@telnyx/ai-sdk-provider

Telnyx provider for the Vercel AI SDK, with support for chat, embeddings, speech generation, and transcription.

Setup

npm install ai @telnyx/ai-sdk-provider zod

zod is a required peer dependency. This package imports zod/v4 internally for speech and transcription model schemas, so consumers must install it even if they are not using tool calling.

Set your Telnyx API key:

export TELNYX_API_KEY="your_api_key_here"

Usage

Chat (LLM)

import { telnyx } from '@telnyx/ai-sdk-provider';
import { generateText } from 'ai';

const { text } = await generateText({
  model: telnyx('Qwen/Qwen3-235B-A22B'),
  prompt: 'Explain WebRTC in simple terms',
});

Streaming

import { telnyx } from '@telnyx/ai-sdk-provider';
import { streamText } from 'ai';

const result = streamText({
  model: telnyx('moonshotai/Kimi-K2.5'),
  prompt: 'Write a poem about the cloud',
});

for await (const chunk of result.textStream) {
  process.stdout.write(chunk);
}

Tool Calling

import { telnyx } from '@telnyx/ai-sdk-provider';
import { generateText, tool } from 'ai';
import { z } from 'zod/v4';

const { text } = await generateText({
  model: telnyx('Qwen/Qwen3-235B-A22B'),
  prompt: 'What is the weather in Santiago, Chile?',
  tools: {
    weather: tool({
      description: 'Get the current weather for a location',
      inputSchema: z.object({
        location: z.string(),
      }),
      execute: async ({ location }) => {
        return { temperature: 18, condition: 'sunny', location };
      },
    }),
  },
});

Embeddings

import { telnyx } from '@telnyx/ai-sdk-provider';
import { embed, embedMany } from 'ai';

// Single embedding
const { embedding } = await embed({
  model: telnyx.embeddingModel('thenlper/gte-large'),
  value: 'What is WebRTC?',
});

// Batch embeddings
const { embeddings } = await embedMany({
  model: telnyx.embeddingModel('thenlper/gte-large'),
  values: ['What is WebRTC?', 'Explain SIP trunking'],
});

Text-to-Speech (TTS)

import { telnyx } from '@telnyx/ai-sdk-provider';
import { experimental_generateSpeech as generateSpeech } from 'ai';

const { audio } = await generateSpeech({
  model: telnyx.speechModel('tts-1'),
  text: 'Hello, welcome to Telnyx!',
  voice: 'Telnyx.NaturalHD.astra',
});

You can also pass additional speech options:

import { telnyx } from '@telnyx/ai-sdk-provider';
import { experimental_generateSpeech as generateSpeech } from 'ai';

const { audio, warnings } = await generateSpeech({
  model: telnyx.speechModel('tts-1'),
  text: 'Hello, welcome to Telnyx!',
  voice: 'Telnyx.KokoroTTS.af_alloy',
  outputFormat: 'mp3',
});

Provider-specific options are also supported via providerOptions.telnyx:

const { audio } = await generateSpeech({
  model: telnyx.speechModel('tts-1'),
  text: 'Hello, welcome to Telnyx!',
  voice: 'Telnyx.NaturalHD.astra',
  providerOptions: {
    telnyx: {
      output_format: 'linear16',
      sample_rate: 24000,
      language_code: 'en',
    },
  },
});

Transcription (STT)

import { telnyx } from '@telnyx/ai-sdk-provider';
import { experimental_transcribe as transcribe } from 'ai';
import { readFile } from 'node:fs/promises';

const result = await transcribe({
  model: telnyx.transcriptionModel('distil-whisper/distil-large-v2'),
  audio: await readFile('./audio.wav'),
  mediaType: 'audio/wav',
});

console.log(result.text);

You can also use provider-specific options:

const result = await transcribe({
  model: telnyx.transcriptionModel('openai/whisper-large-v3-turbo'),
  audio: await readFile('./audio.wav'),
  mediaType: 'audio/wav',
  providerOptions: {
    telnyx: {
      language: 'en',
      response_format: 'verbose_json',
    },
  },
});

Custom Instance

import { createTelnyx } from '@telnyx/ai-sdk-provider';

const telnyx = createTelnyx({
  apiKey: 'KEY_ID_SECRET',
  baseURL: 'https://api.telnyx.com/v2/ai/openai',
  fetch: customFetch, // optional custom fetch implementation
});

Available Models

Chat Models

| Model ID | Best For | |---|---| | moonshotai/Kimi-K2.5 | General use, voice AI | | zai-org/GLM-5.1-FP8 | Highest intelligence open-source | | MiniMaxAI/MiniMax-M2.7 | Cost-effective, high intelligence | | Qwen/Qwen3-235B-A22B | Function calling, reasoning |

Embedding Models

| Model ID | Dimensions | |---|---| | thenlper/gte-large | 1024 |

Speech Models

| Model ID | Description | |---|---| | tts-1 | Supported model identifier for AI SDK speech APIs | | tts-1-hd | Supported model identifier for AI SDK speech APIs |

Note: for the current Telnyx TTS implementation, modelId is used as the AI SDK model identifier and for metadata/logging. The actual synthesis request is controlled by options such as voice, outputFormat, and provider-specific providerOptions.telnyx, not by a different upstream TTS model selected via modelId.

Transcription Models

Examples:

• distil-whisper/distil-large-v2
• openai/whisper-large-v3-turbo
• deepgram/nova-3

Exports

import {
  telnyx,
  createTelnyx,
  VERSION,
  type TelnyxProviderSettings,
  type TelnyxChatModelId,
  type TelnyxEmbeddingModelId,
  type TelnyxSpeechModelId,
  type TelnyxTranscriptionModelId,
} from '@telnyx/ai-sdk-provider';

Notes

• telnyx('model-id') is an alias for telnyx.languageModel('model-id')
• telnyx.speech() and telnyx.speechModel() are equivalent
• telnyx.transcription() and telnyx.transcriptionModel() are equivalent
• imageModel() is not supported and throws NoSuchModelError
• The default telnyx export is lazy, so importing it does not require TELNYX_API_KEY until first use
• Requires ai@6 for speech and transcription APIs

License

MIT