app/models.py

"""Pydantic schemas for request / response models."""

from __future__ import annotations

from typing import Dict, List, Optional

from pydantic import BaseModel, Field

from app.config import cfg


# ═══════════════════════════════════════════════════════════════════════
# CORE SCHEMAS
# ═══════════════════════════════════════════════════════════════════════
class ChatMessage(BaseModel):
    role:    str = Field(..., pattern="^(system|user|assistant)$")
    content: str = Field(..., min_length=1, max_length=4000)


class AnalysisResult(BaseModel):
    keyword:     str
    kw_stemmed:  str
    total_count: int
    by_surah:    Dict[int, Dict]
    examples:    List[dict]


class SourceItem(BaseModel):
    source:  str
    type:    str
    grade:   Optional[str] = None
    arabic:  str
    english: str
    _score:  float


class AskResponse(BaseModel):
    question:   str
    answer:     str
    thinking:   Optional[str] = None
    language:   str
    intent:     str
    analysis:   Optional[AnalysisResult] = None
    sources:    List[SourceItem]
    top_score:  float
    latency_ms: int


class HadithVerifyResponse(BaseModel):
    query:      str
    found:      bool
    collection: Optional[str] = None
    grade:      Optional[str] = None
    reference:  Optional[str] = None
    arabic:     Optional[str] = None
    english:    Optional[str] = None
    latency_ms: int


# ═══════════════════════════════════════════════════════════════════════
# OPENAI-COMPATIBLE SCHEMAS
# ═══════════════════════════════════════════════════════════════════════
class ChatCompletionMessage(BaseModel):
    role:              str = Field(..., description="Message role: system, user, or assistant")
    content:           str = Field(..., description="Message content")
    reasoning_content: Optional[str] = Field(None, description="Model's internal reasoning/thinking")


class ChatCompletionRequest(BaseModel):
    model:       str             = Field(default="QModel", description="Model name")
    messages:    List[ChatCompletionMessage] = Field(..., description="Messages")
    temperature: Optional[float] = Field(default=cfg.TEMPERATURE, ge=0.0, le=2.0)
    top_p:       Optional[float] = Field(default=1.0, ge=0.0, le=1.0)
    max_tokens:  Optional[int]   = Field(default=cfg.MAX_TOKENS, ge=1, le=8000)
    top_k:       Optional[int]   = Field(default=5, ge=1, le=20, description="Islamic sources to retrieve")
    stream:      Optional[bool]  = Field(default=False, description="Enable streaming responses")


class ChatCompletionChoice(BaseModel):
    index:         int
    message:       ChatCompletionMessage
    finish_reason: str = "stop"


class ChatCompletionResponse(BaseModel):
    id:         str
    object:     str = "chat.completion"
    created:    int
    model:      str
    choices:    List[ChatCompletionChoice]
    usage:      dict
    x_metadata: Optional[dict] = None


class ModelInfo(BaseModel):
    id:         str
    object:     str = "model"
    created:    int
    owned_by:   str = "elgendy"
    permission: List[dict] = Field(default_factory=list)
    root:       Optional[str] = None
    parent:     Optional[str] = None


class ModelsListResponse(BaseModel):
    object: str = "list"
    data:   List[ModelInfo]


# ═══════════════════════════════════════════════════════════════════════
# NEW ENDPOINT SCHEMAS
# ═══════════════════════════════════════════════════════════════════════
class VerseItem(BaseModel):
    surah_number:              Optional[int] = None
    surah_name_ar:             str = ""
    surah_name_en:             str = ""
    surah_name_transliteration: str = ""
    ayah:                      Optional[int] = None
    arabic:                    str = ""
    english:                   str = ""
    transliteration:           str = ""
    tafsir_en:                 str = ""
    tafsir_ar:                 str = ""
    source:                    str = ""
    revelation_type:           str = ""
    score:                     Optional[float] = None


class HadithItem(BaseModel):
    collection:    str = ""
    reference:     str = ""
    hadith_number: Optional[int] = None
    chapter:       str = ""
    arabic:        str = ""
    english:       str = ""
    grade:         Optional[str] = None
    author:        str = ""
    score:         Optional[float] = None


class TextSearchResponse(BaseModel):
    query:   str
    count:   int
    results: List[dict]


class ChapterResponse(BaseModel):
    surah_number:              int
    surah_name_ar:             str
    surah_name_en:             str
    surah_name_transliteration: str
    revelation_type:           str
    total_verses:              int
    verses:                    List[dict]


class QuranAnalyticsResponse(BaseModel):
    total_verses_in_dataset: int
    total_surahs:            int
    meccan_surahs:           int
    medinan_surahs:          int
    surahs:                  List[dict]


class HadithAnalyticsResponse(BaseModel):
    total_hadiths: int
    collections:   List[dict]
    grade_summary: dict


class WordFrequencyResponse(BaseModel):
    keyword:     str
    kw_stemmed:  str
    total_count: int
    by_surah:    dict
    examples:    List[dict]


class RootAnalysisResponse(BaseModel):
    root:        str
    total_count: int
    by_surah:    dict
    examples:    List[dict]