Update app.py

app.py

@@ -1,32 +1,23 @@
 import gradio as gr
 from transformers import pipeline
 
-# Učitaj model za generisanje teksta
-generator = pipeline("text-generation", model="gpt2")
+# Inicijalizuj model za generisanje teksta
+text_generator = pipeline("text-generation", model="gpt-2")  # Možeš promeniti model ako želiš
 
-def generate_blog_post(topic, keywords):
-    prompt = f"Write an SEO-optimized blog post about {topic}. Include keywords: {', '.join(keywords)}."
-    
-    generated = generator(prompt, max_length=500, num_return_sequences=1)
-    return generated[0]['generated_text']
+def generate_blog_post(topic):
+    # Generiši tekst na osnovu zadatog teme
+    response = text_generator(topic, max_length=300, num_return_sequences=1)
+    return response[0]['generated_text']
 
 # Gradio interfejs
-def main():
-    with gr.Blocks() as demo:
-        gr.Markdown("# Blog Post Generator")
-        topic_input = gr.Textbox(label="Enter the blog topic", placeholder="e.g. Website Maintenance Tips")
-        keywords_input = gr.Textbox(label="Enter keywords (comma-separated)", placeholder="e.g. website maintenance, SEO, content updates")
-        
-        generate_button = gr.Button("Generate Blog Post")
-        output_area = gr.Textbox(label="Generated Blog Post", placeholder="Your blog post will appear here...", interactive=False)
-
-        generate_button.click(
-            fn=generate_blog_post,
-            inputs=[topic_input, keywords_input],
-            outputs=output_area
-        )
-
-    demo.launch()
+demo = gr.Interface(
+    fn=generate_blog_post,
+    inputs=gr.inputs.Textbox(label="Enter the topic for your blog post"),
+    outputs=gr.outputs.Textbox(label="Generated Blog Post"),
+    title="Blog Post Generator",
+    description="Enter a topic and generate a blog post using AI."
+)
 
+# Pokreni aplikaciju
 if __name__ == "__main__":
-    main()
+    demo.launch()