Tianyi Cui
4209e4af3f
Model-driving ACP snapshot scenarios shipped both session.jsonl (the replay fixture) and session.golden.jsonl (the expected re-persisted log). For recorded scenarios the normalized fixture and golden were byte-identical — pure duplication. Remove session.golden.jsonl entirely: every model scenario now has at most one committed session-log artifact, session.jsonl, which doubles as the replay source AND the expected produced log. The snapshot test compares the replay run's persisted log against the session.jsonl fixture, normalizing BOTH sides — but each against its OWN volatile values, not a shared context. A raw harvested fixture bakes in the recording run's session id / cwd / timestamps, distinct from the live replay run's; since normalizeSessionLog scrubs cwd by exact string match, the fixture must be normalized against its own header (new fixtureContext helper) or its stale recorded cwd would leak unscrubbed and the compare would fail. The session side uses a normalized-string toEqual, NOT toMatchFileSnapshot, so a run never overwrites the fixture. Authored override scenarios (error-finish, cancel) now hold their expected produced log in session.jsonl. Verified llm-replay ignores the fixture for model chunks when an override exists: loadReplayScript() returns the override array and never reads config.file, so committing the full expected log there does not affect replay behavior. The required-fixture guard is now per-kind: every scenario needs input.json + stdout.golden.jsonl; model scenarios need session.jsonl; authored ones additionally need replay.override.json. Updates the ACP-snapshot-tests RFC to the reduced fixture set and moves the proposing RFC proposed -> implemented.
acp-agent example
The DeepSeek Harness coding agent exposed as an Agent Client Protocol (ACP) server over JSON-RPC stdio — drive it from Zed or any other ACP client.
pnpm run demo:acp # needs DEEPSEEK_API_KEY (repo-root .env or env)
This boots @deepseek-ai/dsh-acp over the shared provider/tool core (../base.yml), with agent-loop configured with no pre-created agents (ACP session/new creates them on demand) and JSONL session persistence (so session/load works).
stdout is the protocol
This example loads no stdout logger — stdout carries the JSON-RPC frames, and any other write corrupts them. Do not add @cordisjs/plugin-logger-console or a stdio UI here. Use a stderr exporter if you need logs.
Zed configuration
Add to your Zed settings.json under agent_servers:
{
"agent_servers": {
"DeepSeek Harness": {
"command": "pnpm",
"args": ["--dir", "/path/to/deepseek-harness", "run", "demo:acp"],
"env": { "DEEPSEEK_API_KEY": "sk-…" }
}
}
}
The editor sets each session's cwd to the project it opens; the agent's bash tools run there (see the per-session cwd note in packages/ui/acp), so launch the server from the harness repo with pnpm --dir … and let ACP carry the workspace path per session.
Snapshot tests (record-once / replay-deterministic)
This example is the home of the harness's snapshot tests — they boot this server as a real subprocess, drive it with a deterministic input script, and diff its normalized output against committed golden files. The model is made deterministic by @deepseek-ai/dsh-llm-replay, a function/namespace plugin that installs an llm/stream waterfall listener and short-circuits it, serving model streams reconstructed from a recorded session JSONL fixture (<scenario>/session.jsonl) — so replay needs no API key. The fixture IS the persisted session log: its assistant/chunk events carry every StreamChunk, so grouping them by (turn, step) reconstructs each stream() call (one model call per loop step). Recording is therefore "run the real agent once and harvest the .jsonl". The two failure modes not expressible as logged chunks — a pure throw before any chunk, and cancel/hang — use an optional <scenario>/replay.override.json sidecar (a ReplayEntry[] that replaces the derived script). A scenario that needs the agent to operate on existing files ships an optional <scenario>/workspace/ directory — the harness copies its contents into the temp cwd before the run (see workspace-edit). See docs/rfc/implemented/2026-06-19-acp-snapshot-tests.md for the full design.
MVP limitations
The bridge supports N concurrent sessions per connection, each in its own workspace cwd (RFC 011). Remaining limits: prompts support ACP's baseline text and resource_link blocks only, additionalDirectories and mcpServers are rejected, and the tool-permission gate is deferred (TODO(rfc010-permission-gate) — tools run with the executor's full authority). See packages/ui/acp/README.md for the full contract.