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| # src/models/chat.py | |
| from pydantic import BaseModel | |
| from typing import Optional, List, Dict | |
| from datetime import datetime | |
| from .base import ChatMetadata | |
| from pydantic import BaseModel, validator, Field | |
| from typing import Optional | |
| from config.config import settings | |
| 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): | |
| rating: int = Field(..., ge=0, le=settings.MAX_RATING) | |
| feedback: Optional[str] = None | |
| def validate_rating(cls, v): | |
| if v < 0 or v > settings.MAX_RATING: | |
| raise ValueError(f'Rating must be between 0 and {settings.MAX_RATING}') | |
| return v | |
| def format_rating(self) -> str: | |
| """Format rating as a fraction of maximum""" | |
| return f"{self.rating}/{settings.MAX_RATING}" | |
| 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 |