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import gradio as gr
import replicate
import os
import requests
from PIL import Image
from io import BytesIO
examples = [
"Astronaut in a jungle, cold color palette, muted colors, detailed, 8k",
"An astronaut riding a green horse",
"A delicious ceviche cheesecake slice",
]
css="""
#col-container {
margin: 0 auto;
max-width: 640px;
}
"""
def generate_image(prompt, api_key):
# Set the API key for the current session
os.environ["REPLICATE_API_TOKEN"] = api_key
# Prepare the input for the model
inputs = {
"prompt": prompt,
"prompt_upsampling": True
}
# Run the model and get the output URL
output_url = replicate.run(
"black-forest-labs/flux-1.1-pro",
input=inputs
)
# Fetch the image from the URL
response = requests.get(output_url)
image = Image.open(BytesIO(response.content))
# Return the image
return image
with gr.Blocks(css=css) as demo:
with gr.Column(elem_id="col-container"):
gr.Markdown(f"""
# FLUX 1.1 Pro Text-to-Image Generator
""")
with gr.Row():
with gr.Column():
api_key = gr.Text(
label="Replicate API Key",
show_label=False,
max_lines=1,
placeholder="Enter your Replicate API key...",
container=False,
type="password",
)
prompt = gr.Text(
label="Prompt",
show_label=False,
max_lines=1,
placeholder="Enter your prompt",
container=False,
)
run_button = gr.Button("Run", scale=0)
result = gr.Image(label="Result", show_label=False)
gr.Examples(
examples = examples,
inputs = [prompt]
)
gr.on(
triggers=[run_button.click, prompt.submit],
fn = generate_image,
inputs = [prompt, api_key],
outputs = [result,]
)
demo.queue().launch() |