from fastapi import APIRouter, Depends, Request
from app.api.deps import get_api_key
from app.core.limiter import limiter
from app.core.config import settings
from pydantic import BaseModel

router = APIRouter()

class ChatRequest(BaseModel):
    prompt: str
    context: str = ""

@router.post("/chat")
@limiter.limit(settings.RATE_LIMIT)
async def story_chat(
    request: Request,
    chat_data: ChatRequest,
    api_key: str = Depends(get_api_key)
):
    # This is where you would call your LLM (OpenAI, Anthropic, etc.)
    # For now, we return a mock response
    return {
        "status": "success",
        "response": f"Processed prompt: {chat_data.prompt}",
        "metadata": {
            "characters_received": len(chat_data.prompt),
            "context_length": len(chat_data.context)
        }
    }

@router.get("/health")
async def health_check():
    return {"status": "healthy"}