fix(responses): report usage on response.completed so clients can auto-compact

Map upstream Chat Completions usage to the Responses API shape and attach it to response.completed. Capture chunk.usage before the empty-choices guard so the usage-only trailer chunk survives, and defer completion to flushEvents() when usage is not yet known — only on the direct openai:openai-responses route, since a pivoted stream never reaches flushEvents. Fixes #3432.

open-sse/translator/response/openai-responses.js

@@ -14,11 +14,45 @@ import { ROLE, OPENAI_BLOCK, RESPONSES_ITEM, OPENAI_FINISH, MODEL_FALLBACK } fro
  * Translate OpenAI chunk to Responses API events
  * @returns {Array} Array of events with { event, data } structure
  */
+// Upstream Chat Completions usage -> Responses API usage shape.
+// Without this, /v1/responses never reports usage: Responses clients (Codex CLI)
+// keep their "context used" gauge pinned at 0 and never auto-compact, so a long
+// session grows until the upstream context limit rejects it (9router issue #3432).
+//
+// Note this is stored under state.responsesUsage, NOT state.usage: state.usage is
+// owned by the stream layer, which fills it with normalizeUsage()-shaped counts
+// (prompt_tokens/prompt_tokens_details) and hands it to finalizeStream() for
+// logging and cost accounting. Overwriting it with this shape silently drops
+// cached/reasoning tokens from those stats.
+function toResponsesUsage(usage) {
+  if (!usage || typeof usage !== "object") return null;
+
+  const inputTokens = [usage.input_tokens, usage.prompt_tokens].find(Number.isFinite) ?? 0;
+  const outputTokens = [usage.output_tokens, usage.completion_tokens].find(Number.isFinite) ?? 0;
+  const responseUsage = {
+    input_tokens: inputTokens,
+    output_tokens: outputTokens,
+    total_tokens: Number.isFinite(usage.total_tokens) ? usage.total_tokens : inputTokens + outputTokens
+  };
+  const cachedTokens = [usage.input_tokens_details?.cached_tokens, usage.prompt_tokens_details?.cached_tokens].find(Number.isFinite);
+  const reasoningTokens = [usage.output_tokens_details?.reasoning_tokens, usage.completion_tokens_details?.reasoning_tokens].find(Number.isFinite);
+  if (Number.isFinite(cachedTokens)) responseUsage.input_tokens_details = { cached_tokens: cachedTokens };
+  if (Number.isFinite(reasoningTokens)) responseUsage.output_tokens_details = { reasoning_tokens: reasoningTokens };
+
+  return responseUsage;
+}
+
 export function openaiToOpenAIResponsesResponse(chunk, state) {
   if (!chunk) {
     return flushEvents(state);
   }
 
+  // Capture upstream usage BEFORE the choices guard below: the last OpenAI chunk
+  // may carry usage together with an empty choices array, and it must not be dropped.
+  if (chunk.usage) {
+    state.responsesUsage = toResponsesUsage(chunk.usage);
+  }
+
   if (!chunk.choices?.length) return [];
 
   const events = [];
@@ -112,7 +146,19 @@ export function openaiToOpenAIResponsesResponse(chunk, state) {
     for (const i in state.msgItemAdded) closeMessage(state, emit, i);
     closeReasoning(state, emit);
     for (const i in state.funcCallIds) closeToolCall(state, emit, i);
-    sendCompleted(state, emit);
+    // Upstreams report usage either on the finish chunk itself or on a trailing chunk
+    // whose `choices` array is empty (OpenAI does the latter). Emitting
+    // response.completed here would freeze the payload before that trailing chunk is
+    // parsed, so when usage is not known yet we leave completion to flushEvents(),
+    // which runs once the upstream stream ends and by then has seen every chunk.
+    //
+    // That only holds on the direct openai:openai-responses route. When this converter
+    // runs as the second hop of a pivot (Claude/Gemini/Kiro upstream), translateResponse()
+    // drops the terminal null chunk before reaching us — the first hop returns null for
+    // it, leaving nothing to iterate — so flushEvents() is never called and deferring
+    // would swallow the terminal event entirely. Keep the old behaviour there.
+    const flushReachesUs = state.targetFormat === FORMATS.OPENAI;
+    if (state.responsesUsage || !flushReachesUs) sendCompleted(state, emit);
   }
 
   return events;
@@ -376,7 +422,8 @@ function sendCompleted(state, emit) {
         created_at: state.created,
         status: "completed",
         background: false,
-        error: null
+        error: null,
+        ...(state.responsesUsage ? { usage: state.responsesUsage } : {})
       }
     });
   }

open-sse/utils/stream.js

@@ -60,7 +60,13 @@ export function createSSEStream(options = {}) {
   const decoder = new TextDecoder("utf-8", { fatal: false });
 
   const state = mode === STREAM_MODE.TRANSLATE
-    ? { ...initState(sourceFormat), provider, toolNameMap, customToolNames: new Set(customToolNames || []), model, sessionId: credentials?._clientSessionId || null }
+    ? { ...initState(sourceFormat), provider, toolNameMap, customToolNames: new Set(customToolNames || []), model, sessionId: credentials?._clientSessionId || null,
+        // Which upstream format this stream came from. A response translator can be
+        // reached either directly (target === its registered source) or as the second
+        // hop of a pivot, and on the terminal null chunk the pivot drops it — so a
+        // translator that defers closing events until flush needs to know which case
+        // it is in. Absent/undefined means "unknown", i.e. do not defer.
+        targetFormat }
     : null;
 
   let totalContentLength = 0;

tests/unit/openai-responses-usage-completed.test.js

@@ -0,0 +1,162 @@
+import { describe, expect, it } from "vitest";
+
+import { FORMATS } from "../../open-sse/translator/formats.js";
+import { createSSETransformStreamWithLogger } from "../../open-sse/utils/stream.js";
+
+/**
+ * Upstream chunks -> client Responses API events.
+ *
+ * The converter under test is openaiToOpenAIResponsesResponse(), reached through
+ * the registered OPENAI:OPENAI_RESPONSES pair. Without it, /v1/responses never
+ * reports usage and Responses clients (Codex CLI) keep their context gauge at 0,
+ * so they never auto-compact and eventually hit the upstream context limit.
+ *
+ * Signature is (targetFormat, sourceFormat, ...) — targetFormat is what the
+ * UPSTREAM speaks, sourceFormat is what the CLIENT speaks.
+ */
+async function runTransform(chunks, targetFormat = FORMATS.OPENAI) {
+  const encoder = new TextEncoder();
+  const input = chunks.map((c) => `data: ${JSON.stringify(c)}\n\n`).join("");
+
+  const stream = new ReadableStream({
+    start(controller) {
+      controller.enqueue(encoder.encode(input));
+      controller.close();
+    },
+  });
+
+  const output = stream.pipeThrough(
+    createSSETransformStreamWithLogger(
+      targetFormat,
+      FORMATS.OPENAI_RESPONSES,
+      "deepseek",
+      null,
+      null,
+      "deepseek-flash",
+    ),
+  );
+
+  const reader = output.getReader();
+  const decoder = new TextDecoder();
+  let text = "";
+
+  while (true) {
+    const { value, done } = await reader.read();
+    if (done) break;
+    text += decoder.decode(value, { stream: true });
+  }
+
+  text += decoder.decode();
+  return text;
+}
+
+function completedEvents(output) {
+  return output
+    .split("\n")
+    .filter((l) => l.startsWith("data: ") && l.includes('"type":"response.completed"'));
+}
+
+function completedResponse(output) {
+  const lines = completedEvents(output);
+  expect(lines.length, "expected exactly one response.completed").toBe(1);
+  return JSON.parse(lines[0].slice(6)).response;
+}
+
+const TEXT_CHUNK = {
+  id: "chatcmpl-test",
+  object: "chat.completion.chunk",
+  created: 1700000000,
+  model: "deepseek-flash",
+  choices: [{ index: 0, delta: { role: "assistant", content: "好" } }],
+};
+
+const FINISH_CHUNK = {
+  id: "chatcmpl-test",
+  object: "chat.completion.chunk",
+  created: 1700000000,
+  model: "deepseek-flash",
+  choices: [{ index: 0, delta: {}, finish_reason: "stop" }],
+};
+
+// Usage-only trailer: `choices` is empty, exactly as OpenAI emits it when
+// stream_options.include_usage is set.
+const USAGE_ONLY_CHUNK = {
+  id: "chatcmpl-test",
+  object: "chat.completion.chunk",
+  created: 1700000000,
+  model: "deepseek-flash",
+  choices: [],
+  usage: {
+    prompt_tokens: 884,
+    completion_tokens: 37,
+    total_tokens: 921,
+    prompt_tokens_details: { cached_tokens: 256 },
+  },
+};
+
+const EXPECTED_USAGE = {
+  input_tokens: 884,
+  output_tokens: 37,
+  total_tokens: 921,
+  input_tokens_details: { cached_tokens: 256 },
+};
+
+// Claude-shaped stream with NO usage anywhere: the only way the client gets a
+// terminal event is the finish_reason branch, because the pivot never reaches
+// flushEvents() with the terminal null chunk.
+const CLAUDE_CHUNKS = [
+  { type: "message_start", message: { id: "msg_1", model: "claude-x" } },
+  { type: "content_block_start", index: 0, content_block: { type: "text", text: "" } },
+  { type: "content_block_delta", index: 0, delta: { type: "text_delta", text: "hi" } },
+  { type: "content_block_stop", index: 0 },
+  { type: "message_delta", delta: { stop_reason: "end_turn" } },
+  { type: "message_stop" },
+];
+
+describe("OpenAI Responses usage on response.completed", () => {
+  it("maps usage reported on the finish chunk", async () => {
+    const output = await runTransform([
+      TEXT_CHUNK,
+      {
+        ...FINISH_CHUNK,
+        usage: {
+          prompt_tokens: 884,
+          completion_tokens: 37,
+          total_tokens: 921,
+          prompt_tokens_details: { cached_tokens: 256 },
+          completion_tokens_details: { reasoning_tokens: 12 },
+        },
+      },
+    ]);
+
+    expect(completedResponse(output).usage).toEqual({
+      ...EXPECTED_USAGE,
+      output_tokens_details: { reasoning_tokens: 12 },
+    });
+  });
+
+  it("maps usage reported on a trailing usage-only chunk with empty choices", async () => {
+    const output = await runTransform([TEXT_CHUNK, FINISH_CHUNK, USAGE_ONLY_CHUNK]);
+
+    expect(completedResponse(output).usage).toEqual(EXPECTED_USAGE);
+  });
+
+  it("still completes when the upstream reports no usage at all", async () => {
+    const output = await runTransform([TEXT_CHUNK, FINISH_CHUNK]);
+
+    const response = completedResponse(output);
+    expect(response.status).toBe("completed");
+    expect(response).not.toHaveProperty("usage");
+  });
+
+  // Regression guard for the pivot: with a Claude upstream the converter runs as
+  // the second hop, translateResponse() drops the terminal null chunk before it
+  // reaches this converter, so flushEvents() never runs. Deferring completion
+  // there would leave the client without any terminal event.
+  it("completes on a pivoted stream whose upstream never reports usage", async () => {
+    const output = await runTransform(CLAUDE_CHUNKS, FORMATS.CLAUDE);
+
+    const response = completedResponse(output);
+    expect(response.status).toBe("completed");
+  });
+});