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/telnyx-ai-inference-ruby

Access Telnyx LLM inference APIs, embeddings, and AI analytics for call insights and summaries. This skill provides Ruby SDK examples.

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$ npx -y skills add team-telnyx/ai --skill telnyx-ai-inference-ruby --agent claude-code

SKILL.md

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

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

Telnyx Ai Inference - Ruby

Installation

gem install telnyx

Setup

require "telnyx"

client = Telnyx::Client.new(
  api_key: ENV["TELNYX_API_KEY"], # This is the default and can be omitted
  public_key: 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:

begin
  result = client.messages.send_(to: "+13125550001", from: "+13125550002", text: "Hello")
rescue Telnyx::Errors::APIConnectionError
  puts "Network error — check connectivity and retry"
  raise
rescue Telnyx::Errors::RateLimitError
  # 429: rate limited — wait, then retry the request (bounded exponential backoff)
  sleep(1) # Check Retry-After header for actual delay
  # ...retry the call here (give up after a few attempts); otherwise re-raise:
  raise
rescue Telnyx::Errors::APIStatusError => e
  puts "API error #{e.status}: #{e.message}"
  if e.status == 422
    puts "Validation error — check required fields and formats"
  end
  raise # A failed request must never look like success to the caller
end

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:** Use `.auto_paging_each` for automatic iteration: `page.auto_paging_each { |item| puts item.id }`.

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`

response = client.ai.audio.transcribe(model: :"distil-whisper/distil-large-v2")

puts(response)

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`

conversations = client.ai.conversations.list

puts(conversations)

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)

conversation = client.ai.conversations.create

puts(conversation)

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`

response = client.ai.conversations.conversation_insights.retrieve_aggregates

puts(response)

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`

page = client.ai.conversations.insight_groups.retrieve_insight_groups

puts(page)

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)

insight_template_group_detail = client.ai.conversations.insight_groups.insight_groups(name: "my-resource")

puts(insight_template_group_detail)

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}`

insight_template_group_detail = client.ai.conversations.insight_groups.retrieve("182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e")

puts(insight_template_group_detail)

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.

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

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

insight_template_group_detail = client.ai.conversations.insight_groups.update("182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e")

puts(insight_template_group_detail)

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

Delete Insight Template Group

Permanently deletes the specified insight template group by its ID.

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

result = client.ai.c
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