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Wauplin HF staff
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#!/usr/bin/env python
import json
import pathlib
import tempfile
from pathlib import Path
import gradio as gr
from gradio_client import Client
import user_history
client = Client("runwayml/stable-diffusion-v1-5")
def generate(prompt: str, profile: gr.OAuthProfile | None) -> tuple[str, list[str]]:
out_dir = client.predict(prompt, fn_index=1)
metadata = {
"prompt": prompt,
"negative_prompt": "",
"guidance_scale": 0.9,
}
with tempfile.NamedTemporaryFile(mode="w", suffix=".json", delete=False) as metadata_file:
json.dump(metadata, metadata_file)
with (pathlib.Path(out_dir) / "captions.json").open() as f:
paths = list(json.load(f).keys())
# Saving user history
for path in paths:
user_history.save_image(label=prompt, image=path, profile=profile, metadata=metadata)
return paths # type: ignore
with gr.Blocks(css="style.css") as demo:
with gr.Group():
prompt = gr.Text(show_label=False, placeholder="Prompt")
gallery = gr.Gallery(
show_label=False,
columns=2,
rows=2,
height="600px",
object_fit="scale-down",
)
prompt.submit(fn=generate, inputs=prompt, outputs=gallery)
with gr.Blocks() as demo_with_history:
with gr.Tab("Demo"):
demo.render()
with gr.Tab("Past generations"):
user_history.render()
with gr.Tab("README"):
gr.Markdown(Path("README.md").read_text().split("---")[-1])
if __name__ == "__main__":
demo_with_history.queue().launch()