/telnyx-ai-inference-javascript

name: telnyx-ai-inference-javascript
description: >-
  Access Telnyx LLM inference APIs, embeddings, and AI analytics for call
  insights and summaries. This skill provides JavaScript SDK examples.
metadata:
  author: telnyx
  product: ai-inference
  language: javascript
  generated_by: telnyx-openapi-pipeline

<!-- Auto-generated from Telnyx OpenAPI specs. Do not edit. -->

Telnyx Ai Inference - JavaScript

Installation

npm install telnyx@6.74.2

Setup

import Telnyx from 'telnyx';

const client = new Telnyx({
  apiKey: process.env['TELNYX_API_KEY'], // This is the default and can be omitted
  publicKey: process.env['TELNYX_PUBLIC_KEY'], // Required for client.webhooks.unwrap() (webhook verification)
});

All examples below assume `client` is already initialized as shown above.

Error Handling

All API calls can fail with network errors, rate limits (429), validation errors (422), or authentication errors (401). Always handle errors in production code:

try {
  const result = await client.messages.send({ to: '+13125550001', from: '+13125550002', text: 'Hello' });
} catch (err) {
  if (err instanceof Telnyx.APIConnectionError) {
    console.error('Network error — check connectivity and retry');
  } else if (err instanceof Telnyx.RateLimitError) {
    // 429: rate limited — wait, then retry the request (bounded exponential backoff)
    const retryAfter = err.headers?.['retry-after'] || 1;
    await new Promise(r => setTimeout(r, retryAfter * 1000));
    // ...retry the call here (give up after a few attempts)
  } else if (err instanceof Telnyx.APIError) {
    console.error(`API error ${err.status}: ${err.message}`);
    if (err.status === 422) {
      console.error('Validation error — check required fields and formats');
    }
  }
  throw err; // Re-throw: a failed request must never look like success to the caller
}

Common error codes: `401` invalid API key, `403` insufficient permissions, `404` resource not found, `422` validation error (check field formats), `429` rate limited (retry with exponential backoff).

Important Notes

• **Pagination:** List methods return an auto-paginating iterator. Use `for await (const item of result) { ... }` to iterate through all pages automatically.

Transcribe speech to text

Transcribe speech to text. This endpoint is consistent with the [OpenAI Transcription API](https://platform.openai.com/docs/api-reference/audio/createTranscription) and may be used with the OpenAI JS or Python SDK.

`POST /ai/audio/transcriptions`

import fs from 'fs';

const response = await client.ai.audio.transcribe({ model: 'distil-whisper/distil-large-v2' });

console.log(response.text);

Returns: `duration` (number), `segments` (array[object]), `text` (string), `words` (array[object])

List conversations

Retrieve a list of all AI conversations configured by the user. Supports [PostgREST-style query parameters](https://postgrest.org/en/stable/api.html#horizontal-filtering-rows) for filtering. Examples are included for the standard metadata fields, but you can filter on any field in the metadata JSON object.

`GET /ai/conversations`

const conversations = await client.ai.conversations.list();

console.log(conversations.data);

Returns: `created_at` (date-time), `id` (uuid), `last_message_at` (date-time), `metadata` (object), `name` (string)

Create a conversation

Creates a new AI conversation, the container for messages exchanged with an assistant, and returns the created conversation.

`POST /ai/conversations`

Optional: `metadata` (object), `name` (string)

const conversation = await client.ai.conversations.create();

console.log(conversation.id);

Returns: `created_at` (date-time), `id` (uuid), `last_message_at` (date-time), `metadata` (object), `name` (string)

Aggregate Conversation Insights

Aggregate conversation insights by specified fields

`GET /ai/conversations/conversation-insights/aggregates`

const response = await client.ai.conversations.conversationInsights.retrieveAggregates();

console.log(response.data);

Returns: `record_count` (integer)

Get Insight Template Groups

Returns a paginated list of your insight template groups. Groups organize related insight templates that are applied together when analyzing conversations.

`GET /ai/conversations/insight-groups`

// Automatically fetches more pages as needed.
for await (const insightTemplateGroup of client.ai.conversations.insightGroups.retrieveInsightGroups()) {
  console.log(insightTemplateGroup.id);
}

Returns: `created_at` (date-time), `description` (string), `id` (uuid), `insights` (array[object]), `name` (string), `webhook` (string)

Create Insight Template Group

Creates a new insight template group for organizing related insight templates, and returns the created group.

`POST /ai/conversations/insight-groups` — Required: `name`

Optional: `description` (string), `webhook` (string)

const insightTemplateGroupDetail = await client.ai.conversations.insightGroups.insightGroups({
  name: 'my-resource',
});

console.log(insightTemplateGroupDetail.data);

Returns: `created_at` (date-time), `description` (string), `id` (uuid), `insights` (array[object]), `name` (string), `webhook` (string)

Get Insight Template Group

Returns the details of a single insight template group, including the insight templates assigned to it.

`GET /ai/conversations/insight-groups/{group_id}`

const insightTemplateGroupDetail = await client.ai.conversations.insightGroups.retrieve(
  '182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e',
);

console.log(insightTemplateGroupDetail.data);

Returns: `created_at` (date-time), `description` (string), `id` (uuid), `insights` (array[object]), `name` (string), `webhook` (string)

Update Insight Template Group

Updates the specified insight template group and returns the updated group.