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library for agent-compose — define agents, runtimes, and workflows, and invoke them against an agent-compose server.","maintainers":[{"name":"chris-moller","email":"cmoller02@gmail.com"}],"readme":"# @agent-compose/sdk\n\nTypeScript SDK for [agent-compose](https://github.com/Layr-Labs/agent-compose). Use it to:\n\n- **Author workflows** that run agentic LLM loops inside isolated sandboxes\n- **Define runtimes** that wrap a coding-CLI tool (Claude Code, OpenAI Desktop, …) into a sandbox-portable agent loop\n- **Register, invoke, observe, and cancel** workflows via the HTTP API (`AgentComposeClient`)\n- **Manage factories, secrets, API keys, and snapshots** programmatically\n\nThe hierarchy: a **team** owns one or more **factories** (project containers); each factory owns workflow templates, secrets, and runs. Workflows are versioned per `(factory, name, version)`. New code that doesn't care about factories transparently lands in `default` — every team has one.\n\n---\n\n## Installation\n\n```bash\nnpm install @agent-compose/sdk\n# peer dep:\nnpm install zod\n```\n\n---\n\n## Authoring a workflow\n\nA workflow is a typed chain of discrete steps:\n`defineWorkflow({ id, input, output }).step(defineStep(...)).build()`.\nEvery step is a durable replay checkpoint — the engine records each\nstep's validated output, so a retry or resume picks up after the last\ncompleted step instead of re-running the whole workflow. Pausing for\nhuman input (`ctx.pause`, `ctx.waitForEvent`) only works in this\nstep-form.\n\n```typescript\n// my-workflow.ts\nimport { defineWorkflow, defineStep, agent, claudeRuntime } from \"@agent-compose/sdk\";\nimport { z } from \"zod\";\nimport PROMPT from \"./prompt.md\" with { type: \"text\" };\n\nconst Input = z.object({ repo: z.string() });\nconst Output = z.object({ ok: z.boolean(), summary: z.string().optional() });\n\nconst review = defineStep({\n name: \"review\",\n input: Input,\n output: Output,\n run: async (ctx) => {\n const result = await agent({\n sandbox: ctx.sandbox, // the run's own VM\n runtime: claudeRuntime,\n prompt: `${PROMPT}\\n\\nRepository: ${ctx.input.repo}`,\n tools: [\"Bash\", \"Read\", \"Edit\", \"Write\", \"Grep\", \"Glob\"],\n budget: { turnsPerIteration: 40, maxIterations: 8 },\n });\n await ctx.setMetadata({ summary: result.status?.summary });\n return { ok: result.status?.completed ?? false, summary: result.status?.summary };\n },\n});\n\nexport default defineWorkflow({\n id: \"my-workflow\",\n input: Input,\n output: Output,\n // Optional: outbound network rules that the runner sandbox will enforce\n // (Vercel only — E2B ignores). Use `$VAR` placeholders for secrets that\n // get resolved from the per-workflow secret store at dispatch time.\n networkPolicy: {\n allow: {\n \"*\": [],\n \"api.anthropic.com\": [{ transform: [{ headers: { \"x-api-key\": \"$ANTHROPIC_API_KEY\" } }] }],\n },\n },\n})\n .step(review)\n .build();\n```\n\nThe builder chain enforces at compile time that each step's `input`\nschema matches the previous step's `output`, and `.build()` verifies\nthe final step's `output` is the same Zod instance as the workflow's\ndeclared `output`. `networkPolicy` / `placeholders` / `snapshots` on\nthe definition become metadata the bundler picks up at registration\ntime.\n\n> **Legacy run-form.** `defineWorkflow({ run(ctx, sandbox) { … } })` is\n> `@deprecated` — it compiles to a single opaque step, so there is no\n> per-step replay and pause doesn't work. Don't author new ones.\n\n### What a step can do with `ctx`\n\nEach step's `run(ctx)` receives a `StepContext`:\n\n```ts\ninterface StepContext {\n input: TInput; // validated against the step's `input` schema\n run: { id: string };\n sandbox?: SandboxProvider; // the run's VM — pass to `agent({ sandbox: ctx.sandbox })`\n setMetadata: (data: Record) => Promise;\n step(name: string, fn: () => Promise): Promise; // durable named sub-step\n pause(req: PauseRequest): Promise; // wait for a human, durably\n sleep(durationMs: number): Promise;\n waitForEvent(req: WaitForEventRequest): Promise;\n invokeChild(name, input?, opts?): Promise; // run another workflow\n}\n```\n\n`ctx.step(\"phase-name\", () => …)` wraps a phase *within* a step for the\nrun timeline — it memoises the result (a pause-resume re-entry restores\nit instead of re-running) and emits `workflow_substep_started` /\n`workflow_substep_completed` / `workflow_substep_failed` lifecycle\nevents with duration. Use it for setup, external API calls, or anything\nyou want visible on the dashboard's run detail page.\n\n### The `agent` loop\n\n```ts\nagent({\n sandbox, // ctx.sandbox — the run's VM\n runtime, // claudeRuntime, or your own via createClaudeRuntime / defineRuntime\n prompt, // raw markdown — `--- frontmatter ---` is auto-stripped\n tools?, // model tool allowlist (defaults inside agentLoop)\n budget?, // { turnsPerIteration, maxIterations }\n workingDir?, // every shell command runs here\n responseSchema?, // zod — when set, the loop demands a `` block on exit\n onAgentEvent?, // per-message hook (e.g. wire to telemetry)\n onIteration?, // per-iteration hook with parsed `` block\n})\n// → AgentLoopResult { status?, response? (when responseSchema set), iterations, … }\n```\n\nThe protocol is simple: the model emits XML-tagged blocks (`` /\n``) the loop parses. See `sdk/src/agent/protocol-suffix.md` for\nthe full instructions appended to every prompt.\n\n---\n\n## Defining a runtime\n\nA \"runtime\" wraps an agent's underlying execution model — usually a coding\nCLI like Claude Code or OpenAI Desktop — so `agent` can drive it. The SDK\nships built-ins; you only need a custom one for an exotic provider.\n\n### Built-in runtimes\n\n```ts\nimport {\n createClaudeRuntime, // factory, takes config\n claudeRuntime, // pre-built default (DEFAULT_CLAUDE_MODEL)\n ClaudeRunner, // class, if you need to override\n} from \"@agent-compose/sdk\";\n\n// openAIDesktopRuntime is NOT in the package root (it pulls in `sharp` for\n// screenshot capture; the native binding can't be cross-compiled). Import\n// directly when you actually want the desktop runtime:\nimport openAIDesktopRuntime from \"@agent-compose/sdk/runtimes/openai-desktop.js\";\n```\n\n### Custom runtime\n\n```ts\nimport { defineRuntime, type AgentRuntime } from \"@agent-compose/sdk\";\n\nconst myRuntime: AgentRuntime = defineRuntime({\n create: (sandbox, opts) => {\n // Return a ModelExecutionContract — see sdk/src/types/runtime.ts\n return {\n sendMessage({ prompt, sessionId, signal }) {\n // Async generator that yields AgentMessage chunks the loop parses.\n return /* … */;\n },\n };\n },\n});\n```\n\n`AgentRuntime` is a tagged record with `create(sandbox, RuntimeOptions) →\nModelExecutionContract`. There is **no `provider` field** on it — the\nruntime is bound to the workflow at author time (you pass it to `agent`),\nnot selected by the server.\n\n---\n\n## Registering a workflow\n\nThe `agentc` CLI handles the bundling-and-registration step for you:\n\n```bash\nagentc register my-workflow.ts -n my-workflow\n```\n\nUnder the hood that calls `bundleWorkflow(workflowPath)` (resolves imports,\ninlines runtime sources via dynamic-require traversal) and `POST\n/api/v1/factories//templates` with the bundled source. If you need\nto drive registration from your own build pipeline, you can do the same\nthing via the SDK directly:\n\n```ts\nimport { AgentComposeClient, bundleWorkflow } from \"@agent-compose/sdk\";\n\nconst client = new AgentComposeClient(\n \"https://your-server.example.com\",\n process.env.AGENT_COMPOSE_API_KEY!,\n);\n\nconst bundled = await bundleWorkflow(\"./my-workflow.ts\");\nawait client.register({\n name: \"my-workflow\",\n source: bundled.source,\n runtimes: bundled.runtimes, // [{ name, source }] — embedded so the runner has them locally\n schedule: \"*/30 * * * *\", // optional cron\n factorySlug: \"default\", // optional — defaults to \"default\"\n // snapshots, networkPolicy, placeholders — all optional\n});\n```\n\n`register()` requires the caller's API key to carry the `admin` scope\n(or full team-access for legacy keys without scopes).\n\n---\n\n## Invoking a workflow\n\nTwo flavours:\n\n```ts\n// Fire-and-forget — returns the run id immediately.\nconst { id } = await client.invoke(\"my-workflow\", {\n repo: \"owner/repo\",\n});\n\n// Block until the run settles (default 30min timeout, 1s poll).\nconst status = await client.invokeAndWait(\"my-workflow\", { repo: \"owner/repo\" }, {\n timeoutMs: 5 * 60_000,\n pollIntervalMs: 2000,\n});\nconsole.log(status.status); // \"success\" | \"failed\" | \"abandoned\" | \"canceled\"\nconsole.log(status.output); // workflow's return value\n```\n\n`output` is the final step's return value, validated against the\nworkflow's declared `output` schema. `setMetadata()` writes to a\nseparate `metadata` field — useful for \"side-channel\" facts (PR url, plan\nurl) without polluting the structured return.\n\n`invoke` and `invokeAndWait` both accept `{ factorySlug, snapshots,\nnetworkPolicy, placeholders, parentRunId }` as the\nthird argument. Per-invocation `snapshots` merges field-by-field with\nthe registered default. `factorySlug` defaults to `\"default\"`.\n\n### Auto parent/child tracing\n\nThe SDK detects `process.env.RUN_ID` (set by the runner sandbox on every\ndispatch) and automatically threads it as `parentRunId` on subsequent\n`invoke()` calls. Workflows that fan out to other workflows get a\nparent/child tree in the dashboard for free. Pass `parentRunId: null`\nto opt out.\n\n### Cancelling a run\n\n```ts\nawait client.cancelRun(runId);\n```\n\nIdempotent — cancelling an already-terminal run returns the current state\nwithout throwing. The server stamps the run as `canceled`, kills any live\nsandboxes, and emits a `run_canceled` event on the stream.\n\n### Streaming live logs\n\n`streamRunLogs` returns an async generator of `RunEvent`s in real time,\nre-attaching via SSE under the hood. Pass `lastEventId` (the highest\n`seq` you've already processed) to resume after a reconnect.\n\n```ts\nfor await (const ev of client.streamRunLogs(runId, { lastEventId: 0 })) {\n console.log(ev.event, ev.seq, ev.data);\n if (ev.event === \"run_complete\" || ev.event === \"run_failed\" || ev.event === \"run_canceled\") {\n break;\n }\n}\n```\n\n`AbortSignal` works too — pass `{ signal }` and call `controller.abort()`\nto tear the stream down from the caller side.\n\n---\n\n## Factories\n\nFactories are project containers within a team. Each factory has its own\nworkflow templates, secrets, runs, and (optionally) scoped API keys. New\nprojects don't need to think about them — `default` is auto-created per\nteam and is what the SDK falls back to when `factorySlug` is omitted.\n\n```ts\n// CRUD on factories\nawait client.createFactory({ slug: \"ci-bots\", name: \"CI Bots\", description: \"…\" });\nconst factories = await client.listFactories();\nconst f = await client.getFactory(\"ci-bots\");\nawait client.updateFactory(\"ci-bots\", { name: \"Continuous-Integration Bots\" });\nawait client.deleteFactory(\"ci-bots\");\n\n// Templates list — flat across factories, or scoped to one\nconst all = await client.listTemplates();\nconst scoped = await client.listTemplates({ factorySlug: \"ci-bots\" });\n\n// Register / invoke / secret operations all accept factorySlug\nawait client.register({ name: \"scrape\", source, factorySlug: \"ci-bots\", … });\nawait client.invoke(\"scrape\", { url: \"…\" }, { factorySlug: \"ci-bots\" });\nawait client.setSecret(\"scrape\", \"GH_TOKEN\", \"ghp_…\", { factorySlug: \"ci-bots\" });\n```\n\nCLI equivalents: `agentc factory list | create | get | update | delete`,\nplus `--factory ` on every other command.\n\n---\n\n## Per-workflow secrets\n\nSecrets live in GCP Secret Manager, one row per `(factory, workflow, key)`.\nThey're injected as env vars into the runner sandbox at dispatch time,\nnever persisted in the VM. Values are write-only — the API only returns\nmetadata (key, timestamps).\n\n```ts\nawait client.setSecret(\"my-workflow\", \"ANTHROPIC_API_KEY\", process.env.ANTHROPIC_API_KEY!);\nconst list = await client.listSecrets(\"my-workflow\"); // [{ key, createdAt, updatedAt }]\nawait client.deleteSecret(\"my-workflow\", \"STALE_KEY\");\n\n// Scope to a non-default factory:\nawait client.setSecret(\"scrape\", \"GH_TOKEN\", \"ghp_…\", { factorySlug: \"ci-bots\" });\n```\n\nMutations require `admin` scope.\n\n---\n\n## API keys\n\nMint and list scoped keys programmatically (requires an `admin`-scoped\ncaller key). New keys are returned **once**, in the same response as the\nmetadata — copy the `ac_…` value immediately.\n\n```ts\nconst created = await client.createApiKey({\n name: \"ci-dispatcher\",\n scopes: [\"read\", \"invoke\"],\n expiresAt: new Date(Date.now() + 30 * 86_400_000).toISOString(), // 30 days\n // factorySlug: \"ci-bots\" // optional — scopes the key to a single factory\n});\nconsole.log(created.key); // \"ac_…\" — the only time you'll see this\n\nconst all = await client.listApiKeys();\n```\n\nCLI equivalent: `agentc keys create --scopes read,invoke\n--expires-in 30d`.\n\n---\n\n## Usage\n\n```ts\nconst usage = await client.getUsage(\n new Date(Date.now() - 30 * 86_400_000),\n new Date(),\n);\n// usage.rows: [{ day, runs, sandbox_seconds, … }]\n```\n\nCLI equivalent: `agentc usage`.\n\n---\n\n## Snapshots (replay-friendly sandboxes)\n\nLong-running workflows can capture the runner sandbox as a Vercel snapshot\non success (`snapshots: { saveLatest: true }`). Other workflows reference\nthat snapshot via `snapshots.bootFrom` to boot into the same prepared VM\n(deps installed, repo cloned, etc.) instead of repeating setup.\n\n```ts\n// Capture per-invocation:\nawait client.invoke(\"my-workflow\", input, { snapshots: { saveLatest: true } });\n\n// Boot from a captured snapshot — pick the id from `agentc snapshot\n// list` or the dashboard snapshots page:\nawait client.invoke(\"my-workflow\", input, {\n snapshots: { bootFrom: { snapshotId: \"snap_…\" } },\n});\n\n// Set a default at registration time:\ndefineWorkflow({ id, input, output, snapshots: { saveLatest: true } }).step(…).build();\n\n// Retain every step's snapshot (not just the latest):\ndefineWorkflow({ id, input, output, snapshots: { saveLatest: true, retainSteps: true } }).step(…).build();\n\n// Browse / clean up:\nconst page = await client.listSnapshotsPage({ workflow: \"my-workflow\", limit: 50 });\nconst snaps = page.data;\nawait client.deleteRunSnapshot(snaps[0].runId, snaps[0].snapshotId);\n```\n\nCLI equivalents: `agentc snapshot list` / `agentc snapshot delete `.\n\n### Per-invocation overrides merge field-by-field\n\nThe `snapshots` object on `invoke()` is **merged** with the registered template's `snapshots` config — you can override `bootFrom` alone without losing `saveLatest`, or vice versa.\n\n---\n\n## Authentication\n\nThe SDK accepts a Bearer API key (`ac_…`). Mint one from the dashboard:\nsign in at `/login`, then **Settings → API Keys → Create key**.\n\nDefault scopes (`read + invoke`) are right for a CI / dispatch caller. Tick\n`admin` only if this key needs to register templates, mint other keys, or\nmanage secrets.\n\n```ts\nconst client = new AgentComposeClient(\n process.env.AGENT_COMPOSE_URL!,\n process.env.AGENT_COMPOSE_API_KEY!,\n);\n```\n\nThe dashboard itself uses the cookie-bound session path; the SDK is for\nprogrammatic / server-to-server callers.\n\n---\n\n## Public exports — quick reference\n\n| Export | What |\n|---|---|\n| `defineWorkflow` | Typed step-workflow builder — `defineWorkflow({ id, input, output }).step(...).build()` |\n| `defineStep` | Declare one typed workflow step (`{ name, input, output, run }`) |\n| `defineRuntime` | Wrap an agent execution provider as an `AgentRuntime` |\n| `defineSandboxEnvironment` | Sugar for declaring a workflow whose primary purpose is to build a snapshot for others to boot from |\n| `agent` / `agentLoop` | Embed an LLM loop inside a workflow |\n| `runWorkflow` | Local engine for running a workflow in-process (test harness) |\n| `bundleWorkflow` | Resolve + inline a workflow's runtime sources for registration |\n| `claudeRuntime` / `createClaudeRuntime` / `ClaudeRunner` | Built-in Claude Code runtime + factory |\n| `AgentComposeClient` | HTTP client — register, invoke, cancel, stream logs, factories, snapshots, secrets, API keys, usage |\n| `AgentComposeError` | Thrown by every non-2xx HTTP response |\n| `parseAgentStatus` / `parseAgentResponse` / `AgentStatusSchema` / `AgentMessageSchema` | Protocol parsers |\n| `parseSseStream` | Generic SSE chunk decoder (used by `streamRunLogs`) |\n| `createSandbox` / `reconnectSandbox` / `killAllSandboxes` / `killSandboxById` / `getSandboxQuotas` / `listOwnedSandboxes` / `deleteSandboxSnapshot` | Sandbox-provider helpers (Vercel + E2B) |\n\nType exports: `Workflow`, `Step`, `StepContext`, `WorkflowBuilder`,\n`WorkflowHooks`, `AgentBudget`, `AgentRuntime`, `RuntimeOptions`,\n`ModelExecutionContract`, `McpServerConfig`, `AgentMessage` (and its\nvariants), `AgentStatus`, `RunStatus`, `RegisterResult`, `RunEvent`,\n`FactoryRow`, `SnapshotListEntry`, `ApiKey`, `ApiKeyCreated`,\n`UsageRollupRow`, `UsageResponse`, `CancelRunResponse`, `AgentLoopResult`,\n`AgentOpts`, `SandboxProvider`, `DesktopSandboxProvider`,\n`SandboxNetworkPolicy`, `SandboxCreateOpts`, `OwnedSandbox`,\n`BundledWorkflow`.\n\nFor the canonical signatures, follow your IDE's go-to-definition into\n`@agent-compose/sdk` — `sdk/src/index.ts` is the public surface and the\nfiles it re-exports from carry full inline docstrings.\n\n---\n\n## Errors\n\nAll non-2xx HTTP responses throw `AgentComposeError(status, message)`. The\n`message` is the server's `{ error: string }` body when present, falling\nback to the HTTP status text:\n\n```ts\nimport { AgentComposeError } from \"@agent-compose/sdk\";\n\ntry {\n await client.invoke(\"missing-workflow\");\n} catch (err) {\n if (err instanceof AgentComposeError && err.status === 404) {\n // template not registered\n }\n}\n```\n\n`invokeAndWait` throws `AgentComposeError(504, …)` on timeout for symmetry.\n","readmeFilename":"README.md"}