34 lines
901 B
Python
34 lines
901 B
Python
from fastapi import APIRouter, Depends, Request
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from app.api.deps import get_api_key
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from app.core.limiter import limiter
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from app.core.config import settings
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from pydantic import BaseModel
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router = APIRouter()
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class ChatRequest(BaseModel):
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prompt: str
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context: str = ""
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@router.post("/chat")
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@limiter.limit(settings.RATE_LIMIT)
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async def story_chat(
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request: Request,
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chat_data: ChatRequest,
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api_key: str = Depends(get_api_key)
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):
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# This is where you would call your LLM (OpenAI, Anthropic, etc.)
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# For now, we return a mock response
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return {
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"status": "success",
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"response": f"Processed prompt: {chat_data.prompt}",
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"metadata": {
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"characters_received": len(chat_data.prompt),
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"context_length": len(chat_data.context)
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}
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}
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@router.get("/health")
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async def health_check():
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return {"status": "healthy"}
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