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File size: 1,420 Bytes
5e6aba8 a10afeb 5e6aba8 a10afeb 5e6aba8 a10afeb a844efb a10afeb 5e6aba8 a844efb 5e6aba8 a10afeb 5e6aba8 a10afeb 5e6aba8 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 | from __future__ import annotations
import os
from fastapi import Depends, FastAPI, HTTPException, Security
from fastapi.middleware.cors import CORSMiddleware
from fastapi.security import HTTPAuthorizationCredentials, HTTPBearer
from pydantic import BaseModel
from inference.predict import predict
API_KEY = os.environ.get("API_KEY", "")
CORS_ORIGINS = os.environ.get("CORS_ORIGINS", "http://localhost:3001").split(",")
app = FastAPI(title="M2Predict API")
app.add_middleware(
CORSMiddleware,
allow_origins=CORS_ORIGINS,
allow_methods=["POST"],
allow_headers=["Content-Type", "Authorization"],
)
security = HTTPBearer()
def verify_api_key(
credentials: HTTPAuthorizationCredentials = Security(security),
) -> str:
if not API_KEY:
raise HTTPException(status_code=500, detail="API_KEY not configured")
if credentials.credentials != API_KEY:
raise HTTPException(status_code=403, detail="Invalid API key")
return credentials.credentials
class PredictRequest(BaseModel):
code_postal: str
surface_reelle_bati: float
nombre_pieces_principales: int
type_local: str
@app.post("/predict")
def predict_endpoint(
req: PredictRequest,
model_version: str = "v1_rf_te",
_key: str = Depends(verify_api_key),
):
result = predict(req.model_dump(), model_version=model_version)
return result
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