Deepgram Js Text Intelligence

Using Deepgram Text Intelligence (JavaScript / TypeScript SDK)

Analyze text or a hosted text URL for sentiment, summarization, topics, and intents via /v1/read.

When to use this product

• You already have text (transcript, document, email, chat log) and want analytics.
• You want a single REST call; there is no streaming Read API in this SDK.

Use a different skill when:

• Your source is audio and you want the analytics applied during transcription → deepgram-js-audio-intelligence.

Authentication

require("dotenv").config();

const { DeepgramClient } = require("@deepgram/sdk");

const deepgramClient = new DeepgramClient({
  apiKey: process.env.DEEPGRAM_API_KEY,
});

Quick start

From examples/12-text-intelligence.ts:

const data = await deepgramClient.read.v1.text.analyze({
  body: {
    text: "Hello, world! This is a sample text for analysis.",
  },
  language: "en",
  summarize: "v2",
});

console.log("Analysis result:", JSON.stringify(data, null, 2));

For broader coverage, examples/28-text-intelligence-advanced.ts also demonstrates sentiment, topics, intents, custom topics/intents, callbacks, and URL input.

Key parameters / API surface

| Param | Notes |

|---|---|

| body | Required. Use { text: "..." } or { url: "https://..." } |

| language | Usually required for analytics features |

| sentiment | Per-segment + aggregate sentiment |

| summarize | SDK examples use both "v2" and true; see gotchas |

| topics, intents | Model-detected topics and intents |

| custom_topic, custom_intent | string or string[] |

| custom_topic_mode, custom_intent_mode | Usually "extended" or "strict" |

| callback, callback_method, tag | Async delivery and labeling |

API reference (layered)

• In-repo reference: reference.md → Read V1 Text; request typing also lives in src/api/resources/read/resources/v1/resources/text/client/{Client,requests/TextAnalyzeRequest.ts}.
• Canonical OpenAPI (REST): https://developers.deepgram.com/openapi.yaml
• Canonical AsyncAPI (WSS): https://developers.deepgram.com/asyncapi.yaml
• Context7: library ID /llmstxt/developers_deepgram_llms_txt
• Product docs:
• https://developers.deepgram.com/reference/text-intelligence/analyze-text
• https://developers.deepgram.com/docs/text-intelligence
• https://developers.deepgram.com/docs/text-sentiment-analysis

Gotchas

• Prefer body: { text | url } in typed code. That matches TextAnalyzeRequest; some examples also use top-level text, which is less reliable for strict TS.
• summarize is inconsistent across examples and generated comments. The request type points at TextAnalyzeRequestSummarize ("v2" today), while generated comments mention boolean for Read and examples use both forms.
• This API is REST-only here. No read.v1 WebSocket exists in the repo.
• Custom topics/intents need a mode for predictable behavior. Use extended or strict.
• The body is JSON, not raw text bytes. Send { body: { text: ... } }, not a string payload.
• Language support is product-side, not SDK-side. If analytics look sparse, verify the feature/model/language combination in docs.

Example files in this repo

• examples/12-text-intelligence.ts
• examples/28-text-intelligence-advanced.ts

Central product skills

For cross-language Deepgram product knowledge — the consolidated API reference, documentation finder, focused runnable recipes, third-party integration examples, and MCP setup — install the central skills:

npx skills add deepgram/skills

This SDK ships language-idiomatic code skills; deepgram/skills ships cross-language product knowledge (see api, docs, recipes, examples, starters, setup-mcp).