Create. app.py

app.py

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+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+
+# Using a robust and stable model for the free tier
+MODEL = "google/flan-t5-large"
+tokenizer = AutoTokenizer.from_pretrained(MODEL)
+model = AutoModelForSeq2SeqLM.from_pretrained(MODEL)
+
+def generate_content(topic, lang_choice, content_type):
+    # Language selection based on user input
+    if lang_choice == "Arabic":
+        if content_type == "YouTube Script":
+            prompt = f"اكتب سكربت يوتيوب احترافي باللغة العربية عن: {topic}. اجعله دقيقة واحدة مع مقدمة جذابة ونقاط أساسية وخاتمة."
+        elif content_type == "YouTube Title":
+            prompt = f"أنشئ عنوان يوتيوب جذاب قصير لا يتجاوز 60 حرفاً عن: {topic}."
+        elif content_type == "Description + SEO":
+            prompt = f"اكتب وصف يوتيوب مُحسَّن للسيو عن: {topic} مع هاشتاغات مقترحة."
+        else: # LinkedIn Post
+            prompt = f"اكتب منشور لينكدإن احترافي قصير بالعربية عن: {topic}."
+    else: # English
+        if content_type == "YouTube Script":
+            prompt = f"Write a professional YouTube script in English about: {topic}. Make it one minute long with an engaging intro, key points, and a conclusion."
+        elif content_type == "YouTube Title":
+            prompt = f"Create a catchy YouTube title in English, under 60 characters, about: {topic}."
+        elif content_type == "Description + SEO":
+            prompt = f"Write an SEO-friendly YouTube description about: {topic} with suggested hashtags."
+        else: # LinkedIn Post
+            prompt = f"Write a professional LinkedIn post in English about: {topic}."
+
+    # Using try-except block to handle potential model errors
+    try:
+        inputs = tokenizer(prompt, return_tensors="pt")
+        outs = model.generate(**inputs, max_length=300)
+        return tokenizer.decode(outs[0], skip_special_tokens=True)
+    except Exception as e:
+        return f"حدث خطأ: {str(e)}. حاول مرة أخرى أو غيّر الموضوع."
+
+iface = gr.Interface(
+    fn=generate_content,
+    inputs=[
+        gr.Textbox(label="Topic"),
+        gr.Radio(["Arabic", "English"], label="Language"),
+        gr.Radio(["YouTube Script", "YouTube Title", "Description + SEO", "LinkedIn Post"], label="Content Type")
+    ],
+    outputs=gr.Textbox(label="Result")
+)
+
+if __name__ == "__main__":
+    iface.launch()