Delete app.py

app.py

@@ -1,78 +0,0 @@
-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()