"""Pydantic models for request/response schemas."""
from pydantic import BaseModel, Field
from typing import Optional, List, Dict, Any
from datetime import datetime
from .enums import ModelName, AgentType


# ============ Auth Models ============

class TokenRequest(BaseModel):
    """Request for JWT token (can be extended with username/password)."""
    # Pour l'instant, on pourrait juste retourner un token
    # Plus tard, on peut ajouter username/password
    pass


class TokenResponse(BaseModel):
    """JWT token response."""
    access_token: str
    token_type: str = "bearer"
    expires_in: int


# ============ Completion Models ============

class CompletionRequest(BaseModel):
    """Request for text completion."""
    message: str = Field(..., description="User message to complete")
    model: ModelName = Field(default=ModelName.GPT_5_PRO, description="LLM model to use")
    agent_type: AgentType = Field(default=AgentType.SIMPLE, description="Agent type to use")
    stream: bool = Field(default=False, description="Enable streaming response")
    temperature: float = Field(default=0.7, ge=0.0, le=2.0, description="Sampling temperature")
    max_tokens: Optional[int] = Field(default=None, description="Maximum tokens to generate")
    conversation_history: Optional[List[Dict[str, str]]] = Field(
        default=None,
        description="Optional conversation history"
    )


class CompletionResponse(BaseModel):
    """Response for text completion (non-streaming)."""
    response: str
    model: str
    agent_type: str
    usage: Optional[Dict[str, Any]] = None
    metadata: Optional[Dict[str, Any]] = None


class StreamChunk(BaseModel):
    """Single chunk in streaming response."""
    content: str
    done: bool = False
    metadata: Optional[Dict[str, Any]] = None


# ============ Transcription Models ============

class TranscriptionResponse(BaseModel):
    """Response for audio transcription."""
    text: str
    language: Optional[str] = None
    duration: Optional[float] = None
    model: str = "whisper-1"


# ============ Model Info Models ============

class ModelInfo(BaseModel):
    """Information about an available model."""
    name: str
    provider: str
    description: Optional[str] = None
    supports_streaming: bool = True
    context_window: Optional[int] = None


class ModelsListResponse(BaseModel):
    """List of available models."""
    models: List[ModelInfo]
    total: int


class AgentInfo(BaseModel):
    """Information about an available agent."""
    type: AgentType
    name: str
    description: str
    available: bool = True


class AgentsListResponse(BaseModel):
    """List of available agents."""
    agents: List[AgentInfo]
    total: int


# ============ Error Models ============

class ErrorResponse(BaseModel):
    """Error response."""
    error: str
    detail: Optional[str] = None
    timestamp: datetime = Field(default_factory=datetime.utcnow)


# ============ Health Check ============

class HealthResponse(BaseModel):
    """Health check response."""
    status: str
    version: str
    timestamp: datetime = Field(default_factory=datetime.utcnow)