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"""Server that will listen for GET requests from the client.""" | |
from fastapi import FastAPI | |
from joblib import load | |
from concrete.ml.deployment import FHEModelServer | |
from pydantic import BaseModel | |
import base64 | |
from pathlib import Path | |
current_dir = Path(__file__).parent | |
# Load the model | |
fhe_model = FHEModelServer(Path.joinpath(current_dir, "sentiment_fhe_model/deployment")) | |
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!"} | |
def predict_sentiment(query: PredictRequest): | |
encrypted_encoding = base64.b64decode(query.encrypted_encoding) | |
evaluation_key = base64.b64decode(query.evaluation_key) | |
prediction = fhe_model.run(encrypted_encoding, evaluation_key) | |
# Encode base64 the prediction | |
encoded_prediction = base64.b64encode(prediction).decode() | |
return {"encrypted_prediction": encoded_prediction} |