5077a7c057
Nasr workspace path typo fixed (2026-04-22). Snapshot of Nasr (Smithers) workspace: SOUL, USER, IDENTITY, MEMORY, AGENTS, HEARTBEAT. Skills manifest: 18 skills on disk, none yet in git. progress.json: per-agent status tracking (nasr, parlo, peter, m2, alfred, gunnar). docs/concept.md: full architecture — 3 tracks (memory, config, secrets). CLAUDE.md: project overview, data sources, restore order, gotchas. Kickoff Friday 2026-04-25.
131 lines
4.7 KiB
Markdown
131 lines
4.7 KiB
Markdown
# Restore Harness — Concept & Architecture
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Explored 2026-04-22. Kickoff Friday 2026-04-25.
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## The problem
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OpenClaw agent state lives in 3 layers that drift from each other:
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```
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Layer 1: Coolify env vars → rebuild source but incomplete, no skill manifest
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Layer 2: /agent_home volume → actual live state, ephemeral if volume lost
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Layer 3: m2-config git repo → intended source but not always synced
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```
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On Nasr's container: 18+ skills installed manually, not in any env var or git.
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On rebuild: those skills vanish. Projects, SOUL.md etc. survive (volume), memory doesn't.
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## 3 restoration tracks
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### Track 1: Memory (episodic context)
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Data sources (all on spark3:/home/m2spark3/telegram/):
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- `m2.zip` — 85MB uncompressed, 38 HTML files — FULL m2 DM history from day 1
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- `parlobyg.zip` — 41MB — Parlo's full chat
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- `machine.machine.zip` — 2.7MB — Machine.Machine group chat (GMI clinic context)
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- `m2-devops.zip` — 80KB — devops channel
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Tool already exists: `agent.memory.system/ingest/telegram_export.py` (stdlib only)
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Outputs JSONL matching the memory API schema.
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Pipeline per agent:
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```bash
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# On spark3
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cd /home/m2spark3/telegram
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python3 -m ingest.telegram_export m2.zip m2-all.jsonl --agent-id m2 --chat-slug m2-dm
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# Filter for agent-specific context, then POST to memory API:
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curl -s http://172.18.0.20:8000/store -X POST \
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-H "Content-Type: application/json" \
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-d @m2-filtered.jsonl
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```
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spark4 also has 22,744 restored points (read-only, Redis degraded) — can be queried
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and selectively copied to m2 memory API per agent_id.
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### Track 2: Workspace files (config-as-code)
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Already have snapshot for Nasr in agents/nasr/ (done 2026-04-22).
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`snapshot.sh` (to build):
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```bash
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# Run from m2 against any named agent
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AGENT=nasr
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CONTAINER=$(docker ps --filter name=$AGENT --format '{{.Names}}' | head -1)
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for f in SOUL.md USER.md IDENTITY.md MEMORY.md AGENTS.md; do
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docker cp $CONTAINER:/home/developer/.openclaw/workspace/$f agents/$AGENT/$f
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done
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# Export sanitized openclaw.json (strip secrets)
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docker exec $CONTAINER cat ~/.openclaw/openclaw.json | \
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python3 scripts/sanitize-config.py > agents/$AGENT/openclaw.json
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# Skills manifest
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docker exec $CONTAINER ls ~/.openclaw/skills/ > agents/$AGENT/skills.txt
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```
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`restore.sh` (to build):
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```bash
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AGENT=nasr
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CONTAINER=$(docker ps --filter name=$AGENT --format '{{.Names}}' | head -1)
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for f in SOUL.md USER.md IDENTITY.md MEMORY.md AGENTS.md; do
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docker cp agents/$AGENT/$f $CONTAINER:/home/developer/.openclaw/workspace/$f
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done
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# Inject secrets from Vaultwarden, then restart gateway
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docker exec $CONTAINER supervisorctl restart openclaw-gateway
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```
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### Track 3: Secrets (Vaultwarden)
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Vaultwarden is already deployed. Pattern:
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- Collection: "fleet-agents"
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- Item per agent: `agent/nasr` with fields:
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- TELEGRAM_BOT_TOKEN
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- ANTHROPIC_API_KEY
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- OPENROUTER_API_KEY
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- CEREBRAS_API_KEY
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- (nasr-specific) MINIMAX_API_KEY, ZAI_API_KEY
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In sanitized openclaw.json, reference: `"token": "vault:agent/nasr/TELEGRAM_BOT_TOKEN"`
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Restore script fetches via: `bw get password "agent/nasr/TELEGRAM_BOT_TOKEN"`
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## Skills git strategy
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Skills without repos (all of Nasr's custom ones):
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- clinical-pathway, patient-pathway, quantum-trading, trading-app-dev
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- 2dexy-sync, ml-training, xcode-remote, build-verify, cursor-agent
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Create under: `git.machinemachine.ai/nasr/{skill-name}`
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Each skill dir: `SKILL.md` + executable script(s)
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Skills with likely existing repos (fleet-wide, in machine-machine org):
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- m2-memory, rlm-memory, unified-search, agency-agents, harness-engine
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- intent-elicit, intent-router, spec-discovery, mm-pdf
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## GMI agent (Nasr's proposal)
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`machine.machine.zip` has the Machine.Machine group chat — this is where GMI clinic
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discussions happened. Nasr has a `GMI-Cancer-Pathways/` project on disk with:
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- Breast-Cancer-Pathway.md + Visual.html
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- Colorectal-Cancer-Pathway.md + Visual.html
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- NSCLC-Pathway.md
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A dedicated GMI sub-agent inside Smithers (or a separate OpenClaw agent) could:
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1. Hold GMI-specific context in its memory collection
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2. Handle clinical pathway queries
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3. Interface with any GMI-specific tools
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First step: ingest machine.machine.zip filtered for GMI context into `agent_memory_nasr`.
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## Restore order
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1. nasr — container live, workspace files snapshotted ✅, memory pending
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2. parlo — parlobyg.zip ready, container live
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3. peter — in m2.zip, custom image container live
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4. m2 — m2.zip is the primary source, full history
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## Open questions for Friday kickoff
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1. Nasr-specific Telegram export? (separate @nasr_s_bot history zip)
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2. Vaultwarden admin access from m2 (bw CLI setup)
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3. Forgejo token for creating skill repos (m2 user, id=1)
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4. spark4 Redis fix — make it writable again or retire as archive-only
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5. Which skills were created vs cloned — affects whether we need to export code to git
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