"""Pydantic request/response models for the FastAPI layer."""
from __future__ import annotations

from typing import List, Optional

from pydantic import BaseModel, Field


# ---------------------------------------------------------------------------
# Shared
# ---------------------------------------------------------------------------

class ProductOut(BaseModel):
    image_id: str
    image_url: Optional[str] = None
    image_urls: List[str] = Field(default_factory=list)
    brand: str
    product_name: str
    title: Optional[str] = None
    category: Optional[str] = None
    description: Optional[str] = None
    price_range: Optional[str] = None
    size_variants: List[str] = Field(default_factory=list)
    providers: List[str] = Field(default_factory=list)
    highlights: List[str] = Field(default_factory=list)
    nutrients: List[str] = Field(default_factory=list)
    fssai_license: Optional[str] = None
    product_sku: Optional[str] = None
    sku_source: Optional[str] = None
    hsn_code: Optional[str] = None
    final_selling_price: Optional[float] = None
    selling_price: Optional[float] = None
    barcode: Optional[str] = None
    barcode_type: Optional[str] = None


class SourceProductOut(BaseModel):
    image_id: str
    image_url: Optional[str] = None
    image_urls: List[str] = Field(default_factory=list)
    brand: str
    product_name: str
    title: Optional[str] = None
    category: Optional[str] = None
    description: Optional[str] = None
    price_range: Optional[str] = None
    size_variants: List[str] = Field(default_factory=list)
    providers: List[str] = Field(default_factory=list)
    highlights: List[str] = Field(default_factory=list)
    nutrients: List[str] = Field(default_factory=list)
    fssai_license: Optional[str] = None
    product_sku: Optional[str] = None
    sku_source: Optional[str] = None
    hsn_code: Optional[str] = None
    final_selling_price: Optional[float] = None
    selling_price: Optional[float] = None
    barcode: Optional[str] = None
    barcode_type: Optional[str] = None
    similarity: float


# ---------------------------------------------------------------------------
# Health
# ---------------------------------------------------------------------------

class AuthConfigOut(BaseModel):
    """
    The effective auth configuration, reported by /api/health.

    Unauthenticated on purpose. The failure this exists to diagnose is "nobody
    can sign in", so anything gated behind an admin token is unreachable
    exactly when it is needed. Nothing here is a secret: the admin username is
    already the documented one, allow_any_login=true is a fact an operator
    urgently needs (and an attacker discovers with a single login attempt
    anyway), and the fingerprint is a truncated hash of a salted digest, not a
    password. What it buys is a one-command answer to "is this deployment
    running the config I think it is?" - compare the fingerprint here against
    the one printed by scripts/make_auth_secrets.py --fingerprint.
    """

    enabled: bool
    allow_any_login: bool
    admin_username: str
    password_hash_valid: bool
    password_hash_iterations: Optional[int] = None
    password_hash_fingerprint: str
    # "process-env" | "env-file" | "default" - which one actually won.
    admin_username_source: str
    password_hash_source: str


class HealthOut(BaseModel):
    status: str
    database: bool
    ollama: bool
    ollama_model: str
    embeddings_model: str
    auth: AuthConfigOut


# ---------------------------------------------------------------------------
# Brands / catalog browsing
# ---------------------------------------------------------------------------

class BrandsOut(BaseModel):
    brands: List[str]


class BrandCardOut(BaseModel):
    """A brand as shown on the home page card grid.

    `name` is the same string GET /api/brands returns, so the frontend can
    pass it straight back to /api/brands/{brand}/products.
    """
    name: str
    slug: str
    product_count: int
    category_count: int
    categories: List[str] = Field(default_factory=list)
    image_url: Optional[str] = None
    initials: str


class BrandCardsOut(BaseModel):
    total_brands: int
    total_products: int
    brands: List[BrandCardOut]


class CategoriesOut(BaseModel):
    brand: str
    categories: List[str]


class ProductListOut(BaseModel):
    brand: str
    total: int
    limit: int
    offset: int
    products: List[ProductOut]


class AllProductsOut(BaseModel):
    total: int
    limit: int
    offset: int
    products: List[ProductOut]


# ---------------------------------------------------------------------------
# Semantic search (retrieval only, no LLM generation)
# ---------------------------------------------------------------------------

class SearchOut(BaseModel):
    query: str
    # Echoes the *request* param, as it always has. The brand inferred from the
    # query text goes in `detected_brand` instead - repurposing this field would
    # break any consumer reading it as "the filter I sent".
    brand: Optional[str] = None
    results: List[SourceProductOut]
    # Exact in brand_catalog mode. None in hybrid mode: the merge happens in
    # Python across N brand tables after per-table LIMITs, so there is no cheap
    # exact count and inventing one would misreport how much was found.
    total: Optional[int] = None
    limit: int = 0
    offset: int = 0
    match_mode: str = "hybrid"          # "brand_catalog" | "hybrid"
    detected_brand: Optional[str] = None
    detected_category: Optional[str] = None


class SuggestionOut(BaseModel):
    """One row in the search box's autocomplete dropdown."""
    type: str                           # "brand" | "category"
    value: str                          # what the search box / filter should use
    label: str                          # display text
    sublabel: Optional[str] = None      # e.g. "128 products"
    score: float = 0.0


class SuggestOut(BaseModel):
    query: str
    suggestions: List[SuggestionOut]


# ---------------------------------------------------------------------------
# RAG chat
# ---------------------------------------------------------------------------

class ChatTurn(BaseModel):
    role: str = Field(..., description="'user' or 'assistant'")
    content: str


class ChatRequest(BaseModel):
    query: str = Field(..., min_length=1, max_length=2000)
    brand: Optional[str] = Field(None, description="Restrict retrieval to a single brand")
    category: Optional[str] = Field(None, description="Restrict retrieval to a category")
    top_k: Optional[int] = Field(None, ge=1, le=15)
    history: Optional[List[ChatTurn]] = Field(default=None, description="Prior turns for follow-up questions")


class ChatResponseOut(BaseModel):
    answer: str
    query: str
    brand: Optional[str] = None
    detected_category: Optional[str] = Field(
        None, description="Product category auto-detected from the query and used to scope retrieval, if any"
    )
    sources: List[SourceProductOut]


# ---------------------------------------------------------------------------
# Catalog generation (admin/ingestion trigger)
# ---------------------------------------------------------------------------

class CatalogGenerateRequest(BaseModel):
    brand: str = Field(..., min_length=1, max_length=120)
    max_products: int = Field(50, ge=1, le=300)


class CatalogJobOut(BaseModel):
    job_id: str
    brand: str
    status: str
    detail: Optional[str] = None