Files
OmniRoute/tests/integration/server-owned-tool-loop-pipeline.test.ts
Bob.Hou d6f315018a fix(chat): continue after a server-owned tool on Chat Completions (#12867)
Validado numa worktree combinada com as 16 PRs desta leva sobre `release/v3.8.51`: typecheck:core limpo, check-file-size e check-changelog-integrity OK, complexity 2788/3218 e cognitive 1261/1437, ESLint 0 erros nos 152 arquivos alterados, e a suíte vitest:ui completa (2149) verde.

Sobre esta PR especificamente: rodei os **23 arquivos de teste** que ela toca sobre o tip final, depois do merge da base — **392/392**. A migration `174_server_tool_executions.sql` não colide (o tip está em 173, e você já a renumerou em `c35f0fd7`).

O dono foi consultado antes do merge, porque o loop está atrás da flag `SERVER_OWNED_TOOL_LOOP_ENABLED` mas o primeiro send não-streaming mudou de dono sem flag, e a verificação manual em combo com Memory continuava desmarcada. A condição dele foi: entra se os testes focados passarem aqui. Passaram.

O lock de passthrough (`fetchCalls.length === 1`) é a parte que mais me convenceu — o double-dispatch que um `if (stream)` em volta do send existente causaria é exatamente o tipo de regressão que não aparece em teste de comportamento, só em contagem de chamada.

**Três ajustes meus na sua branch:**

1. `tests/unit/chatcore-stream-error-result.test.ts` procurava `"const legResult = await runNonStreamingProviderLeg"`, mas o seu commit final `6077b9dd` passou a reatribuir `legResult` e trocou para `let`. O guard falhava na sua própria branch (confirmei que o arquivo e o `chatCore.ts` eram byte-idênticos ao head da PR, então não era efeito da leva). Passou a aceitar `const|let` — a intenção do guard é o try/catch em volta da chamada, não a palavra-chave.

2. `tests/integration/skills-pipeline.test.ts` foi de 1156 para 1338 linhas e estourou o `testCap` de 1200. Segui o mesmo caminho que você já tinha tomado em `a1d2d20d` para os testes unitários: extraí os três casos do server-owned tool loop para `tests/integration/server-owned-tool-loop-pipeline.test.ts` (259 linhas), com instância própria do harness. O glob `tests/integration/*.test.ts` pega o arquivo novo sem registro adicional. 3/3 verdes isolados.

3. O arquivo novo herdou cinco `any` do original — que só passavam por estarem congelados no `eslint-suppressions.json` sob o nome antigo. Tipei como `Record<string, unknown>`. E `tests/unit/non-streaming-finalization.test.ts` tinha dois argumentos não usados em `trackPendingRequest`, agora prefixados com `_`.

Nada disso toca produção nem enfraquece asserção.
2026-09-07 09:15:00 -03:00

260 lines
7.7 KiB
TypeScript

import test from "node:test";
import assert from "node:assert/strict";
import { encodeSkillToolName } from "../../src/lib/skills/injection.ts";
import { createChatPipelineHarness } from "./_chatPipelineHarness.ts";
// Split out of skills-pipeline.test.ts (#12867): the three server-owned tool loop
// cases pushed that file to 1338 lines, past the 1200-line test cap. Same harness,
// its own instance so the two files stay independently runnable.
const harness = await createChatPipelineHarness("server-owned-tool-loop-pipeline");
const {
BaseExecutor,
buildOpenAIResponse,
buildOpenAIToolCallResponse,
buildRequest,
handleChat,
resetStorage,
seedApiKey,
seedConnection,
settingsDb,
skillExecutor,
skillRegistry,
} = harness;
test.beforeEach(async () => {
BaseExecutor.RETRY_CONFIG.delayMs = 0;
await resetStorage();
});
test.afterEach(async () => {
BaseExecutor.RETRY_CONFIG.delayMs = harness.originalRetryDelayMs;
await resetStorage();
});
test.after(async () => {
await harness.cleanup();
});
async function enableSkills() {
await settingsDb.updateSettings({ skillsEnabled: true });
}
async function registerSkill({
apiKeyId,
name,
version = "1.0.0",
handler,
enabled = true,
description = "Test skill",
mode,
tags,
installCount,
}) {
return skillRegistry.register({
apiKeyId,
name,
version,
description,
schema: {
input: {
type: "object",
properties: {
location: { type: "string" },
path: { type: "string" },
},
},
output: {
type: "object",
},
},
handler,
enabled,
mode,
tags,
installCount,
});
}
test("server-owned tool loop completes end-to-end for OpenAI without returning tool_results (issue #12696)", async () => {
await seedConnection("openai", { apiKey: "test-openai-key" });
const apiKey = await seedApiKey();
await enableSkills();
skillExecutor.registerHandler("weather-handler-loop-openai", async (input) => ({
forecast: `Sunny in ${input.location}`,
}));
await registerSkill({
apiKeyId: apiKey.id,
name: "lookupWeather",
handler: "weather-handler-loop-openai",
});
const prevFlag = process.env.SERVER_OWNED_TOOL_LOOP_ENABLED;
process.env.SERVER_OWNED_TOOL_LOOP_ENABLED = "true";
const fetchCalls: Array<{ url: string; body: Record<string, unknown> }> = [];
globalThis.fetch = async (input, init) => {
const bodyStr = typeof init?.body === "string" ? init.body : "{}";
const body = JSON.parse(bodyStr);
fetchCalls.push({ url: String(input), body });
if (fetchCalls.length === 1) {
return buildOpenAIToolCallResponse({
toolCallId: "call_weather_loop_1",
toolName: encodeSkillToolName("lookupWeather", "1.0.0"),
argumentsObject: { location: "Tokyo" },
});
}
return buildOpenAIResponse("The weather in Tokyo is 18C and sunny.", "gpt-4o-mini");
};
try {
const response = await handleChat(
buildRequest({
authKey: apiKey.key,
body: {
model: "openai/gpt-4o-mini",
stream: false,
messages: [{ role: "user", content: "What is the weather in Tokyo?" }],
},
})
);
assert.equal(response.status, 200);
const json = (await response.json()) as Record<string, unknown>;
assert.equal(fetchCalls.length, 2, "should have dispatched 2 provider legs");
assert.equal(
json.tool_results,
undefined,
"gateway should not return tool_results when loop is enabled"
);
assert.equal(json.choices[0].finish_reason, "stop");
assert.equal(json.choices[0].message.content, "The weather in Tokyo is 18C and sunny.");
assert.equal(fetchCalls[1].body.messages.length, 3);
assert.equal(fetchCalls[1].body.messages[1].role, "assistant");
assert.equal(fetchCalls[1].body.messages[2].role, "tool");
assert.equal(fetchCalls[1].body.messages[2].tool_call_id, "call_weather_loop_1");
} finally {
process.env.SERVER_OWNED_TOOL_LOOP_ENABLED = prevFlag;
}
});
test("server-owned tool loop follow-up failure propagates error cleanly", async () => {
await seedConnection("openai", { apiKey: "test-openai-key" });
const apiKey = await seedApiKey();
await enableSkills();
skillExecutor.registerHandler("weather-handler-loop-fail", async (input) => ({
forecast: `Sunny in ${input.location}`,
}));
await registerSkill({
apiKeyId: apiKey.id,
name: "lookupWeather",
handler: "weather-handler-loop-fail",
});
const prevFlag = process.env.SERVER_OWNED_TOOL_LOOP_ENABLED;
process.env.SERVER_OWNED_TOOL_LOOP_ENABLED = "true";
let callCount = 0;
globalThis.fetch = async () => {
callCount++;
if (callCount === 1) {
return buildOpenAIToolCallResponse({
callId: "call_weather_fail_1",
toolName: encodeSkillToolName("lookupWeather", "1.0.0"),
argumentsObject: { location: "Tokyo" },
});
}
return new Response(JSON.stringify({ error: { message: "Rate limit exceeded" } }), {
status: 429,
headers: { "content-type": "application/json" },
});
};
try {
const response = await handleChat(
buildRequest({
authKey: apiKey.key,
body: {
model: "openai/gpt-4o-mini",
stream: false,
messages: [{ role: "user", content: "What is the weather in Tokyo?" }],
},
})
);
assert.ok(callCount >= 2, `expected at least 2 fetch calls, got ${callCount}`);
assert.equal(response.status, 429);
} finally {
process.env.SERVER_OWNED_TOOL_LOOP_ENABLED = prevFlag;
}
});
test("server-owned tool loop completes end-to-end for Claude messages client without returning tool_results", async () => {
await seedConnection("openai", { apiKey: "test-openai-key" });
const apiKey = await seedApiKey();
await enableSkills();
skillExecutor.registerHandler("weather-handler-loop-claude-client", async (input) => ({
forecast: `Sunny in ${input.location}`,
}));
await registerSkill({
apiKeyId: apiKey.id,
name: "lookupWeather",
handler: "weather-handler-loop-claude-client",
});
const prevFlag = process.env.SERVER_OWNED_TOOL_LOOP_ENABLED;
process.env.SERVER_OWNED_TOOL_LOOP_ENABLED = "true";
const fetchCalls: Array<{ url: string; body: Record<string, unknown> }> = [];
globalThis.fetch = async (input, init) => {
const bodyStr = typeof init?.body === "string" ? init.body : "{}";
const body = JSON.parse(bodyStr);
fetchCalls.push({ url: String(input), body });
if (fetchCalls.length === 1) {
return buildOpenAIToolCallResponse({
toolCallId: "call_weather_claude_1",
toolName: encodeSkillToolName("lookupWeather", "1.0.0"),
argumentsObject: { location: "Tokyo" },
});
}
return buildOpenAIResponse("The weather in Tokyo is 18C and sunny.", "gpt-4o-mini");
};
try {
const response = await handleChat(
buildRequest({
url: "http://localhost/v1/messages",
authKey: apiKey.key,
body: {
model: "openai/gpt-4o-mini",
stream: false,
max_tokens: 256,
messages: [
{ role: "user", content: [{ type: "text", text: "What is the weather in Tokyo?" }] },
],
},
})
);
assert.equal(response.status, 200);
const json = (await response.json()) as Record<string, unknown>;
assert.equal(fetchCalls.length, 2, "should have dispatched 2 provider legs");
assert.equal(json.type, "message");
assert.equal(json.role, "assistant");
assert.equal(json.stop_reason, "end_turn");
assert.equal(json.content[0].text, "The weather in Tokyo is 18C and sunny.");
assert.equal(json.tool_results, undefined);
} finally {
process.env.SERVER_OWNED_TOOL_LOOP_ENABLED = prevFlag;
}
});