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Running
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Zero
import gradio as gr | |
from prompt_generator import PromptGenerator | |
from huggingface_inference_node import LLMInferenceNode | |
from caption_models import florence_caption, qwen_caption, joycaption | |
import random | |
from prompt_generator import ARTFORM, PHOTO_TYPE, FEMALE_BODY_TYPES, MALE_BODY_TYPES, FEMALE_DEFAULT_TAGS, MALE_DEFAULT_TAGS, ROLES, HAIRSTYLES, FEMALE_CLOTHING, MALE_CLOTHING, PLACE, LIGHTING, COMPOSITION, POSE, BACKGROUND, FEMALE_ADDITIONAL_DETAILS, MALE_ADDITIONAL_DETAILS, PHOTOGRAPHY_STYLES, DEVICE, PHOTOGRAPHER, ARTIST, DIGITAL_ARTFORM | |
title = """<h1 align="center">FLUX Prompt Generator</h1> | |
<p><center> | |
<a href="https://x.com/gokayfem" target="_blank">[X gokaygokay]</a> | |
<a href="https://github.com/gokayfem" target="_blank">[Github gokayfem]</a> | |
<a href="https://github.com/dagthomas/comfyui_dagthomas" target="_blank">[comfyui_dagthomas]</a> | |
<p align="center">Create long prompts from images or simple words. Enhance your short prompts with prompt enhancer.</p> | |
</center></p> | |
""" | |
# Add this global variable | |
selected_prompt_type = "happy" # Default value | |
def create_interface(): | |
prompt_generator = PromptGenerator() | |
llm_node = LLMInferenceNode() | |
with gr.Blocks(theme='bethecloud/storj_theme') as demo: | |
gr.HTML(title) | |
with gr.Row(): | |
with gr.Column(scale=2): | |
with gr.Accordion("Basic Settings"): | |
custom = gr.Textbox(label="Custom Input Prompt (optional)") | |
subject = gr.Textbox(label="Subject (optional)") | |
gender = gr.Radio(["female", "male"], label="Gender", value="female") | |
global_option = gr.Radio( | |
["Disabled", "Random", "No Figure Rand"], | |
label="Set all options to:", | |
value="Disabled" | |
) | |
with gr.Accordion("Artform and Photo Type", open=False): | |
artform = gr.Dropdown(["disabled", "random"] + ARTFORM, label="Artform", value="disabled") | |
photo_type = gr.Dropdown(["disabled", "random"] + PHOTO_TYPE, label="Photo Type", value="disabled") | |
with gr.Accordion("Character Details", open=False): | |
body_types = gr.Dropdown(["disabled", "random"] + FEMALE_BODY_TYPES + MALE_BODY_TYPES, label="Body Types", value="disabled") | |
default_tags = gr.Dropdown(["disabled", "random"] + FEMALE_DEFAULT_TAGS + MALE_DEFAULT_TAGS, label="Default Tags", value="disabled") | |
roles = gr.Dropdown(["disabled", "random"] + ROLES, label="Roles", value="disabled") | |
hairstyles = gr.Dropdown(["disabled", "random"] + HAIRSTYLES, label="Hairstyles", value="disabled") | |
clothing = gr.Dropdown(["disabled", "random"] + FEMALE_CLOTHING + MALE_CLOTHING, label="Clothing", value="disabled") | |
with gr.Accordion("Scene Details", open=False): | |
place = gr.Dropdown(["disabled", "random"] + PLACE, label="Place", value="disabled") | |
lighting = gr.Dropdown(["disabled", "random"] + LIGHTING, label="Lighting", value="disabled") | |
composition = gr.Dropdown(["disabled", "random"] + COMPOSITION, label="Composition", value="disabled") | |
pose = gr.Dropdown(["disabled", "random"] + POSE, label="Pose", value="disabled") | |
background = gr.Dropdown(["disabled", "random"] + BACKGROUND, label="Background", value="disabled") | |
with gr.Accordion("Style and Artist", open=False): | |
additional_details = gr.Dropdown(["disabled", "random"] + FEMALE_ADDITIONAL_DETAILS + MALE_ADDITIONAL_DETAILS, label="Additional Details", value="disabled") | |
photography_styles = gr.Dropdown(["disabled", "random"] + PHOTOGRAPHY_STYLES, label="Photography Styles", value="disabled") | |
device = gr.Dropdown(["disabled", "random"] + DEVICE, label="Device", value="disabled") | |
photographer = gr.Dropdown(["disabled", "random"] + PHOTOGRAPHER, label="Photographer", value="disabled") | |
artist = gr.Dropdown(["disabled", "random"] + ARTIST, label="Artist", value="disabled") | |
digital_artform = gr.Dropdown(["disabled", "random"] + DIGITAL_ARTFORM, label="Digital Artform", value="disabled") | |
# Add Next components | |
with gr.Accordion("More Detailed Prompt Options", open=False): | |
next_components = {} | |
for category, fields in prompt_generator.next_data.items(): | |
with gr.Accordion(f"{category.capitalize()} Options", open=False): | |
category_components = {} | |
for field, data in fields.items(): | |
if isinstance(data, list): | |
options = ["None", "Random", "Multiple Random"] + data | |
elif isinstance(data, dict): | |
options = ["None", "Random", "Multiple Random"] + data.get("items", []) | |
else: | |
options = ["None", "Random", "Multiple Random"] | |
category_components[field] = gr.Dropdown(options, label=field.capitalize(), value="None") | |
next_components[category] = category_components | |
with gr.Column(scale=2): | |
generate_button = gr.Button("Generate Prompt") | |
with gr.Accordion("Image and Caption", open=False): | |
input_image = gr.Image(label="Input Image (optional)") | |
caption_output = gr.Textbox(label="Generated Caption", lines=3, show_copy_button=True) | |
caption_model = gr.Radio(["Florence-2", "Qwen2-VL", "JoyCaption"], label="Caption Model", value="Florence-2") | |
create_caption_button = gr.Button("Create Caption") | |
add_caption_button = gr.Button("Add Caption to Prompt") | |
with gr.Accordion("Prompt Generation", open=True): | |
output = gr.Textbox(label="Generated Prompt / Input Text", lines=4, show_copy_button=True) | |
t5xxl_output = gr.Textbox(label="T5XXL Output", visible=True, show_copy_button=True) | |
clip_l_output = gr.Textbox(label="CLIP L Output", visible=True, show_copy_button=True) | |
clip_g_output = gr.Textbox(label="CLIP G Output", visible=True, show_copy_button=True) | |
with gr.Column(scale=2): | |
with gr.Accordion("""Prompt Generation with LLM | |
(You need to use Generate Prompt first)""", open=False): | |
happy_talk = gr.Checkbox(label="Happy Talk", value=True) | |
compress = gr.Checkbox(label="Compress", value=True) | |
compression_level = gr.Dropdown( | |
choices=["soft", "medium", "hard"], | |
label="Compression Level", | |
value="hard" | |
) | |
prompt_type = gr.Dropdown( | |
choices=["happy", "simple", "poster", "only_objects", "no_figure", "landscape", "fantasy"], | |
label="Prompt Type", | |
value="happy", | |
interactive=True | |
) | |
# Add the missing update_prompt_type function | |
def update_prompt_type(value): | |
global selected_prompt_type | |
selected_prompt_type = value | |
print(f"Updated prompt type: {selected_prompt_type}") | |
return value | |
# Connect the update_prompt_type function to the prompt_type dropdown | |
prompt_type.change(update_prompt_type, inputs=[prompt_type], outputs=[prompt_type]) | |
custom_base_prompt = gr.Textbox(label="Custom Base Prompt", lines=5) | |
# Add new components for LLM provider selection | |
llm_provider = gr.Dropdown( | |
choices=["Hugging Face", "OpenAI", "Anthropic", "Groq"], | |
label="LLM Provider", | |
value="Hugging Face" | |
) | |
api_key = gr.Textbox(label="API Key", type="password", visible=False) | |
model = gr.Dropdown(label="Model", choices=["meta-llama/Meta-Llama-3.1-70B-Instruct"], value="meta-llama/Meta-Llama-3.1-70B-Instruct") | |
generate_text_button = gr.Button("Generate Prompt with LLM") | |
text_output = gr.Textbox(label="Generated Text", lines=10, show_copy_button=True) | |
def create_caption(image, model): | |
if image is not None: | |
if model == "Florence-2": | |
return florence_caption(image) | |
elif model == "Qwen2-VL": | |
return qwen_caption(image) | |
elif model == "JoyCaption": | |
return joycaption(image) | |
return "" | |
create_caption_button.click( | |
create_caption, | |
inputs=[input_image, caption_model], | |
outputs=[caption_output] | |
) | |
def generate_prompt_with_dynamic_seed(*args, **kwargs): | |
dynamic_seed = random.randint(0, 1000000) | |
# Extract the main arguments | |
main_args = args[:22] # Assuming there are 22 main arguments before the next_params | |
# Extract next_params | |
next_params = {} | |
next_args = args[22:] # All arguments after the main ones are for next_params | |
next_arg_index = 0 | |
for category, fields in prompt_generator.next_data.items(): | |
category_params = {} | |
for field in fields: | |
value = next_args[next_arg_index] | |
# Include all values, even "None", "Random", and "Multiple Random" | |
category_params[field] = value | |
next_arg_index += 1 | |
if category_params: | |
next_params[category] = category_params | |
# Call generate_prompt with the correct arguments | |
result = prompt_generator.generate_prompt(dynamic_seed, *main_args, next_params=next_params) | |
return [dynamic_seed] + list(result) | |
generate_button.click( | |
generate_prompt_with_dynamic_seed, | |
inputs=[custom, subject, gender, artform, photo_type, body_types, default_tags, roles, hairstyles, | |
additional_details, photography_styles, device, photographer, artist, digital_artform, | |
place, lighting, clothing, composition, pose, background, input_image] + | |
[component for category in next_components.values() for component in category.values()], | |
outputs=[gr.Number(label="Used Seed", visible=False), output, gr.Number(visible=False), t5xxl_output, clip_l_output, clip_g_output] | |
) | |
add_caption_button.click( | |
prompt_generator.add_caption_to_prompt, | |
inputs=[output, caption_output], | |
outputs=[output] | |
) | |
def update_model_choices(provider): | |
provider_models = { | |
"Hugging Face": ["meta-llama/Meta-Llama-3.1-70B-Instruct"], | |
"Groq": ["llama-3.1-70b-versatile"], | |
"OpenAI": ["gpt-4o", "gpt-4o-mini"], | |
"Anthropic": ["claude-3-5-sonnet-20240620"], | |
} | |
models = provider_models[provider] | |
return gr.Dropdown(choices=models, value=models[0]) | |
def update_api_key_visibility(provider): | |
return gr.update(visible=(provider in ["OpenAI", "Anthropic"])) | |
llm_provider.change(update_model_choices, inputs=[llm_provider], outputs=[model]) | |
llm_provider.change(update_api_key_visibility, inputs=[llm_provider], outputs=[api_key]) | |
def generate_text_with_llm(output, happy_talk, compress, compression_level, custom_base_prompt, provider, api_key, model): | |
global selected_prompt_type | |
result = llm_node.generate(output, happy_talk, compress, compression_level, False, selected_prompt_type, custom_base_prompt, provider, api_key, model) | |
selected_prompt_type = "happy" # Reset to "happy" after generation | |
return result, "happy" # Return the result and the new prompt type value | |
generate_text_button.click( | |
generate_text_with_llm, | |
inputs=[output, happy_talk, compress, compression_level, custom_base_prompt, llm_provider, api_key, model], | |
outputs=[text_output, prompt_type], | |
api_name="generate_text" | |
) | |
# Add this line to disable caching for the generate_text_with_llm function | |
generate_text_with_llm.cache_examples = False | |
def update_all_options(choice): | |
updates = {} | |
if choice == "Disabled": | |
for dropdown in [ | |
artform, photo_type, body_types, default_tags, roles, hairstyles, clothing, | |
place, lighting, composition, pose, background, additional_details, | |
photography_styles, device, photographer, artist, digital_artform | |
]: | |
updates[dropdown] = gr.update(value="disabled") | |
elif choice == "Random": | |
for dropdown in [ | |
artform, photo_type, body_types, default_tags, roles, hairstyles, clothing, | |
place, lighting, composition, pose, background, additional_details, | |
photography_styles, device, photographer, artist, digital_artform | |
]: | |
updates[dropdown] = gr.update(value="random") | |
else: # No Figure Random | |
for dropdown in [photo_type, body_types, default_tags, roles, hairstyles, clothing, pose, additional_details]: | |
updates[dropdown] = gr.update(value="disabled") | |
for dropdown in [artform, place, lighting, composition, background, photography_styles, device, photographer, artist, digital_artform]: | |
updates[dropdown] = gr.update(value="random") | |
return updates | |
global_option.change( | |
update_all_options, | |
inputs=[global_option], | |
outputs=[ | |
artform, photo_type, body_types, default_tags, roles, hairstyles, clothing, | |
place, lighting, composition, pose, background, additional_details, | |
photography_styles, device, photographer, artist, digital_artform | |
] | |
) | |
return demo |