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from fastapi import FastAPI | |
import os | |
import sys | |
src_directory = os.path.abspath(os.path.join(os.path.dirname(__file__), "../..", "src")) | |
sys.path.append(src_directory) | |
from modules import encoding_model | |
app = FastAPI() | |
def home(): | |
encoding_model.train_model() | |
return {"message": "Welcome to Prediction Hub"} | |
def display_prediction(message : str = "Hello World"): | |
try: | |
dimention = encoding_model.get_label(message) | |
return dimention | |
except Exception as e: | |
return f"Unable to fetch the data {e}" | |
# @app.post("/predict") | |
# def post_messsage(message, response_model ): | |
# logistic_regression.create_embending(message) |