Update app.py

app.py

@@ -463,100 +463,98 @@ with gr.Blocks(theme="Hev832/Applio", css=css) as demo:
             2. **Choose Your Output**: Select from descriptive captions, training prompts, or tags.
             3. **Customize the Results**: Adjust tone, length, and other parameters to fine-tune the output.
             4. **Generate and Iterate**: Click 'Caption' to analyze your image and use the results to inspire new creations.
-
-            <h6><center>JoyCaption Alpha One</center></h6>
             """
         )
 		
-        with gr.Tab("JoyCaption"):
-            gr.Markdown("""
-            # JoyCaption: AI-Powered Image Analysis Tool
-
-            This tool helps you generate various types of text based on an uploaded image. Here's how to use it:
-
-            1. Upload an image
-            2. Choose your desired output type
-            3. Adjust settings as needed
-            4. Click 'Generate Caption' to get your result
-            """)
-
-            with gr.Row():
-                with gr.Column(scale=1):
-                    input_image = gr.Image(type="pil", label="Upload Your Image")
-
-                    caption_type = gr.Dropdown(
-                        choices=[
-                            "descriptive", 
-                            "training_prompt", 
-                            "rng-tags",
-                            "thematic_analysis",
-                            "stylistic_comparison",
-                            "narrative_suggestion",
-                            "contextual_storytelling",
-                            "style_prompt"
-                        ],
-                        label="Output Type",
-                        value="descriptive",
-                    )
-
-                    gr.Markdown("""
-                    ### Output Types Explained:
-                    - **Descriptive**: A general description of the image
-                    - **Training Prompt**: A prompt for AI image generation
-                    - **RNG-Tags**: Tags for categorizing the image
-                    - **Thematic Analysis**: Exploration of themes in the image
-                    - **Stylistic Comparison**: Compares the image to art styles
-                    - **Narrative Suggestion**: A story idea based on the image
-                    - **Contextual Storytelling**: A background story for the image
-                    - **Style Prompt**: Analyzes the image in context of a specific art style
-                    """)
-
-                    caption_tone = gr.Dropdown(
-                        choices=["formal", "informal"],
-                        label="Tone",
-                        value="formal",
-                    )
-
-                    gr.Markdown("Choose between a formal (professional) or informal (casual) tone for the output.")
-
-                    caption_length = gr.Dropdown(
-                        choices=["any", "very short", "short", "medium-length", "long", "very long"] +
-                                [str(i) for i in range(20, 261, 10)],
-                        label="Length",
-                        value="any",
-                    )
-
-                    gr.Markdown("""
-                    Select the desired length of the output:
-                    - 'any': No specific length
-                    - Descriptive options: very short to very long
-                    - Numeric options: Specify exact word count (20 to 260 words)
-                    """)
-
-                    art_style = gr.Dropdown(
-                        choices=ART_STYLES,
-                        label="Art Style (for Style Prompt)",
-                        value="Impressionism",
-                        visible=False
-                    )
-
-                    gr.Markdown("Select an art style to analyze the image in that context. Only applicable for 'Style Prompt' output type.")
-
-                with gr.Column(scale=1):
-                    output_caption = gr.Textbox(label="Generated Output", lines=10)
-                    generate_button = gr.Button("Generate Caption")
-
-            gr.Markdown("""
-            ### Additional Notes:
-            - The 'Tone' setting doesn't affect 'RNG-Tags' and 'Training Prompt' outputs.
-            - 'Art Style' is only used when 'Style Prompt' is selected as the output type.
-            - The AI model analyzes the image and generates text based on your selections.
-            """)
-
-            run_button = gr.Button("Caption")
+    with gr.Tab("JoyCaption"):
+        gr.Markdown("""
+        # JoyCaption: AI-Powered Image Analysis Tool
+
+        This tool helps you generate various types of text based on an uploaded image. Here's how to use it:
+
+        1. Upload an image
+        2. Choose your desired output type
+        3. Adjust settings as needed
+        4. Click 'Generate Caption' to get your result
+        """)
+
+        with gr.Row():
+            with gr.Column(scale=1):
+                input_image = gr.Image(type="pil", label="Upload Your Image")
+
+                caption_type = gr.Dropdown(
+                    choices=[
+                        "descriptive", 
+                        "training_prompt", 
+                        "rng-tags",
+                        "thematic_analysis",
+                        "stylistic_comparison",
+                        "narrative_suggestion",
+                        "contextual_storytelling",
+                        "style_prompt"
+                    ],
+                    label="Output Type",
+                    value="descriptive",
+                )
+
+                gr.Markdown("""
+                ### Output Types Explained:
+                - **Descriptive**: A general description of the image
+                - **Training Prompt**: A prompt for AI image generation
+                - **RNG-Tags**: Tags for categorizing the image
+                - **Thematic Analysis**: Exploration of themes in the image
+                - **Stylistic Comparison**: Compares the image to art styles
+                - **Narrative Suggestion**: A story idea based on the image
+                - **Contextual Storytelling**: A background story for the image
+                - **Style Prompt**: Analyzes the image in context of a specific art style
+                """)
+
+                caption_tone = gr.Dropdown(
+                    choices=["formal", "informal"],
+                    label="Tone",
+                    value="formal",
+                )
+
+                gr.Markdown("Choose between a formal (professional) or informal (casual) tone for the output.")
+
+                caption_length = gr.Dropdown(
+                    choices=["any", "very short", "short", "medium-length", "long", "very long"] +
+                            [str(i) for i in range(20, 261, 10)],
+                    label="Length",
+                    value="any",
+                )
+
+                gr.Markdown("""
+                Select the desired length of the output:
+                - 'any': No specific length
+                - Descriptive options: very short to very long
+                - Numeric options: Specify exact word count (20 to 260 words)
+                """)
+
+                art_style = gr.Dropdown(
+                    choices=ART_STYLES,
+                    label="Art Style (for Style Prompt)",
+                    value="Impressionism",
+                    visible=False
+                )
+
+                gr.Markdown("Select an art style to analyze the image in that context. Only applicable for 'Style Prompt' output type.")
+
+            with gr.Column(scale=1):
+                output_caption = gr.Textbox(label="Generated Output", lines=10)
+                generate_button = gr.Button("Generate Caption")
+
+        gr.Markdown("""
+        ### Additional Notes:
+        - The 'Tone' setting doesn't affect 'RNG-Tags' and 'Training Prompt' outputs.
+        - 'Art Style' is only used when 'Style Prompt' is selected as the output type.
+        - The AI model analyzes the image and generates text based on your selections.
+        """)
+
+        run_button = gr.Button("Caption")
             
-            with gr.Column():
-                output_caption = gr.Textbox(label="Caption")
+        with gr.Column():
+            output_caption = gr.Textbox(label="Caption")
 
 
         caption_type.change(