feat: 1st class OpenTelemetry support

.gitignore

@@ -16,3 +16,6 @@ logs/
 
 # setuptools_scm
 chatlas/_version.py
+
+# superpowers visual companion working dir
+.superpowers/

CHANGELOG.md

@@ -11,6 +11,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ### New features
 
+* chatlas is now instrumented with [OpenTelemetry](https://opentelemetry.io/) (OTel) out of the box, making it much easier to see how your app behaves in production — where time goes, how many tokens you're spending, which tools run, and where things fail. Without writing any tracing code, you get spans that capture the full structure of a conversation as one connected trace: an `invoke_agent` span over the whole chat loop, a `chat` span per model call, and an `execute_tool` span per tool invocation, with attributes (token usage, response model/ID, tool errors) that follow the [OTel GenAI semantic conventions](https://opentelemetry.io/docs/specs/semconv/gen-ai/). Because chatlas keeps its spans active during each call, HTTP spans from provider instrumentors and any spans your own tools emit nest underneath automatically. Point it at any OTel-compatible backend (Logfire, Datadog, Honeycomb, Jaeger, …); message content is omitted by default and opt-in via `OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT=true`. See the [monitoring guide](https://posit-dev.github.io/chatlas/get-started/monitor.html) to get started. (#310)
 * `Chat` gains a `model` property to get (or set) the model after the chat is created. Setting it does not validate the model name.
 * `ChatGoogle()`'s `reasoning` parameter now accepts a string thinking level (`"minimal"`, `"low"`, `"medium"`, or `"high"`) in addition to an integer token budget.
 * `ChatAnthropic()`'s `reasoning` parameter now accepts a string effort level (`"low"`, `"medium"`, `"high"`, `"xhigh"`, or `"max"`) to enable Claude's adaptive thinking, in addition to an integer token budget.