sensing-track

# Sensing Event History ## Quick Start The primary data source is the **flow events JSONL** at `/root/local/flow_events_YYYY-MM-DD.jsonl`. Each file covers one calendar day (7-day retention, no size-rotation mid-day). Use Bash + `jq` to query it. > **Important:** Always use the absolute path `/root/local/` — the `read` tool cannot access files outside the workspace, so use `exec` (Bash) for all JSONL queries. Persistent camera snapshots are stored under `/var/lib/lelamp/snapshots/sensing_<prefix>/<ms>.jpg` (72h TTL, 50 MB cap) — one subdir per event kind: | Event type | Folder | |---|---| | `presence.enter`, `presence.leave` | `sensing_face/` | | `motion.activity` | `sensing_motion_activity/` | | `emotion.detected` | `sensing_emotion/` | Reference these when the user asks what happened visually. ## JSONL format Each line is a JSON object: ```json {"kind":"enter","node":"sensing_input","ts":1712345678.123,"seq":42,"trace_id":"run-abc","data":{"type":"presence.enter","message":"Person detected — 1 face(s) visible (friend (gray))\n[snapshot: /var/lib/lelamp/snapshots/sensing_face/1712345678123.jpg]"},"version":"1.2.3"} {"kind":"exit","node":"sensing_input","ts":1712345678.456,"seq":43,"trace_id":"run-abc","duration_ms":332,"data":{"path":"agent","run_id":"run-abc"},"version":"1.2.3"} ``` Key fields: - `node` — filter on `"sensing_input"` for sensing events - `kind` — `"enter"` = event received, `"exit"` = event processed (with `duration_ms`) - `data.type` — event type: `presence.enter`, `presence.leave`, `motion`, `motion.activity`, `sound`, `light.level`, `voice`, `voice_command`, `emotion.detected`, `speech_emotion.detected` - `data.message` — natural-language description; may contain `[snapshot: /var/lib/lelamp/snapshots/sensing_<prefix>/<ms>.jpg]` - `data.path` — in `exit` records: `"agent"` (forwarded), `"local"` (handled locally), or has `"error"` key (failed/dropped) - `ts` — Unix timestamp (seconds with fractional ms) - `trace_id` — correlates enter/exit and links to agent turn ## Tools **Bash** — `jq`, `cat`, date arithmetic. No writes. --- ## Query recipes ### Timezone — always set before date arithmetic ```bash export TZ=$(cat /etc/timezone) ``` ### All sensing events in a time range ```bash export TZ=$(cat /etc/timezone) DATE="$(date +%Y-%m-%d)" FROM_TS=$(date -d "$DATE 22:00:00" +%s) TO_TS=$(date -d "$DATE 23:59:59" +%s) jq -c 'select(.node=="sensing_input" and .kind=="enter" and .ts >= '"$FROM_TS"' and .ts <= '"$TO_TS"')' \ "/root/local/flow_events_${DATE}.jsonl" ``` ### Events of a specific type in the last N hours Use `"motion"` for raw motion, `"motion.activity"` for activity analysis (LeLamp-categorised — bucket names `drink`/`break` and raw Kinetics sedentary labels like `using computer`, `writing`, `reading book`). Most queries want both: ```bash export TZ=$(cat /etc/timezone) SINCE=$(date -d "1 hour ago" +%s) TODAY=$(date +%Y-%m-%d) jq -c 'select(.node=="sensing_input" and .kind=="enter" and .ts >= '"$SINCE"' and (.data.type=="motion" or .data.type=="motion.activity"))' \ "/root/local/flow_events_${TODAY}.jsonl" ``` ### Any activity in the last N minutes ```bash export TZ=$(cat /etc/timezone) SINCE=$(date -d "30 minutes ago" +%s) TODAY=$(date +%Y-%m-%d) jq -c 'select(.node=="sensing_input" and .kind=="enter" and .ts >= '"$SINCE"')' \ "/root/local/flow_events_${TODAY}.jsonl" ``` ### Presence events only (who came by) Names in messages are lowercase (`friend (gray)`). Use `test()` with `"i"` flag for case-insensitive search: ```bash TODAY=$(date +%Y-%m-%d) # All presence events jq -c 'select(.node=="sensing_input" and .kind=="enter" and (.data.type=="presence.enter" or .data.type=="presence.leave"))' \ "/root/local/flow_events_${TODAY}.jsonl" # Search for a specific person (case-insensitive) jq -c 'select(.node=="sensing_input" and .kind=="enter" and .data.type=="presence.enter" and (.data.message | test("gray";"i")))' \ "/root/local/flow_events_${TODAY}.jsonl" ``` ### Events spanning multiple days ```bash export TZ=$(cat /etc/timezone) YESTERDAY=$(date -d "yesterday" +%Y-%m-%d) TODAY=$(date +%Y-%m-%d) cat "/root/local/flow_events_${YESTERDAY}.jsonl" "/root/local/flow_events_${TODAY}.jsonl" \ | jq -c 'select(.node=="sensing_input" and .kind=="enter" and .ts >= '"$FROM_TS"' and .ts <= '"$TO_TS"')' ``` ### Dropped events (agent was busy) ```bash TODAY=$(date +%Y-%m-%d) jq -c 'select(.node=="sensing_input" and .kind=="exit" and .data.error != null)' \ "/root/local/flow_events_${TODAY}.jsonl" ``` ### List snapshots (72h TTL — older files may be purged) Snapshots are bucketed into `sensing_face/` (presence), `sensing_motion_activity/`, `sensing_emotion/`. Recurse into subdirs: ```bash # Most-recent snapshots across all categories find /var/lib/lelamp/snapshots -type f -name '*.jpg' -printf '%T@ %p\n' | sort -rn | head -20 | cut -d' ' -f2- # Only a specific category ls -lt /var/lib/lelamp/snapshots/sensing_motion_activity/ | head -20 ``` ### Pose buckets (posture history) Posture snapshots are NOT in `/var/lib/lelamp/snapshots/` — they live in tmp under a per-window bucket layout at `/tmp/lamp-sensing-snapshots/sensing_pose/buckets/<bucket_id>/`. A bucket only exists when a tumbling window closed with bad posture (`bad_ratio >= POSE_BAD_RATIO`). Kept buckets survive ~2 days (`POSE_BUCKET_KEEP_S`); windows that didn't fire a nudge are deleted immediately, so the buckets you can see are by definition "bad posture" sessions. Each kept bucket contains: - `<sample_ts>_<score>.jpg` — annotated frame per sample (skeleton overlay + RULA score) - `bucket.json` — manifest: - `bucket_id`, `window_start_ts`, `window_end_ts`, `kept: true` - `summary` — same shape as the `[posture_summary:]` block on `motion.activity` (`bad_ratio`, `dominant_region`, `samples`, …) - `samples[]` — `{ts, score, risk_level, filename, left, right}` (per-side RULA body_scores + angles) - `worst_snapshots[]` — pre-selected worst filenames (the ones Lamp auto-attaches to `/dm` on posture nudges) ```bash # List recent buckets (newest first) ls -lt /tmp/lamp-sensing-snapshots/sensing_pose/buckets/ | head -10 # Read a specific bucket's manifest jq . /tmp/lamp-sensing-snapshots/sensing_pose/buckets/1779259742/bucket.json # Buckets that closed in the last 2 hours find /tmp/lamp-sensing-snapshots/sensing_pose/buckets -maxdepth 1 -type d -mmin -120 -name '[0-9]*' | sort # Worst-frame paths from the latest kept bucket LATEST=$(ls -t /tmp/lamp-sensing-snapshots/sensing_pose/buckets/ | head -1) jq -r '.worst_snapshots[]' "/tmp/lamp-sensing-snapshots/sensing_pose/buckets/${LATEST}/bucket.json" \ | sed "s|^|/tmp/lamp-sensing-snapshots/sensing_pose/buckets/${LATEST}/|" # Today's bad-posture sessions — bucket id == window_start unix-seconds TODAY_START=$(date -d "today 00:00" +%s) for b in /tmp/lamp-sensing-snapshots/sensing_pose/buckets/*/bucket.json; do jq --arg start "$TODAY_START" 'select((.window_start_ts | floor) >= ($start | tonumber)) | {bucket_id, dominant: .summary.dominant_region, bad_ratio: .summary.bad_ratio, started: .window_start_ts}' "$b" done ``` Note: `motion.activity` event messages contain `[pose_bucket: <id>]` and `[pose_worst: <fn1>,<fn2>,...]` markers — parse these out of `data.message` when you need to map a sensing_input record to its bucket. Markers are present whenever a posture nudge folded in. --- ## Fallback: system log For detailed debugging or when you need Go-side log context (errors, warnings, lifecycle details), fall back to `${LAMP_LOG:-/var/log/lamp.log}`: ```bash LOG="${LAMP_LOG:-/var/log/lamp.log}" sed 's/\x1b\[[0-9;]*m//g' "$LOG" | grep "sensing event received" ``` The system log uses lumberjack rotation (1 MB cap, 3 backups) — it may miss data during high traffic. Use it only when JSONL doesn't have enough detail, or when investigating bugs. --- ## Mood history A dedicated mood history log tracks **user mood** per user. Only the user's emotional state is logged — not system events or lamp emotions. Each user's mood data lives in their own directory. **Read API:** ```bash # Current user's mood history (auto-detects who's present) curl -s "http://127.0.0.1:5000/api/openclaw/mood-history?date=$(date +%Y-%m-%d)&last=100" # Specific user's mood history curl -s "http://127.0.0.1:5000/api/openclaw/mood-history?user=gray&date=$(date +%Y-%m-%d)&last=100" ``` **Write:** Follow the **Mood** skill to log user mood from camera or conversation. ```json {"ts":1776138500,"seq":1,"hour":10,"mood":"happy","source":"camera","trigger":"laughing"} {"ts":1776139200,"seq":2,"hour":10,"mood":"stressed","source":"conversation","trigger":"user said feeling overwhelmed"} ``` Storage: `/root/local/users/{name}/mood/YYYY-MM-DD.jsonl` (30-day retention). --- ## Rules - **Never write to any log file** — they are owned by the system. - **Answer conversationally** — translate results into natural language. Never dump raw JSON to the user. - **Handle empty results** — if no matching events, say "I didn't detect any [type] events in that window." - **Mention dropped events when relevant** — check `exit` records with `data.error` for events the agent missed. Mention it: "There was motion at 10:45 PM but I was mid-conversation and missed it." - **Resolve relative times** — translate "last hour", "this morning", "while I was away" into concrete Unix timestamps using `date -d` before filtering. - **Span multiple days** — for questions covering more than today, `cat` multiple JSONL files together. - **Parse the message field** for who/what details — `friend (gray)`, `friend (chloe)`, `stranger (stranger_1)`, `Large movement detected`, etc.