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Update app.py
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app.py
CHANGED
@@ -15,7 +15,7 @@ API_TOKEN = os.getenv("HF_READ_TOKEN")
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headers = {"Authorization": f"Bearer {API_TOKEN}"}
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timeout = 100
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# Function to query the API and return the generated image
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def query(prompt, is_negative=False, steps=35, cfg_scale=7, sampler="DPM++ 2M Karras", seed=-1, strength=0.7, width=1024, height=1024):
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if prompt == "" or prompt is None:
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return None
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@@ -25,15 +25,15 @@ def query(prompt, is_negative=False, steps=35, cfg_scale=7, sampler="DPM++ 2M Ka
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API_TOKEN = random.choice([os.getenv("HF_READ_TOKEN")])
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headers = {"Authorization": f"Bearer {API_TOKEN}"}
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# Translate the prompt from
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prompt = GoogleTranslator(source='id', target='en').translate(prompt)
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print(f'\033[1mGeneration {key} translation:\033[0m {prompt}')
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#
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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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# Prepare the payload
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payload = {
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"inputs": prompt,
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"is_negative": is_negative,
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@@ -42,12 +42,12 @@ def query(prompt, is_negative=False, steps=35, cfg_scale=7, sampler="DPM++ 2M Ka
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"seed": seed if seed != -1 else random.randint(1, 1000000000),
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"strength": strength,
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"parameters": {
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"width": width,
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"height": height
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}
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}
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#
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response = requests.post(API_URL, headers=headers, json=payload, timeout=timeout)
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if response.status_code != 200:
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print(f"Error: Failed to get image. Response status: {response.status_code}")
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@@ -57,16 +57,23 @@ def query(prompt, is_negative=False, steps=35, cfg_scale=7, sampler="DPM++ 2M Ka
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raise gr.Error(f"{response.status_code}")
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try:
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# Convert
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image_bytes = response.content
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print(f'\033[1mGeneration {key} completed!\033[0m ({prompt})')
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return
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except Exception as e:
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print(f"Error when trying to open the image: {e}")
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return None
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# CSS
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css = """
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#app-container {
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max-width: 800px;
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@@ -75,42 +82,54 @@ css = """
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}
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"""
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#
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with gr.Blocks(theme='Nymbo/Nymbo_Theme', css=css) as app:
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# Add a title to the app
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gr.HTML("<center><h1>FLUX.1-Dev</h1></center>")
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# Container for all the UI elements
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with gr.Column(elem_id="app-container"):
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# Add a text input for the main prompt
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with gr.Row():
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with gr.Column(elem_id="prompt-container"):
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with gr.Row():
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text_prompt = gr.Textbox(
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# Accordion for advanced settings
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with gr.Row():
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with gr.Accordion("Advanced Settings", open=False):
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negative_prompt = gr.Textbox(
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with gr.Row():
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width = gr.Slider(label="Width", value=1024, minimum=64, maximum=1216, step=32)
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height = gr.Slider(label="Height", value=1024, minimum=64, maximum=1216, step=32)
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steps = gr.Slider(label="Sampling steps", value=35, minimum=1, maximum=100, step=1)
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cfg = gr.Slider(label="CFG Scale", value=7, minimum=1, maximum=20, step=1)
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strength = gr.Slider(label="Strength", value=0.7, minimum=0, maximum=1, step=0.001)
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seed = gr.Slider(label="Seed", value=-1, minimum=-1, maximum=1000000000, step=1)
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method = gr.Radio(
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# Add a button to trigger the image generation
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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 area to display the generated image
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with gr.Row():
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image_output = gr.Image(type="pil", label="Image Output", elem_id="gallery")
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# Launch the
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app.launch(show_api=True, share=True)
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headers = {"Authorization": f"Bearer {API_TOKEN}"}
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timeout = 100
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# Function to query the API and return the generated image as PNG
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def query(prompt, is_negative=False, steps=35, cfg_scale=7, sampler="DPM++ 2M Karras", seed=-1, strength=0.7, width=1024, height=1024):
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if prompt == "" or prompt is None:
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return None
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API_TOKEN = random.choice([os.getenv("HF_READ_TOKEN")])
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headers = {"Authorization": f"Bearer {API_TOKEN}"}
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# Translate the prompt from Indonesian to English
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prompt = GoogleTranslator(source='id', target='en').translate(prompt)
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print(f'\033[1mGeneration {key} translation:\033[0m {prompt}')
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# Enhance the 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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# Prepare the payload
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payload = {
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"inputs": prompt,
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"is_negative": is_negative,
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"seed": seed if seed != -1 else random.randint(1, 1000000000),
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"strength": strength,
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"parameters": {
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"width": width,
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"height": height
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}
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}
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# API request
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response = requests.post(API_URL, headers=headers, json=payload, timeout=timeout)
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if response.status_code != 200:
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print(f"Error: Failed to get image. Response status: {response.status_code}")
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raise gr.Error(f"{response.status_code}")
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try:
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# Convert to PNG
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image_bytes = response.content
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img = Image.open(io.BytesIO(image_bytes))
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# Create PNG in memory
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png_buffer = io.BytesIO()
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img.save(png_buffer, format="PNG")
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png_buffer.seek(0)
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png_image = Image.open(png_buffer)
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print(f'\033[1mGeneration {key} completed!\033[0m ({prompt})')
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return png_image
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except Exception as e:
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print(f"Error when trying to open the image: {e}")
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return None
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# CSS styling
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css = """
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#app-container {
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max-width: 800px;
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}
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"""
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# Gradio UI
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with gr.Blocks(theme='Nymbo/Nymbo_Theme', css=css) as app:
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gr.HTML("<center><h1>FLUX.1-Dev</h1></center>")
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with gr.Column(elem_id="app-container"):
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with gr.Row():
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with gr.Column(elem_id="prompt-container"):
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with gr.Row():
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text_prompt = gr.Textbox(
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label="Prompt",
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placeholder="Enter a prompt here",
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lines=2,
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elem_id="prompt-text-input"
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)
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with gr.Row():
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with gr.Accordion("Advanced Settings", open=False):
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negative_prompt = gr.Textbox(
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label="Negative Prompt",
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placeholder="What should not be in the image",
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value="(deformed, distorted, disfigured), poorly drawn, bad anatomy, wrong anatomy, extra limb, missing limb, floating limbs, (mutated hands and fingers), disconnected limbs, mutation, mutated, ugly, disgusting, blurry, amputation, misspellings, typos",
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lines=3,
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elem_id="negative-prompt-text-input"
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)
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with gr.Row():
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width = gr.Slider(label="Width", value=1024, minimum=64, maximum=1216, step=32)
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height = gr.Slider(label="Height", value=1024, minimum=64, maximum=1216, step=32)
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steps = gr.Slider(label="Sampling steps", value=35, minimum=1, maximum=100, step=1)
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cfg = gr.Slider(label="CFG Scale", value=7, minimum=1, maximum=20, step=1)
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strength = gr.Slider(label="Strength", value=0.7, minimum=0, maximum=1, step=0.001)
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seed = gr.Slider(label="Seed", value=-1, minimum=-1, maximum=1000000000, step=1)
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method = gr.Radio(
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label="Sampling method",
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value="DPM++ 2M Karras",
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choices=["DPM++ 2M Karras", "DPM++ SDE Karras", "Euler", "Euler a", "Heun", "DDIM"]
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)
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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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with gr.Row():
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image_output = gr.Image(type="pil", label="Image Output", elem_id="gallery")
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text_button.click(
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query,
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inputs=[text_prompt, negative_prompt, steps, cfg, method, seed, strength, width, height],
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outputs=image_output
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)
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# Launch the app
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app.launch(show_api=True, share=True)
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