app.py

import gradio as gr
import json
import requests

def avaliable_providers():
    providers = []
    
    headers = {
        "Content-Type": "application/json",
    }
    endpoint_url = "https://api.endpoints.huggingface.cloud/provider"
    response = requests.get(endpoint_url, headers=headers)

    for provider in response.json()['items']:
        if provider['status'] == 'available':
            providers.append(provider['vendor'])
    
    return providers   

def update_regions(provider):
    avalialbe_regions = []
    
    headers = {
        "Content-Type": "application/json",
    }
    endpoint_url = f"https://api.endpoints.huggingface.cloud/provider/{provider}/region"
    response = requests.get(endpoint_url, headers=headers)

    for region in response.json()['items']:
        if region['status'] == 'available':
            avalialbe_regions.append(f"{region['region']}/{region['label']}")

    return gr.Dropdown.update(
        choices=avalialbe_regions,
        value=avalialbe_regions[0] if len(avalialbe_regions) > 0 else None
    )

def update_compute_options(provider, region):
    region = region.split("/")[0]
    avalialbe_compute_options = []

    headers = {
        "Content-Type": "application/json",
    }
    endpoint_url = f"https://api.endpoints.huggingface.cloud/provider/{provider}/region/{region}/compute"
    print(endpoint_url)
    response = requests.get(endpoint_url, headers=headers)

    for compute in response.json()['items']:
        if compute['status'] == 'available':
            accelerator = compute['accelerator']
            numAccelerators = compute['numAccelerators']
            memoryGb = compute['memoryGb'].replace("Gi", "GB")
            architecture = compute['architecture']
            instanceType = compute['instanceType']
            
            type = f"{numAccelerators}vCPU {memoryGb} · {architecture}" if accelerator == "cpu" else f"{numAccelerators}x {architecture}"
            
            avalialbe_compute_options.append(
                f"{compute['accelerator'].upper()} [{compute['instanceSize']}] · {type} · {instanceType}"
            )

    return gr.Dropdown.update(
        choices=avalialbe_compute_options,
        value=avalialbe_compute_options[0] if len(avalialbe_compute_options) > 0 else None
    )

def submit(
    hf_token_input,
    endpoint_name_input,
    provider_selector,
    region_selector,
    repository_selector,
    revision_selector,
    task_selector,
    framework_selector,
    compute_selector,
    min_node_selector, 
    max_node_selector, 
    security_selector    
):
    compute_resources = compute_selector.split("·")
    accelerator = compute_resources[0][:3].strip()

    size_l_index = compute_resources[0].index("[") - 1
    size_r_index = compute_resources[0].index("]")
    size = compute_resources[0][size_l_index : size_r_index].strip()

    type = compute_resources[-1].strip()
    
    payload = {
      "accountId": repository_selector.split("/")[0],
      "compute": {
        "accelerator": accelerator.lower(),
        "instanceSize": size[1:],
        "instanceType": type,
        "scaling": {
          "maxReplica": int(max_node_selector),
          "minReplica": int(min_node_selector)
        }
      },
      "model": {
        "framework": "custom",
        "image": {
          "huggingface": {}
        },
        "repository": repository_selector.lower(),
        "revision": revision_selector,
        "task": task_selector.lower()
      },
      "name": endpoint_name_input.strip(),
      "provider": {
        "region": region_selector.split("/")[0].lower(),
        "vendor": provider_selector.lower()
      },
      "type": security_selector.lower()
    }
    
    print(payload)

    payload = json.dumps(payload)
    print(payload)

    headers = {
        "Authorization": f"Bearer {hf_token_input.strip()}",
        "Content-Type": "application/json",
    }
    endpoint_url = f"https://api.endpoints.huggingface.cloud/endpoint"
    print(endpoint_url)

    response = requests.post(endpoint_url, headers=headers, data=payload)
    if response.status_code == 400:
        return f"{response.text}. Malformed data in {payload}"
    elif response.status_code == 401:
        return "Invalid token"
    elif response.status_code == 409:
        return f"Error: {response.text}"
    elif response.status_code == 202:
        return f"Endpoint {endpoint_name_input} created successfully on {provider_selector.lower()} using {repository_selector.lower()}@{revision_selector}. \n Please check out the progress at https://ui.endpoints.huggingface.co/endpoints."
    else:
        return f"something went wrong {response.status_code} = {response.text}"

with gr.Blocks() as demo2:
    gr.Markdown(
    """
    ## Deploy Your Model on 🤗 Endpoint
    """)
    
    gr.Markdown("""
    #### Your 🤗 Access Token
    """)
    hf_token_input = gr.Textbox(
        show_label=False,
        type="password"
    )

    gr.Markdown("""    
    #### Decide the Endpoint name
    """)
    endpoint_name_input = gr.Textbox(
        show_label=False
    )    
        
    providers = avaliable_providers()

    with gr.Row():
        gr.Markdown("""    
        #### Cloud Provider
        """)

        gr.Markdown("""    
        #### Cloud Region
        """)       
    
    with gr.Row():
        provider_selector = gr.Dropdown(
            choices=providers,
            interactive=True,
            show_label=False,
        )
        
        region_selector = gr.Dropdown(
            [],
            value="",
            interactive=True,
            show_label=False,
        )
        
        provider_selector.change(update_regions, inputs=provider_selector, outputs=region_selector)

    with gr.Row():
        gr.Markdown("""    
        #### Target Model
        """)

        gr.Markdown("""    
        #### Target Model Version(branch)
        """)       
    
    with gr.Row():
        repository_selector = gr.Textbox(
            value="",
            interactive=True,
            show_label=False,
        )

        revision_selector = gr.Textbox(
            value="",
            interactive=True,
            show_label=False,
        )        

    with gr.Row():
        gr.Markdown("""    
        #### Task
        """)

        gr.Markdown("""    
        #### Framework
        """)      
    
    with gr.Row():
        task_selector = gr.Textbox(
            value="Custom",
            interactive=True,
            show_label=False,
        )

        framework_selector = gr.Textbox(
            value="Custom",
            interactive=True,
            show_label=False,
        )

    gr.Markdown("""
    
    #### Select Compute Instance Type
    """)    
    compute_selector = gr.Dropdown(
        [],
        value="",
        interactive=True,
        show_label=False,
    )
    region_selector.change(update_compute_options, inputs=[provider_selector, region_selector], outputs=compute_selector)

    with gr.Row():
        gr.Markdown("""    
        #### Min Number of Nodes
        """)

        gr.Markdown("""    
        #### Max Number of Nodes
        """)

        gr.Markdown("""    
        #### Security Level
        """)        
    
    with gr.Row():
        min_node_selector = gr.Number(
            value=1,
            interactive=True,
            show_label=False,
        )

        max_node_selector = gr.Number(
            value=1,
            interactive=True,
            show_label=False,
        )

        security_selector = gr.Radio(
            choices=["Protected", "Public", "Private"],
            value="Public",
            interactive=True,
            show_label=False,
        )
    
    submit_button = gr.Button(
        value="Submit",
    )

    status_txt = gr.Textbox(
        value="any status update will be displayed here",
        interactive=False
    )

    submit_button.click(
        submit, 
        inputs=[
            hf_token_input,
            endpoint_name_input,
            provider_selector,
            region_selector,
            repository_selector,
            revision_selector,
            task_selector,
            framework_selector,
            compute_selector,
            min_node_selector, 
            max_node_selector, 
            security_selector],
        outputs=status_txt)    

    gr.Markdown("""    
    #### Pricing Table(CPU) - 2023/2/22
    """)

    gr.Dataframe(
        headers=["provider", "size", "$/h", "vCPUs", "Memory", "Architecture"],
        datatype=["str", "str", "str", "number", "str", "str"],
        row_count=8,
        col_count=(6, "fixed"),
        value=[
            ["aws", "small", "$0.06", 1, "2GB", "Intel Xeon - Ice Lake"],
            ["aws", "medium", "$0.12", 2, "4GB", "Intel Xeon - Ice Lake"],
            ["aws", "large", "$0.24", 4, "8GB", "Intel Xeon - Ice Lake"],
            ["aws", "xlarge", "$0.48", 8, "16GB", "Intel Xeon - Ice Lake"],
            ["azure", "small", "$0.06", 1, "2GB", "Intel Xeon"],
            ["azure", "medium", "$0.12", 2, "4GB", "Intel Xeon"],
            ["azure", "large", "$0.24", 4, "8GB", "Intel Xeon"],
            ["azure", "xlarge", "$0.48", 8, "16GB", "Intel Xeon"],
        ]
    )

    gr.Markdown("""    
    #### Pricing Table(GPU) - 2023/2/22
    """)    

    gr.Dataframe(
        headers=["provider", "size", "$/h", "GPUs", "Memory", "Architecture"],
        datatype=["str", "str", "str", "number", "str", "str"],
        row_count=6,
        col_count=(6, "fixed"),
        value=[
            ["aws", "small", "$0.60", 1, "14GB", "NVIDIA T4"],
            ["aws", "medium", "$1.30", 1, "24GB", "NVIDIA A10G"],
            ["aws", "large", "$4.50", 4, "56GB", "NVIDIA T4"],
            ["aws", "xlarge", "$6.50", 1, "80GB", "NVIDIA A100"],
            ["aws", "xxlarge", "$7.00", 4, "96GB", "NVIDIA A10G"],
            ["aws", "xxxlarge", "$45.0", 8, "640GB", "NVIDIA A100"],
        ]
    )    

gr.TabbedInterface(
    [demo2], ["Deploy on 🤗 Endpoint"]
).launch(enable_queue=True)