app.py

import os
import gradio as gr
import requests
from huggingface_hub import InferenceClient

# 🔑 Load API keys from environment
GEMINI_API_KEY = os.getenv("GOOGLE_AI_API_KEY")
HF_API_KEY = os.getenv("HUGGINGFACE_API_KEY")  # optional for private HF models

# Hugging Face Client (public model as fallback)
hf_client = InferenceClient(model="HuggingFaceH4/zephyr-7b-beta")

# ========== AI Functions ==========
def generate_with_huggingface(resume_text, job_desc):
    prompt = f"""
    You are an expert career assistant. 
    Resume:
    {resume_text}

    Job Description:
    {job_desc}

    Task:
    1. Create a customized resume version highlighting relevant skills and achievements.
    2. Write a professional cover letter tailored for this role.
    """
    response = hf_client.text_generation(
        prompt,
        max_new_tokens=800,
        temperature=0.7,
    )
    return response

def call_gemini_api(resume_text, job_desc):
    if not GEMINI_API_KEY:
        return None

    prompt = f"""
    You are an expert career assistant. 
    Resume:
    {resume_text}

    Job Description:
    {job_desc}

    Task:
    1. Create a customized resume version highlighting relevant skills and achievements.
    2. Write a professional cover letter tailored for this role.
    """
    url = "https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash:generateContent"
    headers = {
        "Content-Type": "application/json",
        "X-goog-api-key": GEMINI_API_KEY,
    }
    data = {"contents": [{"parts": [{"text": prompt}]}]}
    try:
        response = requests.post(url, headers=headers, json=data, timeout=30)
        result = response.json()
        if "candidates" in result:
            return result["candidates"][0]["content"]["parts"][0]["text"]
        else:
            return None
    except Exception:
        return None

def generate_documents(resume_text, job_desc):
    gemini_output = call_gemini_api(resume_text, job_desc)
    if gemini_output:
        output_text = gemini_output
        source = "✅ Google Gemini"
    else:
        output_text = generate_with_huggingface(resume_text, job_desc)
        source = "⚠️ Gemini failed → Using Hugging Face LLM"

    # Split Resume + Cover Letter
    if "Cover Letter" in output_text:
        parts = output_text.split("Cover Letter")
        resume_out = parts[0].strip()
        cover_letter_out = "Cover Letter" + parts[1].strip()
    else:
        resume_out = output_text
        cover_letter_out = ""

    return resume_out + f"\n\n(Source: {source})", cover_letter_out


# ========== Custom CSS ==========
custom_css = """
body {
    background: linear-gradient(-45deg, #ff9a9e, #fad0c4, #a1c4fd, #c2e9fb);
    background-size: 400% 400%;
    animation: gradientBG 12s ease infinite;
    font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif;
}
@keyframes gradientBG {
    0% {background-position: 0% 50%;}
    50% {background-position: 100% 50%;}
    100% {background-position: 0% 50%;}
}
.gradio-container {
    animation: fadeIn 1.2s ease-in-out;
}
textarea, input {
    border-radius: 14px !important;
    box-shadow: 0px 4px 10px rgba(0,0,0,0.2) !important;
    padding: 10px !important;
}
button {
    background: linear-gradient(90deg, #667eea, #764ba2) !important;
    color: white !important;
    font-weight: bold !important;
    border-radius: 25px !important;
    transition: all 0.3s ease-in-out;
    padding: 12px 20px !important;
}
button:hover {
    transform: scale(1.07);
    box-shadow: 0px 6px 15px rgba(0,0,0,0.3);
}
@keyframes fadeIn {
    from {opacity: 0; transform: translateY(25px);}
    to {opacity: 1; transform: translateY(0);}
}
"""

# ========== Gradio UI ==========
with gr.Blocks(css=custom_css, title="AI Resume & Cover Letter Generator") as demo:
    gr.Markdown("<h1 style='text-align:center; color:white;'>📄 AI Resume & Cover Letter Generator</h1>")
    gr.Markdown("<p style='text-align:center; color:white; font-size:18px;'>Paste your Resume + Job Description → Get a Customized Resume & Cover Letter</p>")

    with gr.Row():
        resume_input = gr.Textbox(label="📑 Paste Resume / LinkedIn profile", lines=10, placeholder="Paste your resume text here...")
        job_input = gr.Textbox(label="💼 Paste Job Description", lines=8, placeholder="Paste job description here...")

    generate_btn = gr.Button("✨ Generate Resume & Cover Letter")

    with gr.Tabs():
        with gr.Tab("🎯 Customized Resume"):
            resume_output = gr.Textbox(label="Customized Resume", lines=20)
        with gr.Tab("✍️ Cover Letter"):
            cover_output = gr.Textbox(label="Cover Letter", lines=20)

    generate_btn.click(generate_documents, inputs=[resume_input, job_input], outputs=[resume_output, cover_output])

demo.launch()