Clean up old code and text

app.py

@@ -1,10 +1,11 @@
-#@title Prepare the Concepts Library to be used
+# ----- Deployment Log -----------------------------------------------------------------
 
-# Deployment Log ---------------------------
 # added beta 4305ed7
 # added beta 4307f62
-# add new beta concept
-# add beta concept...99
+
+
+
+# ----- General Setup -----------------------------------------------------------------
 
 import requests
 import os
@@ -118,16 +119,10 @@ for model in ahx_model_list:
 # -----------------------------------------------------------------------------------------------
 
 
-#@title Dropdown Prompt Tab
-
 model_tags = [model.modelId.split("/")[1] for model in ahx_model_list]
 model_tags.sort()
-
-
 import random 
 
-
-#@title Gradio Concept Loader
 DROPDOWNS = {}
 
 for model in model_tags:
@@ -194,17 +189,19 @@ def get_models_text():
   return f"## Available Artist Models / Concepts:\n" + markdown_model_text + "\n\n## Available Beta Models / Concepts:\n" + markdown_betas_text
 
 
-with gr.Blocks(css=".gradio-container {max-width: 650px}") as dropdown_tab:
+
+# ----- Advanced Tab -----------------------------------------------------------------
+
+with gr.Blocks(css=".gradio-container {max-width: 650px}") as advanced_tab:
   gr.Markdown('''
-      # 🧑‍🚀 Advanced Concept Loader
+      # Advanced Prompting
 
-      This tool allows you to run your own text prompts into fine-tuned artist concepts with individual parameter controls. Text prompts need to manually include artist concept / model tokens, see the examples below. The seed controls the static starting.
-      <br>
-      <br>
-      The images you generate here are not recorded unless you choose to share them. Please share any cool images / prompts on the community tab here or our discord server! 
+      Freely prompt artist models / concepts with open controls for size, inference steps, seed number etc. Text prompts need to manually include artist concept / model tokens which can be found in the welcome tab and beta tab (ie "an alien in the style of <ahx-model-12>"). You can also mix and match models (ie "a landscape in the style of <ahx-model-14> and <ahx-beta-4307f62>>"). To see example images or for more information see the links below.
+      <br><br>
+      <a href="http://www.astronaut.horse">http://www.astronaut.horse</a>
       <br>
+      <a href="https://discord.gg/ZctfW4SvGw">https://discord.com</a><br>
       <br>
-      <a href="http://www.astronaut.horse">http://www.astronaut.horse</a>
   ''')
 
   with gr.Row():
@@ -226,32 +223,16 @@ with gr.Blocks(css=".gradio-container {max-width: 650px}") as dropdown_tab:
   go_button = gr.Button("generate image", elem_id="go-button")
   output = gr.Image(elem_id="output-image")
   output_text = gr.Text(elem_id="output-text")
-  # go_button.click(fn=image_prompt, inputs=[prompt, dropdown, guidance, steps, seed, height, width], outputs=[output, output_text])
   go_button.click(fn=image_prompt, inputs=[prompt, guidance, steps, seed, height, width], outputs=[output, output_text])
-  # gr.Markdown('''
-  #   ## Prompt Examples Using Artist Tokens:
-  #   * "an alien in the style of \<ahx-model-12>"
-  #   * "a painting in the style of \<ahx-model-11>"
-  #   * "a landscape in the style of \<ahx-model-10> and \<ahx-model-14> "
-
-  #   ## Valid Artist Tokens:
-  # ''')
   gr.Markdown("For a complete list of usable models and beta concepts check out the dropdown selectors in the welcome and beta concepts tabs or the project's main website or our discord.\n\nhttp://www.astronaut.horse/concepts")
     
 
 # -----------------------------------------------------------------------------------------------
 
-
-#@title Dropdown Prompt Tab
-
 model_tags = [model.modelId.split("/")[1] for model in ahx_model_list]
 model_tags.sort()
-
-
 import random 
 
-
-#@title Gradio Concept Loader
 DROPDOWNS = {}
 
 # set a default for empty entries...
@@ -301,13 +282,11 @@ def simple_image_prompt(prompt, dropdown, size_dropdown):
   prompt = prompt + DROPDOWNS[dropdown]
   generator = torch.Generator(device="cuda").manual_seed(int(seed))
 
-  # image_count += 1
   curr_time = datetime.datetime.now()
   is_clean = check_prompt(prompt)
     
   print("----- welcome / beta tab prompt ------------------------------")
   print(f"prompt: {prompt}, size: {width}px x {height}px, guidance: {guidance}, steps: {steps}, seed: {int(seed)}")
-  # print(f"image_count: {image_count}, datetime: `{e}`")
   print(f"datetime: `{curr_time}`")
   print(f"is_prompt_clean: {is_clean}")
   print("-------------------------------------------------------")
@@ -323,16 +302,9 @@ def simple_image_prompt(prompt, dropdown, size_dropdown):
       f"Prompt violates Hugging Face's Terms of Service"
     )
 
-    
   
-    
-
-    
-# ~~~ WELCOME TAB ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-
-#       This tool allows you to run your own text prompts into fine-tuned artist concepts from an ongoing series of Stable Diffusion collaborations with visual artists linked below. Select an artist's fine-tuned concept / model from the dropdown and enter any desired text prompt. You can check out example output images and project details on the project's webpage. Additionally you can play around with more controls in the Advanced Prompting tab.
-#       The images you generate here are not recorded unless you choose to share them. Please share any cool images / prompts on the community tab here or our discord server!
-
+  
+# ----- Welcome Tab -----------------------------------------------------------------
 
 rand_model_int = 2
 
@@ -341,8 +313,7 @@ with gr.Blocks(css=".gradio-container {max-width: 650px}") as new_welcome:
       # Stable Diffusion Artist Collaborations
 
       Use the dropdown below to select models / concepts trained on images chosen by collaborating artists. Prompt concepts with any text. To see example images or for more information on the project see the main project page or the discord community linked below. The images you generate here are not recorded unless you save them, they belong to everyone and no one.
-      <br>
-      <br>
+      <br><br>
       <a href="http://www.astronaut.horse">http://www.astronaut.horse</a>
       <br>
       <a href="https://discord.gg/ZctfW4SvGw">https://discord.com</a><br>
@@ -351,7 +322,6 @@ with gr.Blocks(css=".gradio-container {max-width: 650px}") as new_welcome:
   with gr.Row():
     dropdown = gr.Dropdown([dropdown for dropdown in list(DROPDOWNS) if 'ahx-model' in dropdown], label="choose style...")
     size_dropdown = gr.Dropdown(['square', 'portrait', 'landscape'], label="choose size...")
-    # dropdown = gr.Dropdown(['1 image', '2 images', '3 images', '4 images'], label="output image count...")
   prompt = gr.Textbox(label="image prompt...", elem_id="input-text")
 
   go_button = gr.Button("generate image", elem_id="go-button")
@@ -359,83 +329,29 @@ with gr.Blocks(css=".gradio-container {max-width: 650px}") as new_welcome:
   output_text = gr.Text(elem_id="output-text")
   go_button.click(fn=simple_image_prompt, inputs=[prompt, dropdown, size_dropdown], outputs=[output, output_text])
 
-# -----------------------------------------------------------------------------------------------
+# Old Text --> This tool allows you to run your own text prompts into fine-tuned artist concepts from an ongoing series of Stable Diffusion collaborations with visual artists linked below. Select an artist's fine-tuned concept / model from the dropdown and enter any desired text prompt. You can check out example output images and project details on the project's webpage. Additionally you can play around with more controls in the Advanced Prompting tab. <br> The images you generate here are not recorded unless you choose to share them. Please share any cool images / prompts on the community tab here or our discord server!
 
 
 
-def infer(text, dropdown):
-  images_list = pipe(
-              [f"{text} in the style of <{dropdown}>"],
-              num_inference_steps=30,
-              guidance_scale=7.5
-  )
-  return images_list.images, gr.update(visible=True), gr.update(visible=True), gr.update(visible=True)
-
-css = ""
-examples = []
-
-
-# ~~~ UNUSED DEMO TAB ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-
-with gr.Blocks(css=css) as demo:
-  state = gr.Variable({
-        'selected': -1
-  })
-  state = {}
-  def update_state(i):
-        global checkbox_states
-        if(checkbox_states[i]):
-          checkbox_states[i] = False
-          state[i] = False
-        else:
-          state[i] = True
-          checkbox_states[i] = True
-  gr.Markdown('''
-      # 🧑‍🚀 Astronaut Horse Concept Loader
-
-      This tool allows you to run your own text prompts into fine-tuned artist concepts from an ongoing series of Stable Diffusion collaborations with visual artists linked below. Select an artist's fine-tuned concept / model from the dropdown and enter any desired text prompt. You can check out example output images and project details on the project's webpage. Additionally if you can play around with more controls in the Advanced Prompting tab. Enjoy!
-      <a href="http://www.astronaut.horse">http://www.astronaut.horse</a>
-  ''')
-  with gr.Row():
-        with gr.Column():
-          dropdown = gr.Dropdown(list(DROPDOWNS), label="choose style...")
-          text = gr.Textbox(
-              label="Enter your prompt", placeholder="Enter your prompt", show_label=False, max_lines=1, elem_id="prompt_input"
-          )
-          btn = gr.Button("generate image",elem_id="run_btn")
-          infer_outputs = gr.Gallery(show_label=False, elem_id="generated-gallery").style(grid=[1])
-          with gr.Group(elem_id="share-btn-container"):
-            community_icon = gr.HTML(community_icon_html, visible=False)
-            loading_icon = gr.HTML(loading_icon_html, visible=False)
-  checkbox_states = {}
-  inputs = [text, dropdown]
-  btn.click(
-        infer,
-        inputs=inputs,
-        outputs=[infer_outputs, community_icon, loading_icon]
-    )
-
-
-# -----------------------------------------------------------------------------------------------
-
-# ~~~ BETA TAB ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-
+# ----- Beta Concepts -----------------------------------------------------------------
 
 with gr.Blocks() as beta:
   gr.Markdown('''
-      # 🧑‍🚀 Beta Concept Loader
+      # Beta Concepts
 
-      This tool allows you to test out newly trained beta concepts trained by artists. These are experimental and may be removed if they are problematic or uninteresting. If they end up  successful though they'll be renamed and moved into the primary prompting drop-down.
-      
-      To add to this artists can now freely train new models / concepts using the link below. This uses free access to Google's GPUs but will require a password / key that you can get from our discord. After a new concept / model is trained it will be automatically added to this tab after ~24 hours!
-      
-      <a href="https://colab.research.google.com/drive/1FhOpcEjHT7EN53Zv9MFLQTytZp11wjqg#scrollTo=hzUluHT-I42O">https://colab.research.google.com/astronaut-horse-training-tool</a>
+      This tool allows you to test out newly trained beta concepts trained by artists. To add your own beta concept see the link below. This uses free access to Google's GPUs but will require a password / key that you can get from the discord server. After a new concept / model is trained it will be automatically added to this tab when the app is redeployed.
+      <br><br>
+      <a href="https://colab.research.google.com/drive/1FhOpcEjHT7EN53Zv9MFLQTytZp11wjqg#scrollTo=hzUluHT-I42O">train your own beta concept</a>
+      <br><br>
+      <a href="http://www.astronaut.horse">http://www.astronaut.horse</a>
+      <br>
+      <a href="https://discord.gg/ZctfW4SvGw">https://discord.com</a><br>
+      <br>
   ''')
 
   with gr.Row():
     dropdown = gr.Dropdown([dropdown for dropdown in list(DROPDOWNS) if 'ahx-beta' in dropdown], label="choose style...")
     size_dropdown = gr.Dropdown(['square', 'portrait', 'landscape'], label="choose size...")
-    # dropdown = gr.Dropdown(['1 image', '2 images', '3 images', '4 images'], label="output image count...")
   prompt = gr.Textbox(label="image prompt...", elem_id="input-text")
 
   go_button = gr.Button("generate image", elem_id="go-button")
@@ -443,125 +359,9 @@ with gr.Blocks() as beta:
   output_text = gr.Text(elem_id="output-text")
   go_button.click(fn=simple_image_prompt, inputs=[prompt, dropdown, size_dropdown], outputs=[output, output_text])
 
-  
-
-  # with gr.Row():
-  # prompt = gr.Textbox(label="image prompt...", elem_id="input-text")
-
-  # go_button = gr.Button("generate image", elem_id="go-button")
-  # output = gr.Image(elem_id="output-image")
-  # output_text = gr.Text(elem_id="output-text")
-  # go_button.click(fn=simple_image_prompt, inputs=[prompt, dropdown], outputs=[output, output_text])
-
-
-    
-# -----------------------------------------------------------------------------------------------
-
-# ~~~ NOISE STEPS TAB ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-
 
-with gr.Blocks() as noise_steps:
-  gr.Markdown('''
-      # 🧑‍🚀 Noise Steps Loader
-
-      This tool doesn't exist yet! 
-      
-      When it's built out though the plan is for it to let you expose the de-noising process that helps define Stable Diffusion image generation. 
-      
-      The plan is to let you enter custom a custom prompt / seed etc and see how Stable Diffusion is turning it's starting static image into an image that matches your prompt step-by-step. 
-      
-      Hopefully it'll be working soon. Check out the example below for now!
-
-      ![denoising image](https://cdn.discordapp.com/attachments/1082744000806658098/1088575231158923304/Untitled.png)
-  ''')
-  # ![denoising image](https://cdn.discordapp.com/attachments/1082744000806658098/1088577845061759026/Untitled.png)
-  # dropdown = gr.Dropdown([dropdown for dropdown in list(DROPDOWNS) if 'ahx-beta' in dropdown], label="choose style...")
-
-  # with gr.Row():
-  # prompt = gr.Textbox(label="image prompt...", elem_id="input-text")
-
-  # go_button = gr.Button("generate image", elem_id="go-button")
-  # output = gr.Image(elem_id="output-image")
-  # output_text = gr.Text(elem_id="output-text")
-  # go_button.click(fn=simple_image_prompt, inputs=[prompt, dropdown], outputs=[output, output_text])
-
-
-    
-# -----------------------------------------------------------------------------------------------
-
-# ~~~ Depth Map TAB ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-
-
-with gr.Blocks() as depth_map:
-  gr.Markdown('''
-      # 🧑‍🚀 Depth Map Processor
-
-      This tool doesn't exist yet! When it's built it will let you input any image from your phone or computer and process it into a depth map image using a Stable Diffusion control net process. Hopefully it'll be working soon. Check out the example below for now!
-
-      ![Escher hands](https://cdn.discordapp.com/attachments/1065349726007992411/1089030239201534063/IMG_1874.jpg)
-      ![Escher hands depth map](https://cdn.discordapp.com/attachments/1085605267481309197/1089031503612227705/tmp2bsa61a8.png)
-  ''')
-
-
-    
-# -----------------------------------------------------------------------------------------------
-
-# ~~~ Control Net TAB ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-
-
-with gr.Blocks() as control_net:
-  gr.Markdown('''
-      # 🧑‍🚀 Control Net Processor
-
-      This tool doesn't exist yet! When it's built it will let you input any image from your phone or computer and process it using any text prompt or combination of trained artist styles / concepts. If you want to play with normal control net without ahx artist concepts check out the link below. [control net](https://huggingface.co/spaces/hysts/ControlNet)
-  ''')
-
-
-    
-# -----------------------------------------------------------------------------------------------
-
-# ~~~ TEXTUAL INVERSION TAB ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-
-
-with gr.Blocks() as inversion:
-  gr.Markdown('''
-      # 🧑‍🚀 Concept Trainer
-
-      ![textual inversion training](https://textual-inversion.github.io/static/images/training/training.JPG)
-      
-      This external tool lets you train your own new models / concepts from any images you want that will appear automatically be added to the Beta Concepts and Advanced Prompting tabs!
-
-      For now the tool lives on Google Colab, which is Google's free tool for using their GPU's. Someday it might live here on our Hugging Face Space, but the process is a little too demanding for our current resources. To train your own concept visit the link below and follow the instructions and be prepared to wait several hours.
-
-      [textual inversion training tool](https://colab.research.google.com/drive/1FhOpcEjHT7EN53Zv9MFLQTytZp11wjqg#forceEdit=true&sandboxMode=true&scrollTo=ZajfEoWHKAr3)
-
-
-      Note that you will need a access_token to run this. You can request this on our discord or get your own free one at the link below. [hugging face access token](https://huggingface.co/docs/hub/security-tokens)
-  ''')
-
-
-    
-# -----------------------------------------------------------------------------------------------
-
-# ~~~ DREAM BOOTH TAB ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-
-
-with gr.Blocks() as dream_booth:
-  gr.Markdown('''
-      # 🧑‍🚀 Dream Booth Concept Trainer
-
-      This tool doesn't exist yet! When it's built it will let you train concepts using a process distinct from our current concept training tool which uses textual inversion training. To read more about Dream Booth check out the link below!
-      
-      [dream booth](https://huggingface.co/spaces/multimodalart/dreambooth-training)
-  ''')
-
-
-    
-    
-# -----------------------------------------------------------------------------------------------
 
+# ----- Launch Tabs -----------------------------------------------------------------
 
-# tabbed_interface = gr.TabbedInterface([new_welcome, dropdown_tab, beta, inversion, noise_steps, depth_map, control_net, dream_booth], ["Welcome!", "Advanced Prompting", "Beta Concepts", "Concept Trainer", "Noise Steps", "Depth Map", "Control Net", "Dream Booth"])
-# tabbed_interface = gr.TabbedInterface([new_welcome, dropdown_tab, beta, inversion, noise_steps, control_net], ["Welcome!", "Advanced Prompting", "Beta Concepts", "Concept Trainer", "Noise Steps", "Depth Map", "Control Net", "Dream Booth"])
-tabbed_interface = gr.TabbedInterface([new_welcome, dropdown_tab, beta], ["Welcome!", "Advanced Prompting", "Beta Concepts"])
+tabbed_interface = gr.TabbedInterface([new_welcome, advanced_tab, beta], ["Welcome", "Advanced Prompting", "Beta Concepts"])
 tabbed_interface.launch()