chore(release): v1.39.0

.claude-plugin/plugin.json

@@ -1,6 +1,6 @@
 {
   "name": "aimock",
-  "version": "1.38.0",
+  "version": "1.39.0",
   "description": "Fixture authoring guidance for @copilotkit/aimock — LLM, multimedia, MCP, A2A, AG-UI, vector, and service mocking",
   "author": {
     "name": "CopilotKit"

CHANGELOG.md

@@ -2,6 +2,8 @@
 
 ## [Unreleased]
 
+## [1.39.0] - 2026-08-18
+
 ### Added
 
 - **AG-UI `RUN_FINISHED` and `RUN_ERROR` events now carry an optional `usage` field.** AG-UI's canonical `events.ts` declares an optional `usage: TokenUsage[]` on both terminal event schemas, but aimock's event interfaces carried neither. A new exported `AGUITokenUsage` type — numeric-only, mirroring `@ag-ui/core`'s `TokenUsageSchema` field for field (`provider` / `model` labels plus non-negative-integer `inputTokens`, `outputTokens`, `totalTokens`, `reasoningTokens`, `cachedInputTokens`, and no content-bearing or identifying fields) — is added as `usage?: AGUITokenUsage[]` on `AGUIRunFinishedEvent` and `AGUIRunErrorEvent`, and exported from both the package root and the `agui-stub` entrypoint. The field is reachable, not merely declarative: `AGUIBuildOpts` gains a `usage` option that is threaded to the terminal `RUN_FINISHED` of every builder and to `RUN_ERROR` in `buildErrorResponse`. Following the repo's existing usage policy (Bedrock / Cohere / Gemini), token counts are never synthesized from fixture content — `usage` is emitted only when a caller supplies it explicitly, so existing callers see byte-identical events. It is an array so a run that invokes multiple models keeps their counts separate (#378)

charts/aimock/Chart.yaml

@@ -3,4 +3,4 @@ name: aimock
 description: Mock infrastructure for AI application testing (OpenAI, Anthropic, Gemini, MCP, A2A, vector)
 type: application
 version: 0.1.0
-appVersion: "1.38.0"
+appVersion: "1.39.0"

package.json

@@ -1,6 +1,6 @@
 {
   "name": "@copilotkit/aimock",
-  "version": "1.38.0",
+  "version": "1.39.0",
   "description": "Mock infrastructure for AI application testing — LLM APIs, image generation, image editing, text-to-speech, transcription, audio translation, audio generation, video generation, embeddings, MCP tools, A2A agents, AG-UI event streams, vector databases, search, rerank, and moderation. One package, one port, zero dependencies.",
   "license": "MIT",
   "keywords": [