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telnyx-ai-inference-javascript

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

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

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Telnyx Ai Inference - JavaScript

Installation

npm install telnyx@6.74.2

Setup

import Telnyx from 'telnyx';

const client = new Telnyx({
  apiKey: process.env['TELNYX_API_KEY'], // This is the default and can be omitted
});

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:

try {
  const result = await client.messages.send({ to: '+13125550001', from: '+13125550002', text: 'Hello' });
} catch (err) {
  if (err instanceof Telnyx.APIConnectionError) {
    console.error('Network error — check connectivity and retry');
  } else if (err instanceof Telnyx.RateLimitError) {
    // 429: rate limited — wait and retry with exponential backoff
    const retryAfter = err.headers?.['retry-after'] || 1;
    await new Promise(r => setTimeout(r, retryAfter * 1000));
  } else if (err instanceof Telnyx.APIError) {
    console.error(`API error ${err.status}: ${err.message}`);
    if (err.status === 422) {
      console.error('Validation error — check required fields and formats');
    }
  }
}

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 an auto-paginating iterator. Use for await (const item of result) { ... } to iterate through all pages automatically.

Transcribe speech to text

Transcribe speech to text. This endpoint is consistent with the OpenAI Transcription API and may be used with the OpenAI JS or Python SDK.

POST /ai/audio/transcriptions

import fs from 'fs';

const response = await client.ai.audio.transcribe({ model: 'distil-whisper/distil-large-v2' });

console.log(response.text);

Returns: duration (number), segments (array[object]), text (string), words (array[object])

Create a chat completion

Deprecated: Use POST /v2/ai/openai/chat/completions instead. Chat with a language model. This endpoint is consistent with the OpenAI Chat Completions API and may be used with the OpenAI JS or Python SDK.

POST /ai/chat/completions — Required: messages

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), seed (integer), stop (object), stream (boolean), temperature (number), tool_choice (enum: none, auto, required), tools (array[object]), top_logprobs (integer), top_p (number), use_beam_search (boolean)

const response = await client.ai.chat.createCompletion({
  messages: [
    { role: 'system', content: 'You are a friendly chatbot.' },
    { role: 'user', content: 'Hello, world!' },
  ],
});

console.log(response);

List conversations

Retrieve a list of all AI conversations configured by the user. Supports PostgREST-style query parameters 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

const conversations = await client.ai.conversations.list();

console.log(conversations.data);

Returns: created_at (date-time), id (uuid), last_message_at (date-time), metadata (object), name (string)

Create a conversation

Create a new AI Conversation.

POST /ai/conversations

Optional: metadata (object), name (string)

const conversation = await client.ai.conversations.create();

console.log(conversation.id);

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

const response = await client.ai.conversations.conversationInsights.aggregate();

console.log(response.data);

Returns: record_count (integer)

Get Insight Template Groups

Get all insight groups

GET /ai/conversations/insight-groups

// Automatically fetches more pages as needed.
for await (const insightTemplateGroup of client.ai.conversations.insightGroups.retrieveInsightGroups()) {
  console.log(insightTemplateGroup.id);
}

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

Create Insight Template Group

Create a new insight group

POST /ai/conversations/insight-groups — Required: name

Optional: description (string), webhook (string)

const insightTemplateGroupDetail = await client.ai.conversations.insightGroups.insightGroups({
  name: 'my-resource',
});

console.log(insightTemplateGroupDetail.data);

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

Get Insight Template Group

Get insight group by ID

GET /ai/conversations/insight-groups/{group_id}

const insightTemplateGroupDetail = await client.ai.conversations.insightGroups.retrieve(
  '182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e',
);

console.log(insightTemplateGroupDetail.data);

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

Update Insight Template Group

Update an insight template group

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

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

const insightTemplateGroupDetail = await client.ai.conversations.insightGroups.update(
  '182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e',
);

console.log(insightTemplateGroupDetail.data);

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

Delete Insight Template Group

Delete insight group by ID

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

await client.ai.conversations.insightGroups.delete('182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e');

Assign Insight Template To Group

Assign an insight to a group

POST /ai/conversations/insight-groups/{group_id}/insights/{insight_id}/assign

await client.ai.conversations.insightGroups.insights.assign(
  '182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e',
  { group_id: '182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e' },
);

Unassign Insight Template From Group

Remove an insight from a group

DELETE /ai/conversations/insight-groups/{group_id}/insights/{insight_id}/unassign

await client.ai.conversations.insightGroups.insights.deleteUnassign(
  '182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e',
  { group_id: '182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e' },
);

Get Insight Templates

Get all insights

GET /ai/conversations/insights

// Automatically fetches more pages as needed.
for await (const insightTemplate of client.ai.conversations.insights.list()) {
  console.log(insightTemplate.id);
}

Returns: created_at (date-time), id (uuid), insight_type (enum: custom, default), instructions (string), json_schema (object), name (string), webhook (string)

Create Insight Template

Create a new insight

POST /ai/conversations/insights — Required: instructions, name

Optional: json_schema (object), webhook (string)

const insightTemplateDetail = await client.ai.conversations.insights.create({
  instructions: 'You are a helpful assistant.',
  name: 'my-resource',
});

console.log(insightTemplateDetail.data);

Returns: created_at (date-time), id (uuid), insight_type (enum: custom, default), instructions (string), json_schema (object), name (string), webhook (string)

Get Insight Template

Get insight by ID

GET /ai/conversations/insights/{insight_id}

const insightTemplateDetail = await client.ai.conversations.insights.retrieve(
  '182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e',
);

console.log(insightTemplateDetail.data);

Returns: created_at (date-time), id (uuid), insight_type (enum: custom, default), instructions (string), json_schema (object), name (string), webhook (string)

Update Insight Template

Update an insight template

PUT /ai/conversations/insights/{insight_id}

Optional: instructions (string), json_schema (object), name (string), webhook (string)

const insightTemplateDetail = await client.ai.conversations.insights.update(
  '182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e',
);

console.log(insightTemplateDetail.data);

Returns: created_at (date-time), id (uuid), insight_type (enum: custom, default), instructions (string), json_schema (object), name (string), webhook (string)

Delete Insight Template

Delete insight by ID

DELETE /ai/conversations/insights/{insight_id}

await client.ai.conversations.insights.delete('182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e');

Get a conversation

Retrieve a specific AI conversation by its ID.

GET /ai/conversations/{conversation_id}

const conversation = await client.ai.conversations.retrieve('550e8400-e29b-41d4-a716-446655440000');

console.log(conversation.data);

Returns: created_at (date-time), id (uuid), last_message_at (date-time), metadata (object), name (string)

Update conversation metadata

Update metadata for a specific conversation.

PUT /ai/conversations/{conversation_id}

Optional: metadata (object)

const conversation = await client.ai.conversations.update('550e8400-e29b-41d4-a716-446655440000');

console.log(conversation.data);

Returns: created_at (date-time), id (uuid), last_message_at (date-time), metadata (object), name (string)

Delete a conversation

Delete a specific conversation by its ID.

DELETE /ai/conversations/{conversation_id}

await client.ai.conversations.delete('550e8400-e29b-41d4-a716-446655440000');

Get insights for a conversation

Retrieve insights for a specific conversation

GET /ai/conversations/{conversation_id}/conversations-insights

const response = await client.ai.conversations.retrieveConversationsInsights('550e8400-e29b-41d4-a716-446655440000');

console.log(response.data);

Returns: conversation_insights (array[object]), created_at (date-time), id (string), status (enum: pending, in_progress, completed, failed)

Create Message

Add a new message to the conversation. Used to insert a new messages to a conversation manually ( without using chat endpoint )

POST /ai/conversations/{conversation_id}/message — Required: role

Optional: content (string), metadata (object), name (string), sent_at (date-time), tool_call_id (string), tool_calls (array[object]), tool_choice (object)

await client.ai.conversations.addMessage('182bd5e5-6e1a-4fe

Voir la source ↗

Métadonnées du fichier

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

Voir le texte original

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

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

# Telnyx Ai Inference - JavaScript

## Installation

```bash
npm install telnyx@6.74.2
```

## Setup

```javascript
import Telnyx from 'telnyx';

const client = new Telnyx({
  apiKey: process.env['TELNYX_API_KEY'], // This is the default and can be omitted
});
```

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:

```javascript
try {
  const result = await client.messages.send({ to: '+13125550001', from: '+13125550002', text: 'Hello' });
} catch (err) {
  if (err instanceof Telnyx.APIConnectionError) {
    console.error('Network error — check connectivity and retry');
  } else if (err instanceof Telnyx.RateLimitError) {
    // 429: rate limited — wait and retry with exponential backoff
    const retryAfter = err.headers?.['retry-after'] || 1;
    await new Promise(r => setTimeout(r, retryAfter * 1000));
  } else if (err instanceof Telnyx.APIError) {
    console.error(`API error ${err.status}: ${err.message}`);
    if (err.status === 422) {
      console.error('Validation error — check required fields and formats');
    }
  }
}
```

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 an auto-paginating iterator. Use `for await (const item of result) { ... }` to iterate through all pages automatically.

## 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`

```javascript
import fs from 'fs';

const response = await client.ai.audio.transcribe({ model: 'distil-whisper/distil-large-v2' });

console.log(response.text);
```

Returns: `duration` (number), `segments` (array[object]), `text` (string), `words` (array[object])

## Create a chat completion

**Deprecated**: Use `POST /v2/ai/openai/chat/completions` instead. 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.

`POST /ai/chat/completions` — Required: `messages`

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), `seed` (integer), `stop` (object), `stream` (boolean), `temperature` (number), `tool_choice` (enum: none, auto, required), `tools` (array[object]), `top_logprobs` (integer), `top_p` (number), `use_beam_search` (boolean)

```javascript
const response = await client.ai.chat.createCompletion({
  messages: [
    { role: 'system', content: 'You are a friendly chatbot.' },
    { role: 'user', content: 'Hello, world!' },
  ],
});

console.log(response);
```

## 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`

```javascript
const conversations = await client.ai.conversations.list();

console.log(conversations.data);
```

Returns: `created_at` (date-time), `id` (uuid), `last_message_at` (date-time), `metadata` (object), `name` (string)

## Create a conversation

Create a new AI Conversation.

`POST /ai/conversations`

Optional: `metadata` (object), `name` (string)

```javascript
const conversation = await client.ai.conversations.create();

console.log(conversation.id);
```

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`

```javascript
const response = await client.ai.conversations.conversationInsights.aggregate();

console.log(response.data);
```

Returns: `record_count` (integer)

## Get Insight Template Groups

Get all insight groups

`GET /ai/conversations/insight-groups`

```javascript
// Automatically fetches more pages as needed.
for await (const insightTemplateGroup of client.ai.conversations.insightGroups.retrieveInsightGroups()) {
  console.log(insightTemplateGroup.id);
}
```

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

## Create Insight Template Group

Create a new insight group

`POST /ai/conversations/insight-groups` — Required: `name`

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

```javascript
const insightTemplateGroupDetail = await client.ai.conversations.insightGroups.insightGroups({
  name: 'my-resource',
});

console.log(insightTemplateGroupDetail.data);
```

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

## Get Insight Template Group

Get insight group by ID

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

```javascript
const insightTemplateGroupDetail = await client.ai.conversations.insightGroups.retrieve(
  '182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e',
);

console.log(insightTemplateGroupDetail.data);
```

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

## Update Insight Template Group

Update an insight template group

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

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

```javascript
const insightTemplateGroupDetail = await client.ai.conversations.insightGroups.update(
  '182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e',
);

console.log(insightTemplateGroupDetail.data);
```

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

## Delete Insight Template Group

Delete insight group by ID

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

```javascript
await client.ai.conversations.insightGroups.delete('182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e');
```

## Assign Insight Template To Group

Assign an insight to a group

`POST /ai/conversations/insight-groups/{group_id}/insights/{insight_id}/assign`

```javascript
await client.ai.conversations.insightGroups.insights.assign(
  '182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e',
  { group_id: '182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e' },
);
```

## Unassign Insight Template From Group

Remove an insight from a group

`DELETE /ai/conversations/insight-groups/{group_id}/insights/{insight_id}/unassign`

```javascript
await client.ai.conversations.insightGroups.insights.deleteUnassign(
  '182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e',
  { group_id: '182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e' },
);
```

## Get Insight Templates

Get all insights

`GET /ai/conversations/insights`

```javascript
// Automatically fetches more pages as needed.
for await (const insightTemplate of client.ai.conversations.insights.list()) {
  console.log(insightTemplate.id);
}
```

Returns: `created_at` (date-time), `id` (uuid), `insight_type` (enum: custom, default), `instructions` (string), `json_schema` (object), `name` (string), `webhook` (string)

## Create Insight Template

Create a new insight

`POST /ai/conversations/insights` — Required: `instructions`, `name`

Optional: `json_schema` (object), `webhook` (string)

```javascript
const insightTemplateDetail = await client.ai.conversations.insights.create({
  instructions: 'You are a helpful assistant.',
  name: 'my-resource',
});

console.log(insightTemplateDetail.data);
```

Returns: `created_at` (date-time), `id` (uuid), `insight_type` (enum: custom, default), `instructions` (string), `json_schema` (object), `name` (string), `webhook` (string)

## Get Insight Template

Get insight by ID

`GET /ai/conversations/insights/{insight_id}`

```javascript
const insightTemplateDetail = await client.ai.conversations.insights.retrieve(
  '182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e',
);

console.log(insightTemplateDetail.data);
```

Returns: `created_at` (date-time), `id` (uuid), `insight_type` (enum: custom, default), `instructions` (string), `json_schema` (object), `name` (string), `webhook` (string)

## Update Insight Template

Update an insight template

`PUT /ai/conversations/insights/{insight_id}`

Optional: `instructions` (string), `json_schema` (object), `name` (string), `webhook` (string)

```javascript
const insightTemplateDetail = await client.ai.conversations.insights.update(
  '182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e',
);

console.log(insightTemplateDetail.data);
```

Returns: `created_at` (date-time), `id` (uuid), `insight_type` (enum: custom, default), `instructions` (string), `json_schema` (object), `name` (string), `webhook` (string)

## Delete Insight Template

Delete insight by ID

`DELETE /ai/conversations/insights/{insight_id}`

```javascript
await client.ai.conversations.insights.delete('182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e');
```

## Get a conversation

Retrieve a specific AI conversation by its ID.

`GET /ai/conversations/{conversation_id}`

```javascript
const conversation = await client.ai.conversations.retrieve('550e8400-e29b-41d4-a716-446655440000');

console.log(conversation.data);
```

Returns: `created_at` (date-time), `id` (uuid), `last_message_at` (date-time), `metadata` (object), `name` (string)

## Update conversation metadata

Update metadata for a specific conversation.

`PUT /ai/conversations/{conversation_id}`

Optional: `metadata` (object)

```javascript
const conversation = await client.ai.conversations.update('550e8400-e29b-41d4-a716-446655440000');

console.log(conversation.data);
```

Returns: `created_at` (date-time), `id` (uuid), `last_message_at` (date-time), `metadata` (object), `name` (string)

## Delete a conversation

Delete a specific conversation by its ID.

`DELETE /ai/conversations/{conversation_id}`

```javascript
await client.ai.conversations.delete('550e8400-e29b-41d4-a716-446655440000');
```

## Get insights for a conversation

Retrieve insights for a specific conversation

`GET /ai/conversations/{conversation_id}/conversations-insights`

```javascript
const response = await client.ai.conversations.retrieveConversationsInsights('550e8400-e29b-41d4-a716-446655440000');

console.log(response.data);
```

Returns: `conversation_insights` (array[object]), `created_at` (date-time), `id` (string), `status` (enum: pending, in_progress, completed, failed)

## Create Message

Add a new message to the conversation. Used to insert a new messages to a conversation manually ( without using chat endpoint )

`POST /ai/conversations/{conversation_id}/message` — Required: `role`

Optional: `content` (string), `metadata` (object), `name` (string), `sent_at` (date-time), `tool_call_id` (string), `tool_calls` (array[object]), `tool_choice` (object)

```javascript
await client.ai.conversations.addMessage('182bd5e5-6e1a-4fe

Examiner la source

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Licence: MIT
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Réviser avant installation: Éviter l’installation automatique

Licence: MIT

Dependency or permission surface needs review
Permission surface may require sandboxing
The SKILL.md metadata description appears truncated in the parsed output (shows '>-' instead of the full description), though the actual file contains the full description.
The skill is auto-generated and may not cover all Telnyx AI endpoints or edge cases, but it provides a solid foundation.
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
Stars/forks activity: 212 stars, 22 forks; issue activity unavailable in current metadata
Dependency/runtime risk: command execution surface, credential or environment access
Permission surface: secrets or environment access, shell or command execution

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2Demandez un plan à l’agent. Approuvez la configuration et les coûts avant un test isolé.
3Vérifiez résultats et fichiers modifiés. Signalez uniquement ce qui a été exécuté et conservez la révision source.

Vérifiez les dépendances, clés API et frais externes dans la source. Un dépôt public ne rend pas tous les services gratuits.

Source et conseils d’utilisation

Répertorié

Métadonnées et examens sont indicatifs. Popularité, découverte et exécution réussie sont des faits distincts.

Dépôt source: team-telnyx/ai
Licence: MIT
Version: 1.0.0
Dernier push GitHub: 5 sept. 2026
Registre mis à jour: 9 oct. 2026
Chemin des instructions: providers/claude/plugins/telnyx-ai/skills/telnyx-ai-inference-javascript/SKILL.md @ 0443b296fd5b

Version déclarée dans le registre ; vérifiez les versions de la source.

Qualité

67/100

Prometteur

Confiance

56/100

Do not auto-install

Audit

72/100

Revue nécessaire

Ouvrir l’audit complet Voir le rapport d’évaluation

Dependency or permission surface needs review
Permission surface may require sandboxing
The SKILL.md metadata description appears truncated in the parsed output (shows '>-' instead of the full description), though the actual file contains the full description.
The skill is auto-generated and may not cover all Telnyx AI endpoints or edge cases, but it provides a solid foundation.
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
Stars/forks activity: 212 stars, 22 forks; issue activity unavailable in current metadata
Dependency/runtime risk: command execution surface, credential or environment access
Permission surface: secrets or environment access, shell or command execution

Verified installs: —
Résultats: —

Copier ne signifie pas installer. Les compteurs nécessitent un rapport de réussite et ne garantissent pas la qualité globale.

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Créateur: team-telnyx
Source: team-telnyx/ai
Indexé par: Index communautaire OpenAgentSkill

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Telnyx Ai Inference - JavaScript

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