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


class MessageRequest(BaseModel):
    question: str = Field(..., min_length=1, max_length=2000, description="User question")
    conversation_id: Optional[str] = Field(None, description="Conversation ID for context")


class SourceDocument(BaseModel):
    content: str
    source: str
    page: Optional[int] = None
    chunk_id: Optional[str] = None


class MessageResponse(BaseModel):
    answer: str
    conversation_id: str
    sources: List[SourceDocument] = []
    timestamp: str = Field(default_factory=lambda: datetime.utcnow().isoformat() + "Z")


class IngestRequest(BaseModel):
    metadata: Optional[dict] = None


class IngestResponse(BaseModel):
    message: str
    documents_processed: int
    chunks_created: int
    filename: str


class ConversationMessage(BaseModel):
    role: str  # "user" or "assistant"
    content: str
    sources: List[SourceDocument] = []
    timestamp: str = Field(default_factory=lambda: datetime.utcnow().isoformat() + "Z")


class Conversation(BaseModel):
    id: str = Field(default_factory=lambda: str(uuid.uuid4()))
    title: str = "New Conversation"
    messages: List[ConversationMessage] = []
    created_at: str = Field(default_factory=lambda: datetime.utcnow().isoformat() + "Z")
    updated_at: str = Field(default_factory=lambda: datetime.utcnow().isoformat() + "Z")


class ConversationListItem(BaseModel):
    id: str
    title: str
    message_count: int
    created_at: str
    updated_at: str


class HealthResponse(BaseModel):
    status: str = "healthy"
    version: str = "1.0.0"
    environment: str = "development"


class VectorStatsResponse(BaseModel):
    total_vectors: int = 0
    total_documents: int = 0
    index_name: str = ""
    dimension: int = 384
    error: Optional[str] = None


class DocumentInfo(BaseModel):
    name: str
    size: int  # bytes
    type: str  # PDF, Markdown, etc.
    uploaded_at: str