wehub-resource-sync
773 lines
25 KiB
TypeScript
773 lines
25 KiB
TypeScript
import test from "node:test";
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import assert from "node:assert/strict";
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import fs from "node:fs";
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import os from "node:os";
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import path from "node:path";
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const TEST_DATA_DIR = fs.mkdtempSync(path.join(os.tmpdir(), "omniroute-calllogs-artifacts-"));
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process.env.DATA_DIR = TEST_DATA_DIR;
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process.env.CALL_LOG_RETENTION_DAYS = "3650";
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process.env.CALL_LOG_MAX_ENTRIES = "100";
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const ORIGINAL_CALL_LOG_PIPELINE_MAX_SIZE_KB = process.env.CALL_LOG_PIPELINE_MAX_SIZE_KB;
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const core = await import("../../src/lib/db/core.ts");
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const callLogs = await import("../../src/lib/usage/callLogs.ts");
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const detailedLogs = await import("../../src/lib/db/detailedLogs.ts");
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const providersDb = await import("../../src/lib/db/providers.ts");
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async function resetStorage() {
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core.resetDbInstance();
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fs.rmSync(TEST_DATA_DIR, { recursive: true, force: true });
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fs.mkdirSync(TEST_DATA_DIR, { recursive: true });
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}
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function restorePipelineEnv() {
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if (ORIGINAL_CALL_LOG_PIPELINE_MAX_SIZE_KB === undefined) {
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delete process.env.CALL_LOG_PIPELINE_MAX_SIZE_KB;
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} else {
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process.env.CALL_LOG_PIPELINE_MAX_SIZE_KB = ORIGINAL_CALL_LOG_PIPELINE_MAX_SIZE_KB;
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}
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}
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function insertCallLog(row) {
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const db = core.getDbInstance();
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db.prepare(
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`
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INSERT INTO call_logs (
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id, timestamp, method, path, status, model, requested_model, provider, account,
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connection_id, duration, tokens_in, tokens_out, cache_source, source_format, target_format,
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api_key_id, api_key_name, combo_name, combo_step_id, combo_execution_key,
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error_summary, detail_state, artifact_relpath, artifact_size_bytes, artifact_sha256,
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has_request_body, has_response_body, has_pipeline_details, request_summary
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)
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VALUES (
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@id, @timestamp, @method, @path, @status, @model, @requested_model, @provider, @account,
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@connection_id, @duration, @tokens_in, @tokens_out, @cache_source, @source_format, @target_format,
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@api_key_id, @api_key_name, @combo_name, @combo_step_id, @combo_execution_key,
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@error_summary, @detail_state, @artifact_relpath, @artifact_size_bytes, @artifact_sha256,
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@has_request_body, @has_response_body, @has_pipeline_details, @request_summary
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)
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`
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).run({
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requested_model: null,
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connection_id: null,
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duration: 0,
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tokens_in: 0,
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tokens_out: 0,
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cache_source: "upstream",
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source_format: null,
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target_format: null,
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api_key_id: null,
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api_key_name: null,
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combo_name: null,
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combo_step_id: null,
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combo_execution_key: null,
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error_summary: null,
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detail_state: "none",
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artifact_relpath: null,
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artifact_size_bytes: null,
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artifact_sha256: null,
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has_request_body: 0,
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has_response_body: 0,
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has_pipeline_details: 0,
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request_summary: null,
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...row,
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});
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}
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test.beforeEach(async () => {
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restorePipelineEnv();
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process.env.CALL_LOG_RETENTION_DAYS = "3650";
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await resetStorage();
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});
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test.after(() => {
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restorePipelineEnv();
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core.resetDbInstance();
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fs.rmSync(TEST_DATA_DIR, { recursive: true, force: true });
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});
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test("saveCallLog stores only summary metadata in SQLite and writes detailed artifact", async () => {
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const timestamp = "2026-03-30T12:34:56.789Z";
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const logId = "req_artifact_1";
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await callLogs.saveCallLog({
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id: logId,
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timestamp,
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method: "POST",
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path: "/v1/chat/completions",
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status: 200,
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model: "openai/gpt-4.1",
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requestedModel: "openai/gpt-5",
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provider: "openai",
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cacheSource: "semantic",
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duration: 42,
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comboName: "combo-a",
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comboStepId: "step-openai-a",
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comboExecutionKey: "combo-a:0:step-openai-a",
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requestBody: { messages: [{ role: "user", content: "hello" }] },
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responseBody: { id: "resp_1", choices: [{ message: { content: "world" } }] },
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pipelinePayloads: {
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clientRawRequest: { body: { raw: true } },
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providerRequest: { body: { translated: true } },
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providerResponse: { body: { upstream: true } },
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clientResponse: { body: { final: true } },
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},
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});
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const logs = await callLogs.getCallLogs({ limit: 5 });
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assert.equal(logs.length, 1);
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assert.equal(logs[0].hasRequestBody, true);
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assert.equal(logs[0].hasResponseBody, true);
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assert.equal(logs[0].hasPipelineDetails, true);
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assert.equal(logs[0].detailState, "ready");
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const detail = await callLogs.getCallLogById(logId);
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assert.equal(detail?.requestedModel, "openai/gpt-5");
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assert.equal(detail?.cacheSource, "semantic");
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assert.equal(detail?.comboName, "combo-a");
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assert.equal(detail?.comboStepId, "step-openai-a");
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assert.equal(detail?.comboExecutionKey, "combo-a:0:step-openai-a");
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assert.equal(detail?.pipelinePayloads?.clientRawRequest?.body?.raw, true);
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assert.equal((detail?.pipelinePayloads?.providerRequest as any).body?.translated, true);
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assert.equal((detail?.pipelinePayloads as any).providerResponse?.body?.upstream, true);
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assert.equal((detail?.pipelinePayloads as any).clientResponse?.body?.final, true);
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assert.match(
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detail?.artifactRelPath || "",
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/^2026-03-30\/2026-03-30T12-34-56\.789Z_req_artifact_1\.json$/
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);
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const db = core.getDbInstance();
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const columns = db
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.prepare("SELECT name FROM pragma_table_info('call_logs') ORDER BY cid")
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.all()
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.map((row) => (row as any).name);
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assert.equal(columns.includes("request_body"), false);
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assert.equal(columns.includes("response_body"), false);
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assert.equal(columns.includes("error"), false);
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const summaryRow = db
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.prepare(
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`
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SELECT detail_state, artifact_relpath, cache_source, has_request_body, has_response_body, has_pipeline_details
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FROM call_logs WHERE id = ?
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`
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)
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.get(logId);
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(assert as any).equal((summaryRow as any).detail_state, "ready");
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assert.equal((summaryRow as any).cache_source, "semantic");
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assert.equal((summaryRow as any).has_request_body, 1);
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assert.equal((summaryRow as any).has_response_body, 1);
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assert.equal((summaryRow as any).has_pipeline_details, 1);
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assert.equal(typeof (summaryRow as any).artifact_relpath, "string");
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const artifactPath = path.join(TEST_DATA_DIR, "call_logs", detail.artifactRelPath);
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const artifact = JSON.parse(fs.readFileSync(artifactPath, "utf8"));
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assert.equal(artifact.summary.id, logId);
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assert.equal(artifact.summary.requestedModel, "openai/gpt-5");
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assert.equal(artifact.summary.comboExecutionKey, "combo-a:0:step-openai-a");
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});
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test("getCallLogs resolves raw account labels from provider connections", async () => {
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const connection = await providersDb.createProviderConnection({
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provider: "codex",
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authType: "oauth",
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name: "logs.user@example.com",
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email: "logs.user@example.com",
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accessToken: "token",
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});
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insertCallLog({
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id: "masked-account-log",
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timestamp: "2026-03-30T12:34:56.789Z",
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method: "POST",
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path: "/v1/responses",
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status: 200,
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model: "gpt-5.5",
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requested_model: "codex/gpt-5.5",
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provider: "codex",
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account: "log******@********com",
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connection_id: connection.id,
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});
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const logs = await callLogs.getCallLogs({ account: "logs.user@example.com", limit: 10 });
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assert.equal(logs.length, 1);
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assert.equal(logs[0].account, "logs.user@example.com");
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const detail = await callLogs.getCallLogById("masked-account-log");
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assert.equal(detail?.account, "logs.user@example.com");
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});
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test("rotateCallLogs removes expired rows and orphaned artifacts but keeps fresh referenced artifacts", async () => {
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process.env.CALL_LOG_RETENTION_DAYS = "1";
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const oldRelPath = "2026-03-10/2026-03-10T00-00-00.000Z_old.json";
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const oldAbsPath = path.join(TEST_DATA_DIR, "call_logs", oldRelPath);
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fs.mkdirSync(path.dirname(oldAbsPath), { recursive: true });
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fs.writeFileSync(oldAbsPath, JSON.stringify({ schemaVersion: 4 }, null, 2));
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insertCallLog({
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id: "expired-log",
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timestamp: "2026-03-10T00:00:00.000Z",
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method: "POST",
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path: "/v1/chat/completions",
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status: 200,
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model: "openai/gpt-4.1",
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provider: "openai",
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account: "Expired",
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detail_state: "ready",
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artifact_relpath: oldRelPath,
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has_request_body: 1,
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});
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await callLogs.saveCallLog({
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id: "fresh-log",
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timestamp: new Date().toISOString(),
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method: "POST",
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path: "/v1/chat/completions",
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status: 200,
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model: "openai/gpt-4.1",
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provider: "openai",
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requestBody: { ok: true },
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});
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const freshRow = core
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.getDbInstance()
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.prepare("SELECT artifact_relpath FROM call_logs WHERE id = ?")
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.get("fresh-log");
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const freshAbsPath = path.join(TEST_DATA_DIR, "call_logs", (freshRow as any).artifact_relpath);
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assert.equal(
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(
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core
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.getDbInstance()
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.prepare("SELECT COUNT(*) AS cnt FROM call_logs WHERE id = ?")
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.get("expired-log") as any
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).cnt,
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1
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);
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assert.equal(fs.existsSync(oldAbsPath), true);
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assert.equal(fs.existsSync(freshAbsPath), true);
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callLogs.rotateCallLogs();
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const db = core.getDbInstance();
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assert.equal(
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(db.prepare("SELECT COUNT(*) AS cnt FROM call_logs WHERE id = ?").get("expired-log") as any)
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.cnt,
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0
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);
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assert.equal(fs.existsSync(oldAbsPath), false);
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assert.equal(
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(db.prepare("SELECT COUNT(*) AS cnt FROM call_logs WHERE id = ?").get("fresh-log") as any).cnt,
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1
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);
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assert.equal(fs.existsSync(freshAbsPath), true);
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const orphanDir = path.join(TEST_DATA_DIR, "call_logs", "2026-03-31");
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const orphanFile = path.join(orphanDir, "orphan.json");
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fs.mkdirSync(orphanDir, { recursive: true });
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fs.writeFileSync(orphanFile, "{}");
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callLogs.cleanupOrphanCallLogFiles();
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assert.equal(fs.existsSync(orphanFile), false);
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process.env.CALL_LOG_RETENTION_DAYS = "3650";
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});
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test("getCallLogs applies provider, account, apiKey, combo, search, and status filters with summary fields", async () => {
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insertCallLog({
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id: "filter-hit",
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timestamp: "2026-03-30T12:34:56.000Z",
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method: "POST",
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path: "/v1/chat/completions",
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status: 200,
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model: "openai/gpt-4.1",
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requested_model: "openai/gpt-5",
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provider: "openai",
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account: "Primary Account",
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connection_id: "conn-1",
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duration: 42,
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tokens_in: 11,
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tokens_out: 7,
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source_format: "openai",
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target_format: "openai",
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api_key_id: "key-1",
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api_key_name: "Primary Key",
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combo_name: "combo-a",
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combo_step_id: "step-a",
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combo_execution_key: "combo-a:0:step-a",
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has_request_body: 1,
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});
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insertCallLog({
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id: "filter-miss",
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timestamp: "2026-03-30T12:35:56.000Z",
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method: "POST",
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path: "/v1/embeddings",
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status: 200,
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model: "gemini/text-embedding",
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provider: "gemini",
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account: "Backup Account",
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connection_id: "conn-2",
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duration: 9,
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tokens_in: 3,
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tokens_out: 1,
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source_format: "openai",
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target_format: "gemini",
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api_key_id: "key-2",
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api_key_name: "Backup Key",
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});
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insertCallLog({
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id: "status-error-by-message",
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timestamp: "2026-03-30T12:36:56.000Z",
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method: "POST",
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path: "/v1/chat/completions",
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status: 200,
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model: "openai/gpt-4.1",
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provider: "openai",
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account: "Primary Account",
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error_summary: "synthetic failure",
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});
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insertCallLog({
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id: "status-error",
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timestamp: "2026-03-30T12:37:56.000Z",
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method: "POST",
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path: "/v1/chat/completions",
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status: 500,
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model: "openai/gpt-4.1",
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provider: "openai",
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account: "Primary Account",
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});
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assert.deepEqual(
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(await callLogs.getCallLogs({ provider: "openai" })).map((row) => row.id),
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["status-error", "status-error-by-message", "filter-hit"]
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);
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assert.deepEqual(
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(await callLogs.getCallLogs({ account: "primary" })).map((row) => row.id),
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["status-error", "status-error-by-message", "filter-hit"]
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);
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assert.deepEqual(
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(await callLogs.getCallLogs({ apiKey: "Primary" })).map((row) => row.id),
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["filter-hit"]
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);
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assert.deepEqual(
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(await callLogs.getCallLogs({ combo: true })).map((row) => row.id),
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["filter-hit"]
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);
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assert.deepEqual(
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(await callLogs.getCallLogs({ search: "gpt-5" })).map((row) => row.id),
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["filter-hit"]
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);
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assert.deepEqual(
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(await callLogs.getCallLogs({ status: "error" })).map((row) => row.id),
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["status-error", "status-error-by-message"]
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);
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assert.deepEqual(
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(await callLogs.getCallLogs({ status: "ok" })).map((row) => row.id),
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["status-error-by-message", "filter-miss", "filter-hit"]
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);
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});
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test("getCallLogById falls back to legacy inline rows and request_detail_logs", async () => {
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const db = core.getDbInstance();
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db.exec(`
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CREATE TABLE call_logs_v1_legacy (
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id TEXT PRIMARY KEY,
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request_body TEXT,
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response_body TEXT,
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error TEXT
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);
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`);
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insertCallLog({
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id: "legacy-read",
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timestamp: "2026-03-30T12:34:56.000Z",
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method: "POST",
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path: "/v1/chat/completions",
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status: 200,
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model: "openai/gpt-4.1",
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provider: "openai",
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account: "Primary Account",
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detail_state: "legacy-inline",
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has_request_body: 1,
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has_response_body: 1,
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});
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db.prepare(
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`
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INSERT INTO call_logs_v1_legacy (id, request_body, response_body, error)
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VALUES (?, ?, ?, ?)
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`
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).run(
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"legacy-read",
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JSON.stringify({ recovered: "request" }),
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JSON.stringify({ recovered: "response" }),
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JSON.stringify({ message: "legacy-error" })
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);
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detailedLogs.saveRequestDetailLog({
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call_log_id: "legacy-read",
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client_request: { body: { from: "detail-client" } },
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translated_request: { body: { from: "detail-provider-request" } },
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provider_response: { body: { from: "detail-provider-response" } },
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client_response: { body: { from: "detail-client-response" } },
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});
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const detail = await callLogs.getCallLogById("legacy-read");
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assert.deepEqual(detail?.requestBody, { recovered: "request" });
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assert.deepEqual(detail?.responseBody, { recovered: "response" });
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assert.deepEqual(detail?.error, { message: "legacy-error" });
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assert.equal(detail?.pipelinePayloads?.clientRequest?.body?.from, "detail-client");
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assert.equal(
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(detail?.pipelinePayloads?.providerRequest as any).body?.from,
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"detail-provider-request"
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);
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(assert as any).equal(
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(detail?.pipelinePayloads?.providerResponse as any).body?.from,
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"detail-provider-response"
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);
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assert.equal(
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(detail?.pipelinePayloads?.clientResponse as any).body?.from,
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"detail-client-response"
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);
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assert.equal(detail?.hasPipelineDetails, true);
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});
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test("getCallLogById marks missing artifacts explicitly and clears stale DB pointers", async () => {
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insertCallLog({
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id: "missing-artifact",
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timestamp: "2026-03-30T12:34:56.000Z",
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method: "POST",
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path: "/v1/chat/completions",
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status: 200,
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model: "openai/gpt-4.1",
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provider: "openai",
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account: "Primary Account",
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detail_state: "ready",
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artifact_relpath: "2026-03-30/missing.json",
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has_request_body: 1,
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});
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const detail = await callLogs.getCallLogById("missing-artifact");
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assert.equal(detail?.detailState, "missing");
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assert.equal(detail?.requestBody, null);
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const db = core.getDbInstance();
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const row = db
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.prepare("SELECT artifact_relpath, detail_state FROM call_logs WHERE id = ?")
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.get("missing-artifact");
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assert.equal((row as any).artifact_relpath, null);
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assert.equal((row as any).detail_state, "missing");
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});
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test("saveCallLog keeps large payloads out of SQLite while preserving explicit detail export", async () => {
|
|
const requestBody = { payload: "x".repeat(320 * 1024) };
|
|
|
|
await callLogs.saveCallLog({
|
|
id: "artifact-only-large-payload",
|
|
timestamp: "2026-03-31T09:05:00.000Z",
|
|
method: "POST",
|
|
path: "/v1/chat/completions",
|
|
status: 500,
|
|
model: "openai/gpt-4.1",
|
|
provider: "openai",
|
|
duration: 7,
|
|
requestType: "search",
|
|
requestBody,
|
|
error: "upstream unavailable",
|
|
});
|
|
|
|
const db = core.getDbInstance();
|
|
const row = db
|
|
.prepare(
|
|
`
|
|
SELECT detail_state, has_request_body, artifact_relpath, error_summary, request_summary
|
|
FROM call_logs WHERE id = ?
|
|
`
|
|
)
|
|
.get("artifact-only-large-payload");
|
|
assert.equal((row as any).detail_state, "ready");
|
|
assert.equal((row as any).has_request_body, 1);
|
|
(assert as any).equal(typeof (row as any).artifact_relpath, "string");
|
|
assert.equal((row as any).error_summary, "upstream unavailable");
|
|
|
|
const artifactPath = path.join(TEST_DATA_DIR, "call_logs", (row as any).artifact_relpath);
|
|
const artifact = JSON.parse(fs.readFileSync(artifactPath, "utf8"));
|
|
assert.equal(artifact.requestBody.payload.length, requestBody.payload.length);
|
|
|
|
const detail = await callLogs.getCallLogById("artifact-only-large-payload");
|
|
assert.equal(detail?.requestBody?.payload.length, requestBody.payload.length);
|
|
|
|
const exported = await callLogs.exportCallLogsSince("2026-03-31T00:00:00.000Z");
|
|
assert.equal(exported.length, 1);
|
|
assert.equal((exported[0] as any).requestBody.payload.length, requestBody.payload.length);
|
|
});
|
|
|
|
test("saveCallLog truncates oversized call log artifacts for storage", async () => {
|
|
const hugeChunk = "x".repeat(600 * 1024);
|
|
|
|
await callLogs.saveCallLog({
|
|
id: "truncated-artifact",
|
|
timestamp: "2026-03-31T10:05:00.000Z",
|
|
method: "POST",
|
|
path: "/v1/chat/completions",
|
|
status: 200,
|
|
model: "openai/gpt-4.1",
|
|
provider: "openai",
|
|
requestBody: { payload: "request" },
|
|
responseBody: { output: "response" },
|
|
pipelinePayloads: {
|
|
streamChunks: {
|
|
provider: [hugeChunk],
|
|
openai: [hugeChunk],
|
|
client: [hugeChunk],
|
|
},
|
|
},
|
|
});
|
|
|
|
const db = core.getDbInstance();
|
|
const row = db
|
|
.prepare(
|
|
`
|
|
SELECT artifact_relpath, artifact_size_bytes, detail_state
|
|
FROM call_logs WHERE id = ?
|
|
`
|
|
)
|
|
.get("truncated-artifact");
|
|
assert.equal((row as any).detail_state, "ready");
|
|
assert.ok((row as any).artifact_size_bytes <= 512 * 1024);
|
|
|
|
const artifactPath = path.join(TEST_DATA_DIR, "call_logs", (row as any).artifact_relpath);
|
|
const artifact = JSON.parse(fs.readFileSync(artifactPath, "utf8"));
|
|
assert.deepEqual(artifact.requestBody, { payload: "request" });
|
|
assert.deepEqual(artifact.responseBody, { output: "response" });
|
|
assert.equal(artifact.error, null);
|
|
assert.deepEqual(artifact.pipeline.streamChunks, {
|
|
provider: ["[stream chunks omitted: call log artifact size limit exceeded]"],
|
|
openai: ["[stream chunks omitted: call log artifact size limit exceeded]"],
|
|
client: ["[stream chunks omitted: call log artifact size limit exceeded]"],
|
|
});
|
|
});
|
|
|
|
test("saveCallLog omits oversized non-stream pipeline payloads to enforce artifact cap", async () => {
|
|
const hugePayload = "x".repeat(600 * 1024);
|
|
|
|
await callLogs.saveCallLog({
|
|
id: "truncated-pipeline-artifact",
|
|
timestamp: "2026-03-31T10:06:00.000Z",
|
|
method: "POST",
|
|
path: "/v1/chat/completions",
|
|
status: 200,
|
|
model: "openai/gpt-4.1",
|
|
provider: "openai",
|
|
requestBody: { payload: "request" },
|
|
responseBody: { output: "response" },
|
|
pipelinePayloads: {
|
|
providerRequest: { body: hugePayload },
|
|
providerResponse: { body: hugePayload },
|
|
},
|
|
});
|
|
|
|
const db = core.getDbInstance();
|
|
const row = db
|
|
.prepare(
|
|
`
|
|
SELECT artifact_relpath, artifact_size_bytes, detail_state
|
|
FROM call_logs WHERE id = ?
|
|
`
|
|
)
|
|
.get("truncated-pipeline-artifact");
|
|
assert.equal((row as any).detail_state, "ready");
|
|
assert.ok((row as any).artifact_size_bytes <= 512 * 1024);
|
|
|
|
const artifactPath = path.join(TEST_DATA_DIR, "call_logs", (row as any).artifact_relpath);
|
|
const artifact = JSON.parse(fs.readFileSync(artifactPath, "utf8"));
|
|
assert.deepEqual(artifact.requestBody, { payload: "request" });
|
|
assert.deepEqual(artifact.responseBody, { output: "response" });
|
|
assert.deepEqual(artifact.pipeline, {
|
|
error: {
|
|
_omniroute_truncated: true,
|
|
reason: "call_log_artifact_size_limit_exceeded",
|
|
},
|
|
});
|
|
});
|
|
|
|
test("saveCallLog honors CALL_LOG_PIPELINE_MAX_SIZE_KB for pipeline artifacts", async () => {
|
|
process.env.CALL_LOG_PIPELINE_MAX_SIZE_KB = "8";
|
|
const hugePayload = "x".repeat(32 * 1024);
|
|
|
|
await callLogs.saveCallLog({
|
|
id: "configured-pipeline-artifact-cap",
|
|
timestamp: "2026-03-31T10:07:00.000Z",
|
|
method: "POST",
|
|
path: "/v1/chat/completions",
|
|
status: 200,
|
|
model: "openai/gpt-4.1",
|
|
provider: "openai",
|
|
requestBody: { payload: "request" },
|
|
responseBody: { output: "response" },
|
|
pipelinePayloads: {
|
|
providerRequest: { body: hugePayload },
|
|
providerResponse: { body: hugePayload },
|
|
},
|
|
});
|
|
|
|
const db = core.getDbInstance();
|
|
const row = db
|
|
.prepare(
|
|
`
|
|
SELECT artifact_relpath, artifact_size_bytes, detail_state
|
|
FROM call_logs WHERE id = ?
|
|
`
|
|
)
|
|
.get("configured-pipeline-artifact-cap");
|
|
assert.equal((row as any).detail_state, "ready");
|
|
assert.ok((row as any).artifact_size_bytes <= 8 * 1024);
|
|
|
|
const artifactPath = path.join(TEST_DATA_DIR, "call_logs", (row as any).artifact_relpath);
|
|
const artifact = JSON.parse(fs.readFileSync(artifactPath, "utf8"));
|
|
assert.deepEqual(artifact.pipeline, {
|
|
error: {
|
|
_omniroute_truncated: true,
|
|
reason: "call_log_artifact_size_limit_exceeded",
|
|
},
|
|
});
|
|
});
|
|
|
|
test("saveCallLog falls back to a compact sentinel when the configured cap is very small", async () => {
|
|
process.env.CALL_LOG_PIPELINE_MAX_SIZE_KB = "1";
|
|
const hugePayload = "x".repeat(32 * 1024);
|
|
|
|
await callLogs.saveCallLog({
|
|
id: "tiny-pipeline-artifact-cap",
|
|
timestamp: "2026-03-31T10:07:30.000Z",
|
|
method: "POST",
|
|
path: "/v1/chat/completions",
|
|
status: 200,
|
|
model: `openai/${"gpt".repeat(512)}`,
|
|
provider: "openai",
|
|
requestBody: { payload: "request" },
|
|
responseBody: { output: "response" },
|
|
pipelinePayloads: {
|
|
providerRequest: { body: hugePayload },
|
|
providerResponse: { body: hugePayload },
|
|
},
|
|
});
|
|
|
|
const db = core.getDbInstance();
|
|
const row = db
|
|
.prepare(
|
|
`
|
|
SELECT artifact_relpath, artifact_size_bytes, detail_state
|
|
FROM call_logs WHERE id = ?
|
|
`
|
|
)
|
|
.get("tiny-pipeline-artifact-cap");
|
|
assert.equal((row as any).detail_state, "ready");
|
|
assert.ok((row as any).artifact_size_bytes <= 1024);
|
|
|
|
const artifactPath = path.join(TEST_DATA_DIR, "call_logs", (row as any).artifact_relpath);
|
|
const artifact = JSON.parse(fs.readFileSync(artifactPath, "utf8"));
|
|
assert.deepEqual(artifact, {
|
|
schemaVersion: 5,
|
|
_omniroute_truncated: true,
|
|
reason: "call_log_artifact_size_limit_exceeded",
|
|
});
|
|
});
|
|
|
|
test("CALL_LOG_PIPELINE_MAX_SIZE_KB does not cap artifacts without pipeline details", async () => {
|
|
process.env.CALL_LOG_PIPELINE_MAX_SIZE_KB = "8";
|
|
const requestBody = { payload: "x".repeat(16 * 1024) };
|
|
|
|
await callLogs.saveCallLog({
|
|
id: "non-pipeline-artifact-ignores-pipeline-cap",
|
|
timestamp: "2026-03-31T10:08:00.000Z",
|
|
method: "POST",
|
|
path: "/v1/chat/completions",
|
|
status: 200,
|
|
model: "openai/gpt-4.1",
|
|
provider: "openai",
|
|
requestBody,
|
|
responseBody: { output: "response" },
|
|
});
|
|
|
|
const db = core.getDbInstance();
|
|
const row = db
|
|
.prepare(
|
|
`
|
|
SELECT artifact_relpath, artifact_size_bytes, detail_state
|
|
FROM call_logs WHERE id = ?
|
|
`
|
|
)
|
|
.get("non-pipeline-artifact-ignores-pipeline-cap");
|
|
assert.equal((row as any).detail_state, "ready");
|
|
assert.ok((row as any).artifact_size_bytes > 8 * 1024);
|
|
|
|
const artifactPath = path.join(TEST_DATA_DIR, "call_logs", (row as any).artifact_relpath);
|
|
const artifact = JSON.parse(fs.readFileSync(artifactPath, "utf8"));
|
|
assert.equal(artifact.requestBody.payload.length, requestBody.payload.length);
|
|
});
|
|
|
|
test("saveCallLog logs and returns when sqlite persistence throws unexpectedly", async () => {
|
|
const db = core.getDbInstance();
|
|
const originalPrepare = db.prepare;
|
|
const originalConsoleError = console.error;
|
|
const consoleCalls = [];
|
|
|
|
db.prepare = () => {
|
|
throw new Error("simulated sqlite prepare failure");
|
|
};
|
|
console.error = (...args) => {
|
|
consoleCalls.push(args.join(" "));
|
|
};
|
|
|
|
try {
|
|
await assert.doesNotReject(() =>
|
|
callLogs.saveCallLog({
|
|
id: "prepare-failure",
|
|
timestamp: "2026-03-30T12:40:00Z",
|
|
method: "POST",
|
|
path: "/v1/chat/completions",
|
|
status: 200,
|
|
model: "openai/gpt-4.1",
|
|
provider: "openai",
|
|
duration: 1,
|
|
})
|
|
);
|
|
} finally {
|
|
db.prepare = originalPrepare;
|
|
console.error = originalConsoleError;
|
|
}
|
|
|
|
assert.equal(consoleCalls.length, 1);
|
|
assert.match(consoleCalls[0], /Failed to save call log/);
|
|
assert.match(consoleCalls[0], /simulated sqlite prepare failure/);
|
|
});
|
|
|
|
test("getCallLogs and getCallLogById expose combo target identifiers", async () => {
|
|
await callLogs.saveCallLog({
|
|
id: "combo-target-log",
|
|
timestamp: "2026-03-31T08:15:00.000Z",
|
|
method: "POST",
|
|
path: "/v1/chat/completions",
|
|
status: 503,
|
|
model: "openai/gpt-4o-mini",
|
|
requestedModel: "router-fixed-accounts",
|
|
provider: "openai",
|
|
connectionId: "conn-fixed-2",
|
|
comboName: "router-fixed-accounts",
|
|
comboStepId: "step-openai-secondary",
|
|
comboExecutionKey: "router-fixed-accounts:1:step-openai-secondary",
|
|
error: "upstream unavailable",
|
|
});
|
|
|
|
const logs = await callLogs.getCallLogs({ search: "step-openai-secondary" });
|
|
assert.equal(logs.length, 1);
|
|
assert.equal(logs[0].comboStepId, "step-openai-secondary");
|
|
assert.equal(logs[0].comboExecutionKey, "router-fixed-accounts:1:step-openai-secondary");
|
|
|
|
const detail = await callLogs.getCallLogById("combo-target-log");
|
|
assert.equal(detail?.comboName, "router-fixed-accounts");
|
|
assert.equal(detail?.comboStepId, "step-openai-secondary");
|
|
assert.equal(detail?.comboExecutionKey, "router-fixed-accounts:1:step-openai-secondary");
|
|
});
|