/telnyx-ai-inference-java

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

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

Telnyx Ai Inference - Java

Installation

<!-- Maven -->
<dependency>
    <groupId>com.telnyx.sdk</groupId>
    <artifactId>telnyx</artifactId>
    <version>6.95.0</version>
</dependency>

// Gradle
implementation("com.telnyx.sdk:telnyx:6.95.0")

Setup

import com.telnyx.sdk.client.TelnyxClient;
import com.telnyx.sdk.client.okhttp.TelnyxOkHttpClient;

// fromEnv() reads TELNYX_API_KEY and TELNYX_PUBLIC_KEY (the public key is required for
// client.webhooks().unwrap() — webhook verification)
TelnyxClient client = TelnyxOkHttpClient.fromEnv();

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:

import com.telnyx.sdk.errors.TelnyxServiceException;

try {
    var result = client.messages().send(params);
} catch (TelnyxServiceException e) {
    System.err.println("API error " + e.statusCode() + ": " + e.getMessage());
    if (e.statusCode() == 422) {
        System.err.println("Validation error — check required fields and formats");
    } else if (e.statusCode() == 429) {
        // Rate limited — wait, then retry the request (bounded exponential backoff)
        Thread.sleep(1000);
        // ...retry the call here (give up after a few attempts)
    }
    throw e; // 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 a page. Use `.autoPager()` for automatic iteration: `for (var item : page.autoPager()) { ... }`. For manual control, use `.hasNextPage()` and `.nextPage()`.

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 com.telnyx.sdk.models.ai.audio.AudioTranscribeParams;
import com.telnyx.sdk.models.ai.audio.AudioTranscribeResponse;

AudioTranscribeParams params = AudioTranscribeParams.builder()
    .model(AudioTranscribeParams.Model.DISTIL_WHISPER_DISTIL_LARGE_V2)
    .build();
AudioTranscribeResponse response = client.ai().audio().transcribe(params);

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`

import com.telnyx.sdk.models.ai.conversations.ConversationListParams;
import com.telnyx.sdk.models.ai.conversations.ConversationListResponse;

ConversationListResponse conversations = client.ai().conversations().list();

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)

import com.telnyx.sdk.models.ai.conversations.Conversation;
import com.telnyx.sdk.models.ai.conversations.ConversationCreateParams;

Conversation conversation = client.ai().conversations().create();

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`

var response = client.ai().conversations().conversationInsights().retrieveAggregates();

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`

import com.telnyx.sdk.models.ai.conversations.insightgroups.InsightGroupRetrieveInsightGroupsPage;
import com.telnyx.sdk.models.ai.conversations.insightgroups.InsightGroupRetrieveInsightGroupsParams;

InsightGroupRetrieveInsightGroupsPage page = client.ai().conversations().insightGroups().retrieveInsightGroups();

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)

import com.telnyx.sdk.models.ai.conversations.insightgroups.InsightGroupInsightGroupsParams;
import com.telnyx.sdk.models.ai.conversations.insightgroups.InsightTemplateGroupDetail;

InsightGroupInsightGroupsParams params = InsightGroupInsightGroupsParams.builder()
    .name("my-resource")
    .build();
InsightTemplateGroupDetail insightTemplateGroupDetail = client.ai().conversations().insightGroups().insightGroups(params);

Returns: `created_at` (date-time)