romanbredehoft-zama's picture
Update the requirements, fix the notebook and improve the readme
"""Server that will listen for GET requests from the client."""
from fastapi import FastAPI
from joblib import load
from import FHEModelServer
from pydantic import BaseModel
import base64
from pathlib import Path
current_dir = Path(__file__).parent
# Load the model
fhe_model = FHEModelServer("deployment/sentiment_fhe_model")
class PredictRequest(BaseModel):
evaluation_key: str
encrypted_encoding: str
# Initialize an instance of FastAPI
app = FastAPI()
# Define the default route
def root():
return {"message": "Welcome to Your Sentiment Classification FHE Model Server!"}"/predict_sentiment")
def predict_sentiment(query: PredictRequest):
encrypted_encoding = base64.b64decode(query.encrypted_encoding)
evaluation_key = base64.b64decode(query.evaluation_key)
prediction =, evaluation_key)
# Encode base64 the prediction
encoded_prediction = base64.b64encode(prediction).decode()
return {"encrypted_prediction": encoded_prediction}