telnyx-ai-inference-javascript

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

187stars18forks

How to install telnyx-ai-inference-javascript?

team-telnyx/ai/telnyx-ai-inference-javascript

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

Installs into the current project.

Summary

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

Files · 1

View on GitHub

SKILL.md

1	<!-- Auto-generated from Telnyx OpenAPI specs. Do not edit. -->
2
3	# Telnyx Ai Inference - JavaScript
4
5	## Installation
6
7	```bash
8	npm install telnyx
9	```
10
11	## Setup
12
13	```javascript
14	import Telnyx from 'telnyx';
15
16	const client = new Telnyx({
17	apiKey: process.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	```javascript
29	try {
30	const result = await client.messages.send({ to: '+13125550001', from: '+13125550002', text: 'Hello' });
31	} catch (err) {
32	if (err instanceof Telnyx.APIConnectionError) {
33	console.error('Network error — check connectivity and retry');
34	} else if (err instanceof Telnyx.RateLimitError) {
35	// 429: rate limited — wait and retry with exponential backoff
36	const retryAfter = err.headers?.['retry-after'] \|\| 1;
37	await new Promise(r => setTimeout(r, retryAfter * 1000));
38	} else if (err instanceof Telnyx.APIError) {
39	console.error(`API error ${err.status}: ${err.message}`);
40	if (err.status === 422) {
41	console.error('Validation error — check required fields and formats');
42	}
43	}
44	}
45	```
46
47	Common error codes: `401` invalid API key, `403` insufficient permissions,
48	`404` resource not found, `422` validation error (check field formats),
49	`429` rate limited (retry with exponential backoff).
50
51	## Important Notes
52
53	- Pagination: List methods return an auto-paginating iterator. Use `for await (const item of result) { ... }` to iterate through all pages automatically.
54
55	## Transcribe speech to text
56
57	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.
58
59	`POST /ai/audio/transcriptions`
60
61	```javascript
62	const response = await client.ai.audio.transcribe({ model: 'distil-whisper/distil-large-v2' });
63
64	console.log(response.text);
65	```
66
67	Returns: `duration` (number), `segments` (array[object]), `text` (string)
68
69	## Create a chat completion
70
71	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.
72
73	`POST /ai/chat/completions` — Required: `messages`
74
75	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)
76
77	```javascript
78	const response = await client.ai.chat.createCompletion({
79	messages: [
80	{ role: 'system', content: 'You are a friendly chatbot.' },
81	{ role: 'user', content: 'Hello, world!' },
82	],
83	});
84
85	console.log(response);
86	```
87
88	## List conversations
89
90	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.
91
92	`GET /ai/conversations`
93
94	```javascript
95	const conversations = await client.ai.conversations.list();
96
97	console.log(conversations.data);
98	```
99
100	Returns: `created_at` (date-time), `id` (uuid), `last_message_at` (date-time), `metadata` (object), `name` (string)
101
102	## Create a conversation
103
104	Create a new AI Conversation.
105
106	`POST /ai/conversations`
107
108	Optional: `metadata` (object), `name` (string)
109
110	```javascript
111	const conversation = await client.ai.conversations.create();
112
113	console.log(conversation.id);
114	```
115
116	Returns: `created_at` (date-time), `id` (uuid), `last_message_at` (date-time), `metadata` (object), `name` (string)
117
118	## Get Insight Template Groups
119
120	Get all insight groups
121
122	`GET /ai/conversations/insight-groups`
123
124	```javascript
125	// Automatically fetches more pages as needed.
126	for await (const insightTemplateGroup of client.ai.conversations.insightGroups.retrieveInsightGroups()) {
127	console.log(insightTemplateGroup.id);
128	}
129	```
130
131	Returns: `created_at` (date-time), `description` (string), `id` (uuid), `insights` (array[object]), `name` (string), `webhoo

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telnyx-ai-inference-javascript

187stars18forks

View on GitHub

How to install telnyx-ai-inference-javascript?

team-telnyx/ai/telnyx-ai-inference-javascript

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

Installs into the current project.

Summary

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

Files · 1

View on GitHub

SKILL.md

1	<!-- Auto-generated from Telnyx OpenAPI specs. Do not edit. -->
2
3	# Telnyx Ai Inference - JavaScript
4
5	## Installation
6
7	```bash
8	npm install telnyx
9	```
10
11	## Setup
12
13	```javascript
14	import Telnyx from 'telnyx';
15
16	const client = new Telnyx({
17	apiKey: process.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	```javascript
29	try {
30	const result = await client.messages.send({ to: '+13125550001', from: '+13125550002', text: 'Hello' });
31	} catch (err) {
32	if (err instanceof Telnyx.APIConnectionError) {
33	console.error('Network error — check connectivity and retry');
34	} else if (err instanceof Telnyx.RateLimitError) {
35	// 429: rate limited — wait and retry with exponential backoff
36	const retryAfter = err.headers?.['retry-after'] \|\| 1;
37	await new Promise(r => setTimeout(r, retryAfter * 1000));
38	} else if (err instanceof Telnyx.APIError) {
39	console.error(`API error ${err.status}: ${err.message}`);
40	if (err.status === 422) {
41	console.error('Validation error — check required fields and formats');
42	}
43	}
44	}
45	```
46
47	Common error codes: `401` invalid API key, `403` insufficient permissions,
48	`404` resource not found, `422` validation error (check field formats),
49	`429` rate limited (retry with exponential backoff).
50
51	## Important Notes
52
53	- Pagination: List methods return an auto-paginating iterator. Use `for await (const item of result) { ... }` to iterate through all pages automatically.
54
55	## Transcribe speech to text
56
57	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.
58
59	`POST /ai/audio/transcriptions`
60
61	```javascript
62	const response = await client.ai.audio.transcribe({ model: 'distil-whisper/distil-large-v2' });
63
64	console.log(response.text);
65	```
66
67	Returns: `duration` (number), `segments` (array[object]), `text` (string)
68
69	## Create a chat completion
70
71	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.
72
73	`POST /ai/chat/completions` — Required: `messages`
74
75	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)
76
77	```javascript
78	const response = await client.ai.chat.createCompletion({
79	messages: [
80	{ role: 'system', content: 'You are a friendly chatbot.' },
81	{ role: 'user', content: 'Hello, world!' },
82	],
83	});
84
85	console.log(response);
86	```
87
88	## List conversations
89
90	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.
91
92	`GET /ai/conversations`
93
94	```javascript
95	const conversations = await client.ai.conversations.list();
96
97	console.log(conversations.data);
98	```
99
100	Returns: `created_at` (date-time), `id` (uuid), `last_message_at` (date-time), `metadata` (object), `name` (string)
101
102	## Create a conversation
103
104	Create a new AI Conversation.
105
106	`POST /ai/conversations`
107
108	Optional: `metadata` (object), `name` (string)
109
110	```javascript
111	const conversation = await client.ai.conversations.create();
112
113	console.log(conversation.id);
114	```
115
116	Returns: `created_at` (date-time), `id` (uuid), `last_message_at` (date-time), `metadata` (object), `name` (string)
117
118	## Get Insight Template Groups
119
120	Get all insight groups
121
122	`GET /ai/conversations/insight-groups`
123
124	```javascript
125	// Automatically fetches more pages as needed.
126	for await (const insightTemplateGroup of client.ai.conversations.insightGroups.retrieveInsightGroups()) {
127	console.log(insightTemplateGroup.id);
128	}
129	```
130
131	Returns: `created_at` (date-time), `description` (string), `id` (uuid), `insights` (array[object]), `name` (string), `webhoo

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6 picks

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