app.py

import gradio as gr
import os
import uuid
import csv
from datetime import datetime

from services.resume_parser import extract_text
from services.scoring import compute_similarity, skill_score
from services.decision_engine import final_decision


LOG_FILE = "logs.csv"


def log_result(job_title, decision):
    file_exists = os.path.isfile(LOG_FILE)

    with open(LOG_FILE, "a", newline="", encoding="utf-8") as f:
        writer = csv.writer(f)

        if not file_exists:
            writer.writerow(["id", "date", "job_title", "decision"])

        writer.writerow([
            str(uuid.uuid4()),
            datetime.now().isoformat(),
            job_title,
            decision
        ])


def analyze(file, job_title, level):

    try:

        file_path = file.name

        resume_text = extract_text(file_path)

        sim_score = compute_similarity(resume_text, job_title)

        skills = skill_score(resume_text, job_title)

        decision = final_decision(sim_score, skills, level)

        result = {
            "similarity_score": sim_score,
            "skill_score": skills,
            "job_title": job_title,
            "level": level,
            "decision": decision
        }

        log_result(job_title, decision)

        os.remove(file_path)

        return result

    except Exception as e:
        return {"error": str(e)}


demo = gr.Interface(

    fn=analyze,

    inputs=[
        gr.File(label="Upload Resume (PDF/DOCX)"),
        gr.Textbox(label="Job Title"),
        gr.Dropdown(
            ["Entry", "Junior", "Mid", "Senior"],
            label="Job Level",
            value="Junior"
        )
    ],

    outputs="json",

    title="AI Resume Screening System",

    description="Upload a resume and evaluate its compatibility with a job role using AI screening."
)

demo.launch()