google/gemini-2.5-pro-tts

Text-zu-Audio

PRO

Gemini 2.5 Pro TTS API by Google

google/gemini-2.5-pro-tts

Gemini-2.5-pro-tts

Gemini text-to-speech (Pro): studio-quality, expressive speech from text with 30 prebuilt voices and natural-language style control. Powered by gemini-2.5-pro-preview-tts.

Gemini 2.5 Pro TTS wurde von Google entwickelt. Atlas Cloud (betrieben von Atlas Cloud AI LLC) stellt lediglich den Zugang bereit und ist nicht Eigentümerin des Modells. Alle Marken sind Eigentum ihrer jeweiligen Inhaber.

Eingabe

Text *

Stimme

Ausgabe

Inaktiv

Dein generiertes Audio erscheint hier

Text eingeben und auf Ausführen klicken, um Sprache zu synthetisieren.

Parameter

Codebeispiel
import requests
import time

# Step 1: Start audio generation
generate_url = "https://api.atlascloud.ai/api/v1/model/generateAudio"
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer $ATLASCLOUD_API_KEY"
}
data = {
    "model": "google/gemini-2.5-pro-tts",  # Required. Model name. options: google/gemini-2.5-pro-tts
    "text": "Welcome to Atlas Cloud — One API for All Media AI.",  # Required. Text to synthesize into speech audio
    "voice": "Kore",  # Gemini prebuilt voice
}

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 audio:", 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)

audio_url = check_status()

Installieren

Installieren Sie das erforderliche Paket für Ihre Programmiersprache.

pip install requests

Authentifizierung

Alle API-Anfragen erfordern eine Authentifizierung über einen API-Schlüssel. Sie können Ihren API-Schlüssel über das Atlas Cloud Dashboard erhalten.

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

HTTP-Header

import os

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

Schützen Sie Ihren API-Schlüssel

Geben Sie Ihren API-Schlüssel niemals in clientseitigem Code oder öffentlichen Repositories preis. Verwenden Sie stattdessen Umgebungsvariablen oder einen Backend-Proxy.

Anfrage senden

import requests

url = "https://api.atlascloud.ai/api/v1/model/generateAudio"
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer $ATLASCLOUD_API_KEY"
}
data = {
    "model": "your-model",
    "text": "Hello, welcome to AtlasCloud text-to-speech."
}

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

Anfrage senden

Senden Sie eine asynchrone Generierungsanfrage. Die API gibt eine Vorhersage-ID zurück, mit der Sie den Status prüfen und das Ergebnis abrufen können.

POST/api/v1/model/generateAudio

Anfragekörper

import requests

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

data = {
    "model": "google/gemini-2.5-pro-tts",
    "text": "Hello, welcome to AtlasCloud text-to-speech."
}

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

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

Antwort

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

Status prüfen

Fragen Sie den Vorhersage-Endpunkt ab, um den aktuellen Status Ihrer Anfrage zu überprüfen.

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

Abfrage-Beispiel

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)

Statuswerte

processingDie Anfrage wird noch verarbeitet.

completedDie Generierung ist abgeschlossen. Ergebnisse sind verfügbar.

succeededDie Generierung war erfolgreich. Ergebnisse sind verfügbar.

failedDie Generierung ist fehlgeschlagen. Überprüfen Sie das Fehlerfeld.

Abgeschlossene Antwort

{
  "data": {
    "id": "pred_abc123",
    "status": "completed",
    "outputs": [
      "https://storage.atlascloud.ai/outputs/result.mp3"
    ],
    "metrics": {
      "predict_time": 8.3
    },
    "created_at": "2025-01-01T00:00:00Z",
    "completed_at": "2025-01-01T00:00:10Z"
  }
}

Eingabe-Schema

Die folgenden Parameter werden im Anfragekörper akzeptiert.

Gesamt: 3Erforderlich: 2Optional: 1

modelstringrequired

Model name.

Default: "google/gemini-2.5-pro-tts"

google/gemini-2.5-pro-tts

textstringrequired

Text to synthesize into speech audio. Use natural-language instructions in the text for style, accent, pace, and tone control.

Default: "Welcome to Atlas Cloud — One API for All Media AI."

voicestring

Gemini prebuilt voice.

Default: "Kore"

ZephyrPuckCharonKoreFenrirLedaOrusAoedeCallirrhoeAutonoeEnceladusIapetusUmbrielAlgiebaDespinaErinomeAlgenibRasalgethiLaomedeiaAchernarAlnilamSchedarGacruxPulcherrimaAchirdZubenelgenubiVindemiatrixSadachbiaSadaltagerSulafat

Beispiel-Anfragekörper

{
  "model": "google/gemini-2.5-pro-tts",
  "text": "Welcome to Atlas Cloud — One API for All Media AI.",
  "voice": "Kore"
}

Ausgabe-Schema

Die API gibt eine Vorhersage-Antwort mit den generierten Ausgabe-URLs zurück.

idstring

Unique identifier for the prediction.

modelstring

Model ID used for the prediction.

statusstring

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

outputsarray

Array of URLs to the generated audio.

created_atstring

ISO timestamp of when the request was created.

Beispielantwort

{
  "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 integriert über 400 KI-Modelle direkt in Ihren KI-Programmierassistenten. Ein Befehl zur Installation, dann generieren Sie per natürlicher Sprache Bilder und Videos und chatten mit LLMs.

Unterstützte Clients

Claude Code

OpenAI Codex

Gemini CLI

Cursor

Windsurf

VS Code

Trae

GitHub Copilot

Cline

Roo Code

Amp

Goose

Replit

40+ unterstützte clients

Installieren

npx skills add AtlasCloudAI/atlas-cloud-skills

API-Schlüssel einrichten

Erhalten Sie Ihren API-Schlüssel über das Atlas Cloud Dashboard und setzen Sie ihn als Umgebungsvariable.

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

Funktionen

Nach der Installation können Sie natürliche Sprache in Ihrem KI-Assistenten verwenden, um auf alle Atlas Cloud Modelle zuzugreifen.

BildgenerierungGenerieren Sie Bilder mit Modellen wie Nano Banana 2, Z-Image und mehr.

VideoerstellungErstellen Sie Videos aus Text oder Bildern mit Kling, Vidu, Veo usw.

LLM-ChatChatten Sie mit Qwen, DeepSeek und anderen großen Sprachmodellen.

Medien-UploadLaden Sie lokale Dateien für Bildbearbeitung und Bild-zu-Video-Workflows hoch.

Mehr erfahren

github.com/AtlasCloudAI/atlas-cloud-skills

MCP-Server

Der Atlas Cloud MCP-Server verbindet Ihre IDE mit über 400 KI-Modellen über das Model Context Protocol. Funktioniert mit jedem MCP-kompatiblen Client.

Unterstützte Clients

Cursor

VS Code

Windsurf

Claude Code

OpenAI Codex

Gemini CLI

Cline

Roo Code

100+ unterstützte clients

Installieren

npx -y atlascloud-mcp

Konfiguration

Fügen Sie die folgende Konfiguration zur MCP-Einstellungsdatei Ihrer IDE hinzu.

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

Verfügbare Werkzeuge

atlas_generate_imageGenerieren Sie Bilder aus Textbeschreibungen.

atlas_generate_videoErstellen Sie Videos aus Text oder Bildern.

atlas_chatChatten Sie mit großen Sprachmodellen.

atlas_list_modelsDurchsuchen Sie über 400 verfügbare KI-Modelle.

atlas_quick_generateInhaltserstellung in einem Schritt mit automatischer Modellauswahl.

atlas_upload_mediaLaden Sie lokale Dateien für API-Workflows hoch.

Mehr erfahren

github.com/AtlasCloudAI/mcp-server

API-Schema

{
  "info": {
    "title": "AtlasCloud API",
    "version": "1.0.0",
    "description": "The AtlasCloud API."
  },
  "openapi": "3.0.0",
  "paths": {
    "/api/v1/model/generateAudio": {
      "post": {
        "requestBody": {
          "content": {
            "application/json": {
              "schema": {
                "$ref": "#/components/schemas/Input"
              }
            }
          },
          "required": true
        },
        "responses": {
          "200": {
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/PredictionResponse"
                }
              }
            },
            "description": "The request status."
          }
        }
      },
      "x-api-name": "model_run"
    },
    "/api/v1/model/prediction/{request_id}": {
      "get": {
        "parameters": [
          {
            "in": "path",
            "name": "request_id",
            "required": true,
            "schema": {
              "description": "Request ID",
              "type": "string"
            }
          }
        ],
        "responses": {
          "200": {
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/PredictionResponse"
                }
              }
            },
            "description": "Result of the request."
          }
        }
      },
      "x-api-name": "model_result"
    }
  },
  "components": {
    "schemas": {
      "Input": {
        "type": "object",
        "properties": {
          "model": {
            "type": "string",
            "description": "Model name.",
            "default": "google/gemini-2.5-pro-tts",
            "enum": [
              "google/gemini-2.5-pro-tts"
            ]
          },
          "text": {
            "type": "string",
            "description": "Text to synthesize into speech audio. Use natural-language instructions in the text for style, accent, pace, and tone control.",
            "default": "Welcome to Atlas Cloud — One API for All Media AI.",
            "x-ui-component": "textarea"
          },
          "voice": {
            "type": "string",
            "description": "Gemini prebuilt voice.",
            "default": "Kore",
            "enum": [
              "Zephyr",
              "Puck",
              "Charon",
              "Kore",
              "Fenrir",
              "Leda",
              "Orus",
              "Aoede",
              "Callirrhoe",
              "Autonoe",
              "Enceladus",
              "Iapetus",
              "Umbriel",
              "Algieba",
              "Despina",
              "Erinome",
              "Algenib",
              "Rasalgethi",
              "Laomedeia",
              "Achernar",
              "Alnilam",
              "Schedar",
              "Gacrux",
              "Pulcherrima",
              "Achird",
              "Zubenelgenubi",
              "Vindemiatrix",
              "Sadachbia",
              "Sadaltager",
              "Sulafat"
            ],
            "x-ui-component": "select",
            "x-enum-options": {
              "Zephyr": {
                "name": "Zephyr (Bright)",
                "example": "https://static.atlascloud.ai/model/example/gemini-tts/zephyr.wav"
              },
              "Puck": {
                "name": "Puck (Upbeat)",
                "example": "https://static.atlascloud.ai/model/example/gemini-tts/puck.wav"
              },
              "Charon": {
                "name": "Charon (Informative)",
                "example": "https://static.atlascloud.ai/model/example/gemini-tts/charon.wav"
              },
              "Kore": {
                "name": "Kore (Firm)",
                "example": "https://static.atlascloud.ai/model/example/gemini-tts/kore.wav"
              },
              "Fenrir": {
                "name": "Fenrir (Excitable)",
                "example": "https://static.atlascloud.ai/model/example/gemini-tts/fenrir.wav"
              },
              "Leda": {
                "name": "Leda (Youthful)",
                "example": "https://static.atlascloud.ai/model/example/gemini-tts/leda.wav"
              },
              "Orus": {
                "name": "Orus (Firm)",
                "example": "https://static.atlascloud.ai/model/example/gemini-tts/orus.wav"
              },
              "Aoede": {
                "name": "Aoede (Breezy)",
                "example": "https://static.atlascloud.ai/model/example/gemini-tts/aoede.wav"
              },
              "Callirrhoe": {
                "name": "Callirrhoe (Easy-going)",
                "example": "https://static.atlascloud.ai/model/example/gemini-tts/callirrhoe.wav"
              },
              "Autonoe": {
                "name": "Autonoe (Bright)",
                "example": "https://static.atlascloud.ai/model/example/gemini-tts/autonoe.wav"
              },
              "Enceladus": {
                "name": "Enceladus (Breathy)",
                "example": "https://static.atlascloud.ai/model/example/gemini-tts/enceladus.wav"
              },
              "Iapetus": {
                "name": "Iapetus (Clear)",
                "example": "https://static.atlascloud.ai/model/example/gemini-tts/iapetus.wav"
              },
              "Umbriel": {
                "name": "Umbriel (Easy-going)",
                "example": "https://static.atlascloud.ai/model/example/gemini-tts/umbriel.wav"
              },
              "Algieba": {
                "name": "Algieba (Smooth)",
                "example": "https://static.atlascloud.ai/model/example/gemini-tts/algieba.wav"
              },
              "Despina": {
                "name": "Despina (Smooth)",
                "example": "https://static.atlascloud.ai/model/example/gemini-tts/despina.wav"
              },
              "Erinome": {
                "name": "Erinome (Clear)",
                "example": "https://static.atlascloud.ai/model/example/gemini-tts/erinome.wav"
              },
              "Algenib": {
                "name": "Algenib (Gravelly)",
                "example": "https://static.atlascloud.ai/model/example/gemini-tts/algenib.wav"
              },
              "Rasalgethi": {
                "name": "Rasalgethi (Informative)",
                "example": "https://static.atlascloud.ai/model/example/gemini-tts/rasalgethi.wav"
              },
              "Laomedeia": {
                "name": "Laomedeia (Upbeat)",
                "example": "https://static.atlascloud.ai/model/example/gemini-tts/laomedeia.wav"
              },
              "Achernar": {
                "name": "Achernar (Soft)",
                "example": "https://static.atlascloud.ai/model/example/gemini-tts/achernar.wav"
              },
              "Alnilam": {
                "name": "Alnilam (Firm)",
                "example": "https://static.atlascloud.ai/model/example/gemini-tts/alnilam.wav"
              },
              "Schedar": {
                "name": "Schedar (Even)",
                "example": "https://static.atlascloud.ai/model/example/gemini-tts/schedar.wav"
              },
              "Gacrux": {
                "name": "Gacrux (Mature)",
                "example": "https://static.atlascloud.ai/model/example/gemini-tts/gacrux.wav"
              },
              "Pulcherrima": {
                "name": "Pulcherrima (Forward)",
                "example": "https://static.atlascloud.ai/model/example/gemini-tts/pulcherrima.wav"
              },
              "Achird": {
                "name": "Achird (Friendly)",
                "example": "https://static.atlascloud.ai/model/example/gemini-tts/achird.wav"
              },
              "Zubenelgenubi": {
                "name": "Zubenelgenubi (Casual)",
                "example": "https://static.atlascloud.ai/model/example/gemini-tts/zubenelgenubi.wav"
              },
              "Vindemiatrix": {
                "name": "Vindemiatrix (Gentle)",
                "example": "https://static.atlascloud.ai/model/example/gemini-tts/vindemiatrix.wav"
              },
              "Sadachbia": {
                "name": "Sadachbia (Lively)",
                "example": "https://static.atlascloud.ai/model/example/gemini-tts/sadachbia.wav"
              },
              "Sadaltager": {
                "name": "Sadaltager (Knowledgeable)",
                "example": "https://static.atlascloud.ai/model/example/gemini-tts/sadaltager.wav"
              },
              "Sulafat": {
                "name": "Sulafat (Warm)",
                "example": "https://static.atlascloud.ai/model/example/gemini-tts/sulafat.wav"
              }
            }
          }
        },
        "required": [
          "model",
          "text"
        ],
        "x-order-properties": [
          "model",
          "text",
          "voice"
        ]
      },
      "PredictionResponse": {
        "type": "object",
        "properties": {
          "id": {
            "description": "Unique identifier for the prediction.",
            "type": "string"
          },
          "model": {
            "description": "Model ID used for the prediction.",
            "type": "string"
          },
          "status": {
            "description": "Status of the task: created, processing, completed, or failed.",
            "type": "string"
          },
          "outputs": {
            "description": "Array of URLs to the generated audio.",
            "items": {
              "type": "string",
              "x-format": "audio"
            },
            "type": "array"
          },
          "created_at": {
            "description": "ISO timestamp of when the request was created.",
            "format": "date-time",
            "type": "string"
          },
          "urls": {
            "description": "Object containing related API endpoints.",
            "type": "object"
          }
        }
      }
    }
  },
  "servers": [
    {
      "url": "https://api.atlascloud.ai"
    }
  ]
}

LLM-freundliche Prompt-Vorlage

# google/gemini-2.5-pro-tts

> Gemini text-to-speech (Pro): studio-quality, expressive speech from text with 30 prebuilt voices and natural-language style control. Powered by gemini-2.5-pro-preview-tts.


## Overview

- **Submit endpoint (POST)**: `https://api.atlascloud.ai/api/v1/model/generateAudio` — 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**: `google/gemini-2.5-pro-tts`


## 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: `"google/gemini-2.5-pro-tts"`
  - Options: "google/gemini-2.5-pro-tts"

- **`text`** (`string`, _required_):
  Text to synthesize into speech audio. Use natural-language instructions in the text for style, accent, pace, and tone control.
  - Default: `"Welcome to Atlas Cloud — One API for All Media AI."`

- **`voice`** (`string`, _optional_):
  Gemini prebuilt voice.
  - Default: `"Kore"`
  - Options: "Zephyr", "Puck", "Charon", "Kore", "Fenrir", "Leda", "Orus", "Aoede", "Callirrhoe", "Autonoe", "Enceladus", "Iapetus", "Umbriel", "Algieba", "Despina", "Erinome", "Algenib", "Rasalgethi", "Laomedeia", "Achernar", "Alnilam", "Schedar", "Gacrux", "Pulcherrima", "Achird", "Zubenelgenubi", "Vindemiatrix", "Sadachbia", "Sadaltager", "Sulafat"



**Required Parameters Example**:

```json
{
  "model": "google/gemini-2.5-pro-tts",
  "text": "Welcome to Atlas Cloud — One API for All Media AI."
}
```


**Full Example**:

```json
{
  "model": "google/gemini-2.5-pro-tts",
  "text": "Welcome to Atlas Cloud — One API for All Media AI.",
  "voice": "Kore"
}
```


### Output Schema

The API returns the following output format:


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

- **`model`** (`string`, _optional_):
  Model ID used for the prediction.

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

- **`outputs`** (`array[string]`, _optional_):
  Array of URLs to the generated audio.

- **`created_at`** (`string`, _optional_):
  ISO timestamp of when the request was created.

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



**Example Response**:

```json
{
  "id": "",
  "model": "",
  "status": "",
  "outputs": [
    ""
  ],
  "created_at": "",
  "urls": {}
}
```


## Usage Examples

### cURL

```bash
# Step 1: Start generation (async)
curl -X POST "https://api.atlascloud.ai/api/v1/model/generateAudio" \
  -H "Authorization: Bearer $ATLASCLOUD_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
  "model": "google/gemini-2.5-pro-tts",
  "text": "Welcome to Atlas Cloud — One API for All Media AI.",
  "voice": "Kore"
}'

# 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/google/gemini-2.5-pro-tts)

Step into the heart of the forest, where towering trees whisper with the wind and golden light filters through the leaves. Every footstep echoes with stories older than time, inviting you to slow down, breathe deeply, and rediscover the beauty hidden in silence.

Wird geladen...

Gemini 2.5 Pro TTS

Studio-quality, expressive text-to-speech powered by Google's gemini-2.5-pro-preview-tts.

Highlights

30 prebuilt voices — Kore, Puck, Charon, Aoede, Fenrir, Leda, Orus, Zephyr, and more.
Style prompting — steer tone, pace and emotion in natural language inside text, e.g. "Say cheerfully: ..." or "Read slowly and calmly: ...".
Output is a WAV file (24 kHz PCM); billed per 1k characters.

Parameters

field	required	notes
`text`	yes	text to synthesize (may embed a style instruction), ≤10000 chars
`voice_name`	no	prebuilt voice, default `Kore`

MiniMax Music 3.0

MiniMax Music 3.0 is MiniMax's 11.1B-parameter open-weights music model that turns a musical description and optional lyrics into a complete, fully arranged and mixed song of up to five minutes - vocals, instrumentation and production included - in a single generation, with section-tag control over the arrangement and vocal or instrumental output.

Gemini 2.5 Pro TTS API by Google

Eingabe

Ausgabe

Parameter

Codebeispiel

Installieren

Authentifizierung

HTTP-Header

Anfrage senden

Anfrage senden

Anfragekörper

Antwort

Status prüfen

Abfrage-Beispiel

Statuswerte

Abgeschlossene Antwort

Eingabe-Schema

Beispiel-Anfragekörper

Ausgabe-Schema

Beispielantwort

Atlas Cloud Skills

Unterstützte Clients

Installieren

API-Schlüssel einrichten

Funktionen

MCP-Server

Unterstützte Clients

Installieren

Konfiguration

Verfügbare Werkzeuge

API-Schema

LLM-freundliche Prompt-Vorlage

Gemini 2.5 Pro TTS

Highlights

Parameters

Ähnliche Modelle Erkunden

MiniMax Music 3.0

MiniMax Lyrics Generation

Suno chirp-v4-5-all

Suno chirp-v4-5-plus

Suno chirp-auk

Suno chirp-fenix

Suno chirp-v3-5

Suno chirp-v4

Suno chirp-v5

Seed Audio 1.0

xAI TTS v1

Seed ASR 2.0

MiniMax Music 2.6

ElevenLabs v3 Text-to-Speech

xAI STT v1

Eine API für alle Media-KI.

Eingabe

Ausgabe

Parameter

Codebeispiel

Installieren

Authentifizierung

HTTP-Header

Anfrage senden

Anfrage senden

Anfragekörper

Antwort

Status prüfen

Abfrage-Beispiel

Statuswerte

Abgeschlossene Antwort

Eingabe-Schema

Beispiel-Anfragekörper

Ausgabe-Schema

Beispielantwort

Atlas Cloud Skills

Unterstützte Clients

Installieren

API-Schlüssel einrichten

Funktionen

MCP-Server

Unterstützte Clients

Installieren

Konfiguration