app.py

import os
import openai
import gradio as gr
from bs4 import BeautifulSoup
import requests
import nest_asyncio
import asyncio

from playwright.sync_api import sync_playwright

nest_asyncio.apply()
openai.api_key = os.getenv("OPENAI_API_KEY")

# Synchronous version for HF Spaces compatibility
def extract_text_from_url(url):
    with sync_playwright() as pw:
        browser = pw.chromium.launch(headless=True)
        page = browser.new_page()
        page.goto(url, timeout=60000)
        page.wait_for_load_state('networkidle')
        content = page.content()
        browser.close()

    soup = BeautifulSoup(content, "html.parser")
    text = ' '.join(p.get_text(strip=True) for p in soup.find_all(['p', 'span', 'h1', 'h2', 'li']))
    return text[:4000]  # limit to 4000 characters

def extract_keywords(text):
    prompt = f"""
    Extract up to 10 concise, relevant SEO keywords suitable for an automotive advertisement from the following content:
    
    {text}

    Keywords:
    """
    response = openai.ChatCompletion.create(
        model="gpt-4",
        messages=[{"role": "user", "content": prompt}],
        temperature=0.6,
        max_tokens=100
    )
    keywords = response.choices[0].message.content.strip().split(',')
    return [kw.strip() for kw in keywords]

def generate_ad_copy(platform, keywords):
    prompt = f"""
    Create a compelling, SEO-optimized {platform} ad using these keywords: {', '.join(keywords)}. 
    Include a clear and enticing call-to-action.
    """
    response = openai.ChatCompletion.create(
        model="gpt-4",
        messages=[{"role": "user", "content": prompt}],
        temperature=0.7,
        max_tokens=300
    )
    return response.choices[0].message.content.strip()

def generate_ad_image(keywords):
    kw_str = ", ".join(keywords)
    image_prompt = f"Professional automotive social media ad featuring: {kw_str}. Bright visuals, luxury theme, with text overlay space."
    response = openai.Image.create(
        prompt=image_prompt,
        n=1,
        size="512x512"
    )
    image_url = response["data"][0]["url"]
    img_data = requests.get(image_url).content
    img_file = "generated_ad_image.png"
    with open(img_file, "wb") as f:
        f.write(img_data)
    return img_file

def main_workflow(input_mode, url_or_keywords):
    error = None
    # Step 1: Get keywords
    if input_mode == "URL":
        try:
            text = extract_text_from_url(url_or_keywords)
            keywords = extract_keywords(text)
        except Exception as e:
            return None, None, None, f"URL extraction error: {e}"
    else:
        keywords = [kw.strip() for kw in url_or_keywords.split(",") if kw.strip()]
        if not keywords:
            return None, None, None, "Please provide at least one keyword."

    # Step 2: Generate ad copies
    platforms = ["Facebook", "Instagram", "X (Twitter)", "Google Search"]
    ad_copies = {}
    for platform in platforms:
        ad_copies[platform] = generate_ad_copy(platform, keywords)
    
    # Step 3: Generate ad image
    try:
        image_path = generate_ad_image(keywords)
    except Exception as e:
        image_path = None
        error = f"Image generation error: {e}"

    # Step 4: Save ad copies to txt
    output_txt = "generated_ads.txt"
    with open(output_txt, "w", encoding="utf-8") as f:
        for platform, content in ad_copies.items():
            f.write(f"--- {platform} Ad Copy ---\n{content}\n\n")
    
    return keywords, ad_copies, image_path, error

def run_space(input_mode, url, keywords):
    url_or_keywords = url if input_mode == "URL" else keywords
    keywords, ad_copies, image_path, error = main_workflow(input_mode, url_or_keywords)
    ad_previews = ""
    if ad_copies:
        for platform, ad in ad_copies.items():
            ad_previews += f"### {platform}\n{ad}\n\n"
    return (
        keywords,
        ad_previews,
        image_path,
        "generated_ads.txt" if ad_copies else None,
        error
    )

with gr.Blocks() as demo:
    gr.Markdown("# 🚗 Auto Ad Generator\nPaste a car listing URL **or** enter your own keywords, then preview AI-generated ads for each social media platform, plus an auto-generated image!")
    input_mode = gr.Radio(["URL", "Keywords"], value="URL", label="Input Type")
    url_input = gr.Textbox(label="Listing URL", placeholder="https://www.cars.com/listing/...", visible=True)
    kw_input = gr.Textbox(label="Manual Keywords (comma separated)", placeholder="e.g. BMW, used car, sunroof", visible=False)
    submit_btn = gr.Button("Generate Ads")

    gr.Markdown("## Keywords")
    kw_out = gr.JSON(label="Extracted/Provided Keywords")

    gr.Markdown("## Ad Copy Previews")
    ad_out = gr.Markdown(label="Ad Copy Preview")

    gr.Markdown("## Generated Ad Image")
    img_out = gr.Image(label="Generated Ad Image", type="filepath")

    gr.Markdown("## Download Ad Copies")
    file_out = gr.File(label="Download TXT")

    err_out = gr.Textbox(label="Errors", interactive=False)

    def show_hide_fields(choice):
        return (
            gr.update(visible=choice == "URL"),
            gr.update(visible=choice == "Keywords"),
        )

    input_mode.change(show_hide_fields, input_mode, [url_input, kw_input])

    submit_btn.click(
        run_space,
        inputs=[input_mode, url_input, kw_input],
        outputs=[kw_out, ad_out, img_out, file_out, err_out]
    )

demo.launch()