Using Deepgram Text Intelligence (Python SDK)

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

When to use this product

• You have text already (a transcript, document, chat log, email) and want analytics.
• You want a quick one-shot analysis — REST only, no streaming.

Use a different skill when:

• The source is audio and you want analytics overlays → deepgram-python-audio-intelligence (same analytics, applied at transcription time).

Authentication

from dotenv import load_dotenv
load_dotenv()

from deepgram import DeepgramClient
client = DeepgramClient()

Header: Authorization: Token <api_key>.

Quick start

response = client.read.v1.text.analyze(
    request={"text": "Hello, world! This is a sample text for analysis."},
    language="en",
    sentiment=True,
    summarize=True,   # /v1/read is boolean-only (see gotchas)
    topics=True,
    intents=True,
)

if response.results.sentiments:
    print("sentiment avg:", response.results.sentiments.average)
if response.results.summary:
    print("summary:", response.results.summary.text)
if response.results.topics:
    print("topics:", response.results.topics.segments)
if response.results.intents:
    print("intents:", response.results.intents.segments)

Pass request={"text": "..."} for raw text OR request={"url": "https://..."} for a hosted plain-text document.

Async equivalent

from deepgram import AsyncDeepgramClient
client = AsyncDeepgramClient()
response = await client.read.v1.text.analyze(request={"text": "..."}, language="en", sentiment=True)

Key parameters

Response shape (abridged)

response.results.summary.text
response.results.sentiments.segments[]
response.results.sentiments.average
response.results.topics.segments[]
response.results.intents.segments[]
response.metadata

See reference.md → "Read V1 Text" for full shape. Request body model: ReadV1RequestParams.

API reference (layered)

1. In-repo reference: reference.md — "Read V1 Text".
2. OpenAPI (REST): https://developers.deepgram.com/openapi.yaml
3. Context7: library ID /llmstxt/developers_deepgram_llms_txt.
4. 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

1. Token auth, not Bearer.
2. English-only for sentiment / summarize / topics / intents today.
3. summarize on /v1/read is boolean only. Pass True or False. Do not pass "v2" on /v1/read — that's a Listen-only option (see deepgram-python-audio-intelligence). The SDK type Union[Literal["v2"], Any] is shared with Listen and wider than Read actually accepts; the analyze docstring clarifies: "For Read API, accepts boolean only." The generated wire test passing summarize="v2" against a mock server is a Fern artifact and does not indicate real /v1/read support.
4. language is required for the gated analytics features above.
5. Body is JSON request=, not query parameters. Don't confuse with /v1/listen which takes audio as the body.
6. Custom topics/intents need a mode (custom_topic_mode="extended", "strict") or they are ignored.

Example files in this repo

• examples/40-text-intelligence.py
• tests/wire/test_read_v1_text.py

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).