app.py

import gradio as gr
from gradio_huggingfacehub_search import HuggingfaceHubSearch
import requests

processed_inputs = {}

def process_inputs(markdown, model_id, q_method, email, oauth_token: gr.OAuthToken | None, profile: gr.OAuthProfile | None):
    if oauth_token is None or oauth_token.token is None or profile.username is None:
        return "##### You must be logged in to use this service."

    if not model_id or not q_method or not email:
        return "##### All fields are required!"
    
    input_hash = hash((model_id, q_method, oauth_token.token, profile.username))

    if input_hash in processed_inputs and processed_inputs[input_hash] == 200:
        return "##### This request has already been submitted successfully. Please do not submit the same request multiple times."

    url = "https://sdk.nexa4ai.com/task"

    data = {
        "repository_url": f"https://huggingface.co/{model_id}",
        "username": profile.username,
        "access_token": oauth_token.token,
        "email": email,
        "quantization_option": q_method,
    }
    
    response = requests.post(url, json=data)
    
    if response.status_code == 200:
        processed_inputs[input_hash] = 200  
        return "##### Your request has been submitted successfully. We will notify you by email once processing is complete. There is no need to submit the same request multiple times."
    else:
        processed_inputs[input_hash] = response.status_code 
        return f"##### Failed to submit request: {response.text}"

iface = gr.Interface(
    fn=process_inputs,
    inputs=[
        gr.Markdown(value="##### 🔔   You must grant access to the model repository before use."),
        HuggingfaceHubSearch(
            label="Hub Model ID",
            placeholder="Search for model id on Huggingface",
            search_type="model",
        ),
        gr.Dropdown(
            ["q2_K", "q3_K", "q3_K_S", "q3_K_M", "q3_K_L", "q4_0", "q4_1", "q4_K", "q4_K_S", "q4_K_M", "q5_0", "q5_1", "q5_K", "q5_K_S", "q5_K_M", "q6_K", "q8_0", "f16"],
            label="Quantization Option",
            info="GGML quantisation options",
            value="q4_0",
            filterable=False
        ),
        gr.Textbox(label="Email", placeholder="Enter your email here")
    ],
    outputs = gr.Markdown(
        label="output", 
        value="##### Please enter the model URL, select a quantization method, and provide your email address."
    ),
    title="Create your own GGUF Quants, blazingly fast ⚡!",
    allow_flagging="never"
)

head = f"""
<script async src="https://www.googletagmanager.com/gtag/js?id=G-55J2KVJH6R"></script>
<script>
  window.dataLayer = window.dataLayer || [];
  function gtag(){{dataLayer.push(arguments);}}
  gtag('js', new Date());
  gtag('config', 'G-55J2KVJH6R');
</script>
"""

theme = gr.themes.Base(text_size="lg")
with gr.Blocks(theme=theme, head=head) as demo:
    gr.Markdown(value="### 🔔   You must be logged in to use this service.")
    gr.LoginButton(min_width=250)
    iface.render()

demo.launch(share=True)