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