"""
Pydantic models for the tiered content generation pipeline.
"""

from datetime import datetime
from enum import Enum
from typing import Optional, List, Dict, Any
from pydantic import BaseModel, Field


class ContentType(str, Enum):
    """Types of content the pipeline can generate."""
    ROUNDUP = "roundup"
    HOW_I_SOLVED = "how_i_solved"
    BUILD_LOG = "build_log"
    ESSAY = "essay"
    TUTORIAL = "tutorial"


class PipelineStage(str, Enum):
    """Stages in the content generation pipeline."""
    QUEUED = "queued"
    STRATEGY = "strategy"      # Llama 3.1 8B - brief + angle
    STRUCTURE = "structure"    # Qwen 2.5 7B - validate angle
    DRAFT = "draft"            # Phi-4 14B - full draft (~90s)
    SEO = "seo"                # Llama 3.1 8B - excerpt, tags, meta
    COMPLIANCE = "compliance"  # Python - strip banned words, flag dates
    COMPLETED = "completed"
    FAILED = "failed"
    CANCELLED = "cancelled"


class JobStatus(BaseModel):
    """Status of a pipeline job."""
    job_id: str
    status: PipelineStage
    stage_number: int = Field(default=0, description="Current stage number (0-5)")
    total_stages: int = Field(default=5)
    progress_percent: int = Field(default=0, ge=0, le=100)
    current_stage_name: Optional[str] = None
    estimated_seconds_remaining: Optional[int] = None
    started_at: Optional[datetime] = None
    completed_at: Optional[datetime] = None
    error: Optional[str] = None


class GenerateRequest(BaseModel):
    """Request to start content generation."""
    topic: str = Field(..., description="Topic or title idea")
    content_type: ContentType = Field(default=ContentType.HOW_I_SOLVED)
    outline: Optional[List[str]] = Field(default=None, description="Optional bullet points")
    context: Optional[str] = Field(default=None, description="Additional context or notes")


class GenerateResponse(BaseModel):
    """Immediate response after queuing generation."""
    job_id: str
    status: PipelineStage
    estimated_seconds: int = Field(default=90, description="Estimated total time")


class StrategyOutput(BaseModel):
    """Output from Stage 1: Strategy (Llama 3.1 8B)."""
    title: str
    angle: str
    target_audience: str
    key_takeaways: List[str]
    tone_notes: str


class StruggleFirstBrief(BaseModel):
    """V2: Struggle-first content brief."""
    struggle_angle: str = Field(..., description="What broke — the human moment")
    origin_story: str = Field(..., description="Why you were trying this")
    attempts: List[Dict[str, str]] = Field(..., description="Failed attempts with why they failed")
    the_moment: str = Field(..., description="The realization or breaking point")
    the_fix: str = Field(..., description="What worked, with caveats")
    reflection: str = Field(..., description="Honest reflection, not preachy")
    target_length: int = Field(default=1200)


class StructureOutput(BaseModel):
    """Output from Stage 2: Structure (Qwen 2.5 7B)."""
    validated: bool
    structure: List[str]  # Section headers / flow
    estimated_word_count: int
    concerns: Optional[List[str]] = None  # Issues with the angle


class DraftOutput(BaseModel):
    """Output from Stage 3: Draft (Phi-4 14B)."""
    content: str  # Full markdown draft
    word_count: int
    reading_time_minutes: int


class SEOOutput(BaseModel):
    """Output from Stage 4: SEO (Llama 3.1 8B)."""
    excerpt: str
    tags: List[str]
    meta_description: str
    keywords: List[str]


class ComplianceReport(BaseModel):
    """Output from Stage 5: Compliance filter."""
    replacements_made: int
    warnings: List[str]
    is_compliant: bool
    banned_words_found: List[str]
    dates_flagged: List[str]
    names_flagged: List[str]


class PipelineResult(BaseModel):
    """Final result of the complete pipeline."""
    title: str
    content: str
    excerpt: str
    tags: List[str]
    meta_description: str
    word_count: int
    reading_time_minutes: int
    compliance: ComplianceReport
    
    class Config:
        from_attributes = True


class JobDetailResponse(BaseModel):
    """Full job status including partial or complete results."""
    job_id: str
    status: PipelineStage
    stage_number: int
    total_stages: int
    progress_percent: int
    current_stage_name: Optional[str]
    estimated_seconds_remaining: Optional[int]
    started_at: Optional[datetime]
    completed_at: Optional[datetime]
    error: Optional[str]
    result: Optional[PipelineResult] = None
    partial_outputs: Optional[Dict[str, Any]] = Field(
        default=None,
        description="Intermediate outputs from completed stages"
    )


class CancelResponse(BaseModel):
    """Response after attempting to cancel a job."""
    job_id: str
    was_cancelled: bool
    message: str