chore: import upstream snapshot with attribution
This commit is contained in:
wehub-resource-sync
@@ -0,0 +1,260 @@
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import test from "node:test";
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import assert from "node:assert/strict";
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const { openaiResponsesToOpenAIResponse } =
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await import("../../open-sse/translator/response/openai-responses.ts");
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const { FORMATS } = await import("../../open-sse/translator/formats.ts");
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const { createSSETransformStreamWithLogger } = await import("../../open-sse/utils/stream.ts");
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test("Responses->Chat: output_item.done emits arguments when no delta chunks were sent", () => {
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const state = {
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started: true,
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chatId: "chatcmpl-test",
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created: 1234567890,
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toolCallIndex: 0,
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finishReasonSent: false,
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currentToolCallId: "call_abc",
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currentToolCallArgsBuffer: "",
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};
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const chunk = {
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type: "response.output_item.done",
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item: {
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type: "function_call",
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call_id: "call_abc",
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name: "search_tasks",
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status: "completed",
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arguments: '{"query":"select:TaskCreate,TaskUpdate","max_results":10}',
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},
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};
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const result = openaiResponsesToOpenAIResponse(chunk, state);
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assert.ok(result);
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assert.equal(
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result.choices[0].delta.tool_calls[0].function.arguments,
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'{"query":"select:TaskCreate,TaskUpdate","max_results":10}'
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);
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assert.equal(state.toolCallIndex, 1);
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});
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test("Responses->Chat: output_item.done does not re-emit arguments already streamed via deltas", () => {
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const state = {
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started: true,
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chatId: "chatcmpl-test",
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created: 1234567890,
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toolCallIndex: 0,
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finishReasonSent: false,
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currentToolCallId: "call_abc",
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currentToolCallArgsBuffer: '{"query":"search"}',
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};
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const chunk = {
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type: "response.output_item.done",
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item: {
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type: "function_call",
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call_id: "call_abc",
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name: "search",
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status: "completed",
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arguments: '{"query":"search"}',
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},
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};
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const result = openaiResponsesToOpenAIResponse(chunk, state);
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assert.equal(result, null);
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assert.equal(state.toolCallIndex, 1);
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});
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test("Responses->Chat: empty-name tool call is deferred until done provides a valid name", () => {
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const state = {
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started: true,
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chatId: "chatcmpl-test",
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created: 1234567890,
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toolCallIndex: 0,
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finishReasonSent: false,
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currentToolCallArgsBuffer: "",
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currentToolCallDeferred: false,
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};
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const added = openaiResponsesToOpenAIResponse(
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{
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type: "response.output_item.added",
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item: { type: "function_call", call_id: "call_deferred", name: " " },
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},
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state
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);
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assert.equal(added, null);
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const delta = openaiResponsesToOpenAIResponse(
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{
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type: "response.function_call_arguments.delta",
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delta: '{"query":"deferred"}',
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},
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state
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);
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assert.equal(delta, null);
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const done = openaiResponsesToOpenAIResponse(
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{
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type: "response.output_item.done",
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item: {
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type: "function_call",
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call_id: "call_deferred",
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name: "search_tasks",
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arguments: '{"query":"deferred"}',
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},
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},
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state
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);
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assert.ok(done);
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assert.equal(done.choices[0].delta.tool_calls[0].function.name, "search_tasks");
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assert.equal(done.choices[0].delta.tool_calls[0].function.arguments, '{"query":"deferred"}');
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});
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test("Responses->Chat: empty-name tool call is dropped when done still has no valid name", () => {
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const state = {
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started: true,
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chatId: "chatcmpl-test",
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created: 1234567890,
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toolCallIndex: 0,
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finishReasonSent: false,
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currentToolCallArgsBuffer: "",
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currentToolCallDeferred: false,
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};
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openaiResponsesToOpenAIResponse(
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{
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type: "response.output_item.added",
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item: { type: "function_call", call_id: "call_empty", name: "" },
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},
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state
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);
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const done = openaiResponsesToOpenAIResponse(
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{
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type: "response.output_item.done",
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item: {
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type: "function_call",
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call_id: "call_empty",
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name: " ",
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arguments: '{"ignored":true}',
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},
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},
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state
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);
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assert.equal(done, null);
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assert.equal(state.toolCallIndex, 0);
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});
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test("Claude->Responses: {event,data} items bypass sanitization in translate mode", async () => {
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// Regression test: when translating Claude-format (GLM) to Responses API for Codex CLI,
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// the sanitizer was stripping {event,data} items to {"object":"chat.completion.chunk"},
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// losing all content and the critical response.completed event.
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const encoder = new TextEncoder();
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const decoder = new TextDecoder();
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// Create stream translating claude → openai-responses (same path as GLM via Codex CLI)
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const stream = createSSETransformStreamWithLogger(
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FORMATS.CLAUDE,
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FORMATS.OPENAI_RESPONSES,
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"glm",
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null,
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null,
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"glm-5.1",
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"conn-test",
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{ messages: [{ role: "user", content: "hi" }] },
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null,
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null
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);
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const writer = stream.writable.getWriter();
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// Simulate Claude-format SSE from GLM
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await writer.write(
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encoder.encode(
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'event: message_start\ndata: {"type":"message_start","message":{"id":"msg_test","type":"message","role":"assistant","model":"glm-5.1","content":[],"stop_reason":null,"usage":{"input_tokens":10,"output_tokens":0}}}\n\n'
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)
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);
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await writer.write(
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encoder.encode(
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'event: content_block_start\ndata: {"type":"content_block_start","index":0,"content_block":{"type":"text","text":""}}\n\n'
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)
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);
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await writer.write(
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encoder.encode(
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'event: content_block_delta\ndata: {"type":"content_block_delta","index":0,"delta":{"type":"text_delta","text":"hello"}}\n\n'
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)
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);
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await writer.write(
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encoder.encode(
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'event: message_delta\ndata: {"type":"message_delta","delta":{"stop_reason":"end_turn"},"usage":{"output_tokens":5}}\n\n'
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)
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);
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await writer.write(encoder.encode('event: message_stop\ndata: {"type":"message_stop"}\n\n'));
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await writer.close();
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const reader = stream.readable.getReader();
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let output = "";
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while (true) {
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const { value, done } = await reader.read();
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if (done) break;
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output += decoder.decode(value, { stream: true });
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}
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output += decoder.decode();
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// Must emit Responses API events (not sanitized chat.completion.chunk objects)
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assert.match(output, /event: response\.created/);
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assert.match(output, /event: response\.output_text\.delta/);
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assert.match(output, /event: response\.completed/);
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assert.match(output, /"delta":"hello"/);
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assert.match(output, /"status":"completed"/);
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// Must NOT contain sanitized empty chunks
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assert.doesNotMatch(output, /data: \{"object":"chat\.completion\.chunk"\}\n\n/);
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});
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test("Responses->Claude: translated Claude SSE is not sanitized into empty OpenAI chunks", async () => {
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const encoder = new TextEncoder();
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const decoder = new TextDecoder();
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const stream = createSSETransformStreamWithLogger(
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FORMATS.OPENAI_RESPONSES,
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FORMATS.CLAUDE,
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"codex",
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null,
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null,
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"gpt-5.4",
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"conn-test",
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{ messages: [{ role: "user", content: "hi" }] },
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null,
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null
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);
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const writer = stream.writable.getWriter();
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await writer.write(
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encoder.encode('data: {"type":"response.output_text.delta","delta":"hello"}\n\n')
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);
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await writer.write(
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encoder.encode(
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'data: {"type":"response.completed","response":{"usage":{"input_tokens":12,"output_tokens":3}}}\n\n'
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)
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);
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await writer.close();
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const reader = stream.readable.getReader();
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let output = "";
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while (true) {
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const { value, done } = await reader.read();
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if (done) break;
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output += decoder.decode(value, { stream: true });
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}
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output += decoder.decode();
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assert.match(output, /event: message_start/);
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assert.match(output, /event: content_block_start/);
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assert.match(output, /event: content_block_delta/);
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assert.match(output, /event: message_delta/);
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assert.match(output, /event: message_stop/);
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assert.doesNotMatch(output, /data: \{"object":"chat\.completion\.chunk"\}\n\n/);
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});
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