alibaba/wan-2.5/text-to-image

Generate AI images with Alibaba WAN 2.5 text-to-image model.

TEXT-TO-IMAGEHOTNEW
Wan-2.5 Text-to-image
text-to-image

Generate AI images with Alibaba WAN 2.5 text-to-image model.

INPUT

Loading parameter configuration...

OUTPUT

Idle
Your generated images will appear here
Configure your settings and click Run to get started

Your request will cost 0.021 per run. For $10 you can run this model approximately 476 times.

Here's what you can do next:

Parametri

Esempio di codice

import requests
import time

# Step 1: Start image generation
generate_url = "https://api.atlascloud.ai/api/v1/model/generateImage"
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer $ATLASCLOUD_API_KEY"
}
data = {
    "model": "alibaba/wan-2.5/text-to-image",
    "prompt": "A beautiful landscape with mountains and lake",
    "width": 512,
    "height": 512,
    "steps": 20,
    "guidance_scale": 7.5,
}

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"] == "completed":
            print("Generated image:", 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)

image_url = check_status()

Installa

Installa il pacchetto richiesto per il tuo linguaggio.

bash
pip install requests

Autenticazione

Tutte le richieste API richiedono l'autenticazione tramite una chiave API. Puoi ottenere la tua chiave API dalla dashboard di Atlas Cloud.

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

Header HTTP

python
import os

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

Non esporre mai la tua chiave API nel codice lato client o nei repository pubblici. Utilizza invece variabili d'ambiente o un proxy backend.

Invia una richiesta

import requests

url = "https://api.atlascloud.ai/api/v1/model/generateImage"
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())

Invia una richiesta

Invia una richiesta di generazione asincrona. L'API restituisce un ID di previsione che puoi usare per controllare lo stato e recuperare il risultato.

POST/api/v1/model/generateImage

Corpo della richiesta

import requests

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

data = {
    "model": "alibaba/wan-2.5/text-to-image",
    "input": {
        "prompt": "A beautiful landscape with mountains and lake"
    }
}

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

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

Risposta

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

Controlla lo stato

Interroga l'endpoint di previsione per verificare lo stato attuale della tua richiesta.

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

Esempio di polling

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)

Valori di stato

processingLa richiesta è ancora in fase di elaborazione.
completedLa generazione è completata. I risultati sono disponibili.
succeededLa generazione è riuscita. I risultati sono disponibili.
failedLa generazione è fallita. Controlla il campo errore.

Risposta completata

{
  "data": {
    "id": "pred_abc123",
    "status": "completed",
    "outputs": [
      "https://storage.atlascloud.ai/outputs/result.png"
    ],
    "metrics": {
      "predict_time": 8.3
    },
    "created_at": "2025-01-01T00:00:00Z",
    "completed_at": "2025-01-01T00:00:10Z"
  }
}

Carica file

Carica file nello storage Atlas Cloud e ottieni un URL utilizzabile nelle tue richieste API. Usa multipart/form-data per il caricamento.

POST/api/v1/model/uploadMedia

Esempio di caricamento

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}")

Risposta

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

Schema di input

I seguenti parametri sono accettati nel corpo della richiesta.

Totale: 0Obbligatorio: 0Opzionale: 0

Nessun parametro disponibile.

Esempio di corpo della richiesta

json
{
  "model": "alibaba/wan-2.5/text-to-image"
}

Schema di output

L'API restituisce una risposta di previsione con gli URL degli output generati.

idstringrequired
Unique identifier for the prediction.
statusstringrequired
Current status of the prediction.
processingcompletedsucceededfailed
modelstringrequired
The model used for generation.
outputsarray[string]
Array of output URLs. Available when status is "completed".
errorstring
Error message if status is "failed".
metricsobject
Performance metrics.
predict_timenumber
Time taken for image generation in seconds.
created_atstringrequired
ISO 8601 timestamp when the prediction was created.
Format: date-time
completed_atstring
ISO 8601 timestamp when the prediction was completed.
Format: date-time

Esempio di risposta

json
{
  "id": "pred_abc123",
  "status": "completed",
  "model": "model-name",
  "outputs": [
    "https://storage.atlascloud.ai/outputs/result.png"
  ],
  "metrics": {
    "predict_time": 8.3
  },
  "created_at": "2025-01-01T00:00:00Z",
  "completed_at": "2025-01-01T00:00:10Z"
}

Atlas Cloud Skills

Atlas Cloud Skills integra oltre 300 modelli di IA direttamente nel tuo assistente di codifica IA. Un comando per installare, poi usa il linguaggio naturale per generare immagini, video e chattare con LLM.

Client supportati

Claude Code
OpenAI Codex
Gemini CLI
Cursor
Windsurf
VS Code
Trae
GitHub Copilot
Cline
Roo Code
Amp
Goose
Replit
40+ client supportati

Installa

bash
npx skills add AtlasCloudAI/atlas-cloud-skills

Configura chiave API

Ottieni la tua chiave API dalla dashboard di Atlas Cloud e impostala come variabile d'ambiente.

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

Funzionalità

Una volta installato, puoi usare il linguaggio naturale nel tuo assistente IA per accedere a tutti i modelli Atlas Cloud.

Generazione di immaginiGenera immagini con modelli come Nano Banana 2, Z-Image e altri.
Creazione di videoCrea video da testo o immagini con Kling, Vidu, Veo, ecc.
Chat LLMChatta con Qwen, DeepSeek e altri grandi modelli linguistici.
Caricamento mediaCarica file locali per la modifica di immagini e flussi di lavoro da immagine a video.

Server MCP

Il server MCP di Atlas Cloud collega il tuo IDE con oltre 300 modelli di IA tramite il Model Context Protocol. Funziona con qualsiasi client compatibile MCP.

Client supportati

Cursor
VS Code
Windsurf
Claude Code
OpenAI Codex
Gemini CLI
Cline
Roo Code
100+ client supportati

Installa

bash
npx -y atlascloud-mcp

Configurazione

Aggiungi la seguente configurazione al file delle impostazioni MCP del tuo IDE.

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

Strumenti disponibili

atlas_generate_imageGenera immagini da prompt testuali.
atlas_generate_videoCrea video da testo o immagini.
atlas_chatChatta con grandi modelli linguistici.
atlas_list_modelsEsplora oltre 300 modelli di IA disponibili.
atlas_quick_generateCreazione di contenuti in un solo passaggio con selezione automatica del modello.
atlas_upload_mediaCarica file locali per i flussi di lavoro API.

API Schema

Schema not available

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Seedance 1.5 Pro

GENERAZIONE AUDIO-VISIVA NATIVA

Suono e Visione, Tutto in Una Sola Ripresa

Il rivoluzionario modello di IA di ByteDance che genera audio e video perfettamente sincronizzati simultaneamente da un unico processo unificato. Sperimenta la vera generazione audio-visiva nativa con sincronizzazione labiale di precisione millimetrica in oltre 8 lingue.

Why Choose Wan 2.5?

More Affordable

Despite Google's recent price cuts, Veo 3 remains expensive overall. Wan 2.5 is lightweight and cost-effective, providing creators with more options while significantly reducing production costs.

One-Step Generation, End-to-End Sync

With Wan 2.5, no separate voice recording or manual lip alignment is needed. Just provide a clear, structured prompt to generate complete videos with audio/voiceover and lip sync in one go - faster and simpler.

Multilingual Friendly

When prompts are in Chinese, Wan 2.5 reliably generates A/V synchronized videos. In contrast, Veo 3 often displays "unknown language" for Chinese prompts.

Precise Character Recreation

Wan 2.5 excels at character trait restoration, accurately presenting character appearance, expressions, and movement styles, making generated video characters more recognizable and personalized for enhanced storytelling and immersion.

Artistic Style Rendering

Supports Studio Ghibli-style rendering, creating hand-painted watercolor textures and animation effects. Brings warm, dreamy visual experiences that enhance artistic appeal and storytelling depth.

Who Can Benefit?

Marketing Teams

Whether it's product launches, promotional campaigns, or brand marketing, Wan 2.5 helps you quickly generate high-quality videos, making creation easy and efficient.

  • Product demos and tutorials without coordination headaches
  • Social media marketing with multilingual subtitles and lip sync
  • AI-generated content lets teams focus on strategy and creativity
Bottom line: Bottom line: Creation has never been so simple, fast, and smart - Wan 2.5 is your secret weapon for marketing!

Global Enterprises

Provides ideal content localization solutions for multinational companies, making creation easier and more efficient.

  • Multilingual video support with prompt recognition
  • One-click generation of lip-synced subtitles and voiceovers
  • Fast content localization for global markets
Bottom line: Bottom line: Cross-border content creation has never been so simple, fast, and smart.

Story Creators / YouTubers

Creators can leverage Wan 2.5 to improve video production efficiency while ensuring high-quality output.

  • Immersive storytelling with precise character actions and expressions
  • Higher publishing efficiency with reduced editing and post-production time
  • Diverse content from short videos to animated story segments

Corporate Training Teams

Wan 2.5 makes corporate training more efficient and engaging.

  • Professional videos replace boring text documents
  • Quick creation of operational demos and training tutorials
  • Consistent style and standardized output for global rollout

Creative Freelancers / Small Studios

Wan 2.5 lets creativity flow without expensive equipment or actors - AI generates everything efficiently.

  • Experiment with diverse works from short films to social media content
  • From inspiration to completion with "one-click generation"
  • High-quality content without expensive equipment or professional actors
Bottom line: Bottom line: Wan 2.5 makes creation easier, freer, and more exciting with every attempt!

Educational Institutions / Online Course Creators

Transform creativity into reality without high costs - Wan 2.5 makes quality content production easy and economical.

  • Experiment with various styles from short films to promotional videos
  • Higher production efficiency from concept to finished product
  • Quality content without expensive equipment or professional talent
Bottom line: Bottom line: Wan 2.5 makes creation effortless, efficient, and free - every attempt is spectacular!

Core Features

One-Step A/V Generation

Generate complete videos with synchronized audio, voiceover, and lip-sync in a single process

Dual Character Sync

Supports simultaneous generation of two characters with synchronized actions, expressions, and lip-sync for natural interactions

Professional Quality

High-quality video output with realistic character expressions and precise lip synchronization

Multilingual Support

Excellent support for Chinese prompts and reliable generation of multilingual content

Cost Effective

Significantly lower costs compared to competitors while maintaining professional quality

Character Trait Restoration

Precisely recreates character appearance, expressions, and movement styles with high fidelity and personality

Artistic Style Rendering

Supports various artistic styles including Studio Ghibli-inspired hand-painted watercolor textures

Immersive Scenes

Perfect for dialogue scenes, interviews, or dual-person short films with natural audio-visual consistency

Wan 2.5 Prompt Showcase

Discover the power of Wan 2.5 through these curated examples. From digital human lip-sync to dual character scenes, artistic rendering to character restoration - experience the possibilities.

Digital Human Sync

Study Room Scholar

Middle-aged man reading with perfect lip-sync in a warm study environment
Lip-sync with audioEnvironmental soundsCharacter emotion
Prompt

A middle-aged man sitting at a wooden desk in a cozy study room, surrounded by bookshelves and a warm lamp glow. He opens an old book and reads aloud with a calm, deep voice: 'History teaches us more than just facts… it shows us who we are.' The room has subtle background sounds: pages turning, the faint ticking of a clock, and distant rain against the window.

Dual Character Scene

Park Sunset Romance

Couple interaction with synchronized dual character actions and expressions
Dual character syncNatural interactionAmbient soundscape
Prompt

A young couple sitting on a park bench during sunset. The woman leans her head on the man's shoulder. He whispers softly: 'No matter where we go, I'll always be here with you.' The sound includes the rustling of leaves, distant laughter of children playing, and the gentle hum of cicadas in the evening air.

Character Restoration

Ballet Performance Art

Precise character trait restoration with artistic movement and expression
Character trait restorationMovement precisionArtistic lighting
Prompt

A graceful ballerina with her hair in a messy bun, performing a powerful and emotional contemporary ballet routine. She is in a minimalist, dark art studio. Abstract patterns of light and shadow, projected from a hidden source, dance across her body and the surrounding walls, constantly shifting with her movements. The camera focuses on the tension in her muscles and the expressive gestures of her hands. A single, dramatic slow-motion shot captures her mid-air leap, with the light patterns swirling around her like a galaxy. Moody, artistic, high contrast.

Artistic Style Rendering

Ghibli Forest Magic

Studio Ghibli-inspired animation with hand-painted watercolor texture
Ghibli art styleHand-painted textureMagical atmosphere
Prompt

Studio Ghibli-inspired anime style. A young girl with a straw hat lies peacefully in a sun-dappled magical forest, surrounded by friendly, glowing forest spirits (Kodama). A gentle breeze rustles the leaves of the giant, ancient trees. The air is filled with sparkling dust motes, illuminated by shafts of sunlight. The art style is soft, with a hand-painted watercolor texture. The scene feels serene, magical, and heartwarming.

Perfetto Per

🎬
Video Production
📢
Marketing Content
🎓
Educational Videos
📱
Social Media
🌐
Multilingual Content
💼
Corporate Training
🎭
Entertainment
💃
Performance Art
🎨
Animation & Anime
📚
Storytelling
👥
Dual Character Videos
🎙️
Interviews
📺
Broadcast Media

Specifiche Tecniche

Model Type:Audio-Visual Synchronized Generation
Key Features:A/V sync, Character restoration, Artistic rendering, Multi-language
Language Support:Chinese, English, and more
Output Quality:Professional HD video with audio
Generation Speed:Fast one-step generation
API Integration:RESTful API with comprehensive documentation

Sperimenta la Generazione Audio-Visiva Nativa

Unisciti a cineasti, inserzionisti e creatori di tutto il mondo che stanno rivoluzionando la creazione di contenuti video con la tecnologia rivoluzionaria di Seedance 1.5 Pro.

🎬One-Step A/V Sync
🌍Multilingual Support
Cost Effective

Alibaba WAN 2.5 Text-to-Image Model

Alibaba WAN 2.5 is a high-quality text-to-image model provided by Alibaba Cloud's DashScope platform.

Inizia con Oltre 300 Modelli,

Esplora tutti i modelli