/telnyx-ai-assistants-java

name: telnyx-ai-assistants-java
description: >-
  AI voice assistants with custom instructions, knowledge bases, and tool
  integrations.
metadata:
  author: telnyx
  product: ai-assistants
  language: java
  generated_by: telnyx-openapi-pipeline
  contract: v2

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

Telnyx AI Assistants - 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.models.ai.assistants.AssistantCreateParams;
import com.telnyx.sdk.models.ai.assistants.InferenceEmbedding;
import com.telnyx.sdk.errors.TelnyxServiceException;

try {
    AssistantCreateParams params = AssistantCreateParams.builder()
        .instructions("You are a helpful assistant.")
        .name("my-resource")
        .model("openai/gpt-4o")
        .build();
    InferenceEmbedding assistant = client.ai().assistants().create(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

• **Phone numbers** must be in E.164 format (e.g., `+13125550001`). Include the `+` prefix and country code. No spaces, dashes, or parentheses.
• **Pagination:** List methods return a page. Use `.autoPager()` for automatic iteration: `for (var item : page.autoPager()) { ... }`. For manual control, use `.hasNextPage()` and `.nextPage()`.

Reference Use Rules

Do not invent Telnyx parameters, enums, response fields, or webhook fields.

• If the parameter, enum, or response field you need is not shown inline in this skill, read [references/api-details.md](references/api-details.md) before writing code.
• Before using any operation in `## Additional Operations`, read [the optional-parameters section](references/api-details.md#optional-parameters) and [the response-schemas section](references/api-details.md#response-schemas).

Core Tasks

Create an assistant

Assistant creation is the entrypoint for any AI assistant integration. Agents need the exact creation method and the top-level fields returned by the SDK.

`client.ai().assistants().create()` — `POST /ai/assistants`

| Parameter | Type | Required | Description | |-----------|------|----------|-------------| | `name` | string | Yes | | | `instructions` | string | Yes | System instructions for the assistant. | | `tags` | array[string] | No | Tags associated with the assistant. | | `model` | string | No | ID of the model to use when `external_llm` is not set. | | `tools` | array[object] | No | Deprecated for new integrations. | | ... | | | +28 optional params in [references/api-details.md](references/api-details.md) |

import com.telnyx.sdk.models.ai.assistants.AssistantCreateParams;
import com.telnyx.sdk.models.ai.assistants.InferenceEmbedding;

AssistantCreateParams params = AssistantCreateParams.builder()
    .instructions("You are a helpful assistant.")
    .name("my-resource")
    .model("openai/gpt-4o")
    .build();
InferenceEmbedding assistant = client.ai().assistants().create(params);

Primary response fields:

• `assistant.id`
• `assistant.name`
• `assistant.model`
• `assistant.instructions`
• `assistant.createdAt`
• `assistant.a2aAgents`

Chat with an assistant

Chat is the primary runtime path. Agents need the exact assistant method and the response content field.

`client.ai().assistants().chat()` — `POST /ai/assistants/{assistant_id}/chat`

| Parameter | Type | Required | Description | |-----------|------|----------|-------------| | `content` | string | Yes | The message content sent by the client to the assistant | | `conversationId` | string (UUID) | Yes | A unique identifier for the conversation thread, used to mai... | | `assistantId` | string (UUID) | Yes | Unique identifier of the assistant. | | `name` | string | No | The optional display name of the user sending the message | | `stream` | boolean | No | When true, the response is streamed as Server-Sent Events (`... |

import com.telnyx.sdk.models.ai.assistants.AssistantChatParams;
import com.telnyx.sdk.models.ai.assistants.AssistantChatResponse;

AssistantChatParams params = AssistantChatParams.builder()
    .assistantId("550e8400-e29b-41d4-a716-446655440000")
    .content("Tell me a joke about cats")
    .conversationId("42b20469-1215-4a9a-8964-c36f66b406f4")
    .build();
AssistantChatResponse response = client.ai().assistants().chat(params);

Primary response fields:

• `response.content`

Create an assistant test

Test creation is the main validation path for production assistant behavior before deployment.

`client.ai().assistants().tests().create()` —