test(skills): add debug chat load gate

This commit is contained in:
huanghuoguoguo
2026-06-25 11:48:59 +08:00
parent 8749a9b56f
commit d59b49ec55
15 changed files with 1975 additions and 0 deletions
+1
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@@ -48,6 +48,7 @@ bin/lbs env show # inspect resolved env defaults (redacted)
bin/lbs env doctor # diagnose local environment readiness
bin/lbs case list --ready
bin/lbs test plan <case-id>
bin/lbs suite plan langbot-debug-chat-load-gate
```
## Maintenance rule
+15
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@@ -117,6 +117,21 @@ bin/lbs suite plan langbot-user-path-performance-gate
bin/lbs suite run langbot-user-path-performance-gate --run-id langbot-user-path-local --include-manual-check
```
Controlled Debug Chat message-path load gate:
```bash
bin/lbs suite plan langbot-debug-chat-load-gate
bin/lbs test run langbot-fake-provider-debug-chat-load --run-id langbot-fake-load-local
bin/lbs test run langbot-space-debug-chat-concurrency-smoke --run-id langbot-space-smoke-local
```
Start with `langbot-fake-provider-debug-chat-load`. It launches a local
OpenAI-compatible fake provider, creates the matching provider/model/pipeline,
then sends concurrent WebSocket Debug Chat messages through the real backend.
Use `langbot-space-debug-chat-concurrency-smoke` only as a low-volume live
provider smoke; it includes Space/model/network latency and should be compared
against the fake-provider baseline before attributing failures to LangBot.
`manual_check` means the agent must confirm the declared preconditions for that
run window. When setup automation is declared, run output may stop early with
`env_issue`; fix that environment input before treating the product path as
+32
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@@ -209,6 +209,38 @@
"automation_debug_chat_max_error_rate": {
"type": "string"
},
"automation_debug_chat_load_requests": {
"type": "string"
},
"automation_debug_chat_load_concurrency": {
"type": "string"
},
"automation_debug_chat_load_timeout_ms": {
"type": "string"
},
"automation_debug_chat_load_response_p95_ms": {
"type": "string"
},
"automation_debug_chat_load_first_response_p95_ms": {
"type": "string"
},
"automation_debug_chat_load_max_error_rate": {
"type": "string"
},
"automation_debug_chat_load_expected_prefix": {
"type": "string"
},
"automation_debug_chat_load_prompt_template": {
"type": "string"
},
"automation_debug_chat_load_stream": {
"type": "string",
"enum": ["0", "1", "false", "true"]
},
"automation_debug_chat_load_reset": {
"type": "string",
"enum": ["0", "1", "false", "true"]
},
"automation_filesystem_checks_json": {
"type": "string"
},
@@ -0,0 +1,539 @@
#!/usr/bin/env node
import { spawn } from "node:child_process";
import { open, readFile, mkdir, writeFile } from "node:fs/promises";
import { dirname, resolve } from "node:path";
import { env } from "node:process";
import {
apiJson,
ensureEvidence,
evidencePaths,
loadEnvFiles,
redact,
resetAndAuthLocalUser,
writeResult,
} from "./lib/langbot-e2e.mjs";
const RUNNER_ID = "local-agent";
const DEFAULT_LOCAL_PASSWORD = "LangBotE2ELocalPass!2026";
const DEFAULT_PIPELINE_NAME = "Agent QA Fake Provider Debug Chat";
const DEFAULT_PROVIDER_NAME = "LangBot QA Fake OpenAI Provider";
const DEFAULT_MODEL_NAME = "gpt-4o-mini";
const DEFAULT_REQUESTER = "openai-chat-completions";
const caseId = "ensure-fake-provider-pipeline";
await loadEnvFiles();
const paths = evidencePaths(caseId);
await ensureEvidence(paths);
const writeEnv = process.argv.includes("--write-env");
const frontendUrl = env.LANGBOT_FRONTEND_URL || "";
const backendUrl = env.LANGBOT_BACKEND_URL || "";
const envLocalPath = resolve("skills/.env.local");
const repoRoot = resolve(env.LANGBOT_REPO || "..");
const fakeStateDir = resolve(env.LANGBOT_FAKE_PROVIDER_STATE_DIR || resolve(repoRoot, ".qa/fake-provider"));
const fakeStatePath = resolve(fakeStateDir, "state.json");
const fakeStdoutPath = resolve(fakeStateDir, "fake-provider.stdout.log");
const fakeStderrPath = resolve(fakeStateDir, "fake-provider.stderr.log");
const pipelineName = env.LANGBOT_FAKE_PROVIDER_PIPELINE_NAME || DEFAULT_PIPELINE_NAME;
const providerName = env.LANGBOT_FAKE_PROVIDER_NAME || DEFAULT_PROVIDER_NAME;
const requester = env.LANGBOT_FAKE_PROVIDER_REQUESTER || DEFAULT_REQUESTER;
const modelName = env.LANGBOT_FAKE_PROVIDER_MODEL_NAME || DEFAULT_MODEL_NAME;
const result = {
source: "automation",
case_id: caseId,
run_id: paths.runId,
status: "fail",
reason: "",
frontend_url: frontendUrl,
backend_url: backendUrl,
fake_provider: {
url: "",
base_url: "",
pid: null,
reused: false,
state_file: fakeStatePath,
stdout_log: fakeStdoutPath,
stderr_log: fakeStderrPath,
},
provider: {
uuid: "",
name: providerName,
requester,
created: false,
updated: false,
},
model: {
uuid: "",
name: modelName,
created: false,
updated: false,
test_status: "not_run",
test_reason: "",
},
pipeline_id: "",
pipeline_name: pipelineName,
pipeline_url: "",
created: false,
updated: false,
wrote_env: false,
evidence: {
console_log: paths.consoleLog,
network_log: paths.networkLog,
automation_result_json: paths.automationResultJson,
result_json: paths.resultJson,
},
evidence_collected: ["api_diagnostic", "network", "filesystem"],
};
try {
if (!backendUrl) {
result.status = "env_issue";
throw new Error("LANGBOT_BACKEND_URL is not configured.");
}
if (!frontendUrl) {
result.status = "env_issue";
throw new Error("LANGBOT_FRONTEND_URL is not configured.");
}
const fakeProvider = await ensureFakeProvider();
result.fake_provider = {
...result.fake_provider,
...fakeProvider,
};
const user = env.LANGBOT_E2E_LOGIN_USER || "";
const password = env.LANGBOT_E2E_LOGIN_PASSWORD || DEFAULT_LOCAL_PASSWORD;
if (!user) {
result.status = "env_issue";
throw new Error("LANGBOT_E2E_LOGIN_USER is required so this setup can create/update the fake provider pipeline.");
}
const auth = await resetAndAuthLocalUser({ backendUrl, user, password });
const wizard = await skipWizard({ backendUrl, token: auth.token });
if (wizard.status !== "pass") {
result.status = "fail";
throw new Error(wizard.reason || "Failed to mark the local QA wizard as skipped.");
}
const provider = await ensureProvider({
backendUrl,
token: auth.token,
name: providerName,
requester,
baseUrl: fakeProvider.base_url,
});
result.provider = provider;
const model = await ensureModel({
backendUrl,
token: auth.token,
providerUuid: provider.uuid,
name: modelName,
});
result.model = model;
const pipeline = await ensurePipeline({
backendUrl,
token: auth.token,
name: pipelineName,
modelUuid: model.uuid,
});
Object.assign(result, pipeline);
result.pipeline_url = `${frontendUrl.replace(/\/$/, "")}/home/pipelines?id=${encodeURIComponent(pipeline.pipeline_id)}`;
if (writeEnv) {
await upsertEnvLocal(envLocalPath, {
LANGBOT_E2E_LOGIN_USER: user,
LANGBOT_FAKE_PROVIDER_URL: fakeProvider.url,
LANGBOT_FAKE_PROVIDER_BASE_URL: fakeProvider.base_url,
LANGBOT_FAKE_PROVIDER_PID: fakeProvider.pid ? String(fakeProvider.pid) : "",
LANGBOT_FAKE_PROVIDER_PROVIDER_UUID: provider.uuid,
LANGBOT_FAKE_PROVIDER_MODEL_UUID: model.uuid,
LANGBOT_FAKE_PROVIDER_PIPELINE_URL: result.pipeline_url,
LANGBOT_FAKE_PROVIDER_PIPELINE_NAME: pipelineName,
});
result.wrote_env = true;
}
result.status = "pass";
result.reason = `Fake provider pipeline is configured with ${requester}/${modelName}.`;
} catch (error) {
result.status = result.status === "env_issue" ? "env_issue" : "fail";
result.reason = result.reason || safeReason(error.message);
} finally {
await writeResult(paths, result);
console.log(JSON.stringify(result, null, 2));
}
process.exit(result.status === "pass" ? 0 : result.status === "env_issue" ? 2 : 1);
async function ensureFakeProvider() {
const envUrl = normalizeProviderRootUrl(env.LANGBOT_FAKE_PROVIDER_URL || "");
if (envUrl && await fakeProviderHealthy(envUrl)) {
return {
url: envUrl,
base_url: `${envUrl}/v1`,
pid: null,
reused: true,
};
}
const state = await readState(fakeStatePath);
const stateUrl = normalizeProviderRootUrl(state.url || "");
if (stateUrl && await fakeProviderHealthy(stateUrl)) {
return {
url: stateUrl,
base_url: state.base_url || `${stateUrl}/v1`,
pid: Number.isInteger(state.pid) ? state.pid : null,
reused: true,
};
}
await mkdir(fakeStateDir, { recursive: true });
await writeFile(fakeStatePath, `${JSON.stringify({ status: "starting", started_at: new Date().toISOString() }, null, 2)}\n`, "utf8");
const stdout = await open(fakeStdoutPath, "a");
const stderr = await open(fakeStderrPath, "a");
const scriptPath = resolve("scripts/e2e/fake-openai-provider.mjs");
const host = env.LANGBOT_FAKE_PROVIDER_HOST || "127.0.0.1";
const port = env.LANGBOT_FAKE_PROVIDER_PORT || "0";
const child = spawn(process.execPath, [
scriptPath,
`--host=${host}`,
`--port=${port}`,
`--state-file=${fakeStatePath}`,
], {
cwd: resolve("."),
detached: true,
env: {
...env,
LANGBOT_FAKE_PROVIDER_MODEL_NAME: modelName,
},
stdio: ["ignore", stdout.fd, stderr.fd],
});
child.unref();
await stdout.close();
await stderr.close();
const started = await waitForFakeProviderState(fakeStatePath, child.pid, 10_000);
if (!started.url || !await fakeProviderHealthy(started.url)) {
throw new Error(`Fake provider did not become healthy. See ${fakeStderrPath}`);
}
return {
url: started.url,
base_url: started.base_url || `${started.url}/v1`,
pid: child.pid ?? started.pid ?? null,
reused: false,
};
}
async function fakeProviderHealthy(rootUrl) {
try {
const response = await fetch(`${rootUrl.replace(/\/$/, "")}/healthz`, {
signal: AbortSignal.timeout(2000),
});
if (!response.ok) return false;
const json = await response.json().catch(() => ({}));
return json.ok === true;
} catch {
return false;
}
}
async function waitForFakeProviderState(path, expectedPid, timeoutMs) {
const startedAt = Date.now();
let lastState = {};
while (Date.now() - startedAt < timeoutMs) {
const state = await readState(path);
if (state.url && (!expectedPid || state.pid === expectedPid)) return state;
lastState = state;
await sleep(150);
}
return lastState;
}
async function readState(path) {
try {
return JSON.parse(await readFile(path, "utf8"));
} catch {
return {};
}
}
function normalizeProviderRootUrl(value) {
const trimmed = String(value || "").trim().replace(/\/$/, "");
return trimmed.endsWith("/v1") ? trimmed.slice(0, -3) : trimmed;
}
async function skipWizard({ backendUrl, token }) {
const response = await apiJson(backendUrl, "/api/v1/system/wizard/completed", {
method: "POST",
token,
body: { status: "skipped" },
});
const ok = response.status < 400 && response.json.code === 0;
return {
status: ok ? "pass" : "fail",
http_status: response.status,
code: response.json.code ?? null,
reason: ok ? "Wizard marked skipped for local QA." : response.json.msg || "Wizard status update failed.",
};
}
async function ensureProvider({ backendUrl, token, name, requester, baseUrl }) {
const list = await apiJson(backendUrl, "/api/v1/provider/providers", { token });
if (isApiFailure(list)) {
throw new Error(list.json.msg || "Failed to list providers.");
}
const providers = list.json.data?.providers || [];
const existing = providers.find((provider) => (
provider.name === name
|| (provider.requester === requester && String(provider.base_url || "").replace(/\/$/, "") === baseUrl.replace(/\/$/, ""))
));
const body = {
name,
requester,
base_url: baseUrl,
api_keys: [env.LANGBOT_FAKE_PROVIDER_API_KEY || "langbot-fake-provider-key"],
};
if (existing?.uuid) {
const update = await apiJson(backendUrl, `/api/v1/provider/providers/${encodeURIComponent(existing.uuid)}`, {
method: "PUT",
token,
body,
});
if (isApiFailure(update)) {
throw new Error(update.json.msg || "Failed to update fake provider.");
}
return {
uuid: existing.uuid,
name,
requester,
created: false,
updated: true,
};
}
const create = await apiJson(backendUrl, "/api/v1/provider/providers", {
method: "POST",
token,
body,
});
const uuid = create.json.data?.uuid || "";
if (isApiFailure(create) || !uuid) {
throw new Error(create.json.msg || "Failed to create fake provider.");
}
return {
uuid,
name,
requester,
created: true,
updated: false,
};
}
async function ensureModel({ backendUrl, token, providerUuid, name }) {
const list = await apiJson(backendUrl, `/api/v1/provider/models/llm?provider_uuid=${encodeURIComponent(providerUuid)}`, { token });
if (isApiFailure(list)) {
throw new Error(list.json.msg || "Failed to list fake provider models.");
}
const models = list.json.data?.models || [];
const existing = models.find((model) => model.name === name);
const body = {
name,
provider_uuid: providerUuid,
abilities: [],
context_length: positiveInteger(env.LANGBOT_FAKE_PROVIDER_CONTEXT_LENGTH, 8192),
extra_args: {},
prefered_ranking: 0,
};
let modelUuid = existing?.uuid || "";
let created = false;
let updated = false;
if (modelUuid) {
const update = await apiJson(backendUrl, `/api/v1/provider/models/llm/${encodeURIComponent(modelUuid)}`, {
method: "PUT",
token,
body,
});
if (isApiFailure(update)) {
throw new Error(update.json.msg || "Failed to update fake provider model.");
}
updated = true;
} else {
const create = await apiJson(backendUrl, "/api/v1/provider/models/llm", {
method: "POST",
token,
body,
});
modelUuid = create.json.data?.uuid || "";
if (isApiFailure(create) || !modelUuid) {
throw new Error(create.json.msg || "Failed to create fake provider model.");
}
created = true;
}
const test = await apiJson(backendUrl, `/api/v1/provider/models/llm/${encodeURIComponent(modelUuid)}/test`, {
method: "POST",
token,
body: { extra_args: {} },
});
if (isApiFailure(test)) {
throw new Error(safeReason(test.json.msg || test.json.message || "Fake provider model test failed."));
}
return {
uuid: modelUuid,
name,
created,
updated,
test_status: "pass",
test_reason: "",
};
}
async function ensurePipeline({ backendUrl, token, name, modelUuid }) {
const list = await apiJson(backendUrl, "/api/v1/pipelines", { token });
if (isApiFailure(list)) {
throw new Error(list.json.msg || "Failed to list pipelines.");
}
const pipelines = list.json.data?.pipelines || [];
let pipeline = pipelines.find((item) => item.name === name) || null;
let created = false;
if (!pipeline) {
const create = await apiJson(backendUrl, "/api/v1/pipelines", {
method: "POST",
token,
body: {
name,
description: "Local QA pipeline for controlled fake-provider Debug Chat load tests.",
emoji: "QA",
},
});
const pipelineId = create.json.data?.uuid || "";
if (isApiFailure(create) || !pipelineId) {
throw new Error(create.json.msg || "Failed to create fake provider pipeline.");
}
created = true;
pipeline = { uuid: pipelineId };
}
const loaded = await apiJson(backendUrl, `/api/v1/pipelines/${encodeURIComponent(pipeline.uuid)}`, { token });
pipeline = loaded.json.data?.pipeline || null;
if (isApiFailure(loaded) || !pipeline?.uuid) {
throw new Error(loaded.json.msg || "Failed to load fake provider pipeline.");
}
const config = pipeline.config && typeof pipeline.config === "object" ? pipeline.config : {};
const ai = config.ai && typeof config.ai === "object" ? config.ai : {};
const existingLocalAgentConfig = ai["local-agent"] && typeof ai["local-agent"] === "object"
? ai["local-agent"]
: {};
const localAgentConfig = {
timeout: 60,
prompt: [{ role: "system", content: "You are a deterministic QA assistant. Reply exactly as instructed." }],
"remove-think": false,
"knowledge-bases": [],
"box-session-id-template": "{launcher_type}_{launcher_id}",
"retrieval-top-k": 5,
"rerank-model": "",
"rerank-top-k": 5,
"max-tool-iterations": 20,
"tool-execution-mode": "parallel",
"max-tool-result-chars": 20000,
"context-history-fetch-limit": 20,
"context-window-tokens": 8192,
"context-reserve-tokens": 1024,
"context-keep-recent-tokens": 2048,
"context-summary-tokens": 1024,
...existingLocalAgentConfig,
// Current backend truncation still reads this field directly.
"max-round": positiveInteger(existingLocalAgentConfig["max-round"], 10),
model: {
primary: modelUuid,
fallbacks: [],
},
};
const updatedConfig = {
...config,
ai: {
...ai,
runner: {
...(ai.runner && typeof ai.runner === "object" ? ai.runner : {}),
id: RUNNER_ID,
runner: RUNNER_ID,
"expire-time": 0,
},
"local-agent": localAgentConfig,
},
};
const update = await apiJson(backendUrl, `/api/v1/pipelines/${encodeURIComponent(pipeline.uuid)}`, {
method: "PUT",
token,
body: {
name,
description: "Local QA pipeline for controlled fake-provider Debug Chat load tests.",
emoji: "QA",
config: updatedConfig,
},
});
if (isApiFailure(update)) {
throw new Error(update.json.msg || "Failed to update fake provider pipeline.");
}
return {
pipeline_id: pipeline.uuid,
pipeline_name: name,
created,
updated: true,
};
}
function isApiFailure(response) {
return response.status >= 400 || (response.json.code !== undefined && response.json.code !== 0);
}
function positiveInteger(value, fallback) {
const parsed = Number(value);
return Number.isInteger(parsed) && parsed > 0 ? parsed : fallback;
}
function sleep(ms) {
return new Promise((resolve) => setTimeout(resolve, ms));
}
function safeReason(value) {
return redact(String(value || "")).slice(0, 1000);
}
async function upsertEnvLocal(path, updates) {
await mkdir(dirname(path), { recursive: true });
let text = "";
try {
text = await readFile(path, "utf8");
} catch {
text = "";
}
const lines = text.split(/\r?\n/);
const seen = new Set();
const next = lines.map((line) => {
const trimmed = line.trim();
const equals = trimmed.indexOf("=");
if (equals <= 0 || trimmed.startsWith("#")) return line;
const key = trimmed.slice(0, equals).trim();
if (!(key in updates)) return line;
seen.add(key);
return `${key}=${updates[key]}`;
});
for (const [key, value] of Object.entries(updates)) {
if (!seen.has(key)) next.push(`${key}=${value}`);
}
await writeFile(path, `${next.filter((line, index) => line !== "" || index < next.length - 1).join("\n")}\n`, "utf8");
}
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@@ -0,0 +1,332 @@
#!/usr/bin/env node
import { createServer } from "node:http";
import { mkdir, writeFile } from "node:fs/promises";
import { dirname, resolve } from "node:path";
import { env, exit } from "node:process";
const args = parseArgs(process.argv.slice(2));
const host = args.host || env.LANGBOT_FAKE_PROVIDER_HOST || "127.0.0.1";
const port = integer(args.port ?? env.LANGBOT_FAKE_PROVIDER_PORT, 0);
const stateFile = args["state-file"] || env.LANGBOT_FAKE_PROVIDER_STATE_FILE || "";
const modelName = env.LANGBOT_FAKE_PROVIDER_MODEL_NAME || "gpt-4o-mini";
const responseText = env.LANGBOT_FAKE_PROVIDER_RESPONSE_TEXT || "OK";
const firstTokenDelayMs = integer(env.LANGBOT_FAKE_PROVIDER_FIRST_TOKEN_DELAY_MS, 25);
const chunkDelayMs = integer(env.LANGBOT_FAKE_PROVIDER_CHUNK_DELAY_MS, 10);
const faultStatus = integer(env.LANGBOT_FAKE_PROVIDER_FAULT_STATUS, 500);
const failFirstN = integer(env.LANGBOT_FAKE_PROVIDER_FAIL_FIRST_N, 0);
const failEveryN = integer(env.LANGBOT_FAKE_PROVIDER_FAIL_EVERY_N, 0);
const failAfterFirstChunk = bool(env.LANGBOT_FAKE_PROVIDER_FAIL_AFTER_FIRST_CHUNK, false);
const requestLogLimit = integer(env.LANGBOT_FAKE_PROVIDER_REQUEST_LOG_LIMIT, 500);
let requestCount = 0;
const recentRequests = [];
const server = createServer(async (request, response) => {
const startedAt = Date.now();
const url = new URL(request.url || "/", `http://${request.headers.host || `${host}:${port}`}`);
try {
if (request.method === "GET" && url.pathname === "/healthz") {
sendJson(response, 200, {
ok: true,
model: modelName,
request_count: requestCount,
recent_request_count: recentRequests.length,
});
return;
}
if (request.method === "GET" && ["/models", "/v1/models"].includes(url.pathname)) {
sendJson(response, 200, {
object: "list",
data: [
{
id: modelName,
object: "model",
created: 1,
owned_by: "langbot-qa",
type: "llm",
},
],
});
return;
}
if (request.method === "POST" && ["/chat/completions", "/v1/chat/completions"].includes(url.pathname)) {
requestCount += 1;
const body = await readJson(request);
const requestId = `chatcmpl-langbot-fake-${requestCount}`;
const shouldFail = requestCount <= failFirstN || (failEveryN > 0 && requestCount % failEveryN === 0);
recordRequest({
id: requestId,
path: url.pathname,
stream: Boolean(body.stream),
model: body.model || "",
message_count: Array.isArray(body.messages) ? body.messages.length : 0,
should_fail: shouldFail,
});
if (shouldFail) {
await sleep(firstTokenDelayMs);
sendJson(response, faultStatus, {
error: {
message: `LangBot fake provider injected HTTP ${faultStatus}`,
type: "fake_provider_fault",
code: "fake_provider_fault",
},
});
return;
}
const replyText = responseTextForBody(body);
if (body.stream) {
await streamCompletion(response, {
requestId,
model: body.model || modelName,
content: replyText,
failAfterFirstChunk,
});
} else {
await sleep(firstTokenDelayMs + chunkDelayMs);
sendJson(response, 200, completionPayload({
requestId,
model: body.model || modelName,
content: replyText,
}));
}
return;
}
sendJson(response, 404, {
error: {
message: `No fake provider route for ${request.method} ${url.pathname}`,
type: "not_found",
},
});
} catch (error) {
sendJson(response, 500, {
error: {
message: error instanceof Error ? error.message : String(error),
type: "fake_provider_error",
},
});
} finally {
const durationMs = Date.now() - startedAt;
if (url.pathname !== "/healthz") {
console.log(JSON.stringify({
at: new Date().toISOString(),
method: request.method,
path: url.pathname,
duration_ms: durationMs,
}));
}
}
});
server.listen(port, host, async () => {
const address = server.address();
const selectedPort = typeof address === "object" && address ? address.port : port;
const url = `http://${host}:${selectedPort}`;
const state = {
status: "ready",
pid: process.pid,
url,
base_url: `${url}/v1`,
model: modelName,
started_at: new Date().toISOString(),
};
if (stateFile) {
const path = resolve(stateFile);
await mkdir(dirname(path), { recursive: true });
await writeFile(path, `${JSON.stringify(state, null, 2)}\n`, "utf8");
}
console.log(JSON.stringify(state));
});
server.on("error", (error) => {
console.error(JSON.stringify({
status: "error",
reason: error instanceof Error ? error.message : String(error),
}));
exit(1);
});
process.on("SIGTERM", () => {
server.close(() => exit(0));
});
function parseArgs(argv) {
const result = {};
for (const item of argv) {
const match = item.match(/^--([^=]+)(?:=(.*))?$/);
if (!match) continue;
result[match[1]] = match[2] ?? "1";
}
return result;
}
function integer(value, fallback) {
const parsed = Number.parseInt(String(value ?? ""), 10);
return Number.isFinite(parsed) && parsed >= 0 ? parsed : fallback;
}
function bool(value, fallback) {
if (value === undefined || value === "") return fallback;
if (/^(1|true|yes|on)$/i.test(String(value))) return true;
if (/^(0|false|no|off)$/i.test(String(value))) return false;
return fallback;
}
function sleep(ms) {
return new Promise((resolve) => setTimeout(resolve, Math.max(0, ms)));
}
async function readJson(request) {
let text = "";
for await (const chunk of request) text += chunk.toString();
if (!text) return {};
return JSON.parse(text);
}
function sendJson(response, status, payload) {
const text = `${JSON.stringify(payload)}\n`;
response.writeHead(status, {
"content-type": "application/json",
"content-length": Buffer.byteLength(text),
});
response.end(text);
}
function completionPayload({ requestId, model, content }) {
const completionTokens = tokenEstimate(content);
return {
id: requestId,
object: "chat.completion",
created: Math.floor(Date.now() / 1000),
model,
choices: [
{
index: 0,
message: {
role: "assistant",
content,
},
finish_reason: "stop",
},
],
usage: {
prompt_tokens: 8,
completion_tokens: completionTokens,
total_tokens: 8 + completionTokens,
},
};
}
async function streamCompletion(response, { requestId, model, content, failAfterFirstChunk: failMidStream }) {
response.writeHead(200, {
"content-type": "text/event-stream; charset=utf-8",
"cache-control": "no-cache",
"connection": "keep-alive",
});
await sleep(firstTokenDelayMs);
writeSse(response, {
id: requestId,
object: "chat.completion.chunk",
created: Math.floor(Date.now() / 1000),
model,
choices: [{ index: 0, delta: { role: "assistant" }, finish_reason: null }],
});
const chunks = splitContent(content);
for (let index = 0; index < chunks.length; index += 1) {
await sleep(chunkDelayMs);
writeSse(response, {
id: requestId,
object: "chat.completion.chunk",
created: Math.floor(Date.now() / 1000),
model,
choices: [{ index: 0, delta: { content: chunks[index] }, finish_reason: null }],
});
if (failMidStream && index === 0) {
response.destroy(new Error("LangBot fake provider injected mid-stream disconnect"));
return;
}
}
await sleep(chunkDelayMs);
const completionTokens = tokenEstimate(content);
writeSse(response, {
id: requestId,
object: "chat.completion.chunk",
created: Math.floor(Date.now() / 1000),
model,
choices: [{ index: 0, delta: {}, finish_reason: "stop" }],
usage: {
prompt_tokens: 8,
completion_tokens: completionTokens,
total_tokens: 8 + completionTokens,
},
});
response.write("data: [DONE]\n\n");
response.end();
}
function writeSse(response, payload) {
response.write(`data: ${JSON.stringify(payload)}\n\n`);
}
function splitContent(content) {
const text = String(content);
const requested = integer(env.LANGBOT_FAKE_PROVIDER_CHUNK_COUNT, 0);
if (requested <= 1 || text.length <= 1) return [text];
const chunkSize = Math.max(1, Math.ceil(text.length / requested));
const chunks = [];
for (let index = 0; index < text.length; index += chunkSize) {
chunks.push(text.slice(index, index + chunkSize));
}
return chunks;
}
function tokenEstimate(content) {
return Math.max(1, Math.ceil(String(content || "").length / 4));
}
function responseTextForBody(body) {
if (/^(0|false|no|off)$/i.test(env.LANGBOT_FAKE_PROVIDER_DYNAMIC_RESPONSE || "")) {
return responseText;
}
const messages = Array.isArray(body.messages) ? body.messages : [];
const lastUser = [...messages].reverse().find((message) => message?.role === "user");
const text = flattenContent(lastUser?.content || "");
const quoted = text.match(/["'“”](.{1,80}?)["'“”]/);
if (quoted?.[1]) return quoted[1].trim();
const exact = text.match(/(?:reply|回复|输出|return)\s+(?:exactly\s+)?([A-Za-z0-9_.:@-]{1,80})/i);
if (exact?.[1]) return exact[1].trim().replace(/[。.!?]+$/, "");
const only = text.match(/只回复\s*([A-Za-z0-9_.:@-]{1,80})/);
if (only?.[1]) return only[1].trim().replace(/[。.!?]+$/, "");
return responseText;
}
function flattenContent(content) {
if (typeof content === "string") return content;
if (Array.isArray(content)) {
return content
.map((item) => {
if (typeof item === "string") return item;
if (item && typeof item === "object") return item.text || "";
return "";
})
.join("\n");
}
return "";
}
function recordRequest(entry) {
recentRequests.push({
...entry,
at: new Date().toISOString(),
});
while (recentRequests.length > requestLogLimit) recentRequests.shift();
}
+103
View File
@@ -151,11 +151,13 @@
"agent-runner-release-preflight",
"agent-runner-runtime-chaos",
"dify-agent-debug-chat",
"langbot-fake-provider-debug-chat-load",
"langbot-fault-taxonomy-contract",
"langbot-live-backend-latency",
"langbot-live-backend-log-health",
"langbot-live-control-plane-api",
"langbot-overhead-accounting-contract",
"langbot-space-debug-chat-concurrency-smoke",
"langrag-kb-retrieve",
"langrag-parser-golden-e2e",
"langrag-sentinel-kb-discover",
@@ -493,6 +495,43 @@
"backend_log"
]
},
{
"id": "langbot-fake-provider-debug-chat-load",
"title": "LangBot Debug Chat controlled fake-provider load probe",
"mode": "probe",
"area": "performance",
"type": "performance",
"priority": "p1",
"risk": "medium",
"ci_eligible": false,
"tags": [
"performance",
"debug-chat",
"websocket",
"fake-provider",
"load",
"metrics"
],
"automation": "skills/langbot-testing/probes/langbot-debug-chat-concurrency.mjs",
"setup_automation": [
"node:scripts/e2e/ensure-fake-provider-pipeline.mjs --write-env"
],
"setup_provides_env": [
"LANGBOT_FAKE_PROVIDER_URL",
"LANGBOT_FAKE_PROVIDER_BASE_URL",
"LANGBOT_FAKE_PROVIDER_PID",
"LANGBOT_FAKE_PROVIDER_PROVIDER_UUID",
"LANGBOT_FAKE_PROVIDER_MODEL_UUID",
"LANGBOT_FAKE_PROVIDER_PIPELINE_URL",
"LANGBOT_FAKE_PROVIDER_PIPELINE_NAME"
],
"evidence_required": [
"metrics",
"network",
"api_diagnostic",
"filesystem"
]
},
{
"id": "langbot-fault-taxonomy-contract",
"title": "LangBot fault taxonomy and cleanup contract",
@@ -615,6 +654,43 @@
"filesystem"
]
},
{
"id": "langbot-space-debug-chat-concurrency-smoke",
"title": "LangBot Debug Chat real Space-provider concurrency smoke",
"mode": "probe",
"area": "performance",
"type": "performance",
"priority": "p1",
"risk": "high",
"ci_eligible": false,
"tags": [
"performance",
"debug-chat",
"websocket",
"space",
"live-provider",
"smoke",
"metrics"
],
"automation": "skills/langbot-testing/probes/langbot-debug-chat-concurrency.mjs",
"setup_automation": [
"node:scripts/e2e/ensure-local-agent-pipeline.mjs --write-env"
],
"setup_provides_env": [
"LANGBOT_PIPELINE_URL",
"LANGBOT_PIPELINE_NAME",
"LANGBOT_LOCAL_AGENT_PIPELINE_URL",
"LANGBOT_LOCAL_AGENT_PIPELINE_NAME",
"LANGBOT_LOCAL_AGENT_MODEL_UUID",
"LANGBOT_E2E_MODEL_UUID"
],
"evidence_required": [
"metrics",
"network",
"api_diagnostic",
"filesystem"
]
},
{
"id": "langrag-kb-retrieve",
"title": "LangRAG knowledge base ingests and retrieves a sentinel document",
@@ -1220,6 +1296,7 @@
"suites": [
"agent-runner-release-gate",
"core-smoke",
"langbot-debug-chat-load-gate",
"langbot-live-backend-gate",
"langbot-performance-contract-gate",
"langbot-performance-reliability-gate",
@@ -1286,6 +1363,23 @@
"local-agent-basic-debug-chat"
]
},
{
"id": "langbot-debug-chat-load-gate",
"title": "LangBot Debug Chat load gate",
"description": "Message-path load checks for Pipeline Debug Chat: controlled fake-provider baseline plus optional real Space-provider smoke.",
"type": "performance",
"priority": "p1",
"tags": [
"performance",
"debug-chat",
"websocket",
"load"
],
"cases": [
"langbot-fake-provider-debug-chat-load",
"langbot-space-debug-chat-concurrency-smoke"
]
},
{
"id": "langbot-live-backend-gate",
"title": "LangBot live backend reliability gate",
@@ -1501,6 +1595,7 @@
"sandbox-native-tools-unavailable",
"socks-proxy-without-socksio",
"survey-widget-blocks-debug-chat",
"telemetry-proxy-noise",
"tool-name-collision-between-mcp-and-plugin",
"uv-run-resyncs-local-sdk"
],
@@ -1685,6 +1780,14 @@
"mcp-stdio-tool-call"
]
},
{
"id": "telemetry-proxy-noise",
"title": "Telemetry posting fails through the proxy while the target flow succeeds",
"category": "env_issue",
"related_cases": [
"langbot-space-debug-chat-concurrency-smoke"
]
},
{
"id": "tool-name-collision-between-mcp-and-plugin",
"title": "MCP and plugin expose the same tool name",
+14
View File
@@ -26,6 +26,20 @@ LANGBOT_NO_PROXY=localhost,127.0.0.1,::1
LANGBOT_PIPELINE_URL=
LANGBOT_PIPELINE_NAME=
# Optional fake OpenAI-compatible provider controls for Debug Chat load tests.
# Leave URL empty to let setup automation start a local provider and write the
# selected URL to skills/.env.local.
LANGBOT_FAKE_PROVIDER_URL=
LANGBOT_FAKE_PROVIDER_HOST=127.0.0.1
LANGBOT_FAKE_PROVIDER_PORT=
LANGBOT_FAKE_PROVIDER_MODEL_NAME=gpt-4o-mini
LANGBOT_FAKE_PROVIDER_RESPONSE_TEXT=OK
LANGBOT_FAKE_PROVIDER_FIRST_TOKEN_DELAY_MS=25
LANGBOT_FAKE_PROVIDER_CHUNK_DELAY_MS=10
LANGBOT_FAKE_PROVIDER_FAIL_FIRST_N=0
LANGBOT_FAKE_PROVIDER_FAIL_EVERY_N=0
LANGBOT_FAKE_PROVIDER_FAULT_STATUS=500
# Optional case-specific runner targets. Prefer these for runner-specific cases
# so the automation cannot silently test the wrong runner.
LANGBOT_LOCAL_AGENT_PIPELINE_URL=
@@ -0,0 +1,81 @@
id: langbot-fake-provider-debug-chat-load
title: "LangBot Debug Chat controlled fake-provider load probe"
mode: probe
area: performance
type: performance
priority: p1
risk: medium
ci_eligible: false
tags:
- performance
- debug-chat
- websocket
- fake-provider
- load
- metrics
skills:
- langbot-env-setup
- langbot-testing
env:
- LANGBOT_BACKEND_URL
- LANGBOT_FRONTEND_URL
- LANGBOT_E2E_LOGIN_USER
automation: skills/langbot-testing/probes/langbot-debug-chat-concurrency.mjs
automation_env:
- LANGBOT_BACKEND_URL
- LANGBOT_E2E_LOGIN_USER
- LANGBOT_FAKE_PROVIDER_PIPELINE_URL
- LANGBOT_FAKE_PROVIDER_PIPELINE_NAME
automation_pipeline_url_env: LANGBOT_FAKE_PROVIDER_PIPELINE_URL
automation_pipeline_name_env: LANGBOT_FAKE_PROVIDER_PIPELINE_NAME
automation_debug_chat_load_requests: "12"
automation_debug_chat_load_concurrency: "4"
automation_debug_chat_load_timeout_ms: "30000"
automation_debug_chat_load_response_p95_ms: "5000"
automation_debug_chat_load_first_response_p95_ms: "3000"
automation_debug_chat_load_max_error_rate: "0"
automation_debug_chat_load_expected_prefix: "FAKEQA"
automation_debug_chat_load_prompt_template: '请只回复 "{expected}",不要解释,不要添加其他字符。'
automation_debug_chat_load_stream: "true"
automation_debug_chat_load_reset: "true"
metrics_thresholds_json: '{"response_p95_ms":{"max":5000},"first_response_p95_ms":{"max":3000},"error_rate":{"max":0}}'
load_profile_json: '{"requests":12,"concurrency":4,"path":"Pipeline Debug Chat WebSocket","provider":"controlled fake OpenAI-compatible provider","metric":"send-to-final-assistant-response"}'
setup_automation:
- "node:scripts/e2e/ensure-fake-provider-pipeline.mjs --write-env"
setup_provides_env:
- LANGBOT_FAKE_PROVIDER_URL
- LANGBOT_FAKE_PROVIDER_BASE_URL
- LANGBOT_FAKE_PROVIDER_PID
- LANGBOT_FAKE_PROVIDER_PROVIDER_UUID
- LANGBOT_FAKE_PROVIDER_MODEL_UUID
- LANGBOT_FAKE_PROVIDER_PIPELINE_URL
- LANGBOT_FAKE_PROVIDER_PIPELINE_NAME
steps:
- "Start or reuse the local fake OpenAI-compatible provider."
- "Create or update the LangBot provider, model, and local-agent pipeline that points at the fake provider."
- "Reset the target Debug Chat session."
- "Open concurrent WebSocket Debug Chat connections and send unique deterministic prompts through the real backend pipeline."
checks:
- "automation-result.json status is pass when every request receives its own expected assistant response."
- "metrics_summary includes request count, concurrency, p50/p95 response latency, first response latency, throughput, and error rate."
- "thresholds_summary shows response_p95_ms, first_response_p95_ms, and error_rate pass."
evidence_required:
- metrics
- network
- api_diagnostic
- filesystem
diagnostics:
- "This probe removes external model latency from the measurement; it still exercises the live LangBot backend, provider requester, local-agent runner, pipeline, and Debug Chat WebSocket adapter."
- "Use this as the repeatable message-path baseline before comparing against Space or another real provider."
success_patterns:
- "Debug Chat WebSocket concurrency probe passed"
- "Streaming completed"
failure_patterns:
- "WebSocket connection error"
- "Timed out after"
- "Final assistant response did not include"
- "All models failed during streaming setup"
troubleshooting:
- backend-not-listening
- debug-chat-history-contaminates-automation
- local-agent-model-route-unavailable
@@ -0,0 +1,84 @@
id: langbot-space-debug-chat-concurrency-smoke
title: "LangBot Debug Chat real Space-provider concurrency smoke"
mode: probe
area: performance
type: performance
priority: p1
risk: high
ci_eligible: false
tags:
- performance
- debug-chat
- websocket
- space
- live-provider
- smoke
- metrics
skills:
- langbot-env-setup
- langbot-testing
env:
- LANGBOT_BACKEND_URL
- LANGBOT_FRONTEND_URL
- LANGBOT_E2E_LOGIN_USER
automation: skills/langbot-testing/probes/langbot-debug-chat-concurrency.mjs
automation_env:
- LANGBOT_BACKEND_URL
- LANGBOT_E2E_LOGIN_USER
- LANGBOT_LOCAL_AGENT_PIPELINE_URL
- LANGBOT_LOCAL_AGENT_PIPELINE_NAME
automation_pipeline_url_env: LANGBOT_LOCAL_AGENT_PIPELINE_URL
automation_pipeline_name_env: LANGBOT_LOCAL_AGENT_PIPELINE_NAME
automation_debug_chat_load_requests: "3"
automation_debug_chat_load_concurrency: "2"
automation_debug_chat_load_timeout_ms: "120000"
automation_debug_chat_load_response_p95_ms: "120000"
automation_debug_chat_load_max_error_rate: "0"
automation_debug_chat_load_expected_prefix: "SPACEQA"
automation_debug_chat_load_prompt_template: '请只回复 "{expected}",不要解释,不要添加其他字符。'
automation_debug_chat_load_stream: "true"
automation_debug_chat_load_reset: "true"
metrics_thresholds_json: '{"response_p95_ms":{"max":120000},"error_rate":{"max":0}}'
load_profile_json: '{"requests":3,"concurrency":2,"path":"Pipeline Debug Chat WebSocket","provider":"LangBot Space model route","metric":"send-to-final-assistant-response","classification":"smoke-not-benchmark"}'
setup_automation:
- "node:scripts/e2e/ensure-local-agent-pipeline.mjs --write-env"
setup_provides_env:
- LANGBOT_PIPELINE_URL
- LANGBOT_PIPELINE_NAME
- LANGBOT_LOCAL_AGENT_PIPELINE_URL
- LANGBOT_LOCAL_AGENT_PIPELINE_NAME
- LANGBOT_LOCAL_AGENT_MODEL_UUID
- LANGBOT_E2E_MODEL_UUID
preconditions:
- "The selected local LangBot instance is safe for a low-volume real Space model smoke run."
- "Treat Space/provider/network failures as environment or dependency findings until fake-provider baseline evidence separates LangBot overhead."
steps:
- "Prepare a local-agent pipeline with a tested Space model and fallback models."
- "Reset the target Debug Chat session."
- "Open a small number of concurrent WebSocket Debug Chat connections and send unique deterministic prompts through the live Space provider path."
checks:
- "automation-result.json status is pass when every request receives its own expected assistant response."
- "metrics_summary includes request count, concurrency, p95 response latency, throughput, and error rate."
- "The report classifies the result as a live-provider smoke, not a stable LangBot overhead benchmark."
evidence_required:
- metrics
- network
- api_diagnostic
- filesystem
diagnostics:
- "This probe measures real user-path latency through Space and includes provider latency, model behavior, and network effects."
- "Compare with langbot-fake-provider-debug-chat-load before attributing slow or failed runs to LangBot itself."
success_patterns:
- "Debug Chat WebSocket concurrency probe passed"
- "Streaming completed"
failure_patterns:
- "invalid api key"
- "WebSocket connection error"
- "Timed out after"
- "Final assistant response did not include"
- "All models failed during streaming setup"
troubleshooting:
- local-agent-model-route-unavailable
- marketplace-network-flaky
- proxy-env-mismatch
- telemetry-proxy-noise
@@ -0,0 +1,664 @@
#!/usr/bin/env node
import crypto from "node:crypto";
import net from "node:net";
import tls from "node:tls";
import { mkdir, writeFile } from "node:fs/promises";
import { join, resolve } from "node:path";
import { env, exit } from "node:process";
import {
apiJson,
appendLine,
ensureEvidence,
evidencePaths,
loadEnvFiles,
localIsoWithOffset,
redact,
resetAndAuthLocalUser,
writeResult,
} from "../../../scripts/e2e/lib/langbot-e2e.mjs";
const DEFAULT_LOCAL_PASSWORD = "LangBotE2ELocalPass!2026";
await loadEnvFiles();
const caseId = env.LBS_CASE_ID || "langbot-debug-chat-concurrency";
const paths = evidencePaths(caseId);
await ensureEvidence(paths);
const startedAt = new Date();
const metricsPath = resolve(paths.evidenceDir, "metrics.json");
const samplesPath = resolve(paths.evidenceDir, "samples.json");
const resetDiagnosticPath = resolve(paths.evidenceDir, "debug-chat-reset-diagnostic.json");
const backendUrl = env.LANGBOT_BACKEND_URL || "";
const pipelineUrl = env.LANGBOT_E2E_PIPELINE_URL || env.LANGBOT_PIPELINE_URL || "";
const pipelineName = env.LANGBOT_E2E_PIPELINE_NAME || env.LANGBOT_PIPELINE_NAME || "";
const sessionType = env.LANGBOT_DEBUG_CHAT_LOAD_SESSION_TYPE || env.LANGBOT_E2E_DEBUG_CHAT_SESSION_TYPE || "person";
const totalRequests = positiveInteger(env.LANGBOT_DEBUG_CHAT_LOAD_REQUESTS, defaultRequests(caseId));
const concurrency = Math.min(totalRequests, positiveInteger(env.LANGBOT_DEBUG_CHAT_LOAD_CONCURRENCY, defaultConcurrency(caseId)));
const timeoutMs = positiveInteger(env.LANGBOT_DEBUG_CHAT_LOAD_TIMEOUT_MS, defaultTimeout(caseId));
const expectedPrefix = env.LANGBOT_DEBUG_CHAT_LOAD_EXPECTED_PREFIX || "LBQA";
const promptTemplate = env.LANGBOT_DEBUG_CHAT_LOAD_PROMPT_TEMPLATE
|| "请只回复 \"{expected}\",不要解释,不要添加其他字符。";
const stream = bool(env.LANGBOT_DEBUG_CHAT_LOAD_STREAM, true);
const resetBeforeRun = bool(env.LANGBOT_DEBUG_CHAT_LOAD_RESET, true);
const responseP95BudgetMs = positiveNumber(env.LANGBOT_DEBUG_CHAT_LOAD_RESPONSE_P95_MS, defaultP95Budget(caseId));
const firstResponseP95BudgetMs = positiveNumber(env.LANGBOT_DEBUG_CHAT_LOAD_FIRST_RESPONSE_P95_MS, 0);
const maxErrorRate = positiveNumber(env.LANGBOT_DEBUG_CHAT_LOAD_MAX_ERROR_RATE, 0);
const result = {
source: "automation",
case_id: caseId,
run_id: paths.runId,
status: "fail",
reason: "",
started_at: startedAt.toISOString(),
started_at_local: localIsoWithOffset(startedAt),
finished_at: "",
finished_at_local: "",
duration_ms: 0,
backend_url: backendUrl,
pipeline_url: pipelineUrl,
pipeline_name: pipelineName,
pipeline_id: "",
session_type: sessionType,
load_profile: {
requests: totalRequests,
concurrency,
timeout_ms: timeoutMs,
stream,
reset_before_run: resetBeforeRun,
},
evidence: {
network_log: paths.networkLog,
metrics_json: metricsPath,
samples_json: samplesPath,
debug_chat_reset_diagnostic_json: resetDiagnosticPath,
automation_result_json: paths.automationResultJson,
result_json: paths.resultJson,
},
evidence_collected: ["metrics", "network", "api_diagnostic", "filesystem"],
};
try {
if (!backendUrl) {
result.status = "env_issue";
throw new Error("LANGBOT_BACKEND_URL is not configured.");
}
if (!["person", "group"].includes(sessionType)) {
throw new Error(`LANGBOT_DEBUG_CHAT_LOAD_SESSION_TYPE must be person or group, got ${sessionType}.`);
}
const backendReady = await backendReachable(backendUrl);
if (!backendReady) {
result.status = "env_issue";
throw new Error(`Backend did not respond at ${backendUrl}.`);
}
const user = env.LANGBOT_E2E_LOGIN_USER || "";
const password = env.LANGBOT_E2E_LOGIN_PASSWORD || DEFAULT_LOCAL_PASSWORD;
if (!user) {
result.status = "env_issue";
throw new Error("LANGBOT_E2E_LOGIN_USER is required so this probe can resolve/reset the Debug Chat session.");
}
const auth = await resetAndAuthLocalUser({ backendUrl, user, password });
const pipeline = await resolvePipeline({ backendUrl, token: auth.token, pipelineUrl, pipelineName });
result.pipeline_id = pipeline.id;
result.pipeline_name = pipeline.name || pipelineName;
if (!result.pipeline_url && env.LANGBOT_FRONTEND_URL) {
result.pipeline_url = `${env.LANGBOT_FRONTEND_URL.replace(/\/$/, "")}/home/pipelines?id=${encodeURIComponent(pipeline.id)}`;
}
if (resetBeforeRun) {
const reset = await apiJson(backendUrl, `/api/v1/pipelines/${encodeURIComponent(pipeline.id)}/ws/reset/${encodeURIComponent(sessionType)}`, {
method: "POST",
token: auth.token,
});
const resetDiagnostic = {
status: isApiFailure(reset) ? "fail" : "ready",
http_status: reset.status,
code: reset.json.code ?? null,
reason: isApiFailure(reset) ? reset.json.msg || "Debug Chat reset failed." : "Debug Chat session reset.",
};
await writeFile(resetDiagnosticPath, `${JSON.stringify(resetDiagnostic, null, 2)}\n`, "utf8");
if (resetDiagnostic.status === "fail") {
throw new Error(resetDiagnostic.reason);
}
}
const wsUrl = websocketUrl(backendUrl, pipeline.id, sessionType);
const loadStartedAt = performance.now();
const samples = await runLoad({
wsUrl,
totalRequests,
concurrency,
timeoutMs,
promptTemplate,
expectedPrefix,
stream,
});
const loadDurationMs = performance.now() - loadStartedAt;
const metrics = buildMetrics({
samples,
totalRequests,
concurrency,
timeoutMs,
loadDurationMs,
backendUrl,
pipelineId: pipeline.id,
sessionType,
});
const thresholds = buildThresholds(metrics);
const passed = Object.values(thresholds).every((item) => item.pass);
result.status = passed ? "pass" : "fail";
result.reason = passed
? "Debug Chat WebSocket concurrency probe passed all thresholds."
: "Debug Chat WebSocket concurrency probe breached latency or error-rate thresholds.";
result.metrics_summary = {
requests: metrics.total_requests,
concurrency: metrics.concurrency,
ok_count: metrics.ok_count,
error_count: metrics.error_count,
timeout_count: metrics.timeout_count,
error_rate: metrics.error_rate,
response_p50_ms: metrics.response_duration_ms.p50,
response_p95_ms: metrics.response_duration_ms.p95,
first_response_p95_ms: metrics.first_response_ms.p95,
throughput_rps: metrics.throughput_rps,
status_counts: metrics.status_counts,
};
result.thresholds_summary = thresholds;
result.artifacts = {
metrics_json: metricsPath,
samples_json: samplesPath,
network_log: paths.networkLog,
automation_result_json: paths.automationResultJson,
result_json: paths.resultJson,
};
await writeFile(metricsPath, `${JSON.stringify({ ...metrics, thresholds }, null, 2)}\n`, "utf8");
await writeFile(samplesPath, `${JSON.stringify(samples, null, 2)}\n`, "utf8");
} catch (error) {
if (!["env_issue", "blocked"].includes(result.status)) {
result.status = looksLikeEnvIssue(error) ? "env_issue" : "fail";
}
result.reason = result.reason || safeReason(error.message);
} finally {
const finishedAt = new Date();
result.finished_at = finishedAt.toISOString();
result.finished_at_local = localIsoWithOffset(finishedAt);
result.duration_ms = finishedAt.getTime() - startedAt.getTime();
await mkdir(paths.evidenceDir, { recursive: true });
await writeResult(paths, result);
console.log(JSON.stringify(result, null, 2));
}
exit(result.status === "pass" ? 0 : result.status === "env_issue" || result.status === "blocked" ? 2 : 1);
function defaultRequests(id) {
return id.includes("space") ? 3 : 12;
}
function defaultConcurrency(id) {
return id.includes("space") ? 1 : 4;
}
function defaultTimeout(id) {
return id.includes("space") ? 120_000 : 30_000;
}
function defaultP95Budget(id) {
return id.includes("space") ? 120_000 : 5_000;
}
function positiveInteger(value, fallback) {
const parsed = Number.parseInt(String(value || ""), 10);
return Number.isInteger(parsed) && parsed > 0 ? parsed : fallback;
}
function positiveNumber(value, fallback) {
const parsed = Number(value || "");
return Number.isFinite(parsed) && parsed >= 0 ? parsed : fallback;
}
function bool(value, fallback) {
if (value === undefined || value === "") return fallback;
if (/^(1|true|yes|on)$/i.test(String(value))) return true;
if (/^(0|false|no|off)$/i.test(String(value))) return false;
return fallback;
}
async function backendReachable(baseUrl) {
try {
const response = await fetch(`${baseUrl.replace(/\/$/, "")}/healthz`, {
signal: AbortSignal.timeout(3000),
});
return response.status < 500;
} catch {
return false;
}
}
function pipelineIdFromUrl(url) {
if (!url) return "";
try {
const parsed = new URL(url);
return parsed.searchParams.get("id") || "";
} catch {
return "";
}
}
async function resolvePipeline({ backendUrl, token, pipelineUrl, pipelineName }) {
const idFromUrl = pipelineIdFromUrl(pipelineUrl);
if (idFromUrl) {
const response = await apiJson(backendUrl, `/api/v1/pipelines/${encodeURIComponent(idFromUrl)}`, { token });
const pipeline = response.json.data?.pipeline;
if (isApiFailure(response) || !pipeline?.uuid) {
throw new Error(response.json.msg || `Could not load pipeline ${idFromUrl}.`);
}
return { id: pipeline.uuid, name: pipeline.name || "" };
}
if (!pipelineName) {
throw new Error("Set LANGBOT_E2E_PIPELINE_URL or LANGBOT_E2E_PIPELINE_NAME before running this probe.");
}
const response = await apiJson(backendUrl, "/api/v1/pipelines", { token });
if (isApiFailure(response)) {
throw new Error(response.json.msg || "Failed to list pipelines.");
}
const pipeline = (response.json.data?.pipelines || []).find((item) => item.name === pipelineName);
if (!pipeline?.uuid) {
throw new Error(`Could not find pipeline named ${pipelineName}.`);
}
return { id: pipeline.uuid, name: pipeline.name || pipelineName };
}
function isApiFailure(response) {
return response.status >= 400 || (response.json.code !== undefined && response.json.code !== 0);
}
function websocketUrl(baseUrl, pipelineId, sessionType) {
const parsed = new URL(baseUrl);
parsed.protocol = parsed.protocol === "https:" ? "wss:" : "ws:";
parsed.pathname = `/api/v1/pipelines/${encodeURIComponent(pipelineId)}/ws/connect`;
parsed.search = `?session_type=${encodeURIComponent(sessionType)}`;
return parsed.toString();
}
async function runLoad(options) {
const samples = [];
let nextIndex = 0;
const workers = Array.from({ length: options.concurrency }, async () => {
while (nextIndex < options.totalRequests) {
const index = nextIndex;
nextIndex += 1;
const sample = await runSingleRequest({ ...options, index });
samples.push(sample);
}
});
await Promise.all(workers);
return samples.sort((left, right) => left.index - right.index);
}
function expectedForIndex(prefix, index) {
return `${prefix}-${String(index + 1).padStart(4, "0")}`;
}
function promptForIndex(template, expected) {
return template.replaceAll("{expected}", expected);
}
function runSingleRequest({
wsUrl,
index,
timeoutMs,
promptTemplate,
expectedPrefix,
stream,
}) {
return new Promise((resolve) => {
const expected = expectedForIndex(expectedPrefix, index);
const prompt = promptForIndex(promptTemplate, expected);
const sample = {
index,
status: "running",
ok: false,
expected_text: expected,
prompt,
response_text: "",
connected_ms: null,
first_response_ms: null,
response_duration_ms: null,
event_count: 0,
foreign_response_count: 0,
last_foreign_response_text: "",
error: "",
close_code: null,
close_reason: "",
};
let closed = false;
let connectedAt = 0;
let sentAt = 0;
const startedAt = performance.now();
let client = null;
const timer = setTimeout(() => {
finish("timeout", `Timed out after ${timeoutMs} ms.`);
}, timeoutMs);
client = openRawWebSocket(wsUrl, {
onOpen() {
connectedAt = performance.now();
sample.connected_ms = rounded(connectedAt - startedAt);
},
onMessage(text) {
sample.event_count += 1;
let data;
try {
data = JSON.parse(String(text || ""));
} catch (error) {
finish("error", `Invalid WebSocket JSON: ${error.message}`);
return;
}
appendLine(paths.networkLog, JSON.stringify({
request_index: index,
type: data.type,
session_type: data.session_type || "",
role: data.data?.role || "",
is_final: data.data?.is_final ?? null,
content_preview: redact(String(data.data?.content || data.message || "").slice(0, 200)),
})).catch(() => {});
if (data.type === "connected") {
sentAt = performance.now();
client.send(JSON.stringify({
type: "message",
message: [{ type: "Plain", text: prompt }],
stream,
}));
return;
}
if (data.type === "error") {
finish("error", data.message || "WebSocket error message.");
return;
}
if (data.type !== "response" || data.data?.role !== "assistant") return;
const content = String(data.data.content || "");
if (content) sample.response_text = content;
if (data.data.is_final === true) {
const ok = sample.response_text.includes(expected);
if (ok) {
if (sample.first_response_ms === null && sentAt > 0) {
sample.first_response_ms = rounded(performance.now() - sentAt);
}
finish("pass", "");
} else {
sample.foreign_response_count += 1;
sample.last_foreign_response_text = sample.response_text;
}
}
},
onError(error) {
finish("connection_error", `WebSocket connection error: ${error.message}`);
},
onClose(event) {
sample.close_code = event.code;
sample.close_reason = event.reason || "";
if (!closed) finish("closed", `WebSocket closed before final assistant response: ${event.code}`);
},
});
function finish(status, reason) {
if (closed) return;
closed = true;
clearTimeout(timer);
sample.status = status;
sample.ok = status === "pass";
sample.error = status === "timeout" && sample.foreign_response_count > 0
? `${reason || ""} Saw ${sample.foreign_response_count} foreign assistant response(s); last=${sample.last_foreign_response_text}`
: reason || "";
if (sentAt > 0) sample.response_duration_ms = rounded(performance.now() - sentAt);
else sample.response_duration_ms = rounded(performance.now() - startedAt);
try {
client?.close();
} catch {
// Closing a failed socket should not hide the sample result.
}
resolve(sample);
}
});
}
function openRawWebSocket(wsUrl, handlers) {
const parsed = new URL(wsUrl);
const secure = parsed.protocol === "wss:";
const port = Number(parsed.port || (secure ? 443 : 80));
const host = parsed.hostname;
const path = `${parsed.pathname}${parsed.search}`;
const key = crypto.randomBytes(16).toString("base64");
const socket = secure
? tls.connect({ host, port, servername: host })
: net.connect({ host, port });
let opened = false;
let closed = false;
let buffer = Buffer.alloc(0);
socket.setNoDelay(true);
socket.on("connect", () => {
const originProtocol = secure ? "https" : "http";
const request = [
`GET ${path} HTTP/1.1`,
`Host: ${parsed.host}`,
"Upgrade: websocket",
"Connection: Upgrade",
`Sec-WebSocket-Key: ${key}`,
"Sec-WebSocket-Version: 13",
`Origin: ${originProtocol}://${parsed.host}`,
"",
"",
].join("\r\n");
socket.write(request);
});
socket.on("data", (chunk) => {
buffer = Buffer.concat([buffer, chunk]);
if (!opened) {
const headerEnd = buffer.indexOf("\r\n\r\n");
if (headerEnd === -1) return;
const headerText = buffer.slice(0, headerEnd).toString("utf8");
buffer = buffer.slice(headerEnd + 4);
if (!/^HTTP\/1\.1 101\b/i.test(headerText)) {
handlers.onError(new Error(`Handshake failed: ${headerText.split("\r\n")[0] || "missing status"}`));
socket.destroy();
return;
}
opened = true;
handlers.onOpen();
}
processFrames();
});
socket.on("error", (error) => {
if (!closed) handlers.onError(error);
});
socket.on("close", () => {
if (closed) return;
closed = true;
handlers.onClose({ code: null, reason: "" });
});
function processFrames() {
while (true) {
const frame = readFrame(buffer);
if (!frame) return;
buffer = buffer.slice(frame.consumed);
if (frame.opcode === 0x1) {
handlers.onMessage(frame.payload.toString("utf8"));
} else if (frame.opcode === 0x8) {
const code = frame.payload.length >= 2 ? frame.payload.readUInt16BE(0) : null;
const reason = frame.payload.length > 2 ? frame.payload.slice(2).toString("utf8") : "";
closed = true;
handlers.onClose({ code, reason });
socket.end();
return;
} else if (frame.opcode === 0x9) {
writeFrame(socket, 0xA, frame.payload);
}
}
}
return {
send(text) {
if (closed || !opened) return;
writeFrame(socket, 0x1, Buffer.from(text, "utf8"));
},
close() {
if (closed) return;
closed = true;
if (!socket.destroyed) {
if (opened) writeFrame(socket, 0x8, Buffer.alloc(0));
setTimeout(() => socket.end(), 50).unref();
}
},
};
}
function readFrame(buffer) {
if (buffer.length < 2) return null;
const first = buffer[0];
const second = buffer[1];
const opcode = first & 0x0f;
const masked = Boolean(second & 0x80);
let length = second & 0x7f;
let offset = 2;
if (length === 126) {
if (buffer.length < offset + 2) return null;
length = buffer.readUInt16BE(offset);
offset += 2;
} else if (length === 127) {
if (buffer.length < offset + 8) return null;
const high = buffer.readUInt32BE(offset);
const low = buffer.readUInt32BE(offset + 4);
length = high * 2 ** 32 + low;
offset += 8;
}
let mask = null;
if (masked) {
if (buffer.length < offset + 4) return null;
mask = buffer.slice(offset, offset + 4);
offset += 4;
}
if (buffer.length < offset + length) return null;
let payload = buffer.slice(offset, offset + length);
if (mask) {
payload = Buffer.from(payload);
for (let index = 0; index < payload.length; index += 1) {
payload[index] ^= mask[index % 4];
}
}
return {
opcode,
payload,
consumed: offset + length,
};
}
function writeFrame(socket, opcode, payload) {
const body = Buffer.isBuffer(payload) ? payload : Buffer.from(payload || "");
const mask = crypto.randomBytes(4);
const headerLength = body.length < 126 ? 2 : body.length <= 0xffff ? 4 : 10;
const header = Buffer.alloc(headerLength);
header[0] = 0x80 | opcode;
if (body.length < 126) {
header[1] = 0x80 | body.length;
} else if (body.length <= 0xffff) {
header[1] = 0x80 | 126;
header.writeUInt16BE(body.length, 2);
} else {
header[1] = 0x80 | 127;
header.writeUInt32BE(Math.floor(body.length / 2 ** 32), 2);
header.writeUInt32BE(body.length >>> 0, 6);
}
const masked = Buffer.from(body);
for (let index = 0; index < masked.length; index += 1) {
masked[index] ^= mask[index % 4];
}
socket.write(Buffer.concat([header, mask, masked]));
}
function rounded(value) {
return Number(value.toFixed(3));
}
function percentile(values, percentileValue) {
if (values.length === 0) return 0;
const sorted = [...values].sort((a, b) => a - b);
const index = Math.min(sorted.length - 1, Math.ceil((percentileValue / 100) * sorted.length) - 1);
return rounded(sorted[index]);
}
function stats(values) {
if (values.length === 0) return { min: 0, p50: 0, p95: 0, p99: 0, max: 0 };
return {
min: rounded(Math.min(...values)),
p50: percentile(values, 50),
p95: percentile(values, 95),
p99: percentile(values, 99),
max: rounded(Math.max(...values)),
};
}
function buildMetrics({ samples, totalRequests, concurrency, timeoutMs, loadDurationMs, backendUrl, pipelineId, sessionType }) {
const okSamples = samples.filter((sample) => sample.ok);
const statusCounts = {};
for (const sample of samples) {
statusCounts[sample.status] = (statusCounts[sample.status] || 0) + 1;
}
const errorCount = samples.length - okSamples.length;
return {
probe: caseId,
backend_url: backendUrl,
pipeline_id: pipelineId,
session_type: sessionType,
total_requests: totalRequests,
completed_requests: samples.length,
concurrency,
timeout_ms: timeoutMs,
ok_count: okSamples.length,
error_count: errorCount,
timeout_count: samples.filter((sample) => sample.status === "timeout").length,
error_rate: samples.length === 0 ? 1 : rounded(errorCount / samples.length),
load_duration_ms: rounded(loadDurationMs),
throughput_rps: loadDurationMs <= 0 ? 0 : rounded(okSamples.length / (loadDurationMs / 1000)),
status_counts: statusCounts,
connected_ms: stats(samples.map((sample) => sample.connected_ms).filter(Number.isFinite)),
first_response_ms: stats(okSamples.map((sample) => sample.first_response_ms).filter(Number.isFinite)),
response_duration_ms: stats(okSamples.map((sample) => sample.response_duration_ms).filter(Number.isFinite)),
samples,
};
}
function buildThresholds(metrics) {
const thresholds = {
error_rate: { actual: metrics.error_rate, max: maxErrorRate, pass: metrics.error_rate <= maxErrorRate },
response_p95_ms: {
actual: metrics.response_duration_ms.p95,
max: responseP95BudgetMs,
pass: metrics.ok_count > 0 && metrics.response_duration_ms.p95 <= responseP95BudgetMs,
},
};
if (firstResponseP95BudgetMs > 0) {
thresholds.first_response_p95_ms = {
actual: metrics.first_response_ms.p95,
max: firstResponseP95BudgetMs,
pass: metrics.ok_count > 0 && metrics.first_response_ms.p95 <= firstResponseP95BudgetMs,
};
}
return thresholds;
}
function looksLikeEnvIssue(error) {
const message = String(error?.message || error || "");
return /fetch failed|ECONNREFUSED|ENOTFOUND|LANGBOT_.*not configured|Could not read recovery_key|Backend did not respond/i.test(message);
}
function safeReason(value) {
return redact(String(value || "")).slice(0, 1000);
}
@@ -121,6 +121,45 @@ Do not treat these starter live probes as Debug Chat or model-provider
performance. They are control-plane readiness checks; user-facing performance
needs browser/WebSocket/message-path measurements.
## Debug Chat Load And Fake Provider Baseline
Use `langbot-fake-provider-debug-chat-load` before real-provider load checks.
The setup automation starts a local OpenAI-compatible fake provider, registers
it as a normal LangBot provider/model, configures a local-agent pipeline, resets
Debug Chat, and then drives concurrent WebSocket messages through the live
backend.
This is not a mocked backend test. It still exercises:
- provider/model persistence and runtime reload;
- LiteLLM OpenAI-compatible requester path;
- local-agent runner selection and pipeline execution;
- Debug Chat WebSocket adapter and broadcast behavior;
- backend concurrency, timeout, and error-rate accounting.
The fake provider is deterministic and can inject controlled latency or faults
with `LANGBOT_FAKE_PROVIDER_*` variables, so it is the baseline for LangBot
message-path overhead. The probe uses unique expected response tokens per
request because Debug Chat broadcasts messages to every connection in the same
session; unique tokens prevent one connection from counting another
connection's response as its own.
Use `langbot-space-debug-chat-concurrency-smoke` after the fake-provider
baseline. It runs a deliberately small real Space-provider batch and reports
user-visible latency, not pure LangBot overhead. Space/model/network failures
are dependency findings until the fake baseline shows the same symptom.
If a Space smoke passes but log guard finds telemetry posting Tracebacks,
classify that separately as `telemetry-proxy-noise` instead of clearing the
proxy or treating the Debug Chat path as failed.
Useful commands:
```bash
rtk bin/lbs test run langbot-fake-provider-debug-chat-load --run-id langbot-fake-load-local
rtk bin/lbs test run langbot-space-debug-chat-concurrency-smoke --run-id langbot-space-smoke-local
rtk bin/lbs suite run langbot-debug-chat-load-gate --run-id langbot-debug-chat-load-local --include-manual-check
```
## Gate Layers
Use the smallest gate that answers the quality question:
@@ -134,6 +173,9 @@ Use the smallest gate that answers the quality question:
- `langbot-user-path-performance-gate`: browser-visible user path performance,
starting with Pipeline Debug Chat send-to-visible-completion latency. Run it
only when the browser profile and target pipeline are ready.
- `langbot-debug-chat-load-gate`: WebSocket Debug Chat load checks, starting
with a controlled fake-provider baseline and optionally a low-volume real
Space-provider smoke.
- `langbot-performance-reliability-gate`: combined starter gate for synthetic
contracts plus live backend checks.
@@ -0,0 +1,13 @@
id: langbot-debug-chat-load-gate
title: "LangBot Debug Chat load gate"
description: "Message-path load checks for Pipeline Debug Chat: controlled fake-provider baseline plus optional real Space-provider smoke."
type: performance
priority: p1
tags:
- performance
- debug-chat
- websocket
- load
cases:
- langbot-fake-provider-debug-chat-load
- langbot-space-debug-chat-concurrency-smoke
@@ -0,0 +1,23 @@
id: telemetry-proxy-noise
title: "Telemetry posting fails through the proxy while the target flow succeeds"
date: 2026-06-25
category: env_issue
symptoms:
- "The target Debug Chat or provider smoke request completes successfully."
- "The same log window contains a Traceback for telemetry posting."
- "The traceback references the Space telemetry endpoint."
patterns:
- "Failed to post telemetry"
- "https://space.langbot.app/api/v1/telemetry"
- "httpx.ConnectError"
likely_causes:
- "The backend process inherited proxy settings that are required for model/provider access but unreliable for telemetry posting."
- "The telemetry endpoint is temporarily unreachable through the local proxy route."
- "TLS or proxy negotiation failed for the non-critical telemetry request."
fix_steps:
- "Keep the proxy configuration needed for model/provider access; do not clear it only to hide telemetry noise."
- "Check that uppercase and lowercase proxy variables are consistent before rerunning a live Space smoke."
- "Classify the target flow and log-health result separately: a successful Debug Chat run can still have an environment log-health finding."
verification: "A rerun shows the target case success patterns and no telemetry Traceback in the scanned log window, or the report explicitly records the telemetry issue as environment noise."
related_cases:
- langbot-space-debug-chat-concurrency-smoke
+22
View File
@@ -186,10 +186,32 @@ function validateCaseItem(root: string, item: StructuredItem, skillNames: Set<st
if (timeout && (!/^\d+$/.test(timeout) || Number.parseInt(timeout, 10) <= 0)) {
errors.push(`${item.path}: 'automation_response_timeout_ms' must be a positive integer string`);
}
for (const key of [
"automation_debug_chat_load_requests",
"automation_debug_chat_load_concurrency",
"automation_debug_chat_load_timeout_ms",
"automation_debug_chat_load_response_p95_ms",
"automation_debug_chat_load_first_response_p95_ms",
]) {
const value = scalar(item.fields, key);
if (value && (!/^\d+$/.test(value) || Number.parseInt(value, 10) <= 0)) {
errors.push(`${item.path}: '${key}' must be a positive integer string`);
}
}
const loadMaxErrorRate = scalar(item.fields, "automation_debug_chat_load_max_error_rate");
if (loadMaxErrorRate && (!/^(?:0(?:\.\d+)?|1(?:\.0+)?)$/.test(loadMaxErrorRate))) {
errors.push(`${item.path}: 'automation_debug_chat_load_max_error_rate' must be a number string between 0 and 1`);
}
const streamOutput = scalar(item.fields, "automation_stream_output");
if (streamOutput && !["0", "1", "false", "true"].includes(streamOutput)) {
errors.push(`${item.path}: 'automation_stream_output' must be one of 0, 1, false, or true`);
}
for (const key of ["automation_debug_chat_load_stream", "automation_debug_chat_load_reset"]) {
const value = scalar(item.fields, key);
if (value && !["0", "1", "false", "true"].includes(value)) {
errors.push(`${item.path}: '${key}' must be one of 0, 1, false, or true`);
}
}
const imageBase64Fixture = scalar(item.fields, "automation_image_base64_fixture");
if (imageBase64Fixture && !existsSync(join(root, imageBase64Fixture))) {
errors.push(`${item.path}: automation image fixture does not exist: ${imageBase64Fixture}`);
+10
View File
@@ -116,6 +116,16 @@ export function automationEnvDefaults(item: StructuredItem, env: EnvSource = pro
["automation_debug_chat_session_type", "LANGBOT_E2E_DEBUG_CHAT_SESSION_TYPE"],
["automation_debug_chat_response_p95_ms", "LANGBOT_E2E_DEBUG_CHAT_RESPONSE_P95_MS"],
["automation_debug_chat_max_error_rate", "LANGBOT_E2E_DEBUG_CHAT_MAX_ERROR_RATE"],
["automation_debug_chat_load_requests", "LANGBOT_DEBUG_CHAT_LOAD_REQUESTS"],
["automation_debug_chat_load_concurrency", "LANGBOT_DEBUG_CHAT_LOAD_CONCURRENCY"],
["automation_debug_chat_load_timeout_ms", "LANGBOT_DEBUG_CHAT_LOAD_TIMEOUT_MS"],
["automation_debug_chat_load_response_p95_ms", "LANGBOT_DEBUG_CHAT_LOAD_RESPONSE_P95_MS"],
["automation_debug_chat_load_first_response_p95_ms", "LANGBOT_DEBUG_CHAT_LOAD_FIRST_RESPONSE_P95_MS"],
["automation_debug_chat_load_max_error_rate", "LANGBOT_DEBUG_CHAT_LOAD_MAX_ERROR_RATE"],
["automation_debug_chat_load_expected_prefix", "LANGBOT_DEBUG_CHAT_LOAD_EXPECTED_PREFIX"],
["automation_debug_chat_load_prompt_template", "LANGBOT_DEBUG_CHAT_LOAD_PROMPT_TEMPLATE"],
["automation_debug_chat_load_stream", "LANGBOT_DEBUG_CHAT_LOAD_STREAM"],
["automation_debug_chat_load_reset", "LANGBOT_DEBUG_CHAT_LOAD_RESET"],
["automation_filesystem_checks_json", "LANGBOT_E2E_FILESYSTEM_CHECKS_JSON"],
["automation_plugin_package", "LANGBOT_E2E_PLUGIN_PACKAGE"],
["automation_expected_plugin_id", "LANGBOT_E2E_EXPECTED_PLUGIN_ID"],