Files
deepseek-harness/examples
Hypatia May cec32faa4e refactor(compact): turn-agnostic retention + dedicated agent/pre-request seam
Reform the compaction blueprint so a runaway turn survives and the design
stops drifting across review rounds:

- Drop in-flight-turn protection ("layer 2"). Retention is a uniform tail→head
  whole-unit walk; the only structural guard is step-alignment. A single turn
  that alone exceeds the window now compacts its own early closed steps instead
  of being retained verbatim (the failure mode that motivated this).
- Move auto-compaction off the agent/request waterfall onto a new awaited
  agent/pre-request loop seam, fired before history derivation. Compaction
  mutates the surface; the loop derives once from the result — no double-derive,
  and a listener structurally cannot act on not-yet-derived messages.
- Tighten compactIfNeeded to required (session, system, model, signal).
- Enforce a single-pass convergence invariant in resolveConfig: reject configs
  where summarizationMaxTokens + retainTokens exceeds the threshold, so a
  compaction can never immediately re-trigger.
- Document the crash vs recoverable failure taxonomy; core session repair stays
  compaction-agnostic (a log-only orphaned compact/start is inert).
- Wire dsh-compact-basic into examples/coding-agent and add a with-key
  compaction e2e (compaction's first real-world exercise + runaway net).
- Rewrite the RFC to encode the blueprint and move it to implemented/.

The runaway-turn snapshot is a named deferred follow-up: dsh-llm-replay cannot
yet serve the interleaved summarization model call.
2026-06-26 08:59:33 +08:00
..

Examples

Runnable demos (not workspaces) that showcase how the harness is wired. Each example is now a thin leaf: a cordis.yml that picks the swappable backends (an LLM adapter, a bash executor) and loads ONE app package, plus any demo-only mocks. The composition — the spine, the front-door cluster, and the boot glue — lives in the app packages (@deepseek-ai/dsh-stdio-agent, @deepseek-ai/dsh-acp-agent) and the @deepseek-ai/dsh-agent-core bundle they share. There is no start.ts; the demo:* scripts invoke each app package's bin.

echo-agent

A mock model + echo tool on the stdio chat app — the all-mock skeleton. The leaf swaps dsh-stdio-agent's LLM backend to a local mock-echo adapter and adds a local echo tool. Demonstrates:

  • A thin leaf cordis.yml loading the @deepseek-ai/dsh-stdio-agent app
  • Registering a mock LlmAdapter (streaming scripted responses)
  • Registering a tool via ctx.tools.register()
  • "Swap the backend, keep the app" — the only difference from coding-agent is the adapter

Run with: pnpm run demo:echo. When prompted, type "echo " to trigger a tool call round-trip.

coding-agent

The real thing: DeepSeek V4 + the bash tool suite on the same @deepseek-ai/dsh-stdio-agent app. Where echo-agent proves the skeleton with mocks, this is a usable coding assistant.

Run with: pnpm run demo:coding (needs DEEPSEEK_API_KEY in the environment or a gitignored repo-root .env). See coding-agent/README.md for details.

acp-agent

The same coding agent exposed as an Agent Client Protocol (ACP) server over JSON-RPC stdio, via the @deepseek-ai/dsh-acp-agent app — drive it from Zed or any other ACP client. Also the home of the keyless snapshot tests.

Run with: pnpm run demo:acp (needs DEEPSEEK_API_KEY). See acp-agent/README.md for the Zed setup and the snapshot-test design.