app.py

import gradio as gr
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM

# نموذج أقوى
MODEL = "google/flan-t5-xl"
tokenizer = AutoTokenizer.from_pretrained(MODEL)
model = AutoModelForSeq2SeqLM.from_pretrained(MODEL)

# مولد النصوص
def generate_content(topic, style_choice, lang_choice, length_choice):
    # اختيار الطول
    if length_choice == "Short":
        max_len = 200
    elif length_choice == "Medium":
        max_len = 400
    else:  # Long
        max_len = 700

    # بناء البرومبت
    if lang_choice == "Arabic":
        if style_choice == "Blog Post (Descriptive)":
            prompt = f"اكتب مقالاً احترافياً بأسلوب شخصي عن: {topic}. ركز على التفاصيل والوصف الجذاب. اجعل النص منسقاً بفقرات."
        elif style_choice == "Social Media Post (Short & Catchy)":
            prompt = f"اكتب منشوراً قصيراً وجذاباً عن: {topic}. أضف إيموجي مناسبة واقترح 3 هاشتاغات."
        else:  # Video Script
            prompt = f"اكتب سيناريو فيديو احترافي عن: {topic}. اجعل الأسلوب قصصي وسردي مع تقسيمه إلى مشاهد."
    else:  # English
        if style_choice == "Blog Post (Descriptive)":
            prompt = f"Write a professional blog post about: {topic}. Make it personal and descriptive, well-structured in paragraphs."
        elif style_choice == "Social Media Post (Short & Catchy)":
            prompt = f"Write a short and catchy social media post about: {topic}, add emojis and suggest 3 hashtags."
        else:  # Video Script
            prompt = f"Write a professional video script about: {topic}. Make it emotional, story-driven, and divided into scenes."

    try:
        inputs = tokenizer(prompt, return_tensors="pt")
        outputs = model.generate(
            **inputs,
            max_length=max_len,
            num_beams=5,
            temperature=0.8,
            early_stopping=True
        )
        content = tokenizer.decode(outputs[0], skip_special_tokens=True)

        return content
    except Exception as e:
        return f"⚠️ Error: {str(e)}"

# واجهة Gradio
with gr.Blocks(theme="default") as iface:
    gr.Markdown("## ✨ AI Content Pack - Create Blogs, Posts & Scripts in Seconds")
    
    with gr.Row():
        topic = gr.Textbox(label="Topic / الموضوع", placeholder="مثال: رحلتي إلى باريس وتجربة برج إيفل...")
    
    with gr.Row():
        style_choice = gr.Radio(
            ["Blog Post (Descriptive)", "Social Media Post (Short & Catchy)", "Video Script (Storytelling)"],
            label="Style / نوع المحتوى"
        )
        lang_choice = gr.Radio(["Arabic", "English"], label="Language / اللغة")
        length_choice = gr.Radio(["Short", "Medium", "Long"], label="Length / طول النص", value="Medium")

    output = gr.Textbox(label="Generated Content", lines=20)
    download_btn = gr.File(label="Download", file_types=[".txt"])

    def save_file(content):
        with open("generated.txt", "w", encoding="utf-8") as f:
            f.write(content)
        return "generated.txt"

    btn = gr.Button("🚀 Generate Content")
    btn.click(fn=generate_content, inputs=[topic, style_choice, lang_choice, length_choice], outputs=output)
    output.change(fn=save_file, inputs=output, outputs=download_btn)

if __name__ == "__main__":
    iface.launch()