_photo: str
    bio: str


class InstagramAudit(BaseModel):
    accounts: list[InstagramAccount]
    diagnosis: list[DiagnosisItem]


# --- Facebook ---

class BrandInconsistencyValue(BaseModel):
    channel: str
    value: str
    is_correct: bool


class BrandInconsistency(BaseModel):
    field: str
    values: list[BrandInconsistencyValue]
    impact: str
    recommendation: str


class FacebookPage(BaseModel):
    url: str
    page_name: str
    language: Language
    label: str
    followers: int
    following: int
    category: str
    bio: str
    logo: str
    logo_description: str
    link: str
    linked_domain: str
    reviews: int
    recent_post_age: str
    has_whatsapp: bool
    post_frequency: str | None = None
    top_content_type: str | None = None
    engagement: str | None = None


class FacebookAudit(BaseModel):
    pages: list[FacebookPage]
    diagnosis: list[DiagnosisItem]
    brand_inconsistencies: list[BrandInconsistency]
    consolidation_recommendation: str


# --- 기타 채널 / 웹사이트 ---

class OtherChannel(BaseModel):
    name: str
    status: ChannelStatus
    details: str
    url: str | None = None


class TrackingPixel(BaseModel):
    name: str
    installed: bool
    details: str | None = None


class SnsLink(BaseModel):
    platform: str
    url: str
    location: str


class AdditionalDomain(BaseModel):
    domain: str
    purpose: str


class WebsiteAudit(BaseModel):
    primary_domain: str
    additional_domains: list[AdditionalDomain]
    sns_links_on_site: bool
    sns_links_detail: list[SnsLink] | None = None
    tracking_pixels: list[TrackingPixel]
    main_cta: str


# --- Transformation ---

class AsIsToBeItem(BaseModel):
    area: str
    as_is: str
    to_be: str


class StrategyDetail(BaseModel):
    strategy: str
    detail: str


class PlatformStrategy(BaseModel):
    platform: str
    icon: str
    current_metric: str
    target_metric: str
    strategies: list[StrategyDetail]


class NewChannelProposal(BaseModel):
    channel: str
    priority: str
    rationale: str


class TransformationProposal(BaseModel):
    brand_identity: list[AsIsToBeItem]
    content_strategy: list[AsIsToBeItem]
    platform_strategies: list[PlatformStrategy]
    website_improvements: list[AsIsToBeItem]
    new_channel_proposals: list[NewChannelProposal]


# --- Roadmap / KPI ---

class RoadmapTask(BaseModel):
    task: str
    completed: bool


class RoadmapMonth(BaseModel):
    month: int
    title: str
    subtitle: str
    tasks: list[RoadmapTask]


class KPIMetric(BaseModel):
    metric: str
    current: str
    target_3_month: str
    target_12_month: str


# --- ReportInput (prompt 템플릿 변수) ---

class ReportInput(BaseModel):
    clinic_name: str | None = None
    clinic_name_en: str | None = None
    address: str | None = None
    phone: str | None = None
    slogan: str | None = None
    services: str | None = None
    doctors: str | None = None
    instagram: str | None = None
    facebook: str | None = None
    naver_blog: str | None = None
    youtube: str | None = None
    gangnam_unni: str | None = None
    market_competitors: str | None = None
    market_keywords: str | None = None
    market_trend: str | None = None
    market_target_audience: str | None = None


# --- MarketingReport ---

class MarketingReport(BaseModel):
    id: str
    created_at: str
    target_url: str
    overall_score: int
    clinic_snapshot: ClinicSnapshot
    channel_scores: list[ChannelScore]
    youtube_audit: YouTubeAudit
    instagram_audit: InstagramAudit
    facebook_audit: FacebookAudit
    other_channels: list[OtherChannel]
    website_audit: WebsiteAudit
    problem_diagnosis: list[DiagnosisItem]
    transformation: TransformationProposal
    roadmap: list[RoadmapMonth]
    kpi_dashboard: list[KPIMetric]
    screenshots: list[ScreenshotEvidence] | None = None


ReportOutput = MarketingReport


# --- YouTubeDiagnosis ---

class YouTubeDiagnosisInput(BaseModel):
    channel_name: str | None = None
    subscribers: int | None = None
    total_videos: int | None = None
    total_views: int | None = None
    avg_video_length: str | None = None
    upload_frequency: str | None = None
    top_videos: str | None = None
    playlists: str | None = None


class YouTubeDiagnosisOutput(BaseModel):
    diagnosis: list[DiagnosisItem]


# --- Diagnosis ---

class CriticalIssuesInput(BaseModel):
    clinic_name: str | None = None
    data: str | None = None


class CriticalIssuesOutput(BaseModel):
    diagnosis: list[DiagnosisItem]


# --- BrandConsistency ---

class BrandConsistencyInput(BaseModel):
    clinic_name: str | None = None
    mainpage: str | None = None
    instagram: str | None = None
    facebook: str | None = None
    youtube: str | None = None
    gangnam_unni: str | None = None


class BrandConsistencyOutput(BaseModel):
    brand_inconsistencies: list[BrandInconsistency]