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import gradio as gr |
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from transformers import pipeline |
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generator = pipeline("text-generation", model="gpt2") |
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def generate_blog_post(topic, keywords): |
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prompt = f"Write an SEO-optimized blog post about {topic}. Include keywords: {', '.join(keywords)}." |
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generated = generator(prompt, max_length=500, num_return_sequences=1) |
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return generated[0]['generated_text'] |
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def main(): |
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with gr.Blocks() as demo: |
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gr.Markdown("# Blog Post Generator") |
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topic_input = gr.Textbox(label="Enter the blog topic", placeholder="e.g. Website Maintenance Tips") |
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keywords_input = gr.Textbox(label="Enter keywords (comma-separated)", placeholder="e.g. website maintenance, SEO, content updates") |
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generate_button = gr.Button("Generate Blog Post") |
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output_area = gr.Textbox(label="Generated Blog Post", placeholder="Your blog post will appear here...", interactive=False) |
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generate_button.click( |
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fn=generate_blog_post, |
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inputs=[topic_input, keywords_input], |
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outputs=output_area |
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) |
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demo.launch() |
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if __name__ == "__main__": |
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main() |
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