app.py

import sys
import os
import certifi
from dotenv import load_dotenv
import pymongo
from fastapi.middleware.cors import CORSMiddleware
from fastapi import FastAPI, File, UploadFile, Request
from fastapi.templating import Jinja2Templates
from uvicorn import run as app_run
from fastapi.responses import Response
from starlette.responses import RedirectResponse
import pandas as pd


ca = certifi.where()
load_dotenv()
mongo_db_url = os.getenv("MONGODB_URL_KEY")
print(mongo_db_url)


from networksecurity.exception.exception import NetworkSecurityException
from networksecurity.logging.logger import logging
from networksecurity.pipeline.training_pipeline import TrainingPipeline
from networksecurity.utils.main_utils.utils import load_numpy_object
from networksecurity.utils.ml_utils.model.estimator import NetworkModel
from networksecurity.constant.training_pipeline import (
    DATA_INGESTION_COLLECTION_NAME,
    DATA_INGESTION_DATABASE_NAME,
)


client = pymongo.MongoClient(mongo_db_url, tlsCAFile=ca)
database = client[DATA_INGESTION_DATABASE_NAME]
collection = database[DATA_INGESTION_COLLECTION_NAME]


app = FastAPI()
origins = ["*"]
app.add_middleware(
    CORSMiddleware,
    allow_origins= origins,
    allow_credentials=True,
    allow_methods=["*"],
    allow_headers=["*"],
)

templates = Jinja2Templates(directory= "./templates")

@app.get("/", tags = ["authentication"])
async def index():
    return RedirectResponse(url="/docs")

@app.get("/train")
async def train_route():
    try:
        train_pipeline = TrainingPipeline()
        train_pipeline.run_pipeline()
        return Response("Training is successful")
    except Exception as e:
        raise NetworkSecurityException(e,sys)


@app.post("/predict")
async def predict_route(request: Request, file: UploadFile = File(...)):
    try:
        
        df = pd.read_csv(file.file)
        print(df)

        
        preprocessor = load_numpy_object("final_model/preprocessor.pkl")
        final_model = load_numpy_object("final_model/model.pkl")
        network_model = NetworkModel(preprocessor=preprocessor, model=final_model)

        
        y_pred = network_model.predict(df)
        print(y_pred)

        
        df['predicted_column'] = y_pred
        
        df.to_csv('prediction_output/output.csv', index=False)

        
        table_html = df.to_html(classes="table table-striped")

        
        return templates.TemplateResponse("table.html", {"request" : request, "table":table_html})

    except Exception as e:
        logging.error(f"Error in prediction route: {str(e)}")
        raise NetworkSecurityException(e, sys)


if __name__ == "__main__":
    app_run(app, host="localhost", port=8000)