mirror of
https://github.com/langbot-app/LangBot.git
synced 2026-06-20 12:34:21 +00:00
e9dd584792
* feat(api): support global API key from config.yaml (api.global_api_key) Accept a config-defined global API key anywhere a web-UI key is accepted (X-API-Key / Bearer), with no login session and no DB record. Useful for automated deployments and AI agents (HTTP API + MCP). Defaults to empty (disabled); does not require the lbk_ prefix. - templates/config.yaml: add api.global_api_key with security notes - service/apikey.py: verify_api_key checks global key first (constant-time) - docs/API_KEY_AUTH.md: document the global key + security guidance - tests: cover global-key match, prefix-free, fallback-to-db, disabled * feat(mcp): expose LangBot management as an MCP server at /mcp Add an MCP (Model Context Protocol) server so external AI agents can manage a LangBot instance. Reuses the same API-key auth as the HTTP API (including the config.yaml global API key). - pkg/api/mcp/server.py: FastMCP server wrapping the service layer; 21 curated tools across system/bots/pipelines/models/knowledge/mcp-servers/skills - pkg/api/mcp/mount.py: ASGI dispatcher fronting Quart; authenticates /mcp requests with an API key, runs the streamable-HTTP session manager lifespan - controller/main.py: serve the wrapped ASGI app via hypercorn (was run_task) - web: new 'MCP' tab in the API integration dialog showing endpoint, auth, and client config; i18n for 8 locales - tests/manual/mcp_smoke.py: e2e check (401 unauth, list tools, call tools) Tool surface is intentionally curated (not all ~25 route groups) to keep the agent surface small, safe, and maintainable. Extend deliberately. * feat(skills): add in-repo skills/ as the single source of truth Migrate the agent skills + QA/e2e test harness from the (now archived) langbot-app/langbot-skills repo into LangBot/skills/, and add four new skills. Migrated: - langbot-plugin-dev, langbot-testing (e2e), langbot-env-setup, langbot-skills-maintenance, langbot-eba-adapter-dev - the bin/lbs CLI (src/, test/, scripts/, schemas/, qa-agent-docs/) New: - langbot-dev core backend + web development - langbot-deploy Docker/K8s deployment + config.yaml + global API key - langbot-mcp-ops operating the LangBot MCP server (/mcp) - langbot-space-ops operating the Space marketplace MCP server - src/cli.ts repoRoot(): recognize the skills assets root (skills.index.json + bin/lbs) so the CLI works when nested inside the LangBot repo - README.md: unified skill catalog; skills.index.json regenerated Parity with source verified: bin/lbs validate + node test suite match the source repo (only the uncommitted .lbpkg build-artifact fixture differs). * docs(agents): document agent-facing surfaces + API/MCP/skills sync rule * docs(readme): add 'Built for AI Agents' section across all locales Highlight MCP server, in-repo skills (single source of truth), AGENTS.md sync rule, and llms.txt. Cross-link LangBot Space MCP marketplace. * style(mcp): fix ruff format + prettier lint in MCP server and API panel * style(web): prettier format MCP i18n locale entries * docs(skills): note MCP instance control in dev/testing skills All development-guidance skills now point to the LangBot instance MCP server (/mcp) and the Space marketplace MCP server, reusing API keys.
231 lines
6.9 KiB
JavaScript
231 lines
6.9 KiB
JavaScript
#!/usr/bin/env node
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import { readFile, writeFile } from "node:fs/promises";
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import { resolve } from "node:path";
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import { env } from "node:process";
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import {
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apiJson,
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ensureEvidence,
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evidencePaths,
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loadEnvFiles,
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resetAndAuthLocalUser,
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writeResult,
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} from "./lib/langbot-e2e.mjs";
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const RUNNER_ID = "plugin:qa/agent-runner/default";
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const DEFAULT_PIPELINE_NAME = "Agent QA Deterministic Runner Debug Chat";
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const DEFAULT_LOCAL_PASSWORD = "LangBotE2ELocalPass!2026";
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const caseId = "ensure-qa-agent-runner-pipeline";
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await loadEnvFiles();
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const paths = evidencePaths(caseId);
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await ensureEvidence(paths);
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const writeEnv = process.argv.includes("--write-env");
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const frontendUrl = env.LANGBOT_FRONTEND_URL || "";
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const backendUrl = env.LANGBOT_BACKEND_URL || "";
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const pipelineName = env.LANGBOT_E2E_CREATE_PIPELINE_NAME || env.LANGBOT_QA_AGENT_RUNNER_PIPELINE_NAME || DEFAULT_PIPELINE_NAME;
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const envLocalPath = resolve("skills/.env.local");
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const result = {
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source: "automation",
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case_id: caseId,
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run_id: paths.runId,
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status: "fail",
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reason: "",
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frontend_url: frontendUrl,
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backend_url: backendUrl,
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pipeline_name: pipelineName,
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pipeline_id: "",
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pipeline_url: "",
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runner_id: RUNNER_ID,
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wrote_env: false,
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auth: null,
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evidence: {
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automation_result_json: paths.automationResultJson,
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result_json: paths.resultJson,
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},
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evidence_collected: ["api_diagnostic"],
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};
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try {
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if (!frontendUrl) throw new Error("LANGBOT_FRONTEND_URL is not configured.");
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if (!backendUrl) throw new Error("LANGBOT_BACKEND_URL is not configured.");
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const user = env.LANGBOT_E2E_LOGIN_USER || "";
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const password = env.LANGBOT_E2E_LOGIN_PASSWORD || DEFAULT_LOCAL_PASSWORD;
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if (!user) {
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throw new Error("LANGBOT_E2E_LOGIN_USER is required so this setup can create/update the pipeline via backend API.");
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}
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const auth = await resetAndAuthLocalUser({ backendUrl, user, password });
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result.auth = {
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source: "local_recovery_login",
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user,
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backend_token_check: auth.check,
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};
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const prepared = await ensurePipeline({
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backendUrl,
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token: auth.token,
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pipelineName,
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runnerId: RUNNER_ID,
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runnerConfig: {},
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});
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Object.assign(result, prepared);
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if (result.pipeline_id) {
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result.pipeline_url = `${frontendUrl.replace(/\/$/, "")}/home/pipelines?id=${encodeURIComponent(result.pipeline_id)}`;
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}
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if (writeEnv && result.pipeline_id) {
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await upsertEnvLocal(envLocalPath, {
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LANGBOT_E2E_LOGIN_USER: user,
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LANGBOT_QA_AGENT_RUNNER_PIPELINE_URL: result.pipeline_url,
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LANGBOT_QA_AGENT_RUNNER_PIPELINE_NAME: result.pipeline_name || pipelineName,
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});
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result.wrote_env = true;
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}
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} catch (error) {
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result.reason = result.reason || error.message;
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} finally {
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await writeResult(paths, result);
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console.log(JSON.stringify(result, null, 2));
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}
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process.exit(result.status === "pass" ? 0 : result.status === "env_issue" ? 2 : 1);
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async function ensurePipeline({ backendUrl, token, pipelineName, runnerId, runnerConfig }) {
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const pipelineList = await apiJson(backendUrl, "/api/v1/pipelines", { token });
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if (isApiFailure(pipelineList)) {
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return {
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status: "fail",
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reason: pipelineList.json.msg || "Failed to list pipelines.",
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list_status: pipelineList.status,
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};
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}
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const pipelines = pipelineList.json.data?.pipelines || [];
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let pipeline = pipelines.find((item) => item.name === pipelineName) || null;
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let created = false;
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if (!pipeline) {
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const createdResponse = await apiJson(backendUrl, "/api/v1/pipelines", {
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method: "POST",
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token,
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body: {
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name: pipelineName,
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description: "Local QA pipeline for deterministic QA AgentRunner Debug Chat smoke tests.",
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emoji: "QA",
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},
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});
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if (isApiFailure(createdResponse)) {
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return {
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status: "fail",
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reason: createdResponse.json.msg || "Failed to create pipeline.",
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create_status: createdResponse.status,
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};
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}
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const pipelineId = createdResponse.json.data?.uuid || "";
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const loaded = await apiJson(backendUrl, `/api/v1/pipelines/${encodeURIComponent(pipelineId)}`, { token });
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pipeline = loaded.json.data?.pipeline || null;
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created = true;
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}
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if (!pipeline?.uuid) {
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return {
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status: "fail",
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reason: "Pipeline was not created or resolved.",
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};
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}
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const loaded = await apiJson(backendUrl, `/api/v1/pipelines/${encodeURIComponent(pipeline.uuid)}`, { token });
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if (isApiFailure(loaded) || !loaded.json.data?.pipeline) {
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return {
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status: "fail",
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reason: loaded.json.msg || "Failed to load pipeline.",
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get_status: loaded.status,
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pipeline_id: pipeline.uuid,
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};
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}
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pipeline = loaded.json.data.pipeline;
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const config = pipeline.config && typeof pipeline.config === "object" ? pipeline.config : {};
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const ai = config.ai && typeof config.ai === "object" ? config.ai : {};
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const runnerConfigs = ai.runner_config && typeof ai.runner_config === "object" ? ai.runner_config : {};
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const updatedConfig = {
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...config,
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ai: {
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...ai,
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runner: {
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...(ai.runner && typeof ai.runner === "object" ? ai.runner : {}),
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id: runnerId,
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"expire-time": 0,
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},
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runner_config: {
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...runnerConfigs,
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[runnerId]: runnerConfig,
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},
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},
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};
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const updateResponse = await apiJson(backendUrl, `/api/v1/pipelines/${encodeURIComponent(pipeline.uuid)}`, {
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method: "PUT",
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token,
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body: {
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name: pipelineName,
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description: "Local QA pipeline for deterministic QA AgentRunner Debug Chat smoke tests.",
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emoji: "QA",
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config: updatedConfig,
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},
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});
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if (isApiFailure(updateResponse)) {
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return {
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status: "fail",
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reason: updateResponse.json.msg || "Failed to update pipeline.",
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update_status: updateResponse.status,
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pipeline_id: pipeline.uuid,
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};
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}
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return {
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status: "pass",
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reason: created ? "QA AgentRunner pipeline created and configured." : "QA AgentRunner pipeline updated.",
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pipeline_id: pipeline.uuid,
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pipeline_name: pipelineName,
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created,
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updated: true,
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};
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}
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function isApiFailure(response) {
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return response.status >= 400 || (response.json && response.json.code !== undefined && response.json.code !== 0);
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}
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async function upsertEnvLocal(path, values) {
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let text = "";
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try {
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text = await readFile(path, "utf8");
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} catch {
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text = "";
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}
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const lines = text.split(/\r?\n/);
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const keys = new Set(Object.keys(values));
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const output = [];
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for (const line of lines) {
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const match = line.match(/^([A-Z][A-Z0-9_]*)=/);
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if (match && keys.has(match[1])) {
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output.push(`${match[1]}=${values[match[1]]}`);
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keys.delete(match[1]);
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} else if (line !== "" || output.length > 0) {
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output.push(line);
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}
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}
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if (keys.size > 0 && output.length > 0 && output[output.length - 1] !== "") {
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output.push("");
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}
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for (const key of keys) {
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output.push(`${key}=${values[key]}`);
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}
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await writeFile(path, `${output.join("\n").replace(/\n+$/, "")}\n`, "utf8");
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}
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