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# This is a Gradio app that provides a simple interface to generate images and audio using HuggingFace Spaces.
import gradio as gr
import json
# Dictionary to store Gradio clients for different spaces
mcpServers = {
"gradio": {
"url": "https://inoculatemedia/SanaSprint.hf.space/gradio_api/mcp/sse"
},
"gradio": {
"url": "https://ysharma/Dia-1.6B.hf.space/gradio_api/mcp/sse"
}
}
# Function to get or create a Gradio client for the specified space
def get_client(space_id: str):
"""Get or create a Gradio client for the specified space.
Args:
space_id: HuggingFace Space ID to use
"""
if space_id not in mcpServers:
mcpServers[space_id] = {
"command": "npx",
"args": [
"mcp-remote",
mcpServers["gradio"]["url"],
"--transport",
"sse-only"
]
}
return mcpServers[space_id]
# Function to generate an image using a specified HuggingFace Space
def generate_image(prompt: str, space_id: str = "inoculatemedia/SanaSprint") -> str:
"""Generate an image using Flux.
Args:
prompt: Text prompt describing the image to generate
space_id: HuggingFace Space ID to use
"""
client = get_client(space_id)
result = client["command"](
prompt=prompt,
model_size="1.6B",
seed=0,
randomize_seed=True,
width=1024,
height=1024,
guidance_scale=4.5,
num_inference_steps=2,
api_name="/infer"
)
return result["image_url"]
# Function to perform text-to-speech synthesis using a specified HuggingFace Space
def run_dia_tts(prompt: str, space_id: str = "ysharma/Dia-1.6B") -> str:
"""Text-to-Speech Synthesis.
Args:
prompt: Text prompt describing the conversation between speakers S1, S2
space_id: HuggingFace Space ID to use
"""
client = get_client(space_id)
result = client["command"](
text_input=f"""{prompt}""",
audio_prompt_input=None,
max_new_tokens=3072,
cfg_scale=3,
temperature=1.3,
top_p=0.95,
cfg_filter_top_k=30,
speed_factor=0.94,
api_name="/generate_audio"
)
return result["audio_url"]
# Create a Gradio interface for generating images
image_interface = gr.Interface(
fn=generate_image,
inputs=[
gr.Textbox(label="Text Prompt"),
gr.Textbox(label="Space ID", value="inoculatemedia/SanaSprint")
],
outputs=gr.Image(label="Generated Image"),
title="Image Generation",
description="Generate images using a specified HuggingFace Space."
)
# Create a Gradio interface for text-to-speech synthesis
tts_interface = gr.Interface(
fn=run_dia_tts,
inputs=[
gr.Textbox(label="Text Prompt"),
gr.Textbox(label="Space ID", value="ysharma/Dia-1.6B")
],
outputs=gr.Audio(label="Generated Audio"),
title="Text-to-Speech Synthesis",
description="Generate audio from text using a specified HuggingFace Space."
)
# Combine the interfaces into a tabbed interface
with gr.Blocks() as demo:
with gr.Tab("Generate Image"):
image_interface.render()
with gr.Tab("Text-to-Speech"):
tts_interface.render()
# Launch the Gradio app
demo.launch(show_error=True, show_api=True) |