Update app.py
Browse files
app.py
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import gradio as gr
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import random
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import json
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@@ -333,7 +381,6 @@ class HuggingFaceInferenceNode:
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default_simple_prompt = """Create a brief, straightforward caption for this description, suitable for a text-to-image AI system. Focus on the main elements, key characters, and overall scene without elaborate details. Provide a clear and concise description in one or two sentences."""
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poster_prompt = """Analyze the provided description and extract key information to create a movie poster style description. Format the output as follows:
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Title: A catchy, intriguing title that captures the essence of the scene, place the title in "".
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Main character: Give a description of the main character.
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Background: Describe the background in detail.
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@@ -378,7 +425,6 @@ title = """<h1 align="center">FLUX Prompt Generator</h1>
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<p><center>
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<a href="https://github.com/dagthomas/comfyui_dagthomas" target="_blank">[comfyui_dagthomas]</a>
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<a href="https://github.com/dagthomas" target="_blank">[dagthomas Github]</a>
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-
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<p align="center">Create long prompts from images or simple words. Enhance your short prompts with prompt enhancer.</p>
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</center></p>
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"""
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@@ -394,7 +440,7 @@ def create_interface():
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with gr.Row():
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with gr.Column(scale=2):
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with gr.Accordion("Basic Settings"):
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seed = gr.Number(label="Seed", value
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custom = gr.Textbox(label="Custom Input Prompt (optional)")
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subject = gr.Textbox(label="Subject (optional)")
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@@ -464,22 +510,14 @@ def create_interface():
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outputs=[caption_output]
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)
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def generate_prompt_with_random_seed(*args):
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if args[0] == -1: # If seed is -1, use a random seed
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random_seed = random.randint(0, 2**32 - 1)
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args = list(args)
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args[0] = random_seed
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return prompt_generator.generate_prompt(*args)
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generate_button.click(
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inputs=[seed, custom, subject, artform, photo_type, body_types, default_tags, roles, hairstyles,
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additional_details, photography_styles, device, photographer, artist, digital_artform,
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place, lighting, clothing, composition, pose, background],
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outputs=[output, gr.Number(visible=False), t5xxl_output, clip_l_output, clip_g_output]
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)
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add_caption_button.click(
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prompt_generator.add_caption_to_prompt,
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inputs=[output, caption_output],
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Hugging Face's logo
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Hugging Face
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Search models, datasets, users...
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Models
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Datasets
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Spaces
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Posts
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Docs
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Solutions
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Pricing
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Spaces:
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gokaygokay
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/
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FLUX-Prompt-Generator
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like
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10
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Logs
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App
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Files
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Community
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Settings
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FLUX-Prompt-Generator
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/
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app.py
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gokaygokay's picture
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gokaygokay
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Update app.py
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b65ff3c
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verified
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less than a minute ago
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raw
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Copy download link
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history
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blame
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edit
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delete
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No virus
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26.2 kB
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import gradio as gr
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import random
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import json
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default_simple_prompt = """Create a brief, straightforward caption for this description, suitable for a text-to-image AI system. Focus on the main elements, key characters, and overall scene without elaborate details. Provide a clear and concise description in one or two sentences."""
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poster_prompt = """Analyze the provided description and extract key information to create a movie poster style description. Format the output as follows:
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Title: A catchy, intriguing title that captures the essence of the scene, place the title in "".
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Main character: Give a description of the main character.
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Background: Describe the background in detail.
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<p><center>
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<a href="https://github.com/dagthomas/comfyui_dagthomas" target="_blank">[comfyui_dagthomas]</a>
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<a href="https://github.com/dagthomas" target="_blank">[dagthomas Github]</a>
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<p align="center">Create long prompts from images or simple words. Enhance your short prompts with prompt enhancer.</p>
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</center></p>
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"""
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with gr.Row():
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with gr.Column(scale=2):
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with gr.Accordion("Basic Settings"):
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seed = gr.Number(label="Seed", value=0)
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custom = gr.Textbox(label="Custom Input Prompt (optional)")
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subject = gr.Textbox(label="Subject (optional)")
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outputs=[caption_output]
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)
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generate_button.click(
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prompt_generator.generate_prompt,
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inputs=[seed, custom, subject, artform, photo_type, body_types, default_tags, roles, hairstyles,
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additional_details, photography_styles, device, photographer, artist, digital_artform,
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place, lighting, clothing, composition, pose, background],
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outputs=[output, gr.Number(visible=False), t5xxl_output, clip_l_output, clip_g_output]
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)
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add_caption_button.click(
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prompt_generator.add_caption_to_prompt,
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inputs=[output, caption_output],
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