app.py

import os
import sys
import pymongo
from fastapi.middleware.cors import CORSMiddleware
from fastapi import FastAPI, File, UploadFile, Request
from uvicorn import run as app_run
from fastapi.responses import Response
from starlette.responses import RedirectResponse
import pandas as pd
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_object
from networksecurity.constant.training_pipeline import DATA_INGESTION_COLLECTION_NAME
from networksecurity.constant.training_pipeline import DATA_INGESTION_DATABASE_NAME
from networksecurity.utils.ml_utils.model.estimator import NetworkModel
import certifi
ca = certifi.where()

from dotenv import load_dotenv
load_dotenv
mongo_url = os.getenv("MONGO_DB_URL")

client = pymongo.MongoClient(mongo_url, tlsCAFILE=ca)

database = client[DATA_INGESTION_DATABASE_NAME]
collection = client[DATA_INGESTION_COLLECTION_NAME]


app = FastAPI()
origins = ["*"]

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

from fastapi.templating import Jinja2Templates
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 successfull")
    except Exception as e:
        raise NetworkSecurityException(e,sys)
    
@app.get("/predict")
async def predict_route(request:Request, file: UploadFile=File(...)):
    try:
        df= pd.read_csv(file.file)
        preprocessor = load_object("final_model/preprocessor.pkl")
        final_model = load_object("final_model/model.pkl")
        network_model = NetworkModel(preprocessor=preprocessor, model=final_model)
        print(df.iloc[0])
        y_pred = network_model.predict(df)
        print(y_pred)
        df["predicted_column"]=y_pred
        print(df["predicted_column"])
        df.to_csv("prediction_output/output.csv")
        table_html = df.to_html(classes='table table-striped')
        return templates.TemplateResponse("table.html", {"request": request, "table":table_html})
    except Exception as e:
        raise NetworkSecurityException(e,sys)


if __name__ =="__main__":
    app_run(app,host="0.0.0.0", port=8000)