eSlider
168a0a3b53
OQ3: internal/duckstats + bin/qa/stats.go. Zig stays Ladybug-only. mikefarah/yq for small structured slices. Gitea #30.
35 lines
1.5 KiB
Markdown
35 lines
1.5 KiB
Markdown
# PicoClaw profile (reference agent)
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2dph is the memory/fact gate. Compose profile `picoclaw` runs the official
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PicoClaw gateway (`docker.io/sipeed/picoclaw:v0.3.1`) plus `brain-mcp` and the
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CPU reasoner. Default agent model is `qwen3.5:9b` (RAM path, D18). Weights stay
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in the reasoner volume, not in the 2dph image.
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No secrets in git: Ollama needs no key; MCP is local HTTP.
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```bash
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docker compose --profile picoclaw up -d
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# already serving :8630 / :11435:
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docker compose --profile picoclaw up -d --no-deps picoclaw
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```
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Gateway: `127.0.0.1:18790`. Brain MCP: `http://127.0.0.1:8630/mcp`.
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Cursor-style clients can use [deploy/picoclaw/mcp.json.example](../deploy/picoclaw/mcp.json.example).
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PicoClaw itself uses [deploy/picoclaw/config.json](../deploy/picoclaw/config.json)
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(`127.0.0.1` + host network — loopback publishes are not reachable via docker0).
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OpenAPI: `GET http://127.0.0.1:8630/openapi.json`.
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Before a factual reply: `search` → `get` → `audit`. `throttled` is not a
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negative finding. See `skills/picoclaw/SKILL.md`.
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System performance (MCP gates + qwen3.5:9b tool_call + PicoClaw gateway):
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```bash
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./qa/system_perf.py --json | yq '.gates'
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REASONER_MODEL=qwen3.5:9b ./qa/system_perf.py --reasoner --picoclaw --json | yq '.reasoner'
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```
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The default agent model is `qwen3.5:9b`. PicoClaw `context_window` is 8192
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(heuristic `max_tokens*4` at 512 is 2048, too small for MCP tool schemas).
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`request_timeout` is 600s for a CPU turn (tool_call + MCP search + answer).
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