Using Deepgram Text Intelligence (.NET SDK)

Analyze text input for sentiment, summary, topics, and intents.

When to use this product

• You already have text: transcript, email, document, chat log, etc.
• You want REST-style analysis, not streaming.

Use a different skill when:

• The source is audio and you want analytics during transcription → deepgram-dotnet-audio-intelligence.

Authentication

dotnet add package Deepgram

using Deepgram;

Library.Initialize();
var client = ClientFactory.CreateAnalyzeClient();

ClientFactory reads credentials from the DEEPGRAM_API_KEY (or DEEPGRAM_ACCESS_TOKEN) environment variable by default. To pass them explicitly: ClientFactory.CreateAnalyzeClient(apiKey: "...", options: ...). DeepgramHttpClientOptions throws if neither the env var nor an explicit credential is provided.

Quick start — text

using Deepgram;
using Deepgram.Models.Analyze.v1;

Library.Initialize();

var client = ClientFactory.CreateAnalyzeClient();
var response = await client.AnalyzeText(
    new TextSource("Hello, world! This is a sample text for analysis."),
    new AnalyzeSchema()
    {
        Language = "en",
        Sentiment = true,
        Summarize = true,
        Topics = true,
        Intents = true,
    });

Console.WriteLine(response);

Quick start — file / URL

var client = ClientFactory.CreateAnalyzeClient();

var fileBytes = File.ReadAllBytes("conversation.txt");
var fileResponse = await client.AnalyzeFile(
    fileBytes,
    new AnalyzeSchema() { Language = "en", Summarize = true });

var urlResponse = await client.AnalyzeUrl(
    new UrlSource("https://example.com/conversation.txt"),
    new AnalyzeSchema() { Language = "en", Sentiment = true });

Key params

AnalyzeSchema: Language, Sentiment, Summarize, Topics, Intents, CustomTopic, CustomTopicMode, CustomIntent, CustomIntentMode, CallBack, CallbackMethod.

Input types:

• TextSource
• UrlSource
• byte[]
• Stream

API reference (layered)

1. In-repo source of truth:
   • Deepgram/ClientFactory.cs
   • Deepgram/Clients/Analyze/v1/Client.cs
   • Deepgram/Models/Analyze/v1/AnalyzeSchema.cs
   • Deepgram/Models/Analyze/v1/*.cs
2. Canonical OpenAPI (REST): https://developers.deepgram.com/openapi.yaml
3. AsyncAPI: not applicable for this product in this repo
4. Context7:
   • repo mirror: https://context7.com/deepgram/deepgram-dotnet-sdk
   • docs corpus: /llmstxt/developers_deepgram_llms_txt
5. Product docs:
   • https://developers.deepgram.com/reference/text-intelligence/analyze-text
   • https://developers.deepgram.com/docs/text-intelligence

Gotchas

1. AnalyzeClient maps to /read. The repo uses Analyze* method names, not Read* names.
2. Use AnalyzeText(...) for raw strings. AnalyzeFile(...) is for bytes/streams, even if the file is plain text.
3. Summarize is a boolean here. Do not use the STT-style "v2" string from /listen summarization.
4. Language is effectively English-only for the gated analytics. The schema docs say en only today.
5. Callback flows are separate methods. Use AnalyzeTextCallBack, AnalyzeUrlCallBack, or AnalyzeFileCallBack.

Example files in this repo

• examples/analyze/summary/Program.cs
• examples/analyze/sentiment/Program.cs
• examples/analyze/topic/Program.cs
• examples/analyze/intent/Program.cs

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).