Files
deepseek-harness/packages/core/agent-loop
Tianyi Cui d02e9f1bd6 Reorganize packages into a modular hierarchy
Move the 18 flat packages/<name> packages into role-grouped dirs:
core/, llm/, bash/, session-persistence/, ui/, support/. Group dirs are
pure containers; each package keeps its @deepseek-ai/dsh-* name.

Collapse the per-package tsconfig paths maps (base + typecheck) into one
@deepseek-ai/dsh-* wildcard with a candidate per group, and derive the
publint list from the hierarchy. Update all depth-coupled globs/configs
(workspace, tsdown, vitest, eslint, knip, tsconfig includes/refs,
per-package tsconfigs, generators, doc-script scopes, type-equiv manifest)
and the cross-package/script relative imports in tests.

Fix doc-typecheck's workspacePaths() to parse tsconfig JSONC via the
TypeScript API instead of a regex comment-strip, which corrupted the
new wildcard `/*/` path candidates.

WIP: doc cross-links and package/RFC docs still to update.
2026-06-20 22:55:20 +08:00
..

dsh-agent-loop

THE concrete agent plugin: ReactLoopAgent and the loop driver. Implements the Agent interface and drives the session/turn/step lifecycle.

This is the only package in the harness that contains concrete loop logic. Everything else is an abstract service or a plugin against extension seams — new behavior goes into plugins, not here.

Service: AgentLoop (ctx key: agentLoop)

Public API

  • ctx.agentLoop.create(id: string, options?: AgentOptions): ReactLoopAgent — config-driven create: an agent on a fresh per-run session id ${id}-session-<uuid> (no cwd). Used for cordis.yml-configured agents. The per-run uuid avoids colliding with the on-disk log a prior run materialized once a durable persistence backend is loaded; each run is a new session (a deliberate demo simplification — a real resume-or-create policy is a TODO). Disposed with the calling fiber.

AgentLoop also implements the AgentFactory seam and registers itself via ctx.agents.setFactory(this), so plugins create/resume agents through ctx.agents (the interface):

  • ctx.agents.create({ agentId, sessionId, meta?, agentOptions? }): AgentHandle — programmatic create on a caller-supplied sessionId (e.g. an ACP-generated id), NOT ${id}-session. Returns an AgentHandle — the owner disposes it to tear down exactly this agent (stop loop + await quiescence + unregister + remove session).
  • ctx.agents.resume({ agentId, resumeSessionId, agentOptions? }): Promise<AgentHandle> — load a persisted session via ctx.sessionPersistence (session persistence) and resume an agent on it. The live session id is the resumed id; turn numbering and derived history continue from the loaded log. Requires a session-persistence backend (NOT hard-injected — non-persistent demos still work; resume rejects with a clear error when persistence is absent). Returns an AgentHandle.

The config-driven ctx.agentLoop.create() path keeps its agent owned by the loop fiber (it discards the handle) — only the programmatic factory callers (the ACP bridge) hold a handle and own per-agent teardown.

Injected services

agents, sessions, llm, tools, systemPrompt — all five interface services.

Configuration (schemastery)

interface Config {
  agents: Array<{
    id: string                 // required
    model?: string
    systemPrompt?: string
  }>
}

Agents listed in config are auto-created at startup.

Classes

  • ReactLoopAgent — the concrete Agent implementation. Owns the inbox (Inbox), the per-step AbortController, and the loop driver. Everything observable happens through session events and the agent/* event taxonomy.
  • Inbox — per-agent queued + steering FIFOs (enqueue, steer, drainQueued, drainSteering, waitForQueued).

Loop lifecycle (loop.ts)

One invocation of runLoop() drives one agent for its whole lifetime:

forever:
  wait for queued messages (idle)
  TURN (error-contained):
    drain queued → 'turn/start' → session('user/message')
    STEP loop:
      drain steering
      assembly = systemPrompt.assemble()
      request = waterfall agent/request
      stream llm.stream(request) → session('assistant/chunk')
      message = waterfall agent/step-result
      session('assistant/message')
      each tool-call: session('tool/call') → tools.execute() → session('tool/result')
      drain steering → session('steering/message')
      cont = waterfall agent/turn-continuation
      if !cont: break
    session('turn/end')
    await session/flush
    re-enqueue leftover steering as queued
  idle unless more queued

Error containment: a throwing plugin ends the turn, never the loop. Dispose mid-turn emits agent/status('disposed') and ends with reason disposed. A step that hits the model's output-token ceiling makes the turn end max-tokens (the rule: any max-tokens step in the turn surfaces as max-tokens; disposed/aborted/error still take precedence) — distinct from a clean completed stop.

Cancellation: agent.abort() aborts only the in-flight step; agent.cancel() is the broad verb — it clears the queued + steering FIFOs, aborts the in-flight step, and drives a turn-scoped marker the driver checks at every point a turn could start or continue (right after the idle wait, after the running flip, before each step, and at the continuation gate) so a turn about to start is dropped. A cancelled turn ends aborted; a queued-but-not-started prompt never runs and cannot be batched into the cancelled turn. The marker is reset once per loop iteration, so a cancel governs exactly one turn and never leaks onto a later prompt.

What is NOT here

Everything that goes beyond "call the model, run the tools, repeat" belongs to plugins listening on the event taxonomy:

  • Hooks: agent/request, agent/step-result, tools/execute, agent/turn-continuation
  • Compaction: agent/request
  • Sandbox, permission, plan mode: tools/execute
  • Sub-agents: TODO seam on AgentLoop.create()
  • Persistence: session/event + session/flush
  • UI: agent/stream-chunk + agent/* events