# Tada 3B Text to Speech — API Reference Model ID: `model_tada-3b-text-to-speech` --- ## Authentication - **API_KEY** and **API_SECRET** are found in your [Scenario Project Settings](https://app.scenario.com/team&tab=project_api_keys) under API Keys. - Set them as environment variables `SCENARIO_SDK_API_KEY` and `SCENARIO_SDK_API_SECRET` — both SDKs pick them up by default. - For raw HTTP (cURL), use Basic Auth: `Authorization: Basic base64(":")`. ### Install the SDK - JavaScript / TypeScript: `npm install @scenario-labs/sdk` - Python: `pip install scenario-sdk` --- ## Generate **Endpoint:** `POST https://api.cloud.scenario.com/v1/generate/custom/model_tada-3b-text-to-speech` ### Parameters | Parameter | Type | Required | Default | Description | |-----------|------|----------|---------|-------------| | `audio` | assetId | yes | - | Reference audio for voice cloning. | | `prompt` | string | yes | - | Text to synthesize with the reference voice. | | `transcript` | string | - | `` | Transcript of the reference audio. Required for non-English references. | | `language` | string | - | `en` | Language used for text alignment. | | `numInferenceSteps` | number | - | `20` | Number of ODE solver steps for acoustic generation. | | `speedUpFactor` | number | - | `1` | Values > 1 speed up and values < 1 slow down speech. | | `temperature` | number | - | `0.6` | Sampling temperature for text token generation. | | `topP` | number | - | `0.9` | Top-p nucleus sampling value. | | `repetitionPenalty` | number | - | `1.1` | Penalty applied to repeated tokens. | | `acousticCfgScale` | number | - | `1.6` | Classifier-free guidance scale for acoustic generation. | | `noiseTemperature` | number | - | `0.9` | Temperature for diffusion noise during flow matching. | | `numExtraSteps` | number | - | `0` | Additional autoregressive steps for continuation. | ### Example Requests **cURL** ```bash curl -X POST "https://api.cloud.scenario.com/v1/generate/custom/model_tada-3b-text-to-speech" \ -H "Authorization: Basic $(echo -n ':' | base64)" \ -H "Content-Type: application/json" \ --data-binary @- <<'EOF' { "audio": "", "prompt": "A fantasy landscape", "transcript": "", "language": "en", "numInferenceSteps": 20, "speedUpFactor": 1, "temperature": 0.6, "topP": 0.9, "repetitionPenalty": 1.1, "acousticCfgScale": 1.6, "noiseTemperature": 0.9, "numExtraSteps": 0 } EOF ``` **Python** ```python import os from scenario_sdk import Scenario client = Scenario( api_key=os.environ.get("SCENARIO_SDK_API_KEY"), api_secret=os.environ.get("SCENARIO_SDK_API_SECRET"), ) body = { "audio": "", "prompt": "A fantasy landscape", "transcript": "", "language": "en", "numInferenceSteps": 20, "speedUpFactor": 1, "temperature": 0.6, "topP": 0.9, "repetitionPenalty": 1.1, "acousticCfgScale": 1.6, "noiseTemperature": 0.9, "numExtraSteps": 0 } response = client.generate.run_model( model_id="model_tada-3b-text-to-speech", body=body, ) print(response) ``` **JavaScript** ```javascript import Scenario from "@scenario-labs/sdk"; const client = new Scenario({ apiKey: process.env["SCENARIO_SDK_API_KEY"], apiSecret: process.env["SCENARIO_SDK_API_SECRET"], }); const body = { "audio": "", "prompt": "A fantasy landscape", "transcript": "", "language": "en", "numInferenceSteps": 20, "speedUpFactor": 1, "temperature": 0.6, "topP": 0.9, "repetitionPenalty": 1.1, "acousticCfgScale": 1.6, "noiseTemperature": 0.9, "numExtraSteps": 0 }; const response = await client.generate.runModel("model_tada-3b-text-to-speech", { body }); console.info(response); ``` --- ## Retrieve Results After submitting a generation request, you receive a `jobId`. Poll the job until `job.status` is `"success"`. The generated asset IDs are in `job.metadata.assetIds`. **Endpoint:** `GET https://api.cloud.scenario.com/v1/jobs/{jobId}` ### Example Requests **cURL** ```bash curl -X GET "https://api.cloud.scenario.com/v1/jobs/" \ -H "Authorization: Basic $(echo -n ':' | base64)" ``` **Python** ```python job = client.jobs.retrieve(job_id="") print(job.status) print(job.metadata.asset_ids) ``` **JavaScript** ```javascript // Option 1 — wait on the response from runModel using the SDK helper const completed = await response.job.wait(); console.info(completed.status); console.info(completed.metadata?.assetIds); // Option 2 — retrieve a job by its ID const job = await client.jobs.retrieve(""); console.info(job.status); console.info(job.metadata?.assetIds); ``` **Example response:** ```json { "job": { "jobId": "job_abc123", "status": "success", "metadata": { "assetIds": [ "asset_abc123" ] } } } ``` > **Important:** Generated asset URLs are **temporary** and expire after a short period. Download and store any images you wish to keep before the URL expires. More info: [Content Delivery Network (CDN)](https://docs.scenario.com/get-started/documentation/content-delivery-network-cdn). --- *Generated by [Scenario](https://app.scenario.com)*