Tianyi Cui
e68496fd79
The snapshot tier was built single-session: dsh-llm-replay served calls from one global positional cursor, and the harness harvested one session log. A subagent runs as a second agent with its own session, so a parent→child scenario could neither replay deterministically nor harvest the child's log. This resolves the TODO(subagent-snapshots) deferral from the subagent RFC. - Stamp the calling session id onto the model request: GenerateOptions.sessionId (typed Branded<'SessionId'> to avoid the dsh-llm↔dsh-session cycle), set by the agent loop from agent.session.id. Adapters ignore it; an llm/stream listener routes by it. - Key replay per session: dsh-llm-replay loads the parent log plus one per child (childFiles / $DSH_SNAPSHOT_CHILD_FILES), derives a script per recorded session, and binds each live (freshly-random) session to a recorded script by first-call order — parent first (earliest createdAt, first to stream). Keys by WHO calls, so it survives a future concurrent/backgrounded subagent; a global cursor would not. An unrecorded extra session fails loud. - Harvest every log: the harness collects all .jsonl across cwd buckets, ordered primary-first (top-level, then children by createdAt), and RunResult exposes the plural sessionLogs. The spec writes each back on record (session.jsonl + session.<n>.jsonl) and diffs each against its fixture on replay. - Wire the subagent seam + spawn + fork + tool into the acp-agent example (both cordis configs) and add two nested scenarios recorded against the real API: subagent-spawn (parent + 1 child) and subagent-multi (parent + 2 children, 3 sessions). Both replay keyless in the default gate. A new RFC documents the design (docs/rfc/implemented/testing/). Single-session replay is unchanged (a call with no sessionId is one anonymous primary session). TODO follow-up: a dedicated branded-ids package could own the SessionId brand and dissolve the cross-package cycle note; out of scope for this testing PR.
75 lines
3.0 KiB
YAML
75 lines
3.0 KiB
YAML
# The acp-agent plugin tree: the ACP server. Also the snapshot RECORD config
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# (the dsh-acp-agent bin selects it for DSH_SNAPSHOT=record): a real llm-deepseek
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# run whose persisted log the snapshot harness harvests. Just the two swappable
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# backends — the DeepSeek adapter and the local bash executor — plus the ACP
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# server app (@deepseek-ai/dsh-acp-agent), which bundles the agent-core spine,
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# JSONL persistence, and the ACP bridge.
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#
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# CRITICAL: this tree loads NO stdout logger and NO hmr — stdout is reserved for
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# the ACP JSON-RPC protocol (see packages/ui/acp). That guarantee is now a
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# property of @deepseek-ai/dsh-acp-agent (it contains no logger entry), not a
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# leaf convention: there is no logger here to get wrong.
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#
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# Requires DEEPSEEK_API_KEY (and optionally DEEPSEEK_BASE_URL) — the
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# dsh-acp-agent bin loads the gitignored repo-root .env first (on STDERR only).
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# The DeepSeek adapter.
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- id: llm-deepseek
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name: '@deepseek-ai/dsh-llm-deepseek'
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config:
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apiKey: !!js process.env.DEEPSEEK_API_KEY
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baseURL: !!js process.env.DEEPSEEK_BASE_URL
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models:
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- deepseek-v4-flash
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- deepseek-v4-pro
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# Local bash executor (the agent's only tool, via agent-core's tool-bash schema).
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- id: bash
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name: '@deepseek-ai/dsh-bash-local'
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config:
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timeoutMs: 60000
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# The ACP server app: the agent-core spine + JSONL persistence + the ACP bridge.
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# Persistence root: $DSH_SNAPSHOT_SESSIONS_ROOT when the snapshot harness sets it
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# (so it can harvest / isolate the log), else ./.sessions for the demo.
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- id: acp-agent
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name: '@deepseek-ai/dsh-acp-agent'
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config:
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model: deepseek-v4-flash
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persistenceRoot: !!js process.env.DSH_SNAPSHOT_SESSIONS_ROOT ?? './.sessions'
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systemPrompt: |
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You are a coding assistant driven over the Agent Client Protocol.
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Your tools are bash (plus bash_output/bash_kill for background tasks)
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and subagent. Do ALL file operations through bash: read with
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cat/sed/head, search with grep, write with heredocs (cat <<'EOF' >
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file), edit with sed or a rewrite. Each bash call runs in a fresh
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shell — pass workdir instead of cd. Check the [exit code: N] marker;
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verify your work. Keep answers brief and factual.
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Use the subagent tool to delegate a focused, self-contained subtask to
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a fresh child agent (it works in its own context and returns only its
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final result) — give it a complete, standalone instruction.
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# The subagent seam + both in-process backends + the model-facing `subagent`
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# tool, as leaf entries after the app (which provides ctx.agents/ctx.tools). The
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# tool is bound to the `spawn` backend (a fresh child); the `fork` backend is
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# loaded too so a multi-child scenario can exercise both transports.
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- id: subagent
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name: '@deepseek-ai/dsh-subagent'
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- id: subagent-spawn
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name: '@deepseek-ai/dsh-subagent-spawn'
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config:
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providerName: spawn
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- id: subagent-fork
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name: '@deepseek-ai/dsh-subagent-fork'
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config:
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providerName: fork
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- id: tool-subagent
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name: '@deepseek-ai/dsh-tool-subagent'
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config:
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provider: spawn
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