# src/models/chat.py
from pydantic import BaseModel
from typing import Optional, List, Dict
from datetime import datetime
from .base import ChatMetadata

class ChatRequest(BaseModel):
    """Request model for chat endpoint"""
    query: str
    llm_provider: str = 'openai'
    max_context_docs: int = 3
    temperature: float = 0.7
    stream: bool = False
    conversation_id: Optional[str] = None

class ChatResponse(ChatMetadata):
    """Response model for chat endpoint"""
    response: str
    context: Optional[List[str]] = None
    sources: Optional[List[Dict[str, str]]] = None
    relevant_doc_scores: Optional[List[float]] = None

class FeedbackRequest(BaseModel):
    """Request model for feedback endpoint"""
    rating: int
    feedback: Optional[str] = None

class SummarizeRequest(BaseModel):
    """Request model for summarize endpoint"""
    conversation_id: str
    include_metadata: bool = True

class SummaryResponse(BaseModel):
    """Response model for summarize endpoint"""
    summary: str
    key_insights: Dict
    metadata: Optional[Dict] = None