from datetime import datetime
from typing import Optional
from pydantic import BaseModel, Field


# --- Session Rating Schemas ---

class SessionRatingCreate(BaseModel):
    rating: int = Field(..., ge=1, le=5)
    comment: Optional[str] = Field(None, max_length=500)


class SessionRatingResponse(BaseModel):
    id: str
    session_id: str
    rating: int
    comment: Optional[str]
    created_at: datetime

    model_config = {"from_attributes": True}


class FlowRatingItem(BaseModel):
    """Anonymous feedback item — no user_name for privacy."""
    rating: int
    comment: Optional[str]
    created_at: datetime


# --- Step Feedback Schema ---

class StepFeedbackCreate(BaseModel):
    session_id: str
    was_helpful: bool


# --- Analytics Response Schemas ---

class OutcomeBreakdown(BaseModel):
    resolved: int = 0
    escalated: int = 0
    workaround: int = 0
    unresolved: int = 0


class AnalyticsSummary(BaseModel):
    total_sessions: int
    completed_sessions: int
    completion_rate: float
    median_duration_minutes: float
    active_engineers: int = 0
    outcome_breakdown: OutcomeBreakdown


class TimeSeriesPoint(BaseModel):
    date: str
    sessions: int = 0
    resolved: int = 0
    escalated: int = 0
    workaround: int = 0
    unresolved: int = 0


class TopFlow(BaseModel):
    tree_id: str
    name: str
    sessions: int
    completion_rate: float
    median_duration_minutes: float
    avg_csat: Optional[float] = None


class TopEngineer(BaseModel):
    user_id: str
    name: str
    sessions: int
    completion_rate: float
    median_duration_minutes: float


class TeamAnalyticsResponse(BaseModel):
    summary: AnalyticsSummary
    time_series: list[TimeSeriesPoint]
    top_flows: list[TopFlow]
    top_engineers: list[TopEngineer]


class PersonalAnalyticsResponse(BaseModel):
    summary: AnalyticsSummary
    time_series: list[TimeSeriesPoint]
    top_flows: list[TopFlow]


class StepFeedbackSummary(BaseModel):
    node_id: str
    node_title: str
    helpful_yes: int
    helpful_no: int
    helpful_rate: float
    visit_count: int = 0
    dropoff_count: int = 0
    dropoff_rate: float = 0.0


class FlowAnalyticsResponse(BaseModel):
    summary: AnalyticsSummary
    avg_csat: Optional[float]
    total_ratings: int
    time_series: list[TimeSeriesPoint]
    step_feedback: list[StepFeedbackSummary]
    recent_comments: list[FlowRatingItem]