import gradio as gr
import pandas as pd
import traceback
from model import screen_resumes_backend


def process(job_description, files, model_option, threshold, gmail, password):

    try:
        if not job_description or len(job_description) < 20:
            return "❌ Job description too short", None, None

        # if email provided → use Gmail mode
        if gmail and password:
            results, report, zip_path = screen_resumes_backend(
                job_description,
                files=None,
                model_name=model_option,
                threshold=threshold,
                gmail=gmail,
                password=password
            )
        else:
            # file upload mode
            if not files:
                return "❌ Upload files or provide email", None, None

            results, report, zip_path = screen_resumes_backend(
                job_description,
                files,
                model_option,
                threshold
            )

        df = pd.DataFrame(results)

        return "✅ Process Completed", df, zip_path

    except Exception as e:
        return f"❌ Error: {str(e)}\n{traceback.format_exc()}", None, None


# ================= UI =================
with gr.Blocks(title="AI Resume Screener") as demo:

    gr.Markdown("# 🧠 AI Resume Screening System")

    job_desc = gr.Textbox(label="Job Description", lines=6)

    model = gr.Dropdown(
        ["Fast (MiniLM)", "Balanced (Recommended)", "High Accuracy"],
        value="Balanced (Recommended)"
    )

    threshold = gr.Slider(0.4, 0.9, value=0.6)

    # 🔥 NEW: EMAIL SECTION
    gr.Markdown("## 📧 Email Integration (Optional)")

    gmail = gr.Textbox(label="Gmail Address")
    password = gr.Textbox(label="App Password (NOT normal password)", type="password")

    gr.Markdown("OR Upload Files Below 👇")

    files = gr.File(file_count="multiple", label="Upload CVs (PDF/DOCX)")

    btn = gr.Button("Process")

    output_text = gr.Markdown()
    output_table = gr.DataFrame()
    download_zip = gr.File()

    btn.click(
        process,
        inputs=[job_desc, files, model, threshold, gmail, password],
        outputs=[output_text, output_table, download_zip]
    )

demo.launch()