atlascloud/wan-2.7-spicy/reference-to-video

مرجع إلى فيديو

Wan 2.7 Spicy Reference-to-Video API by Atlas Cloud

atlascloud/wan-2.7-spicy/reference-to-video

Reference-to-video

An image-reference-to-video model that generates one continuous video from one to four reference images with precise subject binding and prompt control. Supports image references only; reference video and audio are not accepted.

الإدخال

الطلب *

اكتب @ أو < للإشارة إلى صورة تم رفعها.

صور مرجعية *(0/4)

اسحب الملف وأفلته هنا أو انقر للرفع

MAX:4

المدة

الدقة

نسبة العرض إلى الارتفاع

الإخراج

في انتظار التنفيذ

سيظهر الفيديو المُنشأ هنا

قم بتعيين المعاملات وانقر فوق تشغيل لبدء الإنشاء

كل مرة ستكلف $0.1 مع $10 يمكنك التشغيل حوالي 100 مرة

يمكنك المتابعة بـ:

Seedance 2.0 Kling v3 Vidu Wan2.7

المعلمات

مثال الكود
import requests
import time

# Step 1: Start video generation
generate_url = "https://api.atlascloud.ai/api/v1/model/generateVideo"
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer $ATLASCLOUD_API_KEY"
}
data = {
    "model": "atlascloud/wan-2.7-spicy/reference-to-video",  # Required. options: atlascloud/wan-2.7-spicy/reference-to-video
    "reference_images": [],  # Required. Ordered image URLs or Base64 data URIs
    "prompt": "A beautiful sunset over the ocean with gentle waves",  # Required. Requested video intent using strict attached subject@imageN bindings
    "duration": 5,  # Generated video duration in seconds. (min: 2, max: 15)
    "resolution": "720P",  # options: 720P | 1080P | 1080P-SR | 1440P-SR
    "aspect_ratio": "auto",  # options: auto | 16:9 | 9:16 | 4:3 | 3:4 | 1:1
}

generate_response = requests.post(generate_url, headers=headers, json=data)
generate_result = generate_response.json()
prediction_id = generate_result["data"]["id"]

# Step 2: Poll for result
poll_url = f"https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}"

def check_status():
    while True:
        response = requests.get(poll_url, headers={"Authorization": "Bearer $ATLASCLOUD_API_KEY"})
        result = response.json()

        if result["data"]["status"] in ["completed", "succeeded"]:
            print("Generated video:", result["data"]["outputs"][0])
            return result["data"]["outputs"][0]
        elif result["data"]["status"] == "failed":
            raise Exception(result["data"]["error"] or "Generation failed")
        else:
            # Still processing, wait 2 seconds
            time.sleep(2)

video_url = check_status()

التثبيت

قم بتثبيت الحزمة المطلوبة للغة البرمجة الخاصة بك.

pip install requests

المصادقة

تتطلب جميع طلبات API المصادقة عبر مفتاح API. يمكنك الحصول على مفتاح API الخاص بك من لوحة تحكم Atlas Cloud.

export ATLASCLOUD_API_KEY="your-api-key-here"

ترويسات HTTP

import os

API_KEY = os.environ.get("ATLASCLOUD_API_KEY")
headers = {
    "Content-Type": "application/json",
    "Authorization": f"Bearer {API_KEY}"
}

حافظ على أمان مفتاح API الخاص بك

لا تكشف أبدًا مفتاح API الخاص بك في الكود من جانب العميل أو المستودعات العامة. استخدم متغيرات البيئة أو وكيل الخادم الخلفي بدلاً من ذلك.

إرسال طلب

import requests

url = "https://api.atlascloud.ai/api/v1/model/generateVideo"
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer $ATLASCLOUD_API_KEY"
}
data = {
    "model": "your-model",
    "prompt": "A beautiful landscape"
}

response = requests.post(url, headers=headers, json=data)
print(response.json())

إرسال طلب

أرسل طلب توليد غير متزامن. تُرجع API معرّف التنبؤ الذي يمكنك استخدامه للتحقق من الحالة واسترداد النتيجة.

POST/api/v1/model/generateVideo

نص الطلب

import requests

url = "https://api.atlascloud.ai/api/v1/model/generateVideo"
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer $ATLASCLOUD_API_KEY"
}

data = {
    "model": "atlascloud/wan-2.7-spicy/reference-to-video",
    "prompt": "A beautiful sunset over the ocean with gentle waves"
}

response = requests.post(url, headers=headers, json=data)
result = response.json()

print(f"Prediction ID: {result['data']['id']}")
print(f"Status: {result['data']['status']}")

الاستجابة

{
  "code": 200,
  "data": {
    "id": "pred_abc123",
    "status": "processing",
    "model": "model-name",
    "created_at": "2025-01-01T00:00:00Z"
  }
}

التحقق من الحالة

استعلم عن نقطة نهاية التنبؤ للتحقق من الحالة الحالية لطلبك.

GET/api/v1/model/prediction/{prediction_id}

مثال الاستعلام

import requests
import time

prediction_id = "pred_abc123"
url = f"https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}"
headers = { "Authorization": "Bearer $ATLASCLOUD_API_KEY" }

while True:
    response = requests.get(url, headers=headers)
    result = response.json()
    status = result["data"]["status"]
    print(f"Status: {status}")

    if status in ["completed", "succeeded"]:
        output_url = result["data"]["outputs"][0]
        print(f"Output URL: {output_url}")
        break
    elif status == "failed":
        print(f"Error: {result['data'].get('error', 'Unknown')}")
        break

    time.sleep(3)

قيم الحالة

processingلا يزال الطلب قيد المعالجة.

completedاكتمل التوليد. المخرجات متاحة.

succeededنجح التوليد. المخرجات متاحة.

failedفشل التوليد. تحقق من حقل الخطأ.

استجابة مكتملة

{
  "data": {
    "id": "pred_abc123",
    "status": "completed",
    "outputs": [
      "https://storage.atlascloud.ai/outputs/result.mp4"
    ],
    "metrics": {
      "predict_time": 45.2
    },
    "created_at": "2025-01-01T00:00:00Z",
    "completed_at": "2025-01-01T00:00:10Z"
  }
}

رفع الملفات

ارفع الملفات إلى تخزين Atlas Cloud واحصل على URL يمكنك استخدامه في طلبات API الخاصة بك. استخدم multipart/form-data للرفع.

POST/api/v1/model/uploadMedia

مثال الرفع

import requests

url = "https://api.atlascloud.ai/api/v1/model/uploadMedia"
headers = { "Authorization": "Bearer $ATLASCLOUD_API_KEY" }

with open("image.png", "rb") as f:
    files = {"file": ("image.png", f, "image/png")}
    response = requests.post(url, headers=headers, files=files)

result = response.json()
download_url = result["data"]["download_url"]
print(f"File URL: {download_url}")

الاستجابة

{
  "data": {
    "download_url": "https://storage.atlascloud.ai/uploads/abc123/image.png",
    "file_name": "image.png",
    "content_type": "image/png",
    "size": 1024000
  }
}

Input Schema

المعاملات التالية مقبولة في نص الطلب.

الإجمالي: 6مطلوب: 3اختياري: 3

modelstringrequired

Default: "atlascloud/wan-2.7-spicy/reference-to-video"

atlascloud/wan-2.7-spicy/reference-to-video

reference_imagesarray[string]required

Ordered image URLs or Base64 data URIs. Images are the only supported reference media type; reference video and audio are not accepted. The product prompt editor exposes images as inline image1, image2, ... mentions; the serialized API prompt uses attached subject@imageN syntax.

Min items: 1Max items: 4

promptstringrequired

Requested video intent using strict attached subject@imageN bindings.

durationinteger

Generated video duration in seconds.

Default: 5Min: 2Max: 15

resolutionstring

Default: "720P"

720P1080P1080P-SR1440P-SR

aspect_ratiostring

Default: "auto"

auto16:99:164:33:41:1

مثال على نص الطلب

{
  "model": "atlascloud/wan-2.7-spicy/reference-to-video",
  "reference_images": [
    "https://example.com/file.jpg"
  ],
  "prompt": "A beautiful landscape",
  "duration": 5,
  "resolution": "720P",
  "aspect_ratio": "auto"
}

Output Schema

تُرجع API استجابة تنبؤ تحتوي على عناوين URL للمخرجات المولّدة.

codeinteger

msgstring

dataobject

مثال على الاستجابة

{
  "id": "pred_abc123",
  "status": "completed",
  "model": "model-name",
  "outputs": [
    "https://storage.atlascloud.ai/outputs/result.mp4"
  ],
  "metrics": {
    "predict_time": 45.2
  },
  "created_at": "2025-01-01T00:00:00Z",
  "completed_at": "2025-01-01T00:00:10Z"
}

Atlas Cloud Skills

يدمج Atlas Cloud Skills أكثر من 400 نموذج ذكاء اصطناعي مباشرة في مساعد البرمجة بالذكاء الاصطناعي الخاص بك. أمر واحد للتثبيت، ثم استخدم اللغة الطبيعية لتوليد الصور ومقاطع الفيديو والدردشة مع LLM.

العملاء المدعومون

Claude Code

OpenAI Codex

Gemini CLI

Cursor

Windsurf

VS Code

Trae

GitHub Copilot

Cline

Roo Code

Amp

Goose

Replit

40+ العملاء المدعومون

التثبيت

npx skills add AtlasCloudAI/atlas-cloud-skills

إعداد مفتاح API

احصل على مفتاح API الخاص بك من لوحة تحكم Atlas Cloud وعيّنه كمتغير بيئة.

export ATLASCLOUD_API_KEY="your-api-key-here"

الإمكانيات

بمجرد التثبيت، يمكنك استخدام اللغة الطبيعية في مساعد الذكاء الاصطناعي الخاص بك للوصول إلى جميع نماذج Atlas Cloud.

توليد الصورأنشئ صورًا باستخدام نماذج مثل Nano Banana 2 و Z-Image والمزيد.

إنشاء الفيديوأنشئ مقاطع فيديو من نص أو صور باستخدام Kling و Vidu و Veo وغيرها.

دردشة LLMتحدث مع Qwen و DeepSeek ونماذج اللغة الكبيرة الأخرى.

رفع الوسائطارفع الملفات المحلية لتحرير الصور وسير عمل تحويل الصور إلى فيديو.

MCP Server

يربط Atlas Cloud MCP Server بيئة التطوير الخاصة بك بأكثر من 400 نموذج ذكاء اصطناعي عبر Model Context Protocol. يعمل مع أي عميل متوافق مع MCP.

العملاء المدعومون

Cursor

VS Code

Windsurf

Claude Code

OpenAI Codex

Gemini CLI

Cline

Roo Code

100+ العملاء المدعومون

التثبيت

npx -y atlascloud-mcp

التكوين

أضف التكوين التالي إلى ملف إعدادات MCP في بيئة التطوير الخاصة بك.

{
  "mcpServers": {
    "atlascloud": {
      "command": "npx",
      "args": [
        "-y",
        "atlascloud-mcp"
      ],
      "env": {
        "ATLASCLOUD_API_KEY": "your-api-key-here"
      }
    }
  }
}

الأدوات المتاحة

atlas_generate_imageتوليد صور من أوصاف نصية.

atlas_generate_videoإنشاء مقاطع فيديو من نص أو صور.

atlas_chatالدردشة مع نماذج اللغة الكبيرة.

atlas_list_modelsتصفح أكثر من 400 نموذج ذكاء اصطناعي متاح.

atlas_quick_generateإنشاء محتوى بخطوة واحدة مع اختيار تلقائي للنموذج.

atlas_upload_mediaرفع الملفات المحلية لسير عمل API.

اعرف المزيد

github.com/AtlasCloudAI/mcp-server

مخطط API

{
  "openapi": "3.0.0",
  "info": {
    "title": "Wan 2.7 Spicy Reference-to-Video API by Atlas Cloud",
    "version": "1.0.0",
    "description": "An image-reference-to-video model that generates a continuous video from one to four reference images and a text prompt. This model accepts image references only; reference video and audio are not supported."
  },
  "paths": {
    "/api/v1/model/generateVideo": {
      "post": {
        "x-api-name": "model_run",
        "requestBody": {
          "required": true,
          "content": {
            "application/json": {
              "schema": {
                "$ref": "#/components/schemas/Input"
              }
            }
          }
        },
        "responses": {
          "200": {
            "description": "Request accepted. Returns a prediction ID for result polling.",
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/PredictionResponse"
                }
              }
            }
          },
          "400": {
            "description": "Invalid request."
          }
        }
      }
    },
    "/api/v1/model/prediction/{request_id}": {
      "get": {
        "x-api-name": "model_result",
        "parameters": [
          {
            "name": "request_id",
            "in": "path",
            "required": true,
            "schema": {
              "type": "string"
            }
          }
        ],
        "responses": {
          "200": {
            "description": "The current generation result.",
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/PredictionResponse"
                }
              }
            }
          }
        }
      }
    }
  },
  "components": {
    "schemas": {
      "Input": {
        "type": "object",
        "required": [
          "model",
          "reference_images",
          "prompt"
        ],
        "properties": {
          "model": {
            "type": "string",
            "enum": [
              "atlascloud/wan-2.7-spicy/reference-to-video"
            ],
            "default": "atlascloud/wan-2.7-spicy/reference-to-video"
          },
          "reference_images": {
            "type": "array",
            "description": "Ordered image URLs or Base64 data URIs. Images are the only supported reference media type; reference video and audio are not accepted. The product prompt editor exposes images as inline image1, image2, ... mentions; the serialized API prompt uses attached subject@imageN syntax.",
            "items": {
              "type": "string",
              "x-format": "image"
            },
            "minItems": 1,
            "maxItems": 4
          },
          "prompt": {
            "type": "string",
            "description": "Requested video intent using strict attached subject@imageN bindings.",
            "minLength": 1,
            "maxLength": 5000,
            "x-image-reference": {
              "enabled": true,
              "source": "reference_images",
              "tag": "image",
              "indexBase": 1,
              "syntax": "@imageN "
            }
          },
          "duration": {
            "type": "integer",
            "description": "Generated video duration in seconds.",
            "minimum": 2,
            "maximum": 15,
            "default": 5
          },
          "resolution": {
            "type": "string",
            "enum": [
              "720P",
              "1080P",
              "1080P-SR",
              "1440P-SR"
            ],
            "default": "720P"
          },
          "aspect_ratio": {
            "type": "string",
            "enum": [
              "auto",
              "16:9",
              "9:16",
              "4:3",
              "3:4",
              "1:1"
            ],
            "default": "auto"
          }
        },
        "x-order-properties": [
          "model",
          "reference_images",
          "prompt",
          "duration",
          "resolution",
          "aspect_ratio"
        ]
      },
      "PredictionResponse": {
        "type": "object",
        "properties": {
          "code": {
            "type": "integer"
          },
          "msg": {
            "type": "string"
          },
          "data": {
            "type": "object",
            "properties": {
              "id": {
                "type": "string"
              },
              "model": {
                "type": "string"
              },
              "status": {
                "type": "string"
              },
              "outputs": {
                "type": "array",
                "items": {
                  "type": "string"
                }
              },
              "error": {
                "type": "string"
              }
            }
          }
        }
      }
    }
  },
  "servers": [
    {
      "url": "https://api.atlascloud.ai"
    }
  ]
}

قالب موجه LLM

# atlascloud/wan-2.7-spicy/reference-to-video

> An image-reference-to-video model that generates one continuous video from one to four reference images with precise subject binding and prompt control. Supports image references only; reference video and audio are not accepted.


## Overview

- **Submit endpoint (POST)**: `https://api.atlascloud.ai/api/v1/model/generateVideo` — start an async generation; returns a `prediction_id`
- **Poll endpoint (GET)**: `https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}` — poll this until the prediction finishes
- **Model ID**: `atlascloud/wan-2.7-spicy/reference-to-video`


## API Information

This model can be used via our HTTP API or more conveniently via our client libraries.
See the input and output schema below, as well as the usage examples.


### Input Schema

The API accepts the following input parameters:

- **`model`** (`string`, _required_):
  - Default: `"atlascloud/wan-2.7-spicy/reference-to-video"`
  - Options: "atlascloud/wan-2.7-spicy/reference-to-video"

- **`reference_images`** (`array[string]`, _required_):
  Ordered image URLs or Base64 data URIs. Images are the only supported reference media type; reference video and audio are not accepted. The product prompt editor exposes images as inline image1, image2, ... mentions; the serialized API prompt uses attached subject@imageN syntax.
  - Min items: 1
  - Max items: 4

- **`prompt`** (`string`, _required_):
  Requested video intent using strict attached subject@imageN bindings.

- **`duration`** (`integer`, _optional_):
  Generated video duration in seconds.
  - Default: `5`
  - Min: 2
  - Max: 15

- **`resolution`** (`string`, _optional_):
  - Default: `"720P"`
  - Options: "720P", "1080P", "1080P-SR", "1440P-SR"

- **`aspect_ratio`** (`string`, _optional_):
  - Default: `"auto"`
  - Options: "auto", "16:9", "9:16", "4:3", "3:4", "1:1"



**Required Parameters Example**:

```json
{
  "model": "atlascloud/wan-2.7-spicy/reference-to-video",
  "reference_images": [
    ""
  ],
  "prompt": ""
}
```


**Full Example**:

```json
{
  "model": "atlascloud/wan-2.7-spicy/reference-to-video",
  "reference_images": [
    ""
  ],
  "prompt": "",
  "duration": 5,
  "resolution": "720P",
  "aspect_ratio": "auto"
}
```


### Output Schema

The API returns the following output format:


- **`code`** (`integer`, _optional_):

- **`msg`** (`string`, _optional_):

- **`data`** (`object`, _optional_):
  - Properties:
    - **`id`** (`string`, _optional_):

    - **`model`** (`string`, _optional_):

    - **`status`** (`string`, _optional_):

    - **`outputs`** (`array[string]`, _optional_):

    - **`error`** (`string`, _optional_):




**Example Response**:

```json
{
  "code": 0,
  "msg": "",
  "data": {
    "id": "",
    "model": "",
    "status": "",
    "outputs": [
      ""
    ],
    "error": ""
  }
}
```


## Usage Examples

### cURL

```bash
# Step 1: Start generation (async)
curl -X POST "https://api.atlascloud.ai/api/v1/model/generateVideo" \
  -H "Authorization: Bearer $ATLASCLOUD_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
  "model": "atlascloud/wan-2.7-spicy/reference-to-video",
  "reference_images": [
    ""
  ],
  "prompt": "",
  "duration": 5,
  "resolution": "720P",
  "aspect_ratio": "auto"
}'

# Response will contain: {"code": 200, "data": {"id": "prediction_id", "status": "processing"}}

# Step 2: Poll for result (replace {prediction_id} with the id returned above)
curl -X GET "https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}" \
  -H "Authorization: Bearer $ATLASCLOUD_API_KEY"

# Keep polling until status is "completed", "succeeded" or "failed"
# When completed, outputs will contain the generated content URL(s)
```

## Additional Resources

### Documentation

- [Model Playground](https://www.atlascloud.ai/models/atlascloud/wan-2.7-spicy/reference-to-video)

A young woman@image1 is sitting on the sofa@image2, drinking a cocktail@image3.

جارٍ التحميل...

Wan 2.7 Spicy Reference-to-Video

atlascloud/wan-2.7-spicy/reference-to-video is an image-reference-to-video model. It turns one to four reference images and a text prompt into a continuous video, combining people, objects, and environments from separate images while following the requested action, composition, camera direction, and visual style.

Reference input scope

This model accepts images only as reference inputs. Unlike Wan 2.7 Reference-to-Video and Seedance 2.0 Reference-to-Video, which also support video and audio references, this model does not accept reference videos or reference audio.

Request

{
  "model": "atlascloud/wan-2.7-spicy/reference-to-video",
  "reference_images": [
    "https://static.atlascloud.ai/media/images/66c94270e84804c2029ef6095567c948.jpg",
    "https://static.atlascloud.ai/media/images/daef59ba6c4afe33225a455aee9e62b5.webp",
    "https://static.atlascloud.ai/media/images/23d7e0acfa10101f5819e43b42c0e2ff.jpg"
  ],
  "prompt": "A young woman@image1 is sitting on the sofa@image2, drinking a cocktail@image3.",
  "duration": 5,
  "resolution": "1440P-SR",
  "aspect_ratio": "16:9"
}

Parameters

Parameter	Required	Description
`model`	Yes	Must be `atlascloud/wan-2.7-spicy/reference-to-video`.
`reference_images`	Yes	Ordered array of 1–4 image URLs or Base64 data URIs. Images are the only supported reference media type; video and audio references are not accepted.
`prompt`	Yes	Describe the desired video and bind every reference with attached `subject@imageN` syntax.
`duration`	No	Video duration from 2–15 seconds. Default: `5`.
`resolution`	No	`720P`, `1080P`, `1080P-SR`, or `1440P-SR`. Default: `720P`.
`aspect_ratio`	No	`auto`, `16:9`, `9:16`, `4:3`, `3:4`, or `1:1`. Default: `auto`.

Reference images

Image numbering follows the order of reference_images:

reference_images[0] → image1
reference_images[1] → image2
reference_images[2] → image3
reference_images[3] → image4

Attach each image tag directly to the subject it represents:

young woman@image1
sofa@image2
cocktail@image3

Multiple subjects from the same image can share one tag:

woman in yellow@image1 and man in blue@image1

Every uploaded image must be referenced in the prompt, and every @imageN must correspond to an uploaded image.

Prompt guidance

Describe the visible action, environment, camera direction, composition, wardrobe, lighting, and style you want in the final video. Explicit instructions in the prompt are followed whenever they are visually compatible.

For best results:

Identify each referenced subject clearly.
Describe one continuous scene rather than multiple cuts or locations.
State which subject should receive the most visual attention.
Include any required camera angle, framing, or wardrobe details directly in the prompt.

Pricing

Pricing depends only on the selected resolution and billed video duration:

Resolution	Price per second	Five-second price
`720P`	`$0.1200`	`$0.6000`
`1080P`	`$0.1800`	`$0.9000`
`1080P-SR`	`$0.1440`	`$0.7200`
`1440P-SR`	approximately `$0.2560`	approximately `$1.2800`

Video generation is billed for at least five seconds. Reference-image count and aspect ratio do not change the price.

Asynchronous generation

Submit a request to /api/v1/model/generateVideo. The response contains a prediction ID that can be used to poll /api/v1/model/prediction/{request_id} until generation finishes. The final video URL is returned in data.outputs.

Wan 2.7 Spicy Reference-to-Video API by Atlas Cloud

الإدخال

الإخراج

المعلمات

مثال الكود

التثبيت

المصادقة

ترويسات HTTP

إرسال طلب

إرسال طلب

نص الطلب

الاستجابة

التحقق من الحالة

مثال الاستعلام

قيم الحالة

استجابة مكتملة

رفع الملفات

مثال الرفع

الاستجابة

Input Schema

مثال على نص الطلب

Output Schema

مثال على الاستجابة

Atlas Cloud Skills

العملاء المدعومون

التثبيت

إعداد مفتاح API

الإمكانيات

MCP Server

العملاء المدعومون

التثبيت

التكوين

الأدوات المتاحة

مخطط API

قالب موجه LLM

Wan 2.7 Spicy Reference-to-Video

Reference input scope

Request

Parameters

Reference images

Prompt guidance

Pricing

Asynchronous generation

استكشف نماذج مماثلة

Wan 2.7 Spicy Image-to-Video

Wan-2.2-turbo-spicy Image-to-video Lora

Wan-2.2-turbo-spicy Image-to-video

Wan 2.2 Turbo Image-to-Video

Wan 2.2 Turbo Infinite Image-to-Video

Wan 2.2 Turbo Infinite Image-to-Video LoRA

Wan 2.2 Turbo Spicy Infinite Image-to-Video

Wan 2.2 Turbo Spicy Infinite Image-to-Video LoRA

Video Upscaler

Face Swap

Van-2.6 Text-to-video

Van-2.6 Image-to-video

Wan 2.6 Spicy Image-to-Video

Van-2.5 Image-to-video

Van-2.5 Text-to-video

Sync.so Lipsync v3

واجهة برمجية واحدة لكل وسائط الذكاء الاصطناعي.

الإدخال

الإخراج

المعلمات

مثال الكود

التثبيت

المصادقة

ترويسات HTTP

إرسال طلب

إرسال طلب

نص الطلب

الاستجابة

التحقق من الحالة

مثال الاستعلام

قيم الحالة

استجابة مكتملة

رفع الملفات

مثال الرفع

الاستجابة

Input Schema