app.py

import gradio as gr
import json
import requests
import pandas as pd  

def update_task_options(framework):
    config = {
        "Custom":["Custom"],
        "Diffusers":["text-to-image"],
        "Transformers":[
            "text-classification", 
            "zero-shot-classification", 
            "token-classification", 
            "question-answering", 
            "fill-mask", 
            "summarization", 
            "translation", 
            "text2text-generation", 
            "text-generation", 
            "feature-extraction", 
            "image-classification", 
            "automatic-speech-recognition", 
            "audio-classification", 
            "object-detection", 
            "image-segmentation", 
            "table-question-answering"
        ]
    }
    return gr.Dropdown.update(
        choices=config[framework],
        value=config[framework][0] if len(config[framework]) > 0 else None
    )

def update_regions(provider):
    available_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':
            available_regions.append(f"{region['region']}/{region['label']}")

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

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

    headers = {
        "Content-Type": "application/json",
    }
    endpoint_url = f"https://api.endpoints.huggingface.cloud/provider/{provider}/region/{region}/compute"
    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}"
            
            available_compute_choices.append(
                f"{compute['accelerator'].upper()} [{compute['instanceSize']}] · {type} · {instanceType}"
            )

    return gr.Dropdown.update(
        choices=available_compute_choices,
        value=available_compute_choices[0] if len(available_compute_choices) > 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()
    }
    

    payload = json.dumps(payload)

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

def delete_endpoint(
    hf_token_input,
    endpoint_name_input
):
    response = requests.delete(
        f"https://api.endpoints.huggingface.cloud/endpoint/{endpoint_name_input}",
        headers = {
        "Authorization": f"Bearer {hf_token_input.strip()}",
        "Content-Type": "application/json",
    }
    )
    if response.status_code == 401:
        return "Invalid token"
    elif response.status_code == 404:
        return f"Error: {response.text}"
    elif response.status_code == 202 or response.status_code == 200:
        return f"Endpoint {endpoint_name_input} deleted successfully."
    else:
        return f"Something went wrong! - StatusCode:{response.status_code} - Error: {response.text}"

def get_all_endpoints(
    hf_token_input,
    method,
):
    response = requests.get(
            f"https://api.endpoints.huggingface.cloud/endpoint",
            headers = {
                "Authorization": f"Bearer {hf_token_input.strip()}",
                "Content-Type": "application/json",
            })
    if response.status_code == 401:
        if method == "info":
            return gr.DataFrame.update(
                value=pd.DataFrame({"Error":["Invalid Token -OR- No Endpoint Found !"]}),
        )
        else:
            return gr.Dropdown.update(
                value="Invalid token or No endpoints found!",
            )
    elif response.status_code == 200:
        endpoints_json = response.json()
        if method == "info":
            endpoints_df = pd.DataFrame(columns=["name", "model", "provider", "compute", "status", "minReplica", "maxReplica", "createdAt", "updatedAt"])
            for endpoint in endpoints_json["items"]:
                endpoints_df = endpoints_df.append({
                    "name": endpoint["name"],
                    "model": endpoint["model"]["repository"] + "@" + endpoint["model"]["revision"],
                    "provider": endpoint["provider"]["vendor"] + "/" + endpoint["provider"]["region"],
                    "compute": endpoint["compute"]["instanceType"] + "·" + endpoint["compute"]["instanceSize"] + " [" + endpoint["compute"]["accelerator"] + "]",
                    "status": endpoint["status"]["state"],
                    "minReplica": endpoint["compute"]["scaling"]["minReplica"],
                    "maxReplica": endpoint["compute"]["scaling"]["maxReplica"],
                    "createdAt": endpoint["status"]["createdAt"],
                    "updatedAt": endpoint["status"]["updatedAt"],
                }, ignore_index=True)
            endpoints_df.columns = ["Endpoint Name", "Model Name @ Revision", "Provider", "Instance Type", "Status", "Min Replica", "Max Replica", "Created At", "Updated At"]
            return gr.DataFrame.update(
                value=endpoints_df,
            )
        else:
            return gr.Dropdown.update( 
            choices=[endpoint["name"] for endpoint in endpoints_json["items"]],
            value=endpoints_json["items"][0]["name"],
        )

def update_endpoint(
    hf_token_input,
    endpoint_name_input,
    min_node_selector,
    max_node_selector,
    instance_type,
):
    payload ={
            "compute": {
                "instanceSize": instance_type.split("·")[0].split("[")[1].split("]")[0],
                "instanceType": instance_type.split("·")[-1].strip(),
                "scaling": {
                    "maxReplica": int(max_node_selector),
                    "minReplica": int(min_node_selector)
                    }
                }}
    payload = json.dumps(payload)
    response = requests.put(
            f"https://api.endpoints.huggingface.cloud/endpoint/{endpoint_name_input}",
            headers = {
            "Authorization": f"Bearer {hf_token_input.strip()}",
            "Content-Type": "application/json",
            },
            data=payload,
        )
    if response.status_code == 401:
        return "Invalid token"
    elif response.status_code == 404:
        return f"Error: {response.text}"
    elif response.status_code == 202 or response.status_code == 200:
        return f"Endpoint {endpoint_name_input} updated successfully."
    else:
        return f"Something went wrong! - StatusCode:{response.status_code} - Error: {response.text}"

def get_endpoint_logs(
    hf_token_input,
    endpoint_name_input,
):
    response = requests.get(
            f"https://api.endpoints.huggingface.cloud/endpoint/{endpoint_name_input}/logs",
            headers = {
                "Authorization": f"Bearer {hf_token_input.strip()}",
                "Content-Type": "application/json",
            })
    if response.status_code == 401:
        return "Invalid token or No logs found!"
    elif response.status_code == 200:
        return response.text
    elif response.status_code == 404:
        return f"Error: {response.text}"

with gr.Blocks() as interface:
    gr.Markdown("""
    #### Your 🤗 Access Token <span style="color:red;">(Required)</span>
    """)
    hf_token_input = gr.Textbox(
        show_label=False,
        placeholder="Your personal/organization Huggingface Access Token. Get it from (https://huggingface.co/settings/tokens)",
        type="password"
    )

    # Get All Endpoints Info
    with gr.Tab("Info"):
        gr.Markdown("""
        ### All Deployed Endpoints
        """)
        endpoints_table = gr.Dataframe(
            headers=["Endpoint Name", "Model Name", "Provider", "Instance Type", "Status", "Min Replica", "Max Replica", "Created At", "Updated At"],
            col_count=(9, "fixed"),
        )
        endpoint_info_button = gr.Button(value="Get Info")
    
    # Deploy Endpoint
    with gr.Tab("Deploy Endpoint"):
        gr.Markdown(
        """
        ### <br><center style="color:green">(Deploy Your Model on 🤗 Endpoint)</center>
        """)
        gr.Markdown("""    
        #### Endpoint Name
        """)
        endpoint_name_input = gr.Textbox(
            show_label=False
        )

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

            gr.Markdown("""    
            #### Cloud Region
            """)       
        
        with gr.Row():
            provider_selector = gr.Dropdown(
                choices=["aws", "azure"],
                value="",
                interactive=True,
                show_label=False,
            )
            
            region_selector = gr.Dropdown(
                [],
                value="",
                interactive=True,
                show_label=False,
            )
    
        with gr.Row():
            gr.Markdown("""    
            #### Target Model e.g (openai/whisper-tiny)
            """)

            gr.Markdown("""    
            #### Branch commit hash e.g (ada5a5d516772e41f9aeb0f984df6ecc4620001f)
            """)       
        
        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():
            framework_selector = gr.Dropdown(
                choices = ["Custom", "Diffusers", "Transformers"],
                value="",
                interactive=True,
                show_label=False,
            )

            task_selector = gr.Dropdown(
                [],
                value="",
                interactive=True,
                show_label=False,
            )

        gr.Markdown("""
        
        #### Select Compute Instance Type
        """)    
        compute_selector = gr.Dropdown(
            [],
            value="",
            interactive=True,
            show_label=False,
        )

        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"],
                value="Protected",
                interactive=True,
                show_label=False,
            )
        submit_button = gr.Button(
            value="Submit",
        )

        status_txt = gr.Textbox(
            value="status",
            interactive=False
        )

    # Update Endpoint
    with gr.Tab("Update Endpoint"):
        gr.Markdown("""
        ### <br><center style="color:green">(Update 🔁 Endpoint)</center>
        """)
        update_endpoint_info_button = gr.Button(value="Load Endpoints 🔃")
        with gr.Row():
            gr.Markdown("""    
            #### Cloud Provider
            """)

            gr.Markdown("""    
            #### Cloud Region
            """)      

        with gr.Row():
            update_provider_selector = gr.Dropdown(
                choices=["aws", "azure"],
                value="",
                interactive=True,
                show_label=False,
            )
            
            update_region_selector = gr.Dropdown(
                [],
                value="",
                interactive=True,
                show_label=False,
            )

        with gr.Row():
            gr.Markdown("""
            #### Endpoint Name
            """)
            gr.Markdown("""
            #### Instance Type
            """)

        with gr.Row():
            update_endpoint_name_input = gr.Dropdown(
                [],
                value="",
                show_label=False
            )
            update_compute_selector = gr.Dropdown(
                [],
                value="",
                interactive=True,
                show_label=False,
            )
        with gr.Row():
            gr.Markdown("""
            #### Min Number of Nodes
            """)
            gr.Markdown("""
            #### Max Number of Nodes
            """)
        with gr.Row():
            update_min_node_input = gr.Number(
                value=1,
                interactive=True,
                show_label=False,
            )
            
            update_max_node_input = gr.Number(
                value=1,
                interactive=True,
                show_label=False,
            )
        update_button = gr.Button(
            value="Update",
        )

        update_status_txt = gr.Textbox(
            value="status",
            interactive=False
        )

    # Delete Endpoint
    with gr.Tab("Delete Endpoint"):
        gr.Markdown("""
        ### <br><center style="color:green">(Delete 🗑️ Endpoint)</center>
        """)
        delete_endpoint_info_button = gr.Button(value="Load Endpoints 🔃")
        gr.Markdown("""    
        #### Endpoint Name
        """)
        delete_endpoint_name_input = gr.Dropdown(
            [],
            value="",
            show_label=False
        )
        delete_button = gr.Button(
            value="Delete",
        )

        delete_status_txt = gr.Textbox(
            value="status",
            interactive=False
        )

    # Endpoint logs
    with gr.Tab("Endpoint Logs"):
        gr.Markdown("""
        ### <br><center style="color:green">(Endpoint 📖 Logs)</center>
        """)
        endpoint_logs_load_button = gr.Button(value="Load Endpoints 🔃")
        gr.Markdown("""
        #### Endpoint Name
        """)
        endpoint_logs_selector = gr.Dropdown(
            [],
            value="",
            show_label=False
        )
        endpoint_logs = gr.Textbox(
            value="",
            interactive=False
        )
        endpoint_logs_button = gr.Button(value="Get Logs")

    # Pricing Table
    with gr.Tab("Pricing Table"):
        gr.Markdown("""
            ### <br><center style="color:green">(Instance Pricing Table)</center>
            #### 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"],
            ]
        )    

    # Info Tab Events
    endpoint_info_button.click(
            get_all_endpoints, 
            inputs=[hf_token_input, gr.TextArea(value="info", interactive=False, visible=False)], 
            outputs=endpoints_table
        )

    # Deploy Tab Events
    framework_selector.change(update_task_options, inputs=framework_selector, outputs=task_selector)
    provider_selector.change(update_regions, inputs=provider_selector, outputs=region_selector)
    region_selector.change(update_compute_options, inputs=[provider_selector, region_selector], outputs=compute_selector)
    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)

    # Update Tab Events
    update_endpoint_info_button.click(
        get_all_endpoints, 
        inputs=[hf_token_input, gr.TextArea(value="update", interactive=False, visible=False)], 
        outputs=update_endpoint_name_input
        )
    update_provider_selector.change(update_regions, inputs=update_provider_selector, outputs=update_region_selector)
    update_region_selector.change(update_compute_options, inputs=[update_provider_selector, update_region_selector], outputs=update_compute_selector)
    update_button.click(
        update_endpoint,
        inputs=[
            hf_token_input,
            update_endpoint_name_input,
            update_min_node_input,
            update_max_node_input,
            update_compute_selector
        ],
        outputs=update_status_txt
    )

    # Delete Tab Events
    delete_endpoint_info_button.click(
        get_all_endpoints,
        inputs=[hf_token_input, gr.TextArea(value="delete", interactive=False, visible=False)],
        outputs=delete_endpoint_name_input
    )
    delete_button.click(
            delete_endpoint,
            inputs=[
                hf_token_input,
                delete_endpoint_name_input
            ],
            outputs=delete_status_txt
        )

    # Endpoint Logs Tab Events
    endpoint_logs_load_button.click(
        get_all_endpoints,
        inputs=[hf_token_input, gr.TextArea(value="logs", interactive=False, visible=False)],
        outputs=endpoint_logs_selector
    )
    endpoint_logs_button.click(
        get_endpoint_logs,
        inputs=[
            hf_token_input,
            endpoint_logs_selector
        ],
        outputs=endpoint_logs
    )
#interface.queue(concurrency_count=5)
interface.launch()