deepgram-rust-text-intelligence

# Using Deepgram Text Intelligence (Rust SDK) Use this skill when the request is about summarization, sentiment, topics, or intents for text input rather than audio. ## When to use this product - Analyzing plain text via Deepgram's `/v1/read` API. - Building text summarization, topic detection, intent recognition, or sentiment analysis. - Analyzing a transcript, document, chat log, or email you already have, rather than audio. ## Authentication Text intelligence lives behind the `read` Cargo feature. It is HTTP-only, so it needs none of the WebSocket dependencies the `listen` and `speak` features pull in and can be enabled on its own. ```toml [dependencies] deepgram = { version = "0.12", default-features = false, features = ["read"] } tokio = { version = "1", features = ["full"] } ``` `read` is also part of the crate's default features, so a plain `cargo add deepgram` includes it. ```rust use deepgram::Deepgram; let dg_client = Deepgram::new(&std::env::var("DEEPGRAM_API_KEY")?)?; let text_intelligence = dg_client.text_intelligence(); ``` ## Quick start: analyze a block of text ```rust use deepgram::{read::options::Options, Deepgram, DeepgramError}; #[tokio::main] async fn main() -> Result<(), DeepgramError> { let api_key = std::env::var("DEEPGRAM_API_KEY").expect("DEEPGRAM_API_KEY"); let dg_client = Deepgram::new(&api_key)?; let options = Options::builder() .sentiment(true) .summarize(true) .topics(true) .intents(true) .build(); let response = dg_client .text_intelligence() .analyze_text( "Customer is asking to cancel the subscription next month.", &options, ) .await?; if let Some(text) = response.results.summary.as_ref().and_then(|s| s.text.as_deref()) { println!("summary: {text}"); } if let Some(sentiments) = &response.results.sentiments { println!("average sentiment: {:?}", sentiments.average); } if let Some(topics) = &response.results.topics { println!("topic segments: {}", topics.segments.len()); } if let Some(intents) = &response.results.intents { println!("intent segments: {}", intents.segments.len()); } Ok(()) } ``` ## Analyze a hosted document `analyze_url` takes the URL of a plain-text document; everything else is the same as `analyze_text`. ```rust let response = dg_client .text_intelligence() .analyze_url("https://example.com/transcript.txt", &options) .await?; ``` ## Callbacks For long inputs, have Deepgram deliver the result to a webhook instead of holding the connection open. The call returns as soon as the request is accepted, with the `request_id` to correlate against; the full analysis arrives at the callback URL. ```rust use deepgram::read::options::{CallbackMethod, Options}; let options = Options::builder() .sentiment(true) .callback_method(CallbackMethod::POST) .build(); let ack = dg_client .text_intelligence() .analyze_text_callback(text, &options, "https://example.com/hook") .await?; println!("request id: {}", ack.request_id); ``` `analyze_url_callback` is the hosted-document equivalent. ## Key parameters - Input: `analyze_text(text, &options)` for inline text, `analyze_url(url, &options)` for a hosted plain-text document. - Analysis flags on `Options::builder()`: `sentiment`, `summarize`, `topics`, `intents`. - Custom taxonomies: `custom_topics` / `custom_topic_mode` and `custom_intents` / `custom_intent_mode`. - `language` defaults to English, the only language `/v1/read` accepts; the builder sends it for you because the endpoint returns 400 without it. - `tag` attaches request tags for usage reporting. - Callbacks: `analyze_text_callback` / `analyze_url_callback` plus `callback_method`. ## Escape hatch `make_read_request_builder` and `make_read_callback_request_builder` return the underlying `reqwest::RequestBuilder` before it is sent, for appending query parameters the typed options do not cover yet. ## API reference (layered) 1. **In-repo** - `src/read/` — `rest.rs` (the four request methods), `options.rs` (the query builder), `response.rs` (`Response`, `ReadMetadata`, `ReadResults`) - `README.md` for install/auth patterns 2. **OpenAPI** - Raw spec: `https://developers.deepgram.com/openapi.yaml` - Endpoint reference: `https://developers.deepgram.com/reference/text-intelligence/analyze-text` 3. **AsyncAPI** - Not applicable for `/v1/read` 4. **Context7** - `/llmstxt/developers_deepgram_llms_txt` 5. **Product docs** - `https://developers.deepgram.com/docs/text-intelligence` ## Gotchas 1. **This is different from audio intelligence.** Audio intelligence is piggybacked on STT and configured through the transcription `Options`; text intelligence is its own `/v1/read` API with its own `read::options::Options`. The two `Options` types are not interchangeable. 2. **Every analysis result is optional.** `results.sentiments`, `summary`, `topics`, and `intents` are `Option`, populated only for the flags you enabled. Match on them rather than unwrapping. `Summary::text` is itself an `Option<String>`, because the reference marks it optional, so reaching the summary text means unwrapping twice. 3. **Every metadata field is optional too.** Each field of `ReadMetadata` (including `request_id`, an `Option<Uuid>`, and `created`) and every field of `AnalysisInfo` is an `Option`, matching the reference, so logging the request id means unwrapping first rather than reading it straight off `response.metadata`. 4. **English only.** `/v1/read` accepts English; the builder sends `language=en` by default because the endpoint rejects a request without it. 5. **`read` can be enabled alone.** If a consumer has `default-features = false`, text intelligence needs `features = ["read"]` — it is not covered by `listen`. 6. **API keys use `Token`.** This API does not use `Bearer` for standard API keys. `Deepgram::new` handles the header for you. ## Example files in this repo - `examples/read/analyze_text.rs` — runnable end-to-end analysis, registered as the `analyze_text` example (`cargo run --features read --example analyze_text`). ## 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`).