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import os
import gradio as gr
import requests
# Get API key from environment variable
api_key = os.environ.get("NVCF_API_KEY")
if not api_key:
raise ValueError("Please set the NVCF_API_KEY environment variable.")
# API details
invoke_url = "https://api.nvcf.nvidia.com/v2/nvcf/pexec/functions/89848fb8-549f-41bb-88cb-95d6597044a4"
fetch_url_format = "https://api.nvcf.nvidia.com/v2/nvcf/pexec/status/"
headers = {
"Authorization": f"Bearer {api_key}",
"Accept": "application/json",
}
# Function to generate image using the API
def generate_image(prompt, negative_prompt, sampler, seed, guidance_scale, inference_steps):
payload = {
"prompt": prompt,
"negative_prompt": negative_prompt,
"sampler": sampler,
"seed": seed,
"guidance_scale": guidance_scale,
"inference_steps": inference_steps
}
session = requests.Session()
response = session.post(invoke_url, headers=headers, json=payload)
while response.status_code == 202:
request_id = response.headers.get("NVCF-REQID")
fetch_url = fetch_url_format + request_id
response = session.get(fetch_url, headers=headers)
response.raise_for_status()
response_body = response.json()
# Extract image URL from response
image_url = response_body.get("output").get("image_url")
return image_url
# Create Gradio interface
iface = gr.Interface(
fn=generate_image,
inputs=[
gr.Textbox(label="Prompt", placeholder="Describe the image you want to generate"),
gr.Textbox(label="Negative Prompt", placeholder="What should not be in the image"),
gr.Dropdown(label="Sampler", choices=["DPM", "DDPM", "PLMS"], value="DPM"),
gr.Number(label="Seed", value=0),
gr.Slider(label="Guidance Scale", minimum=0, maximum=20, value=5),
gr.Slider(label="Inference Steps", minimum=1, maximum=50, value=25)
],
outputs=gr.Image(label="Generated Image")
)
# Launch the Gradio app
iface.launch() |