deepgram-dotnet-text-intelligence

# 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 ```bash dotnet add package Deepgram ``` ```csharp 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 ```csharp 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 ```csharp 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: ```bash 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`).