telnyx-ai-inference-ruby

Name: telnyx-ai-inference-ruby
Author: team-telnyx

187stars18forks

How to install telnyx-ai-inference-ruby?

team-telnyx/ai/telnyx-ai-inference-ruby

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

Installs into the current project.

Summary

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

Files · 1

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SKILL.md

1	<!-- Auto-generated from Telnyx OpenAPI specs. Do not edit. -->
2
3	# Telnyx Ai Inference - Ruby
4
5	## Installation
6
7	```bash
8	gem install telnyx
9	```
10
11	## Setup
12
13	```ruby
14	require "telnyx"
15
16	client = Telnyx::Client.new(
17	api_key: ENV["TELNYX_API_KEY"], # This is the default and can be omitted
18	)
19	```
20
21	All examples below assume `client` is already initialized as shown above.
22
23	## Error Handling
24
25	All API calls can fail with network errors, rate limits (429), validation errors (422),
26	or authentication errors (401). Always handle errors in production code:
27
28	```ruby
29	begin
30	result = client.messages.send_(to: "+13125550001", from: "+13125550002", text: "Hello")
31	rescue Telnyx::Errors::APIConnectionError
32	puts "Network error — check connectivity and retry"
33	rescue Telnyx::Errors::RateLimitError
34	# 429: rate limited — wait and retry with exponential backoff
35	sleep(1) # Check Retry-After header for actual delay
36	rescue Telnyx::Errors::APIStatusError => e
37	puts "API error #{e.status}: #{e.message}"
38	if e.status == 422
39	puts "Validation error — check required fields and formats"
40	end
41	end
42	```
43
44	Common error codes: `401` invalid API key, `403` insufficient permissions,
45	`404` resource not found, `422` validation error (check field formats),
46	`429` rate limited (retry with exponential backoff).
47
48	## Important Notes
49
50	- Pagination: Use `.auto_paging_each` for automatic iteration: `page.auto_paging_each { \|item\| puts item.id }`.
51
52	## Transcribe speech to text
53
54	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.
55
56	`POST /ai/audio/transcriptions`
57
58	```ruby
59	response = client.ai.audio.transcribe(model: :"distil-whisper/distil-large-v2")
60
61	puts(response)
62	```
63
64	Returns: `duration` (number), `segments` (array[object]), `text` (string)
65
66	## Create a chat completion
67
68	Chat with a language model. This endpoint is consistent with the [OpenAI Chat Completions API](https://platform.openai.com/docs/api-reference/chat) and may be used with the OpenAI JS or Python SDK.
69
70	`POST /ai/chat/completions` — Required: `messages`
71
72	Optional: `api_key_ref` (string), `best_of` (integer), `early_stopping` (boolean), `enable_thinking` (boolean), `frequency_penalty` (number), `guided_choice` (array[string]), `guided_json` (object), `guided_regex` (string), `length_penalty` (number), `logprobs` (boolean), `max_tokens` (integer), `min_p` (number), `model` (string), `n` (number), `presence_penalty` (number), `response_format` (object), `stream` (boolean), `temperature` (number), `tool_choice` (enum: none, auto, required), `tools` (array[object]), `top_logprobs` (integer), `top_p` (number), `use_beam_search` (boolean)
73
74	```ruby
75	response = client.ai.chat.create_completion(
76	messages: [{content: "You are a friendly chatbot.", role: :system}, {content: "Hello, world!", role: :user}]
77	)
78
79	puts(response)
80	```
81
82	## List conversations
83
84	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.
85
86	`GET /ai/conversations`
87
88	```ruby
89	conversations = client.ai.conversations.list
90
91	puts(conversations)
92	```
93
94	Returns: `created_at` (date-time), `id` (uuid), `last_message_at` (date-time), `metadata` (object), `name` (string)
95
96	## Create a conversation
97
98	Create a new AI Conversation.
99
100	`POST /ai/conversations`
101
102	Optional: `metadata` (object), `name` (string)
103
104	```ruby
105	conversation = client.ai.conversations.create
106
107	puts(conversation)
108	```
109
110	Returns: `created_at` (date-time), `id` (uuid), `last_message_at` (date-time), `metadata` (object), `name` (string)
111
112	## Get Insight Template Groups
113
114	Get all insight groups
115
116	`GET /ai/conversations/insight-groups`
117
118	```ruby
119	page = client.ai.conversations.insight_groups.retrieve_insight_groups
120
121	puts(page)
122	```
123
124	Returns: `created_at` (date-time), `description` (string), `id` (uuid), `insights` (array[object]), `name` (string), `webhook` (string)
125
126	## Create Insight Template Group
127
128	Create a new insight group
129
130	`POST /ai/conversations/insight-groups` — Required: `name`
131
132	Optional: `description` (string), `webhook` (string)
133
134	```ruby
135	insight_template_group_detail = client.ai.conversations.insight_groups.insight_groups(name: "my-resource")
136
137	puts(insight_template_group_detail)
138	```
139
140	Returns: `created_at` (date-time), `description` (string), `id` (uuid), `insights` (array[object]), `name` (string), `webhook` (string)
141
142	## Get Insight Template Group
143
144	Get insight group by ID
145
146	`GET /ai/

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telnyx-ai-inference-ruby

187stars18forks

View on GitHub

How to install telnyx-ai-inference-ruby?

team-telnyx/ai/telnyx-ai-inference-ruby

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

Installs into the current project.

Summary

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

Files · 1

View on GitHub

SKILL.md

1	<!-- Auto-generated from Telnyx OpenAPI specs. Do not edit. -->
2
3	# Telnyx Ai Inference - Ruby
4
5	## Installation
6
7	```bash
8	gem install telnyx
9	```
10
11	## Setup
12
13	```ruby
14	require "telnyx"
15
16	client = Telnyx::Client.new(
17	api_key: ENV["TELNYX_API_KEY"], # This is the default and can be omitted
18	)
19	```
20
21	All examples below assume `client` is already initialized as shown above.
22
23	## Error Handling
24
25	All API calls can fail with network errors, rate limits (429), validation errors (422),
26	or authentication errors (401). Always handle errors in production code:
27
28	```ruby
29	begin
30	result = client.messages.send_(to: "+13125550001", from: "+13125550002", text: "Hello")
31	rescue Telnyx::Errors::APIConnectionError
32	puts "Network error — check connectivity and retry"
33	rescue Telnyx::Errors::RateLimitError
34	# 429: rate limited — wait and retry with exponential backoff
35	sleep(1) # Check Retry-After header for actual delay
36	rescue Telnyx::Errors::APIStatusError => e
37	puts "API error #{e.status}: #{e.message}"
38	if e.status == 422
39	puts "Validation error — check required fields and formats"
40	end
41	end
42	```
43
44	Common error codes: `401` invalid API key, `403` insufficient permissions,
45	`404` resource not found, `422` validation error (check field formats),
46	`429` rate limited (retry with exponential backoff).
47
48	## Important Notes
49
50	- Pagination: Use `.auto_paging_each` for automatic iteration: `page.auto_paging_each { \|item\| puts item.id }`.
51
52	## Transcribe speech to text
53
54	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.
55
56	`POST /ai/audio/transcriptions`
57
58	```ruby
59	response = client.ai.audio.transcribe(model: :"distil-whisper/distil-large-v2")
60
61	puts(response)
62	```
63
64	Returns: `duration` (number), `segments` (array[object]), `text` (string)
65
66	## Create a chat completion
67
68	Chat with a language model. This endpoint is consistent with the [OpenAI Chat Completions API](https://platform.openai.com/docs/api-reference/chat) and may be used with the OpenAI JS or Python SDK.
69
70	`POST /ai/chat/completions` — Required: `messages`
71
72	Optional: `api_key_ref` (string), `best_of` (integer), `early_stopping` (boolean), `enable_thinking` (boolean), `frequency_penalty` (number), `guided_choice` (array[string]), `guided_json` (object), `guided_regex` (string), `length_penalty` (number), `logprobs` (boolean), `max_tokens` (integer), `min_p` (number), `model` (string), `n` (number), `presence_penalty` (number), `response_format` (object), `stream` (boolean), `temperature` (number), `tool_choice` (enum: none, auto, required), `tools` (array[object]), `top_logprobs` (integer), `top_p` (number), `use_beam_search` (boolean)
73
74	```ruby
75	response = client.ai.chat.create_completion(
76	messages: [{content: "You are a friendly chatbot.", role: :system}, {content: "Hello, world!", role: :user}]
77	)
78
79	puts(response)
80	```
81
82	## List conversations
83
84	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.
85
86	`GET /ai/conversations`
87
88	```ruby
89	conversations = client.ai.conversations.list
90
91	puts(conversations)
92	```
93
94	Returns: `created_at` (date-time), `id` (uuid), `last_message_at` (date-time), `metadata` (object), `name` (string)
95
96	## Create a conversation
97
98	Create a new AI Conversation.
99
100	`POST /ai/conversations`
101
102	Optional: `metadata` (object), `name` (string)
103
104	```ruby
105	conversation = client.ai.conversations.create
106
107	puts(conversation)
108	```
109
110	Returns: `created_at` (date-time), `id` (uuid), `last_message_at` (date-time), `metadata` (object), `name` (string)
111
112	## Get Insight Template Groups
113
114	Get all insight groups
115
116	`GET /ai/conversations/insight-groups`
117
118	```ruby
119	page = client.ai.conversations.insight_groups.retrieve_insight_groups
120
121	puts(page)
122	```
123
124	Returns: `created_at` (date-time), `description` (string), `id` (uuid), `insights` (array[object]), `name` (string), `webhook` (string)
125
126	## Create Insight Template Group
127
128	Create a new insight group
129
130	`POST /ai/conversations/insight-groups` — Required: `name`
131
132	Optional: `description` (string), `webhook` (string)
133
134	```ruby
135	insight_template_group_detail = client.ai.conversations.insight_groups.insight_groups(name: "my-resource")
136
137	puts(insight_template_group_detail)
138	```
139
140	Returns: `created_at` (date-time), `description` (string), `id` (uuid), `insights` (array[object]), `name` (string), `webhook` (string)
141
142	## Get Insight Template Group
143
144	Get insight group by ID
145
146	`GET /ai/

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