### Install ModelsLab Go SDK

Source: https://docs.modelslab.com/sdk/golang

Initialize your Go project and install the ModelsLab SDK using go mod.

```bash
go mod init your-project
go get github.com/modelslab/modelslab-go
```

--------------------------------

### System Details Request Example

Source: https://docs.modelslab.com/enterprise-api/image-to-video-ultra/system-details

Send a POST request to the system_details endpoint to get information about your server. Requires an enterprise API key for authorization.

```bash
--request POST 'https://modelslab.com/api/v1/enterprise/image_to_video_ultra/system_details' \
```

--------------------------------

### Install ModelsLab SDK

Source: https://docs.modelslab.com/sdk/typescript

Commands to install the SDK using npm or yarn.

```bash
npm install modelslab
```

```bash
yarn add modelslab
```

--------------------------------

### Quick Start Image Generation

Source: https://docs.modelslab.com/sdk/typescript

Basic example for generating an image using the Community API.

```javascript
import { Client, Community } from "modelslab";

const client = new Client("your-api-key");
const community = new Community(client.key);

const result = await community.textToImage({
  key: client.key,
  prompt: "A beautiful sunset over mountains, photorealistic, 8k",
  model_id: "flux",
  width: 512,
  height: 512,
  samples: 1,
  num_inference_steps: 30,
  guidance_scale: 7.5
});

if (result.status === "success") {
  console.log("Generated image:", result.output[0]);
} else if (result.status === "processing") {
  console.log("Processing, request ID:", result.id);
}
```

--------------------------------

### ModelsLab CLI Examples

Source: https://docs.modelslab.com/guides/model-selection

Command-line interface examples for various ModelsLab operations, including image generation, chat interactions, video generation, and configuration settings.

```bash
# Generate image with specific model
modelslab generate image --prompt "sunset over mountains" --model flux

# Chat with an LLM
modelslab generate chat --message "Explain AI" --model meta-llama-3-8B-instruct

# Generate video
modelslab generate video --prompt "ocean waves" --model seedance-t2v

# Set a default model
modelslab config set generation.default_model flux
```

--------------------------------

### Install ModelQ via Package Managers

Source: https://docs.modelslab.com/open-source/modelq/installation

Use these commands to install the ModelQ library in your Python environment.

```bash
pip install modelq
```

```bash
pip install git+https://github.com/ModelsLab/modelq.git
```

--------------------------------

### Install ModelsLab Skills

Source: https://docs.modelslab.com/agent-skills

Command to install all available ModelsLab skills via npx.

```bash
npx skills add modelslab/skills --all
```

--------------------------------

### Get ModelQ CLI Version

Source: https://docs.modelslab.com/open-source/modelq/usage

Prints the currently installed version of the ModelQ command-line interface.

```bash
modelq version
```

--------------------------------

### Update Server Request Example (Java)

Source: https://docs.modelslab.com/enterprise-api/image-to-video-ultra/update-server

A Java example using OkHttp to send a POST request for updating your dedicated server. Remember to insert your enterprise API key.

```java
OkHttpClient client = new OkHttpClient().newBuilder()
  .build();
MediaType mediaType = MediaType.parse("application/json");
RequestBody body = RequestBody.create(mediaType, "{\n    \"key\": \"\"\n}");
Request request = new Request.Builder()
  .url("https://modelslab.com/api/v1/enterprise/image_to_video_ultra/update_server")
  .method("POST", body)
  .addHeader("Content-Type", "application/json")
  .build();
Response response = client.newCall(request).execute();
```

--------------------------------

### Wallet Balance Response Example

Source: https://docs.modelslab.com/agents-api/billing-and-wallet

Example JSON response for a wallet balance check, including the current balance and currency.

```json
{
  "data": {
    "balance": 75.50,
    "currency": "USD"
  },
  "error": null,
  "meta": {
    "request_id": "..."
  }
}
```

--------------------------------

### Install ModelsLab Python SDK

Source: https://docs.modelslab.com/sdk/python

Use pip to install the package. Requires Python 3.7 or higher.

```bash
pip install modelslab_py
```

--------------------------------

### System Details API Response Example

Source: https://docs.modelslab.com/enterprise-api/image-to-video-ultra/system-details

Example response from the system_details endpoint, indicating no images are currently queued for processing.

```json
{
  "model_count": 0,
  "queue_time": 0,
  "status": "ok"
}
```

--------------------------------

### ControlNet Normal API Example (SD 1.5)

Source: https://docs.modelslab.com/image-generation/controlnet/controlnet-main

Example for using the ControlNet Normal model. This requires an init_image and your API key. It's useful for controlling surface details and lighting.

```json
{
  "key": "your_api_key",
  "controlnet_model": "normal",
  "controlnet_type": "normal",
  "model_id": "realistic-vision-51",
  "auto_hint": "yes",
  "guess_mode": "no",
  "prompt": "a woman, posing",
  "negative_prompt": null,
  "init_image": "https://images-ext-1.discordapp.net/external/ZOjUvfZxcvlnt84xav_fDdIzXPuuMXcW9fA46OaZSTs/https/i.pinimg.com/736x/9d/09/ff/9d09ff904e082395f71aa12f5c83ea77.jpg",
  "mask_image": null,
  "width": "512",
  "height": "512",
  "samples": "1",
  "scheduler": "UniPCMultistepScheduler",
  "num_inference_steps": "30",
  "safety_checker": "no",
  "enhance_prompt": "yes",
  "guidance_scale": 7.5,
  "strength": 0.55,
  "seed": null,
  "webhook": null
}
```

--------------------------------

### Restart Server Implementation Examples

Source: https://docs.modelslab.com/enterprise-api/image-to-video-ultra/restart-server

Language-specific implementations for the restart server endpoint.

```javascript
var myHeaders = new Headers();myHeaders.append("Content-Type", "application/json");var raw = JSON.stringify({ "key": ""});var requestOptions = {  method: 'POST',  headers: myHeaders,  body: raw,  redirect: 'follow'};fetch("https://modelslab.com/api/v1/enterprise/image_to_video_ultra/restart_server", requestOptions)  .then(response => response.text())  .then(result => console.log(result))  .catch(error => console.log('error', error));
```

```php
<?php$payload = [  "key" => ""];$curl = curl_init();curl_setopt_array($curl, array(  CURLOPT_URL => 'https://modelslab.com/api/v1/enterprise/image_to_video_ultra/restart_server',  CURLOPT_RETURNTRANSFER => true,  CURLOPT_ENCODING => '',  CURLOPT_MAXREDIRS => 10,  CURLOPT_TIMEOUT => 0,  CURLOPT_FOLLOWLOCATION => true,  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,  CURLOPT_CUSTOMREQUEST => 'POST',  CURLOPT_POSTFIELDS => json_encode($payload),  CURLOPT_HTTPHEADER => array(    'Content-Type: application/json'  ),));$response = curl_exec($curl);curl_close($curl);echo $response;
```

```javascript
var request = require('request');var options = {  'method': 'POST',  'url': 'https://modelslab.com/api/v1/enterprise/image_to_video_ultra/restart_server',  'headers': {    'Content-Type': 'application/json'  },  body: JSON.stringify({    "key": ""  })};request(options, function (error, response) {  if (error) throw new Error(error);  console.log(response.body);});
```

```python
import requestsimport jsonurl = "https://modelslab.com/api/v1/enterprise/image_to_video_ultra/restart_server"payload = json.dumps({ "key": ""})headers = {  'Content-Type': 'application/json'}response = requests.request("POST", url, headers=headers, data=payload)print(response.text)
```

```java
OkHttpClient client = new OkHttpClient().newBuilder()  .build();MediaType mediaType = MediaType.parse("application/json");RequestBody body = RequestBody.create(mediaType, "{\n    \"key\": \"\"\n}");Request request = new Request.Builder()  .url("https://modelslab.com/api/v1/enterprise/image_to_video_ultra/restart_server")  .method("POST", body)  .addHeader("Content-Type", "application/json")  .build();Response response = client.newCall(request).execute();
```

--------------------------------

### Example Good Captions for Song Generation

Source: https://docs.modelslab.com/guides/song-generation-guide

These examples demonstrate how to combine style, emotion, instruments, and other dimensions to create detailed and effective captions for song generation.

```text
A modern reggaeton track with strong flamenco influence, featuring female vocal with reverb,
deep sub-bass, crisp percussion, and plucked synth guitar riff
```

```text
Lo-fi hip-hop beat with warm vinyl crackle, mellow piano chords, subtle jazz drums,
and atmospheric pad textures
```

```text
80s synthwave pop with bright synth leads, punchy drum machine, nostalgic atmosphere,
and powerful female vocals
```

--------------------------------

### Initialize Community API

Source: https://docs.modelslab.com/sdk/python

Setup the client for accessing community fine-tuned models.

```python
from modelslab_py.core.client import Client
from modelslab_py.core.apis.community import Community
from modelslab_py.schemas.community import Text2Image, Image2Image, Inpainting, ControlNet

client = Client(api_key="your_api_key")
api = Community(client=client, enterprise=False)
```

--------------------------------

### ControlNet Depth API Example (SD 1.5)

Source: https://docs.modelslab.com/image-generation/controlnet/controlnet-main

This example demonstrates using the ControlNet Depth model for image generation. Provide your API key and an init_image for depth-based control.

```json
{
  "key": "your_api_key",
  "controlnet_model": "depth",
  "controlnet_type": "depth",
  "model_id": "realistic-vision-51",
  "auto_hint": "yes",
  "guess_mode": "no",
  "prompt": "baby, smiling",
  "negative_prompt": null,
  "init_image": "https://img.freepik.com/free-photo/adorable-baby-boy-smiling-camera-blurred-background_132075-10819.jpg",
  "mask_image": null,
  "width": "512",
  "height": "512",
  "samples": "1",
  "scheduler": "UniPCMultistepScheduler",
  "num_inference_steps": "30",
  "safety_checker": "no",
  "enhance_prompt": "yes",
  "guidance_scale": 7.5,
  "strength": 0.55,
  "seed": null,
  "webhook": null,
  "track_id": null
}
```

--------------------------------

### Install ModelsLab PHP SDK

Source: https://docs.modelslab.com/sdk/php

Methods to add the SDK to your project via Composer.

```bash
composer require modelslab/php
```

```json
{
    "require": {
        "modelslab/php": "^1.0.2"
    }
}
```

--------------------------------

### ControlNet Canny API Example (SD 1.5)

Source: https://docs.modelslab.com/image-generation/controlnet/controlnet-main

Use this example to generate images with ControlNet using the Canny edge detection model. Ensure you have a valid API key and provide an init_image.

```json
{
  "key": "your_api_key",
  "controlnet_model": "canny",
  "controlnet_type": "canny",
  "model_id": "realistic-vision-51",
  "auto_hint": "yes",
  "guess_mode": "no",
  "prompt": "a girl, wearing red bikini, looking at camera, ocean in background",
  "negative_prompt": "human, unstructure, (black object, white object), colorful background, nsfw",
  "init_image": "https://pub-3626123a908346a7a8be8d9295f44e26.r2.dev/livewire-tmp/qyA2waUVja192VOgQ3WwIRuKxJzRpA-metaZDc3NTFmOGE3NjgxYzA4MGQ1Yjg3NjA2ZjFlYzU1YTMuanBn-.jpg",
  "mask_image": null,
  "width": "512",
  "height": "512",
  "samples": "1",
  "scheduler": "UniPCMultistepScheduler",
  "num_inference_steps": "30",
  "safety_checker": "no",
  "enhance_prompt": "yes",
  "guidance_scale": 7.5,
  "strength": 0.55,
  "seed": null,
  "webhook": null,
  "track_id": null
}
```

--------------------------------

### Initialize Video API Client

Source: https://docs.modelslab.com/sdk/python

Sets up the client and API instance for video generation operations. Requires an API key.

```python
from modelslab_py.core.client import Client
from modelslab_py.core.apis.video import Video

client = Client(api_key="your_api_key")
api = Video(client=client, enterprise=False)
```

--------------------------------

### Initialize API Instances

Source: https://docs.modelslab.com/sdk/typescript

Create instances for different API services using the client key.

```javascript
import { Community, Audio, Video, ImageEditing } from "modelslab";

// Create instances with your API key
const community = new Community(client.key);
const audio = new Audio(client.key);
const video = new Video(client.key);
const imageEditing = new ImageEditing(client.key);
```

--------------------------------

### Workflow Request Body Example

Source: https://docs.modelslab.com/workflows-api/run-workflow

Provide workflow parameters in the request body. Use the Get Workflow Schema endpoint to discover available parameters for your specific workflow.

```json
{
  "prompt": "A beautiful sunset over mountains",
  "negative_prompt": "blurry, low quality",
  "width": 1024,
  "height": 1024
}
```

--------------------------------

### Create Stripe SetupIntent

Source: https://docs.modelslab.com/agents-api/billing-and-wallet

Creates a Stripe SetupIntent for headless card tokenization, allowing for secure saving of payment methods.

```APIDOC
## POST /api/agents/v1/billing/setup-intent

### Description
Initiates a Stripe SetupIntent, which is used to securely collect and save a customer's payment details for future use. This is part of the headless card tokenization flow.

### Method
POST

### Endpoint
/api/agents/v1/billing/setup-intent

### Auth
Bearer token

### Response
#### Success Response (200)
- **client_secret** (string) - The client secret for the SetupIntent, used to confirm the setup on the client side.

#### Response Example
{
  "client_secret": "seti_1JfPKxSDo1BGXG2x..._secret_...
}
```

--------------------------------

### Initialize Basic Go Client

Source: https://docs.modelslab.com/sdk/golang

Create a new ModelsLab client instance using only your API key.

```go
import "github.com/modelslab/modelslab-go/pkg/client"

// Simple client
c := client.New("your-api-key")
```

--------------------------------

### Configure Client

Source: https://docs.modelslab.com/sdk/typescript

Methods for initializing the client with API keys and custom settings.

```javascript
import { Client } from "modelslab";

// Method 1: Direct API key
const client = new Client("your-api-key");

// Method 2: Environment variable
// Reads from process.env.API_KEY when called without args
const clientFromEnv = new Client();

// Method 3: With custom settings
// new Client(apiKey, retries, timeoutSeconds)
const clientCustom = new Client("your-api-key", 5, 10);
```

--------------------------------

### Get Uploaded Voices

Source: https://docs.modelslab.com/voice-cloning/voice-list

Allows you to get a list of all uploaded voices associated with your account.

```APIDOC
## POST /voice/voice_list

### Description
Retrieves all uploaded voices for the account.

### Method
POST

### Endpoint
/api/v6/voice/voice_list

### Parameters
#### Request Body
- **key** (string) - Required - Your API Key used for request authorization
- **type** (string) - Optional - Type of voices to retrieve. Allowed values: "manual", "trained", "voice_cover". Defaults to "manual".

### Request Example
```json
{
    "key": "YOUR_API_KEY",
    "type": "trained"
}
```

### Response
#### Success Response (200)
- **status** (string) - Status of the request. Enum: "success", "error".
- **voices** (array) - Array of available voices. Each voice object contains:
  - **voice_id** (string) - Unique identifier for the voice.
  - **name** (string) - Display name of the voice.
  - **language** (string) - Language of the voice.

#### Response Example
```json
{
  "status": "success",
  "voices": [
    {
      "voice_id": "123e4567-e89b-12d3-a456-426614174000",
      "name": "Example Voice",
      "language": "en-US"
    }
  ]
}
```

#### Error Response (400)
- **status** (string) - Status of the request. Must be "error".
- **message** (string) - Error message description.

#### Error Response Example
```json
{
  "status": "error",
  "message": "Invalid API Key"
}
```
```

--------------------------------

### Initialize Video API Client

Source: https://docs.modelslab.com/sdk/dart

Instantiate the client with your API key and then create a Video API instance.

```dart
import 'package:modelslab/core/apis/video.dart';
import 'package:modelslab/core/apis/base.dart';
import 'package:modelslab/schemas/video.dart';
import 'package:modelslab/core/client.dart';

var client = Client(key: "Your api key");
var api = Video(client: client);
```

--------------------------------

### Payment link response example

Source: https://docs.modelslab.com/agents-api/billing-and-wallet

Example JSON response returned when creating a payment link.

```json
{
  "payment_url": "https://checkout.stripe.com/c/pay/cs_live_...",
  "session_id": "cs_live_...",
  "purpose": "fund",
  "amount": 25,
  "expires_at": "2026-02-20T12:30:00Z",
  "instructions": "Forward this URL to the user. They will complete payment on Stripe's hosted checkout page. After payment, they are redirected to ModelsLab's success page where the session_id is displayed for copy-to-clipboard. Use the session_id to confirm the payment via POST /wallet/confirm-checkout or POST /subscriptions/confirm-checkout."
}
```

--------------------------------

### Serve ModelQ API via CLI

Source: https://docs.modelslab.com/open-source/modelq/usage

Starts a FastAPI server to enable task submission to ModelQ over HTTP. Configure host, port, and log level as needed.

```bash
modelq serve-api --app-path main:modelq_app --host 0.0.0.0 --port 8000 --log-level info
```

--------------------------------

### Manage ModelsLab Skills via CLI

Source: https://docs.modelslab.com/agent-skills

Use these commands to install all skills, specific skills, or list available options.

```bash
# Install all ModelsLab skills
npx skills add modelslab/skills --all

# Install a specific skill
npx skills add modelslab/skills --skill modelslab-image-generation

# List available skills
npx skills add modelslab/skills --list
```

--------------------------------

### Chat Completion API (Python Example)

Source: https://docs.modelslab.com/guides/model-selection

Example of how to use the Chat Completion API with Python requests.

```Python
import requests

response = requests.post(
    "https://modelslab.com/api/v7/llm/chat/completions",
    json={
        "key": "your_api_key",
        "model_id": "meta-llama-3-8B-instruct",
        "messages": [
            {"role": "system", "content": "You are a helpful assistant."},
            {"role": "user", "content": "Explain quantum computing briefly."}
        ],
        "max_tokens": 200,
        "temperature": 0.7
    }
)

data = response.json()
print(data["choices"][0]["message"]["content"])
```

--------------------------------

### Initialize Go Client with Custom Configuration

Source: https://docs.modelslab.com/sdk/golang

Configure the ModelsLab client with custom settings including API key, base URL, and timeouts.

```go
import (
	"time"
	"github.com/modelslab/modelslab-go/pkg/client"
)

config := &client.Config{
	APIKey:       "your-api-key",
	BaseURL:      "https://modelslab.com/api/",
	FetchRetry:   10,
	FetchTimeout: 2 * time.Second,
	HTTPTimeout:  30 * time.Second,
}

c := client.NewWithConfig(config)
```

--------------------------------

### Install Skills to Specific Agents

Source: https://docs.modelslab.com/agent-skills

Target specific MCP-compatible agents like Claude Code or Cursor during the installation process.

```bash
npx skills add modelslab/skills --all -a claude-code -a cursor
```

--------------------------------

### POST /text-to-video-ultra/system_details

Source: https://docs.modelslab.com/enterprise-api/text-to-video-ultra/system-details

Retrieve system details by sending a POST request with your API key.

```APIDOC
## POST /text-to-video-ultra/system_details

### Description
This endpoint returns information about your server.

### Method
POST

### Endpoint
https://modelslab.com/api/v1/enterprise/text-to-video-ultra/system_details

### Request Body
- **key** (string) - Required - Your API key

### Request Example
```json
{
    "key": "enterprise_api_key"
}
```

### Response
#### Success Response (200)
- **status** (string) - Indicates the status of the operation (e.g., "success").
- **message** (string) - A message describing the outcome of the operation.

#### Error Response (401)
- **status** (string) - Indicates the status of the error (e.g., "error").
- **message** (string) - A message describing the error (e.g., "Invalid API Key").

#### Response Example
```json
{
  "status": "success",
  "message": "Operation completed successfully"
}
```
```

--------------------------------

### Update Server Response Example

Source: https://docs.modelslab.com/enterprise-api/image-to-video-ultra/update-server

This is an example of a successful response when updating your dedicated server. It indicates the server is being updated and the operation was successful.

```json
{
  "message": "server updating",
  "status": "success"
}
```

--------------------------------

### Magic Mix API Request Example

Source: https://docs.modelslab.com/enterprise-api/image-editing/magic-mix

This is an example of a cURL request to the Magic Mix endpoint. Ensure your API key is included for authorization.

```curl
curl --request POST 'https://modelslab.com/api/v1/enterprise/image_editing/magic_mix' \

```

--------------------------------

### Wallet Transactions Response Example

Source: https://docs.modelslab.com/agents-api/billing-and-wallet

Example JSON response structure for wallet transactions, showing item details, counts, and wallet summary.

```json
{
  "data": {
    "items": [
      {
        "id": 456,
        "source": "stripe",
        "transaction_id": "pi_xxx",
        "type": "credit",
        "amount": 25.00,
        "status": "success",
        "usecase": "wallet_funding",
        "created_at": "2026-02-15T10:00:00Z"
      }
    ],
    "count": 1,
    "total": 12,
    "wallet": {
      "balance": 75.50,
      "currency": "USD",
      "total_credited": 150.00,
      "amount_used": 74.50
    }
  },
  "error": null,
  "meta": {
    "request_id": "..."
  }
}
```

--------------------------------

### Fetch System Details using Java

Source: https://docs.modelslab.com/enterprise-api/image-to-video-ultra/system-details

Implement the system_details request in Java using OkHttpClient. The request body must be created with MediaType set to application/json.

```java
OkHttpClient client = new OkHttpClient().newBuilder()
  .build();
MediaType mediaType = MediaType.parse("application/json");
RequestBody body = RequestBody.create(mediaType, "{\n    \"key\": \"\"\n}");
Request request = new Request.Builder()
  .url("https://modelslab.com/api/v1/enterprise/image_to_video_ultra/system_details")
  .method("POST", body)
  .addHeader("Content-Type", "application/json")
  .build();
Response response = client.newCall(request).execute();
```

--------------------------------

### ControlNet for Guided Image Generation

Source: https://docs.modelslab.com/sdk/python

Generate images guided by a control image and a specified ControlNet model (e.g., Canny, depth, pose).

```python
schema = ControlNet(
    model_id="flux",
    controlnet_model="canny",  # canny, depth, pose, etc.
    controlnet_image="https://example.com/control-image.jpg",
    prompt="A beautiful house, photorealistic",
    width=512,
    height=512
)
response = api.controlnet(schema)
```

--------------------------------

### Text-to-Video Generation with Go

Source: https://docs.modelslab.com/sdk/golang

Create a video from a text prompt using the specified model. Ensure the client is initialized with your API key.

```go
package main

import (
	"context"
	"encoding/json"
	"fmt"

	"github.com/modelslab/modelslab-go/pkg/apis/video"
	"github.com/modelslab/modelslab-go/pkg/client"
	videoSchema "github.com/modelslab/modelslab-go/pkg/schemas/video"
)

func main() {
	c := client.New("your-api-key")
	videoAPI := video.New(c, false)

	req := videoSchema.Text2VideoRequest{
		Prompt:  "A cat playing with a ball in a sunny garden",
		ModelID: "cogvideox",
	}

	resp, err := videoAPI.TextToVideo(context.Background(), &req)
	if err != nil {
		panic(err)
	}

	prettyJSON, _ := json.MarshalIndent(resp, "", "  ")
	fmt.Println(string(prettyJSON))
}
```

--------------------------------

### Subscription plans response structure

Source: https://docs.modelslab.com/agents-api/subscriptions

Example JSON response showing the structure of subscription plans and pay-as-you-go configuration.

```json
{
  "data": {
    "subscription_plans": [
      {
        "id": 10,
        "name": "Basic Enterprise",
        "category": "enterprise",
        "period": "monthly",
        "type": "basic",
        "price": 249.0,
        "api_call_limit": 0,
        "rate_limit": 0,
        "features": ["Unlimited Images", "No Rate Limiter", "..."]
      }
    ],
    "pay_as_you_go": {
      "available": true,
      "description": "Pay only for what you use with wallet-based billing. No subscription required.",
      "minimum_topup_usd": 10.00,
      "currency": "USD",
      "auto_payments": {
        "supported": true,
        "description": "Automatically top up your wallet when balance drops below a threshold.",
        "configure_endpoint": "PUT /api/agents/v1/wallet/auto-funding",
        "disable_endpoint": "DELETE /api/agents/v1/wallet/auto-funding"
      },
      "fund_endpoint": "POST /api/agents/v1/wallet/fund"
    },
    "count": 37
  }
}
```

--------------------------------

### Update Server Request Example (Node.js)

Source: https://docs.modelslab.com/enterprise-api/image-to-video-ultra/update-server

A Node.js example for updating your dedicated server. This snippet uses the 'request' library and requires your enterprise API key.

```javascript
var request = require('request');
var options = {
  'method': 'POST',
  'url': 'https://modelslab.com/api/v1/enterprise/image_to_video_ultra/update_server',
  'headers': {
    'Content-Type': 'application/json'
  },
  body: JSON.stringify({
    "key": ""
  })
};
request(options, function (error, response) {
  if (error) throw new Error(error);
  console.log(response.body);
});
```

--------------------------------

### Configure ModelsLab Client

Source: https://docs.modelslab.com/sdk/php

Methods for initializing the client with direct keys or custom options, and using environment variables.

```php
<?php
use ModelsLab\ModelsLab;

// Method 1: Direct API key
$modelslab = new ModelsLab('your-api-key');

// Method 2: With custom options
$modelslab = new ModelsLab('your-api-key', [
    'base_url' => 'https://modelslab.com/api/',
    'fetch_retry' => 10,
    'fetch_timeout' => 2
]);
```

```bash
export MODELSLAB_API_KEY="your-actual-api-key"
# Or
export API_KEY="your-actual-api-key"
```

```php
$modelslab = new ModelsLab(getenv('MODELSLAB_API_KEY'));
```

--------------------------------

### Payment Status Response Example

Source: https://docs.modelslab.com/agents-api/billing-and-wallet

This is an example of the JSON response you might receive when checking a PaymentIntent's status. The `status` field can be `succeeded`, `pending`, or `failed`.

```json
{
  "data": {
    "status": "succeeded",
    "payment_intent_id": "pi_xxx",
    "amount": 25.00,
    "currency": "usd"
  },
  "error": null,
  "meta": {
    "request_id": "..."
  }
}
```

--------------------------------

### Run Go Application

Source: https://docs.modelslab.com/sdk/golang

Execute your Go program from the command line.

```bash
go run main.go
```

--------------------------------

### Initialize Image Editing API Client

Source: https://docs.modelslab.com/sdk/python

Sets up the client and API instance for image editing operations. Requires an API key.

```python
from modelslab_py.core.client import Client
from modelslab_py.core.apis.image_editing import Image_editing

client = Client(api_key="your_api_key")
api = Image_editing(client=client, enterprise=False)
```

--------------------------------

### POST /qwen/system_details

Source: https://docs.modelslab.com/enterprise-api/qwen/system-details

This endpoint returns information about your server. It requires an enterprise API key in the request body.

```APIDOC
## POST /qwen/system_details

### Description
This endpoint returns information about your server.

### Method
POST

### Endpoint
https://modelslab.com/api/v1/enterprise/qwen/system_details

### Request Body
- **key** (string) - Required - Your API key

### Request Example
{
  "key": "enterprise_api_key"
}

### Response
#### Success Response (200)
- **status** (string) - Example: success
- **message** (string) - Example: Operation completed successfully

#### Error Response (401)
- **status** (string) - Example: error
- **message** (string) - Example: Error message

#### Response Example
{
  "status": "success",
  "message": "Operation completed successfully"
}
```

--------------------------------

### Webhook Example for Training Status Updates

Source: https://docs.modelslab.com/image-generation/train-model/lora-finetune

This JSON payload is an example of a webhook notification you might receive, indicating the status of your model training. It includes status, logs, and the model ID.

```json
{
    "status": "success",
    "training_status": "deploying_gpu",
    "logs": "it will take upto 25 minutes",
    "model_id": "F5jvdzGnYi"
}
```

--------------------------------

### ControlNet MLSD API Example (SD 1.5)

Source: https://docs.modelslab.com/image-generation/controlnet/controlnet-main

This example shows how to use the ControlNet MLSD (Mobile Line Segment Detection) model. Provide an init_image and your API key for architectural or line-based generation.

```json
{
  "key": "your_api_key",
  "controlnet_model": "mlsd",
  "controlnet_type": "mlsd",
  "model_id": "realistic-vision-51",
  "auto_hint": "yes",
  "guess_mode": "no",
  "prompt": "ROOM INTERIOR, OLD SCHOOL, VINTAGE",
  "negative_prompt": null,
  "init_image": "https://images-ext-1.discordapp.net/external/f_MuFioFIYcAuhbGrCXkiDfRJq1nZd-L0z_DibDpMc0/https/i.pinimg.com/736x/8a/2b/1e/8a2b1e6ca4779d787ae3c98b7b1100b2.jpg",
  "mask_image": null,
  "width": "512",
  "height": "512",
  "samples": "1",
  "scheduler": "UniPCMultistepScheduler",
  "num_inference_steps": "30",
  "safety_checker": "no",
  "enhance_prompt": "yes",
  "guidance_scale": 7.5,
  "strength": 0.55,
  "seed": null,
  "webhook": null,
  "track_id": null
}
```

--------------------------------

### POST /enterprise/video/system_details

Source: https://docs.modelslab.com/enterprise-api/video/system-details

Retrieves information about the server using an enterprise API key.

```APIDOC
## POST /enterprise/video/system_details

### Description
This endpoint returns information about your server.

### Method
POST

### Endpoint
https://modelslab.com/api/v1/enterprise/video/system_details

### Request Body
- **key** (string) - Required - Your API key

### Request Example
{
  "key": "enterprise_api_key"
}

### Response
#### Success Response (200)
- **status** (string) - Status of the operation
- **message** (string) - Description of the result

#### Response Example
{
  "status": "success",
  "message": "Operation completed successfully"
}

#### Error Response (401)
- **status** (string) - Status of the error
- **message** (string) - Error message
```

--------------------------------

### GET /api/agents/v1/wallet/coupons/validate

Source: https://docs.modelslab.com/agents-api/billing-and-wallet

Validates a coupon code before attempting to redeem it.

```APIDOC
## GET /api/agents/v1/wallet/coupons/validate

### Description
Validate a coupon before redeeming.

### Method
GET

### Endpoint
/api/agents/v1/wallet/coupons/validate

### Parameters
#### Query Parameters
- **coupon_code** (string) - Required - The coupon code to validate
```

--------------------------------

### GET /fetch-video

Source: https://docs.modelslab.com/mcp-web-api/tools-reference

Retrieves the status and results of a video generation request.

```APIDOC
## GET /fetch-video

### Description
Retrieve the status and results of a video generation request.

### Method
GET

### Endpoint
/fetch-video

### Parameters
#### Query Parameters
- **id** (string) - Required - Request ID from a previous video generation call
```

--------------------------------

### File Input Options in Go

Source: https://docs.modelslab.com/sdk/golang

Demonstrates how to provide file inputs using URLs, Base64 encoded data, or local file paths with the Modelslab Go SDK.

```go
import "github.com/modelslab/modelslab-go/pkg/schemas/base"

// URL input
imageURL := "https://example.com/image.jpg"
fileInput := base.FileInput{
    URL: &imageURL,
}
```

```go
base64Data := "data:image/jpeg;base64,/9j/4AAQSkZJRgABAQAAAQ..."
fileInput := base.FileInput{
    Base64: &base64Data,
}
```

```go
// File path (for local files)
filePath := "/path/to/image.jpg"
fileInput := base.FileInput{
    FilePath: &filePath,
}
```

--------------------------------

### GET /fetch-image

Source: https://docs.modelslab.com/mcp-web-api/tools-reference

Retrieve the status and results of an image generation request.

```APIDOC
## GET /fetch-image

### Description
Retrieve the status and results of an image generation request.

### Method
GET

### Endpoint
/fetch-image

### Parameters
#### Query Parameters
- **id** (integer) - Required - Request ID from a previous generation call
```

--------------------------------

### System Details

Source: https://docs.modelslab.com/enterprise-api/image-to-video-ultra/overview

Get information about the current status of your dedicated server.

```APIDOC
## GET /enterprise-api/image-to-video-ultra/system-details

### Description
Get information about your server status.

### Method
GET

### Endpoint
/enterprise-api/image-to-video-ultra/system-details
```

--------------------------------

### GET /enterprise-api/flux-headshot/fetch

Source: https://docs.modelslab.com/enterprise-api/flux-headshot/overview

Fetches the status of queued or currently processing requests.

```APIDOC
## GET /enterprise-api/flux-headshot/fetch

### Description
This endpoint fetches queued or processing requests.

### Method
GET

### Endpoint
/enterprise-api/flux-headshot/fetch
```