krea-2-turbo/text-to-image

Tekst-naar-Beeld

Krea 2 Trubo Text-to-Image API

krea-2-turbo/text-to-image

Text-to-image

Generate high-fidelity images from text in seconds with Krea 2 Turbo, the speed-optimized open-source version of Krea 2, preserving its aesthetic range for rapid ideation.

Invoer

Prompt *

Image size

Beeldverhouding vergrendeld: als u één zijde wijzigt, wordt de andere proportioneel aangepast. Klik op het slot om vrij te bewerken.

Aantal afbeeldingen

Seed

Output format

Uitvoer

Inactief

Uw gegenereerde afbeeldingen verschijnen hier

Configureer parameters en klik op Uitvoeren om te beginnen met genereren

Elke uitvoering kost $0.008. Voor $10 kunt u ongeveer 1250 keer uitvoeren.

U kunt doorgaan met:

Beeld naar video Beeld naar beeld

Parameters

Codevoorbeeld
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": "krea-2-turbo/text-to-image",  # Required. model name
    "prompt": "A beautiful landscape with mountains and lake",  # Required. The text prompt describing the image to generate
    "image_size": "square_hd",  # Output image size. options: square_hd | square | portrait_3_4 | portrait_9_16 | landscape_4_3 | landscape_16_9
    "num_images": 1,  # Number of images to generate. (min: 1, max: 4)
    "seed": 1,  # Seed for reproducible generation
    "output_format": "png",  # Output image format. options: png | jpeg
}

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()

Installeren

Installeer het vereiste pakket voor uw programmeertaal.

pip install requests

Authenticatie

Alle API-verzoeken vereisen authenticatie via een API-sleutel. U kunt uw API-sleutel ophalen via het Atlas Cloud dashboard.

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

HTTP-headers

import os

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

Bescherm uw API-sleutel

Stel uw API-sleutel nooit bloot in client-side code of openbare repositories. Gebruik in plaats daarvan omgevingsvariabelen of een backend-proxy.

Een verzoek indienen

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())

Een verzoek indienen

Dien een asynchroon generatieverzoek in. De API retourneert een voorspellings-ID waarmee u de status kunt controleren en het resultaat kunt ophalen.

POST/api/v1/model/generateImage

Verzoekinhoud

import requests

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

data = {
    "model": "krea-2-turbo/text-to-image",
    "prompt": "A beautiful landscape with mountains and lake"
}

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

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

Antwoord

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

Status controleren

Bevraag het voorspellings-eindpunt om de huidige status van uw verzoek te controleren.

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

Polling-voorbeeld

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)

Statuswaarden

processingHet verzoek wordt nog verwerkt.

completedDe generatie is voltooid. Resultaten zijn beschikbaar.

succeededDe generatie is geslaagd. Resultaten zijn beschikbaar.

failedDe generatie is mislukt. Controleer het foutveld.

Voltooid antwoord

{
  "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"
  }
}

Bestanden uploaden

Upload bestanden naar Atlas Cloud opslag en ontvang een URL die u kunt gebruiken in uw API-verzoeken. Gebruik multipart/form-data om te uploaden.

POST/api/v1/model/uploadMedia

Upload-voorbeeld

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}")

Antwoord

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

Invoer-Schema

De volgende parameters worden geaccepteerd in de verzoekinhoud.

Totaal: 6Vereist: 2Optioneel: 4

modelstringrequired

model name

Default: "krea-2-turbo/text-to-image"

promptstringrequired

The text prompt describing the image to generate.

image_sizestring

Output image size. Choose a preset or specify custom dimensions.

Default: "square_hd"

square_hdsquareportrait_3_4portrait_9_16landscape_4_3landscape_16_9

num_imagesinteger

Number of images to generate.

Default: 1Min: 1Max: 4

seedinteger

Seed for reproducible generation. Omit for a random seed.

output_formatstring

Output image format.

Default: "png"

pngjpeg

Voorbeeld verzoekinhoud

{
  "model": "krea-2-turbo/text-to-image",
  "prompt": "A beautiful landscape",
  "image_size": "square_hd",
  "num_images": 1,
  "output_format": "png"
}

Uitvoer-Schema

De API retourneert een voorspellingsantwoord met de gegenereerde uitvoer-URL's.

modelstring

model name

Default: "krea-2-turbo/text-to-image"

created_atstring

ISO timestamp of when the request was created (e.g., "2023-04-01T12:34:56.789Z").

idstring

Unique identifier for the prediction.

outputsarray

Array of URLs to the generated images. Null when status is not completed.

statusstring

Status of the task: created, processing, completed, or failed.

Voorbeeldantwoord

{
  "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 integreert meer dan 400 AI-modellen rechtstreeks in uw AI-codeerassistent. Eén commando om te installeren, gebruik daarna natuurlijke taal om afbeeldingen, video's te genereren en te chatten met LLMs.

Ondersteunde clients

Claude Code

OpenAI Codex

Gemini CLI

Cursor

Windsurf

VS Code

Trae

GitHub Copilot

Cline

Roo Code

Amp

Goose

Replit

40+ ondersteunde clients

Installeren

npx skills add AtlasCloudAI/atlas-cloud-skills

API-sleutel instellen

Haal uw API-sleutel op via het Atlas Cloud dashboard en stel deze in als omgevingsvariabele.

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

Mogelijkheden

Eenmaal geïnstalleerd kunt u natuurlijke taal gebruiken in uw AI-assistent om toegang te krijgen tot alle Atlas Cloud modellen.

BeeldgeneratieGenereer afbeeldingen met modellen zoals Nano Banana 2, Z-Image en meer.

VideocreatieMaak video's van tekst of afbeeldingen met Kling, Vidu, Veo, enz.

LLM-chatChat met Qwen, DeepSeek en andere grote taalmodellen.

Media uploadenUpload lokale bestanden voor beeldbewerking en afbeelding-naar-video workflows.

Meer informatie

github.com/AtlasCloudAI/atlas-cloud-skills

MCP-server

De Atlas Cloud MCP-server verbindt uw IDE met meer dan 400 AI-modellen via het Model Context Protocol. Werkt met elke MCP-compatibele client.

Ondersteunde clients

Cursor

VS Code

Windsurf

Claude Code

OpenAI Codex

Gemini CLI

Cline

Roo Code

100+ ondersteunde clients

Installeren

npx -y atlascloud-mcp

Configuratie

Voeg de volgende configuratie toe aan het MCP-instellingenbestand van uw IDE.

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

Beschikbare tools

atlas_generate_imageGenereer afbeeldingen op basis van tekstprompts.

atlas_generate_videoMaak video's van tekst of afbeeldingen.

atlas_chatChat met grote taalmodellen.

atlas_list_modelsBlader door meer dan 300 beschikbare AI-modellen.

atlas_quick_generateContentcreatie in één stap met automatische modelselectie.

atlas_upload_mediaUpload lokale bestanden voor API-workflows.

Meer informatie

github.com/AtlasCloudAI/mcp-server

API Schema

{
  "info": {
    "description": "The AtlasCloud API.",
    "title": "AtlasCloud API",
    "version": "1.0.0"
  },
  "paths": {
    "/api/v1/model/generateImage": {
      "post": {
        "responses": {
          "200": {
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/PredictionResponse"
                }
              }
            },
            "description": "The request status."
          }
        },
        "requestBody": {
          "required": true,
          "content": {
            "application/json": {
              "schema": {
                "$ref": "#/components/schemas/Input"
              }
            }
          }
        }
      },
      "x-api-name": "model_run"
    },
    "/api/v1/model/prediction/{request_id}": {
      "get": {
        "responses": {
          "200": {
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/PredictionResponse"
                }
              }
            },
            "description": "Result of the request."
          }
        },
        "parameters": [
          {
            "in": "path",
            "name": "request_id",
            "schema": {
              "type": "string",
              "description": "Request ID"
            },
            "required": true
          }
        ]
      },
      "x-api-name": "model_result"
    }
  },
  "openapi": "3.0.0",
  "servers": [
    {
      "url": "https://api.atlascloud.ai"
    }
  ],
  "components": {
    "schemas": {
      "Input": {
        "properties": {
          "model": {
            "type": "string",
            "description": "model name",
            "default": "krea-2-turbo/text-to-image"
          },
          "prompt": {
            "description": "The text prompt describing the image to generate.",
            "type": "string",
            "minLength": 1
          },
          "image_size": {
            "description": "Output image size. Choose a preset or specify custom dimensions.",
            "type": "string",
            "default": "square_hd",
            "enum": [
              "square_hd",
              "square",
              "portrait_3_4",
              "portrait_9_16",
              "landscape_4_3",
              "landscape_16_9"
            ],
            "x-ui-component": "select",
            "x-enum-labels": {
              "square_hd": "Square HD (1024×1024)",
              "square": "Square (512×512)",
              "portrait_3_4": "Portrait 3:4",
              "portrait_9_16": "Portrait 9:16",
              "landscape_4_3": "Landscape 4:3",
              "landscape_16_9": "Landscape 16:9"
            }
          },
          "num_images": {
            "description": "Number of images to generate.",
            "type": "integer",
            "default": 1,
            "minimum": 1,
            "maximum": 4
          },
          "seed": {
            "description": "Seed for reproducible generation. Omit for a random seed.",
            "type": "integer"
          },
          "output_format": {
            "description": "Output image format.",
            "type": "string",
            "default": "png",
            "enum": [
              "png",
              "jpeg"
            ],
            "x-ui-component": "select"
          }
        },
        "required": [
          "model",
          "prompt"
        ],
        "type": "object",
        "x-order-properties": [
          "model",
          "prompt",
          "image_size",
          "num_images",
          "seed",
          "output_format"
        ]
      },
      "PredictionResponse": {
        "properties": {
          "model": {
            "type": "string",
            "description": "model name",
            "default": "krea-2-turbo/text-to-image"
          },
          "created_at": {
            "description": "ISO timestamp of when the request was created (e.g., \"2023-04-01T12:34:56.789Z\").",
            "format": "date-time",
            "type": "string"
          },
          "has_nsfw_contents": {
            "description": "Array of boolean values indicating NSFW detection for each output.",
            "items": {
              "type": "boolean"
            },
            "type": "array"
          },
          "id": {
            "description": "Unique identifier for the prediction.",
            "type": "string"
          },
          "outputs": {
            "description": "Array of URLs to the generated images. Null when status is not completed.",
            "items": {
              "type": "string"
            },
            "nullable": true,
            "type": "array"
          },
          "status": {
            "description": "Status of the task: created, processing, completed, or failed.",
            "type": "string"
          },
          "urls": {
            "description": "Object containing related API endpoints.",
            "type": "object"
          }
        },
        "type": "object"
      }
    },
    "securitySchemes": {
      "apiKeyAuth": {
        "in": "header",
        "name": "Authorization",
        "type": "apiKey"
      }
    }
  }
}

LLM-vriendelijke Promptsjabloon

# krea-2-turbo/text-to-image

> Generate high-fidelity images from text in seconds with Krea 2 Turbo, the speed-optimized open-source version of Krea 2, preserving its aesthetic range for rapid ideation.


## Overview

- **Submit endpoint (POST)**: `https://api.atlascloud.ai/api/v1/model/generateImage` — 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**: `krea-2-turbo/text-to-image`


## 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_):
  model name
  - Default: `"krea-2-turbo/text-to-image"`

- **`prompt`** (`string`, _required_):
  The text prompt describing the image to generate.

- **`image_size`** (`string`, _optional_):
  Output image size. Choose a preset or specify custom dimensions.
  - Default: `"square_hd"`
  - Options: "square_hd", "square", "portrait_3_4", "portrait_9_16", "landscape_4_3", "landscape_16_9"

- **`num_images`** (`integer`, _optional_):
  Number of images to generate.
  - Default: `1`
  - Min: 1
  - Max: 4

- **`seed`** (`integer`, _optional_):
  Seed for reproducible generation. Omit for a random seed.

- **`output_format`** (`string`, _optional_):
  Output image format.
  - Default: `"png"`
  - Options: "png", "jpeg"



**Required Parameters Example**:

```json
{
  "model": "krea-2-turbo/text-to-image",
  "prompt": ""
}
```


**Full Example**:

```json
{
  "model": "krea-2-turbo/text-to-image",
  "prompt": "",
  "image_size": "square_hd",
  "num_images": 1,
  "seed": 0,
  "output_format": "png"
}
```


### Output Schema

The API returns the following output format:


- **`model`** (`string`, _optional_):
  model name
  - Default: `"krea-2-turbo/text-to-image"`

- **`created_at`** (`string`, _optional_):
  ISO timestamp of when the request was created (e.g., "2023-04-01T12:34:56.789Z").

- **`has_nsfw_contents`** (`array[boolean]`, _optional_):
  Array of boolean values indicating NSFW detection for each output.

- **`id`** (`string`, _optional_):
  Unique identifier for the prediction.

- **`outputs`** (`array[string]`, _optional_):
  Array of URLs to the generated images. Null when status is not completed.

- **`status`** (`string`, _optional_):
  Status of the task: created, processing, completed, or failed.

- **`urls`** (`object`, _optional_):
  Object containing related API endpoints.



**Example Response**:

```json
{
  "model": "krea-2-turbo/text-to-image",
  "created_at": "",
  "has_nsfw_contents": [],
  "id": "",
  "outputs": [
    ""
  ],
  "status": "",
  "urls": {}
}
```


## Usage Examples

### cURL

```bash
# Step 1: Start generation (async)
curl -X POST "https://api.atlascloud.ai/api/v1/model/generateImage" \
  -H "Authorization: Bearer $ATLASCLOUD_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
  "model": "krea-2-turbo/text-to-image",
  "prompt": "",
  "image_size": "square_hd",
  "num_images": 1,
  "seed": 0,
  "output_format": "png"
}'

# 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/krea-2-turbo/text-to-image)

A colorful alpine meadow blooming beneath towering snow-capped mountains, butterflies dancing among vibrant flowers, crystal stream flowing gently through the valley, cinematic realism, breathtaking scenery

Laden...

Krea 2 Turbo

Krea 2 Turbo is a high-fidelity text-to-image model that generates images from text prompts in seconds. Tuned for speed without sacrificing detail, it delivers crisp, aesthetically strong results with flexible aspect ratios and optional prompt expansion — ideal for rapid creative iteration and production-ready visuals.

🌟 Key Features

✏️ Text-to-Image

Generate high-fidelity images from detailed text prompts with strong semantic understanding and photorealistic quality.

⚡ Turbo Speed

Optimized for fast generation, delivering crisp results in seconds.

📐 Flexible Output Sizes

Choose from six standard presets — square HD, portrait, landscape — or specify custom dimensions to match your layout.

🔁 Reproducible Results

Pin a seed value to reproduce or iterate on a specific generation, enabling systematic prompt refinement.

🖼 Batch Generation

Request up to 4 images per call with num_images to explore multiple variations at once.

⚙️ Parameters

Parameter	Required	Description
`prompt`	✅	Text description of the image to generate.
`image_size`	❌	Output size preset: `square_hd` (default), `square`, `portrait_4_3`, `portrait_16_9`, `landscape_4_3`, `landscape_16_9`. Also accepts custom `WxH` (e.g. `1024x768`).
`num_images`	❌	Number of images to generate (1–4, default: 1).
`seed`	❌	Seed for reproducible output. Omit for a random seed.
`output_format`	❌	Output format: `png` (default) or `jpeg`.

💲 Pricing

Billing Standard	Price
Per megapixel	$0.0088

💡 Prompt Tips

A vintage travel poster for Mars, bold retro typography, warm sunset palette, rocket silhouette, textured paper grain, cinematic composition.

Be specific about subject, environment, lighting, and camera angle for best results.
Fix seed when iterating on a prompt to isolate the effect of each change.
Request multiple images with num_images to explore variations in a single call.

🎯 Use Cases

Creative Illustration — Generate concept art, characters, and environments from descriptive text prompts.
Marketing Visuals — Produce eye-catching posters, banners, and ad creatives quickly.
Social Media Content — Generate scroll-stopping visuals in portrait or square formats for any platform.
Rapid Prototyping — Iterate on creative directions at scale before committing to production assets.
Design Exploration — Batch-generate variations to compare styles, compositions, and color palettes.

📝 Notes

prompt is the only required field (besides model).
image_size accepts either a preset name or a custom WxH string (e.g. 1024x768).
Task status values: created, processing, completed, failed.
Generated image URLs are returned in outputs once status is completed.

Krea 2 Trubo Text-to-Image API

Invoer

Uitvoer

Parameters

Codevoorbeeld

Installeren

Authenticatie

HTTP-headers

Een verzoek indienen

Een verzoek indienen

Verzoekinhoud

Antwoord

Status controleren

Polling-voorbeeld

Statuswaarden

Voltooid antwoord

Bestanden uploaden

Upload-voorbeeld

Antwoord

Invoer-Schema

Voorbeeld verzoekinhoud

Uitvoer-Schema

Voorbeeldantwoord

Atlas Cloud Skills

Ondersteunde clients

Installeren

API-sleutel instellen

Mogelijkheden

MCP-server

Ondersteunde clients

Installeren

Configuratie

Beschikbare tools

API Schema

LLM-vriendelijke Promptsjabloon

Krea 2 Turbo

🌟 Key Features

✏️ Text-to-Image

⚡ Turbo Speed

📐 Flexible Output Sizes

🔁 Reproducible Results

🖼 Batch Generation

⚙️ Parameters

💲 Pricing

💡 Prompt Tips

🎯 Use Cases

📝 Notes

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Youchuan V8.1 Style Transfer

Youchuan V8.1 Blend

Eén API voor alle media-AI.

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Invoer

Uitvoer

Parameters

Codevoorbeeld

Installeren

Authenticatie

HTTP-headers

Een verzoek indienen

Een verzoek indienen

Verzoekinhoud

Antwoord

Status controleren

Polling-voorbeeld

Statuswaarden