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import gradio as gr
import torch
import os
import requests
import io
from PIL import Image
API_URL = "https://api-inference.huggingface.co/models/black-forest-labs/FLUX.1-dev"
headers = {"Authorization": "Bearer " + os.getenv("HF_TOKEN")}
def infer(prompt):
def query(payload):
response = requests.post(API_URL, headers=headers, json=payload)
return response.content
image_bytes = query({
"inputs": prompt,
})
with gr.Blocks() as demo:
with gr.Column(elem_id="col-container"):
gr.Markdown(" # Text-to-Image Gradio Template")
with gr.Row():
prompt = gr.Text(
label="Prompt",
show_label=False,
max_lines=1,
placeholder="Enter your prompt",
container=False,
)
run_button = gr.Button("Run", scale=0, variant="primary")
result = gr.Image(label="Result", show_label=False)
# Run inference when run_button is clicked
run_button.click(
infer,
inputs=[
prompt
],
outputs=[result],
)
if __name__ == "__main__":
demo.launch()
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