| name | deepgram-js-text-intelligence |
| description | Use when writing or reviewing JavaScript/TypeScript in this repo that calls Deepgram Text Intelligence / Read (`/v1/read`) for sentiment, summarization, topic detection, and intent recognition on text input. Covers `client.read.v1.text.analyze(...)` with `body: { text }` or `body: { url }`. Use `deepgram-js-audio-intelligence` when the source is audio instead of text. Triggers include "read API", "text intelligence", "analyze text", "sentiment", "summarize text", "topics", "intents", and "read.v1". |
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:
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.tsexamples/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).
