Update app.py

app.py

@@ -20,16 +20,20 @@ def infer(input):
     prompt = pipe(input+',', num_return_sequences=1)[0]["generated_text"]
     img = get_images(prompt) 
     result = get_new_prompt(img, 'fast')    
-    return result[0]
+    return prompt,result[0]
     
 input_prompt = gr.Text(label="Enter the initial prompt")
-sd2_output = gr.Text(label="Extended prompt suitable for Stable Diffusion 2")
-
-
-gr.Markdown(""" ## Prompt Extender for SD 2 """)
-gr.HTML('''<p style="margin-bottom: 10px; font-size: 94%">
-            Enter a main initial idea for a prompt, and the model will generate a prompt suitable for Stable Diffusion 2</p>''')
-
-demo = gr.Interface(fn=infer, inputs=input_prompt, outputs=sd2_output)
+sd1_output = gr.Text(label="Extended prompt suitable for Stable Diffusion 1.x")
+sd2_output = gr.Text(label="Extended prompt suitable for Stable Diffusion 2.x")
+
+description="""
+<p style="text-align:center;">
+Since Stable Diffusion 2 uses OpenCLIP ViT-H model trained on LAION dataset compared to the OpenAI ViT-L we're all used to prompting, the prompting style varies and the exact prompt is often hard to write.
+<br />This demo extends an initial idea and generates suitable prompts compatible with v1.x stable diffusion and v2.x stable diffusion, 
+<br />by generating an image through <a href="https://huggingface.co/runwayml/stable-diffusion-v1-5" target="_blank">RunwayML Stable Diffusion 1.5</a>, then Interrogate the resulting image through <a href="https://huggingface.co/spaces/fffiloni/CLIP-Interrogator-2" target="_blank">CLIP Interrogator 2</a> to give you a Stable Diffusion 2 equivalent prompt.
+</p>
+"""
+
+demo = gr.Interface(fn=infer, inputs=input_prompt, outputs=[sd1_output,sd2_output], description = description)
 demo.queue(max_size=10,concurrency_count=20)
 demo.launch(enable_queue=True)