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Update app.py
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app.py
CHANGED
@@ -6,7 +6,7 @@ import random
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import os
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from PIL import Image
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from deep_translator import GoogleTranslator
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from gradio_client import Client
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# os.makedirs('assets', exist_ok=True)
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if not os.path.exists('icon.jpg'):
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@@ -16,19 +16,15 @@ API_URL = "https://api-inference.huggingface.co/models/black-forest-labs/FLUX.1-
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timeout = 100
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def enhance_prompt(prompt):
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client = Client("K00B404/mistral-nemo-prompt-enhancer")
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result = client.predict(
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temperature=0.7,
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top_p=0.95,
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api_name="/chat"
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)
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return result
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def query(prompt, is_negative=False, steps=30, cfg_scale=7, sampler="DPM++ 2M Karras", seed=-1, strength=0.7, huggingface_api_key=None, use_dev=False):
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# Determine which API URL to use
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api_url = API_URL_DEV if use_dev else API_URL
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@@ -53,11 +49,11 @@ def query(prompt, is_negative=False, steps=30, cfg_scale=7, sampler="DPM++ 2M Ka
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prompt = GoogleTranslator(source='ru', target='en').translate(prompt)
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print(f'\033[1mGeneration {key} translation:\033[0m {prompt}')
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prompt = f"{
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print(f'\033[1mGeneration {key}:\033[0m {prompt}')
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# If seed is -1, generate a random seed and use it
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@@ -142,6 +138,7 @@ with gr.Blocks(theme='Nymbo/Nymbo_Theme', css=css) as app:
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seed = gr.Slider(label="Seed", value=-1, minimum=-1, maximum=1000000000, step=1)
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huggingface_api_key = gr.Textbox(label="Hugging Face API Key (required for API calls)", placeholder="Enter your Hugging Face API Key here", type="password", elem_id="api-key")
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use_dev = gr.Checkbox(label="Use Dev API", value=False, elem_id="use-dev-checkbox")
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with gr.Row():
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text_button = gr.Button("Run", variant='primary', elem_id="gen-button")
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@@ -149,7 +146,7 @@ with gr.Blocks(theme='Nymbo/Nymbo_Theme', css=css) as app:
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image_output = gr.Image(type="pil", label="Image Output", elem_id="gallery")
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seed_output = gr.Textbox(label="Seed Used", elem_id="seed-output")
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# Adjust the click function to include the API key and
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text_button.click(query, inputs=[text_prompt, negative_prompt, steps, cfg, method, seed, strength, huggingface_api_key, use_dev], outputs=[image_output, seed_output])
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app.launch(show_api=True, share=False,show_error=True)
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import os
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from PIL import Image
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from deep_translator import GoogleTranslator
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from gradio_client import Client
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# os.makedirs('assets', exist_ok=True)
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if not os.path.exists('icon.jpg'):
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timeout = 100
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def enhance_prompt(prompt):
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client = Client("K00B404/Mistral-Nemo-custom")
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result = client.predict(
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system_prompt="You are a image generation prompt enhancer and must respond only with the enhanced version of the users input prompt",
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user_message=f"###input image generation prompt### {prompt}",
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api_name="/predict"
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)
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return result
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def query(prompt, is_negative=False, steps=30, cfg_scale=7, sampler="DPM++ 2M Karras", seed=-1, strength=0.7, huggingface_api_key=None, use_dev=False, enhance_prompt_option=False):
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# Determine which API URL to use
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api_url = API_URL_DEV if use_dev else API_URL
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prompt = GoogleTranslator(source='ru', target='en').translate(prompt)
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print(f'\033[1mGeneration {key} translation:\033[0m {prompt}')
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if enhance_prompt_option:
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prompt = enhance_prompt(prompt)
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print(f'\033[1mGeneration {key} enhanced prompt:\033[0m {prompt}')
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prompt = f"{prompt} | ultra detail, ultra elaboration, ultra quality, perfect."
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print(f'\033[1mGeneration {key}:\033[0m {prompt}')
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# If seed is -1, generate a random seed and use it
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seed = gr.Slider(label="Seed", value=-1, minimum=-1, maximum=1000000000, step=1)
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huggingface_api_key = gr.Textbox(label="Hugging Face API Key (required for API calls)", placeholder="Enter your Hugging Face API Key here", type="password", elem_id="api-key")
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use_dev = gr.Checkbox(label="Use Dev API", value=False, elem_id="use-dev-checkbox")
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enhance_prompt_option = gr.Checkbox(label="Enhance Prompt", value=False, elem_id="enhance-prompt-checkbox")
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with gr.Row():
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text_button = gr.Button("Run", variant='primary', elem_id="gen-button")
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image_output = gr.Image(type="pil", label="Image Output", elem_id="gallery")
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seed_output = gr.Textbox(label="Seed Used", elem_id="seed-output")
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# Adjust the click function to include the API key, use_dev, and enhance_prompt_option as inputs
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text_button.click(query, inputs=[text_prompt, negative_prompt, steps, cfg, method, seed, strength, huggingface_api_key, use_dev, enhance_prompt_option], outputs=[image_output, seed_output])
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app.launch(show_api=True, share=False,show_error=True)
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