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| import gradio as gr | |
| import requests | |
| import os | |
| API_URL = "https://fal.run/fal-ai/dia-tts" | |
| headers = {"Authorization": f"Bearer {os.getenv('HF_TOKEN')}"} | |
| def query(text): | |
| payload = {"text": text} | |
| response = requests.post(API_URL, headers=headers, json=payload) | |
| if response.status_code != 200: | |
| return f"β Error: {response.status_code} - {response.text}" | |
| return response.json() | |
| with gr.Blocks(fill_height=True) as demo: | |
| with gr.Sidebar(): | |
| gr.Markdown("# Inference Provider") | |
| gr.Markdown("This Space showcases the nari-labs/Dia-1.6B model, served by the fal-ai API. Sign in with your Hugging Face account to use this API.") | |
| gr.Markdown("π Make sure your Hugging Face access token is available in the environment.") | |
| with gr.Row(): | |
| inp = gr.Textbox(label="Input your text", placeholder="Type something...") | |
| out = gr.Textbox(label="Response") | |
| submit_btn = gr.Button("Submit") | |
| submit_btn.click(fn=query, inputs=inp, outputs=out) | |
| print("TOKEN LOADED:", os.getenv("HF_TOKEN")) | |
| demo.launch() |