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Store valid_from/valid_to on leafs and filter search by calendar day without overloading D16 source staleness; stack start/start-assistant wires brain + PicoClaw.
1.9 KiB
PicoClaw profile (reference agent)
2dph is the memory/fact gate. Compose profile picoclaw runs the official
PicoClaw gateway (docker.io/sipeed/picoclaw:v0.3.1) plus brain-mcp and the
CPU reasoner. Default agent model is qwen3.5:9b (RAM path, D18). Weights stay
in the reasoner volume, not in the 2dph image.
No secrets in git: Ollama needs no key; MCP is local HTTP.
bin/stack/start-assistant
bin/stack/start-assistant --no-attach
bin/stack/start-assistant -- -m "search the 2dph brain for LadybugDB"
bin/stack/status
bin/stack/stop
start-assistant reuses a healthy brain on :8630, starts the CPU reasoner,
pulls qwen3.5:9b if missing, brings up the gateway with --no-deps picoclaw,
then picoclaw agent (MCP search → get → audit). Gateway-only Compose:
docker compose --profile picoclaw up -d
# already serving :8630 / :11435:
docker compose --profile picoclaw up -d --no-deps picoclaw
Gateway: 127.0.0.1:18790. Brain MCP: http://127.0.0.1:8630/mcp.
Cursor-style clients can use deploy/picoclaw/mcp.json.example.
PicoClaw itself uses deploy/picoclaw/config.json
(127.0.0.1 + host network — loopback publishes are not reachable via docker0).
OpenAPI: GET http://127.0.0.1:8630/openapi.json.
Before a factual reply: search → get → audit. throttled is not a
negative finding. See skills/picoclaw/SKILL.md.
System performance (MCP gates + qwen3.5:9b tool_call + PicoClaw gateway):
./qa/system_perf.py --json | yq '.gates'
REASONER_MODEL=qwen3.5:9b ./qa/system_perf.py --reasoner --picoclaw --json | yq '.reasoner'
The default agent model is qwen3.5:9b. PicoClaw context_window is 8192
(heuristic max_tokens*4 at 512 is 2048, too small for MCP tool schemas).
request_timeout is 600s for a CPU turn (tool_call + MCP search + answer).