{"type":"session","version":3,"id":"18dfbad6-95d5-4459-9c3e-858b6ec6e3f8","timestamp":"2026-05-04T01:06:37.689Z","cwd":"/home/rurouni"} {"type":"model_change","id":"7dc0f9bb","parentId":null,"timestamp":"2026-05-04T01:06:37.778Z","provider":"openai-codex","modelId":"gpt-5.5"} {"type":"thinking_level_change","id":"e0d9066c","parentId":"7dc0f9bb","timestamp":"2026-05-04T01:06:37.778Z","thinkingLevel":"off"} {"type":"custom","customType":"model-snapshot","data":{"timestamp":1777856797785,"provider":"openai-codex","modelApi":"openai-codex-responses","modelId":"gpt-5.5"},"id":"a89411c8","parentId":"e0d9066c","timestamp":"2026-05-04T01:06:37.785Z"} {"type":"message","id":"f5ccf5f9","parentId":"a89411c8","timestamp":"2026-05-04T01:06:37.791Z","message":{"role":"user","content":[{"type":"text","text":"Goal:\nBuild the best OpenClaw memory and context system with token cost in mind. I want fast memory retrieval, low prompt injection size, and relevant context only. Do not build a bloated memory setup that injects everything every turn.\n\nTarget architecture:\n\nRUNTIME:\n1. Mem0 OSS + Qdrant\n - Main long-term memory brain\n - Self-hosted\n - Used for personal memory, project memory, decisions, preferences, commands, and facts\n - Must use strict retrieval and injection limits\n\n2. Qwen3-Embedding-0.6B\n - Use as the embedder\n - Prefer GPU acceleration if it fits safely\n - Keep it small and efficient\n - Do not let it starve my main chat model of VRAM\n - If GPU memory is too tight, fall back to CPU automatically or explain the tradeoff before changing anything\n\n3. QMD Light\n - Workspace/document search only\n - Use BM25 search first\n - Use vector search only as fallback\n - Do not use reranker\n - Do not use heavy qmd query mode by default\n - No GPU reranking\n\n4. Lossless Claw / LCM\n - Long-session context compaction\n - DAG summaries\n - Version pinned\n - Keeps conversation history from bloating prompt context\n\n5. OpenClaw base memory\n - Keep MEMORY.md tiny\n - Keep identity/personality files tiny\n - Do not inject all daily notes every turn\n - Do not inject giant Markdown memory files every turn\n\nMAINTENANCE:\n- Weekly memory hygiene:\n - duplicate merging\n - stale memory pruning\n - decay scoring\n - contradiction cleanup\n - promote important memories to pinned facts\n- Weekly backups:\n - Qdrant snapshots\n - Mem0 state/config\n - QMD indexes\n - OpenClaw memory files\n\nImportant token budget rules:\n- Normal turn memory injection target: 300–800 tokens\n- Project-heavy turn: 800–1,500 tokens\n- Hard max: 2,000 memory/doc tokens\n- Never inject full MEMORY.md, full daily notes, or full workspace docs every turn\n- Mem0 topK should start at 4–6\n- Mem0 injected memory should start at 512 tokens and max at 768 unless I manually change it\n- QMD retrieved snippets should only be injected when the user asks about docs, configs, commands, or files\n- LCM summaries should only be injected when the conversation is long enough to need them\n\nMemory ownership rules:\n- Mem0 owns long-term memory.\n- QMD owns workspace/document search.\n- LCM owns long-session conversation compaction.\n- OpenClaw base memory stays tiny.\n- Only one system should inject long-term memory into the prompt.\n- Avoid duplicate memory injection.\n\nStorage layout:\nUse these folders unless there is a better reason not to:\n\n/data/openclaw-memory/qdrant\n/data/openclaw-memory/mem0\n/data/openclaw-memory/qmd\n/data/openclaw-memory/cache\n/models/embeddings/Qwen3-Embedding-0.6B\n/backup/openclaw-memory\n/archive/openclaw-memory\n\nBefore changing anything:\n1. Inspect my current OpenClaw install and config.\n2. Detect how OpenClaw memory plugins are currently configured.\n3. Detect whether Docker/Podman is installed.\n4. Detect whether Qdrant is already installed.\n5. Detect whether Mem0 is already installed.\n6. Detect whether QMD is installed.\n7. Detect whether Lossless Claw / LCM is installed.\n8. Detect current GPU VRAM usage with nvidia-smi.\n9. Confirm where OpenClaw stores config, memory, plugins, and logs.\n10. Print a clear plan before making changes.\n\nImplementation requirements:\n- Prefer production-stable versions.\n- Version-pin anything that could break later.\n- Use /data for active databases and indexes.\n- Use /models for embedding model files.\n- Use /backup for backup snapshots.\n- Do not put big databases on the root partition.\n- Do not overwrite existing OpenClaw memory files without backing them up first.\n- Do not delete anything unless I explicitly approve it.\n- Create rollback steps.\n- Create health-check commands.\n- Create a simple status command/script if possible."}],"timestamp":1777856797790}} {"type":"custom_message","customType":"openclaw.runtime-context","content":"System: [2026-05-03 18:05:00 PDT] Elevated ASK - exec runs on host; approvals may still apply.\n\nConversation info (untrusted metadata):\n```json\n{\n \"chat_id\": \"telegram:7229867039\",\n \"message_id\": \"1522\",\n \"sender_id\": \"7229867039\",\n \"sender\": \"Raymond\",\n \"timestamp\": \"Sun 2026-05-03 18:06 PDT\"\n}\n```\n\nSender (untrusted metadata):\n```json\n{\n \"label\": \"Raymond (7229867039)\",\n \"id\": \"7229867039\",\n \"name\": \"Raymond\"\n}\n```","display":false,"details":{"source":"openclaw-runtime-context"},"id":"708512f3","parentId":"f5ccf5f9","timestamp":"2026-05-04T01:06:37.792Z"} {"type":"message","id":"817640bc","parentId":"708512f3","timestamp":"2026-05-04T01:06:40.905Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"id\":\"rs_02b86be3bb6b669e0169f7f11edd3c81969dfb0bd5a88fdbdd\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABp9_EfePGSCB1yR4fNyeYnF9z66tw2I9X6sz4VvH-urjfa34umarnSGlw1Y70x_Eh_hxZPp5Qza9FBimBw97KWH-btRKvlzWBdQZrIDfkVUvBcp9bVrn00Laip0BVIvh1HvwB73Bk9roWPrzlmMpJMKDG66rVZcrVypXeLyKTvDGiK9waMLdVrpczQcHaYgOFG0uh_YhKE6lVgRiGd1MsfmETs8RV9yVv4GydCSDhe4tUktBq5D6tz_DJ0uVN_0nJKpi8YJABsxJHkxhMDqBMJNmXYR-K6V-ZHuWDQj6RdKlhpfcv0Ggj7xng_rDViOEyBsYY4OojX4l0KRGE7P4IDjNZJQO3J66v2Gz6i6adwfKmlYxyiqsAEMzY2a8pp5zVH-sWbAsKaTrEwtoyfqlaDihozfcEdRJfPmso3y6ULQt9_SkOpEdqVo-8FqX775bj9Fio2GWWXRoWFTQygosVRiTXvZyUWvvRxu0eMnaeoizaIJsh8qbWtbtYQoUXdL0ivdQe7tVxtPvD6ta9SpRWZPZXARewn-_BOqFAueS4ctjQAVfQaJbl5JslCZdwW6Z2qQbd8RNO1NZ_DxfMD-1AoROn_ndEn1Mbw79dYdwE8Wx5VDfqG_HSTdhkmeaCuKB4NnSFpk-i8uJwLAEL4ttWwmJqSJgvou7S8eujVUrqxG8gdPsZSbbDk8vVeNeaGoGY4SqmTrBIoN65vOZag7eI-_Q9yvWaOBkUw0Qd5_bbrlEaqxdsvEb0nE-zfNvOIwefHcfnDRRdI5i_NBmgIslqR1MunTtCMb-QT-CnD3nopMfR0iccQfM-qFZh4TqB4nKk79OjFWgUj2XBBYiV6t1iqYesDF_eRxXxtILnHkv8v-XqXFhzzW3eJ0GsUhFubBDJUO0ONM848MgNhNEvepO6vGi05WJpv_fo4-pqdWYzHLw1iWcD8JMuVYLxbegjBHzoKEopt-dR1uAaBH2SFNVwUYX3fpLmdSGxX8jwemiGDqvNmEcyZ8OEB3_3FuSuOWu9p31mH3j2zHaYJrm6KOJaaRahhs_6H4uLbtrysWLcv2D4NRYrBSzoidLH8ta_9SKd9NS2OQKb73tzIjukiOO8dTWUkjrBYCoEphzH5GNPf130S_ZPO4Y8CRbBI7y68UITta-q2QMZMi-aN9vlELvvvxQH4ppS0_VRymqXxK00RS3-Bmv0=\",\"summary\":[]}"},{"type":"toolCall","id":"call_Jpvc7b83cc8VlghaC0Zskj4C|fc_02b86be3bb6b669e0169f7f11fb6f88196acd7813ac44dff94","name":"update_plan","arguments":{"plan":[{"step":"Recall existing memory/setup notes","status":"in_progress"},{"step":"Inspect OpenClaw config/install paths","status":"pending"},{"step":"Detect container/services/tools","status":"pending"},{"step":"Check GPU/VRAM and storage","status":"pending"},{"step":"Report findings and change plan","status":"pending"}]}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.5","usage":{"input":10944,"output":132,"cacheRead":3584,"cacheWrite":0,"totalTokens":14660,"cost":{"input":0.054720000000000005,"output":0.00396,"cacheRead":0.001792,"cacheWrite":0,"total":0.060472000000000005}},"stopReason":"toolUse","timestamp":1777856797792,"responseId":"resp_02b86be3bb6b669e0169f7f11e0bf08196a3a3326849e2fa66"}} {"type":"message","id":"2491b7dc","parentId":"817640bc","timestamp":"2026-05-04T01:06:40.979Z","message":{"role":"toolResult","toolCallId":"call_Jpvc7b83cc8VlghaC0Zskj4C|fc_02b86be3bb6b669e0169f7f11fb6f88196acd7813ac44dff94","toolName":"update_plan","content":[],"details":{"status":"updated","plan":[{"step":"Recall existing memory/setup notes","status":"in_progress"},{"step":"Inspect OpenClaw config/install paths","status":"pending"},{"step":"Detect container/services/tools","status":"pending"},{"step":"Check GPU/VRAM and storage","status":"pending"},{"step":"Report findings and change plan","status":"pending"}]},"isError":false,"timestamp":1777856800978}} {"type":"message","id":"99a2328c","parentId":"2491b7dc","timestamp":"2026-05-04T01:06:43.518Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_QMVN9YP2uh7Zm4wzjNjmvaMR|fc_02b86be3bb6b669e0169f7f122bd7081969d3994ed5b9f8acf","name":"memory_search","arguments":{"query":"OpenClaw memory QMD Mem0 Qdrant LCM embeddings current setup config storage GPU VRAM","maxResults":8,"corpus":"all"}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.5","usage":{"input":340,"output":48,"cacheRead":14336,"cacheWrite":0,"totalTokens":14724,"cost":{"input":0.0017000000000000001,"output":0.00144,"cacheRead":0.007168,"cacheWrite":0,"total":0.010308000000000001}},"stopReason":"toolUse","timestamp":1777856800980,"responseId":"resp_02b86be3bb6b669e0169f7f12156608196bd080e47529aff85"}} {"type":"message","id":"c7152b37","parentId":"99a2328c","timestamp":"2026-05-04T01:06:44.012Z","message":{"role":"toolResult","toolCallId":"call_QMVN9YP2uh7Zm4wzjNjmvaMR|fc_02b86be3bb6b669e0169f7f122bd7081969d3994ed5b9f8acf","toolName":"memory_search","content":[{"type":"text","text":"{\n \"results\": [\n {\n \"id\": \"d4f45f6f2d9b01457138bb6d6a34874506c44344dcd88679c8312f43ee6b56a9\",\n \"path\": \"MEMORY.md\",\n \"startLine\": 37,\n \"endLine\": 46,\n \"score\": 1,\n \"textScore\": 0.43467721792167235,\n \"snippet\": \"- OpenClaw builtin memory has embeddings but no reranking; QMD is the OpenClaw path to local BM25 + vectors + reranking/query expansion. Verify CPU-only behavior before enabling QMD or downloading models.\\n- Memory hygiene: keep active indexed markdown small. Active files should usually be `MEMORY.md`, `memory/YYYY-MM-DD.md`; archive raw/session fragments as `.txt`.\\n\\n## System / Storage / Admin\\n\\n- Storage: root/home on NVMe; `/backup` HDD; `/archive` HDD cold storage; `/models` Samsung SSD; `/data` RAID0 Intel SSDs; `/dev/shm/ai-hot` 16G tmpfs.\\n- `/home/rurouni/backups` symlinks to `/backup/rurouni/openclaw-backups`.\\n- AI storage env: HF/cache under `/data/cache/hf`; temp under `/data/tmp`; p\\n\\nSource: MEMORY.md#L37-L46\",\n \"source\": \"memory\",\n \"citation\": \"MEMORY.md#L37-L46\",\n \"corpus\": \"memory\"\n },\n {\n \"id\": \"33f1a5981d3b87f931f049f0d1e94b998a584f51ec307114663db1e8afa6635e\",\n \"path\": \"MEMORY.md\",\n \"startLine\": 1,\n \"endLine\": 19,\n \"score\": 1,\n \"textScore\": 0.6353243501957506,\n \"snippet\": \"# MEMORY.md — Ruruni Long-Term Memory\\n\\nCompact durable memory for Raymond’s main direct session. Keep this file lean: stable preferences, active setup, standing cautions, and current decisions only. Put raw/session details in `memory/YYYY-MM-DD.md`; archive low-value fragments as `.txt`.\\n\\n## Raymond / Style\\n\\n- Raymond; Pacific time. Assistant name: **Ruruni** 🗡️.\\n- Tone: casual, direct, warm, witty, technically sharp, privacy-protective, not yappy.\\n- Technical help: start with the answer/next action, use copy/paste commands, prefer safe/reversible steps, warn before risky/destructive/external actions.\\n- Preserve Raymond’s natural voice when rewriting. Key domains: Linux/Debian/CachyOS, serv\\n\\nSource: MEMORY.md#L1-L19\",\n \"source\": \"memory\",\n \"citation\": \"MEMORY.md#L1-L19\",\n \"corpus\": \"memory\"\n },\n {\n \"id\": \"7fd15436533cbba337df015874ab1b954949c5462722d88263ece85c94c1db29\",\n \"path\": \"MEMORY.md\",\n \"startLine\": 28,\n \"endLine\": 39,\n \"score\": 1,\n \"textScore\": 0.39272519405005146,\n \"snippet\": \"- Hardware observed 2026-05-03: GTX 1080 Ti 11GB, Xeon E5-2697A v4 (32 threads), 62GiB RAM. With Qwen3.5-9B 65k context loaded: ~9.0GB VRAM used / ~2.1GB free. Tight but workable; avoid extra GPU loads.\\n- Old Qwen3.5-4B was removed from config and moved to `/archive/models/old-qwen/Qwen3.5-4B-Q8_0.gguf`; do not re-add unless Raymond asks.\\n\\n## Memory / Retrieval Direction\\n\\n- Builtin memory search currently works via FTS/text; embeddings unavailable until an embedding provider/backend is configured. Codex OAuth does **not** satisfy OpenAI embedding API requests.\\n- `openclaw memory status --deep` on 2026-05-03: provider `none`, FTS ready, no direct OpenAI/Gemini/Voyage/Mistral/DeepInfra/Bedrock\\n\\nSource: MEMORY.md#L28-L39\",\n \"source\": \"memory\",\n \"citation\": \"MEMORY.md#L28-L39\",\n \"corpus\": \"memory\"\n },\n {\n \"id\": \"ba64fb4551ef866c469fe4aa0a9f2b3be39684c18dfadbfda55db79756d7064f\",\n \"path\": \"memory/2026-05-03-memory-cleanup.md\",\n \"startLine\": 27,\n \"endLine\": 64,\n \"score\": 1,\n \"textScore\": 0.4408856901324577,\n \"snippet\": \"FINAL CONTEXT\\nPass ONLY reranked top results into generator\\nAvoid flooding context (do not exceed necessary tokens)\\nPERFORMANCE RULES\\nNever load embedder or reranker on GPU\\nAvoid VRAM overflow at all costs\\nPrioritize quality over minor latency gains\\nCHUNKING STRATEGY\\nChunk size: 512–1024 tokens\\nUse overlap if needed (10–20%)\\nPreserve semantic boundaries when possible\\nEXPECTED OUTCOME\\nHigh-quality retrieval\\nReduced hallucination\\nStable GPU performance\\nEfficient use of CPU for preprocessing\\nFAILURE CONDITIONS\\nGPU VRAM exceeds limits\\nSystem slows due to swapping\\nRetrieval quality is poor due to missing reranking\\nPRIORITY\\nStability\\nRetrieval accuracy\\nResponse quality\\nSpeed\\nassistant: Bet. I’ll c\\n\\nSource: memory/2026-05-03-memory-cleanup.md#L27-L64\",\n \"source\": \"memory\",\n \"citation\": \"memory/2026-05-03-memory-cleanup.md#L27-L64\",\n \"corpus\": \"memory\"\n },\n {\n \"id\": \"cdd4e51eeedfaddb67441c25833408b4b17c510173bdabdbfa3fd96606b77cb3\",\n \"path\": \"memory/2026-05-03-memory-cleanup.md\",\n \"startLine\": 1,\n \"endLine\": 36,\n \"score\": 1,\n \"textScore\": 0.4230316598690105,\n \"snippet\": \"# Session: 2026-05-03 17:09:14 PDT\\n\\n- **Session Key**: agent:main:telegram:direct:7229867039\\n- **Session ID**: 28b60577-c433-4c14-9b35-25733568288a\\n- **Source**: telegram\\n\\n## Conversation Summary\\n\\nuser: can you clean up our memoery compress it orginize it also can you check our local models config is it optmized it works right now just want to make sure we have the best model for our set up also i need to add an embedder soon not sure which yet but i need to make sure our gpu has enough room or should i have gone with a bit smaller local ai\\nassistant: Bet — I’ll clean the memory safely first, then verify the local model config against actual GPU/service state. I’ll avoid touching anything de\\n\\nSource: memory/2026-05-03-memory-cleanup.md#L1-L36\",\n \"source\": \"memory\",\n \"citation\": \"memory/2026-05-03-memory-cleanup.md#L1-L36\",\n \"corpus\": \"memory\"\n },\n {\n \"id\": \"f07026628738e6c8a8cf9de1e6144a8dfd9f8413f41aab026760fe8df2dda0af\",\n \"path\": \"memory/2026-05-03.md\",\n \"startLine\": 25,\n \"endLine\": 31,\n \"score\": 1,\n \"textScore\": 0.4652622247567929,\n \"snippet\": \"- OpenClaw docs indicate builtin memory does not do reranking; QMD is the likely OpenClaw path for local BM25 + vectors + reranking/query expansion. Need verify CPU-only behavior before enabling QMD or downloading models.\\n\\n## Standing cautions\\n\\n- Do not change LAN-bound OpenClaw/OPNsense exposure posture without asking.\\n- Do not store Raymond’s sudo password; ask or use narrow allowlisted sudo rules.\\n\\nSource: memory/2026-05-03.md#L25-L31\",\n \"source\": \"memory\",\n \"citation\": \"memory/2026-05-03.md#L25-L31\",\n \"corpus\": \"memory\"\n },\n {\n \"id\": \"70d3e1c1d79183247f8fed6d10fd98e5ca1c64064a52b7f6f895fc72c2b3fb83\",\n \"path\": \"memory/2026-05-03.md\",\n \"startLine\": 15,\n \"endLine\": 29,\n \"score\": 1,\n \"textScore\": 0.39369947962402185,\n \"snippet\": \"- `llama-local` serves the 9B model at `127.0.0.1:8081` with `--parallel 1`, `-c 65536`, and full 65k context per request. Initial `--parallel 2` split context and was changed per Raymond’s preference.\\n- Stale 4B config refs were removed; old 4B model moved to `/archive/models/old-qwen/Qwen3.5-4B-Q8_0.gguf`.\\n\\n## Memory / embedding work\\n\\n- Cleaned memory bloat: consolidated durable facts into `MEMORY.md`, moved low-value fragments to `memory/archive/**/*.txt`, and kept active indexed markdown small.\\n- Backups created during cleanup: `/home/rurouni/backups/memory-cleanup-20260503-164258` and `/home/rurouni/backups/memory-final-clean-{ts}`.\\n- `openclaw memory status --deep` showed builtin FTS r\\n\\nSource: memory/2026-05-03.md#L15-L29\",\n \"source\": \"memory\",\n \"citation\": \"memory/2026-05-03.md#L15-L29\",\n \"corpus\": \"memory\"\n },\n {\n \"id\": \"f26a714dc456bda13869a1a6858b51f55ee4562d773b3c746d88f3b4deb39eb3\",\n \"path\": \"memory/2026-05-03.md\",\n \"startLine\": 1,\n \"endLine\": 19,\n \"score\": 1,\n \"textScore\": 0.45296015951897095,\n \"snippet\": \"# 2026-05-03 Daily Notes\\n\\n## Durable setup changes\\n\\n- Raymond confirmed assistant identity as **Ruruni** 🗡️; durable persona/preferences live in `SOUL.md`, `IDENTITY.md`, `USER.md`, and compact `MEMORY.md`.\\n- OpenClaw context tuning increased to reduce compaction: `contextTokens: 128000`, `reserveTokensFloor: 24000`, `maxActiveTranscriptBytes: 1000000`, `memoryFlush.softThresholdTokens: 60000`. Backup: `/home/rurouni/backups/context-memory-20260503-012153`.\\n- Storage layout verified and documented: backups moved off root through `/home/rurouni/backups` symlink to `/backup/rurouni/openclaw-backups`; model/cache/temp paths documented in long-term memory.\\n\\n## Local model / OpenClaw routing\\n\\n-\\n\\nSource: memory/2026-05-03.md#L1-L19\",\n \"source\": \"memory\",\n \"citation\": \"memory/2026-05-03.md#L1-L19\",\n \"corpus\": \"memory\"\n }\n ],\n \"provider\": \"none\",\n \"citations\": \"auto\",\n \"debug\": {\n \"backend\": \"builtin\",\n \"effectiveMode\": \"n/a\",\n \"searchMs\": 477,\n \"hits\": 8\n }\n}"}],"details":{"results":[{"id":"d4f45f6f2d9b01457138bb6d6a34874506c44344dcd88679c8312f43ee6b56a9","path":"MEMORY.md","startLine":37,"endLine":46,"score":1,"textScore":0.43467721792167235,"snippet":"- OpenClaw builtin memory has embeddings but no reranking; QMD is the OpenClaw path to local BM25 + vectors + reranking/query expansion. Verify CPU-only behavior before enabling QMD or downloading models.\n- Memory hygiene: keep active indexed markdown small. Active files should usually be `MEMORY.md`, `memory/YYYY-MM-DD.md`; archive raw/session fragments as `.txt`.\n\n## System / Storage / Admin\n\n- Storage: root/home on NVMe; `/backup` HDD; `/archive` HDD cold storage; `/models` Samsung SSD; `/data` RAID0 Intel SSDs; `/dev/shm/ai-hot` 16G tmpfs.\n- `/home/rurouni/backups` symlinks to `/backup/rurouni/openclaw-backups`.\n- AI storage env: HF/cache under `/data/cache/hf`; temp under `/data/tmp`; p\n\nSource: MEMORY.md#L37-L46","source":"memory","citation":"MEMORY.md#L37-L46","corpus":"memory"},{"id":"33f1a5981d3b87f931f049f0d1e94b998a584f51ec307114663db1e8afa6635e","path":"MEMORY.md","startLine":1,"endLine":19,"score":1,"textScore":0.6353243501957506,"snippet":"# MEMORY.md — Ruruni Long-Term Memory\n\nCompact durable memory for Raymond’s main direct session. Keep this file lean: stable preferences, active setup, standing cautions, and current decisions only. Put raw/session details in `memory/YYYY-MM-DD.md`; archive low-value fragments as `.txt`.\n\n## Raymond / Style\n\n- Raymond; Pacific time. Assistant name: **Ruruni** 🗡️.\n- Tone: casual, direct, warm, witty, technically sharp, privacy-protective, not yappy.\n- Technical help: start with the answer/next action, use copy/paste commands, prefer safe/reversible steps, warn before risky/destructive/external actions.\n- Preserve Raymond’s natural voice when rewriting. Key domains: Linux/Debian/CachyOS, serv\n\nSource: MEMORY.md#L1-L19","source":"memory","citation":"MEMORY.md#L1-L19","corpus":"memory"},{"id":"7fd15436533cbba337df015874ab1b954949c5462722d88263ece85c94c1db29","path":"MEMORY.md","startLine":28,"endLine":39,"score":1,"textScore":0.39272519405005146,"snippet":"- Hardware observed 2026-05-03: GTX 1080 Ti 11GB, Xeon E5-2697A v4 (32 threads), 62GiB RAM. With Qwen3.5-9B 65k context loaded: ~9.0GB VRAM used / ~2.1GB free. Tight but workable; avoid extra GPU loads.\n- Old Qwen3.5-4B was removed from config and moved to `/archive/models/old-qwen/Qwen3.5-4B-Q8_0.gguf`; do not re-add unless Raymond asks.\n\n## Memory / Retrieval Direction\n\n- Builtin memory search currently works via FTS/text; embeddings unavailable until an embedding provider/backend is configured. Codex OAuth does **not** satisfy OpenAI embedding API requests.\n- `openclaw memory status --deep` on 2026-05-03: provider `none`, FTS ready, no direct OpenAI/Gemini/Voyage/Mistral/DeepInfra/Bedrock\n\nSource: MEMORY.md#L28-L39","source":"memory","citation":"MEMORY.md#L28-L39","corpus":"memory"},{"id":"ba64fb4551ef866c469fe4aa0a9f2b3be39684c18dfadbfda55db79756d7064f","path":"memory/2026-05-03-memory-cleanup.md","startLine":27,"endLine":64,"score":1,"textScore":0.4408856901324577,"snippet":"FINAL CONTEXT\nPass ONLY reranked top results into generator\nAvoid flooding context (do not exceed necessary tokens)\nPERFORMANCE RULES\nNever load embedder or reranker on GPU\nAvoid VRAM overflow at all costs\nPrioritize quality over minor latency gains\nCHUNKING STRATEGY\nChunk size: 512–1024 tokens\nUse overlap if needed (10–20%)\nPreserve semantic boundaries when possible\nEXPECTED OUTCOME\nHigh-quality retrieval\nReduced hallucination\nStable GPU performance\nEfficient use of CPU for preprocessing\nFAILURE CONDITIONS\nGPU VRAM exceeds limits\nSystem slows due to swapping\nRetrieval quality is poor due to missing reranking\nPRIORITY\nStability\nRetrieval accuracy\nResponse quality\nSpeed\nassistant: Bet. I’ll c\n\nSource: memory/2026-05-03-memory-cleanup.md#L27-L64","source":"memory","citation":"memory/2026-05-03-memory-cleanup.md#L27-L64","corpus":"memory"},{"id":"cdd4e51eeedfaddb67441c25833408b4b17c510173bdabdbfa3fd96606b77cb3","path":"memory/2026-05-03-memory-cleanup.md","startLine":1,"endLine":36,"score":1,"textScore":0.4230316598690105,"snippet":"# Session: 2026-05-03 17:09:14 PDT\n\n- **Session Key**: agent:main:telegram:direct:7229867039\n- **Session ID**: 28b60577-c433-4c14-9b35-25733568288a\n- **Source**: telegram\n\n## Conversation Summary\n\nuser: can you clean up our memoery compress it orginize it also can you check our local models config is it optmized it works right now just want to make sure we have the best model for our set up also i need to add an embedder soon not sure which yet but i need to make sure our gpu has enough room or should i have gone with a bit smaller local ai\nassistant: Bet — I’ll clean the memory safely first, then verify the local model config against actual GPU/service state. I’ll avoid touching anything de\n\nSource: memory/2026-05-03-memory-cleanup.md#L1-L36","source":"memory","citation":"memory/2026-05-03-memory-cleanup.md#L1-L36","corpus":"memory"},{"id":"f07026628738e6c8a8cf9de1e6144a8dfd9f8413f41aab026760fe8df2dda0af","path":"memory/2026-05-03.md","startLine":25,"endLine":31,"score":1,"textScore":0.4652622247567929,"snippet":"- OpenClaw docs indicate builtin memory does not do reranking; QMD is the likely OpenClaw path for local BM25 + vectors + reranking/query expansion. Need verify CPU-only behavior before enabling QMD or downloading models.\n\n## Standing cautions\n\n- Do not change LAN-bound OpenClaw/OPNsense exposure posture without asking.\n- Do not store Raymond’s sudo password; ask or use narrow allowlisted sudo rules.\n\nSource: memory/2026-05-03.md#L25-L31","source":"memory","citation":"memory/2026-05-03.md#L25-L31","corpus":"memory"},{"id":"70d3e1c1d79183247f8fed6d10fd98e5ca1c64064a52b7f6f895fc72c2b3fb83","path":"memory/2026-05-03.md","startLine":15,"endLine":29,"score":1,"textScore":0.39369947962402185,"snippet":"- `llama-local` serves the 9B model at `127.0.0.1:8081` with `--parallel 1`, `-c 65536`, and full 65k context per request. Initial `--parallel 2` split context and was changed per Raymond’s preference.\n- Stale 4B config refs were removed; old 4B model moved to `/archive/models/old-qwen/Qwen3.5-4B-Q8_0.gguf`.\n\n## Memory / embedding work\n\n- Cleaned memory bloat: consolidated durable facts into `MEMORY.md`, moved low-value fragments to `memory/archive/**/*.txt`, and kept active indexed markdown small.\n- Backups created during cleanup: `/home/rurouni/backups/memory-cleanup-20260503-164258` and `/home/rurouni/backups/memory-final-clean-{ts}`.\n- `openclaw memory status --deep` showed builtin FTS r\n\nSource: memory/2026-05-03.md#L15-L29","source":"memory","citation":"memory/2026-05-03.md#L15-L29","corpus":"memory"},{"id":"f26a714dc456bda13869a1a6858b51f55ee4562d773b3c746d88f3b4deb39eb3","path":"memory/2026-05-03.md","startLine":1,"endLine":19,"score":1,"textScore":0.45296015951897095,"snippet":"# 2026-05-03 Daily Notes\n\n## Durable setup changes\n\n- Raymond confirmed assistant identity as **Ruruni** 🗡️; durable persona/preferences live in `SOUL.md`, `IDENTITY.md`, `USER.md`, and compact `MEMORY.md`.\n- OpenClaw context tuning increased to reduce compaction: `contextTokens: 128000`, `reserveTokensFloor: 24000`, `maxActiveTranscriptBytes: 1000000`, `memoryFlush.softThresholdTokens: 60000`. Backup: `/home/rurouni/backups/context-memory-20260503-012153`.\n- Storage layout verified and documented: backups moved off root through `/home/rurouni/backups` symlink to `/backup/rurouni/openclaw-backups`; model/cache/temp paths documented in long-term memory.\n\n## Local model / OpenClaw routing\n\n-\n\nSource: memory/2026-05-03.md#L1-L19","source":"memory","citation":"memory/2026-05-03.md#L1-L19","corpus":"memory"}],"provider":"none","citations":"auto","debug":{"backend":"builtin","effectiveMode":"n/a","searchMs":477,"hits":8}},"isError":false,"timestamp":1777856804011}} {"type":"message","id":"f7cd4590","parentId":"c7152b37","timestamp":"2026-05-04T01:06:46.881Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"id\":\"rs_02b86be3bb6b669e0169f7f1250b108196b9d37f8e5a805871\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABp9_ElEKSo5a3fWZMiS__zyLzU3kGPGi2EsdAJZuqtalUp9D-vlPFglEhW6hLJvDBydr3UlpwF0JR4uVmjZzoSJGjKXvhf4NcGjjau1EUvEJMdQfGdQP9-bWsSkcbrSJzZioUSF-ftOy19gbVFq_nuAEZY5ZSIHD-dAlTLFjDDhn2Ca0Lz4GPi4UYxVmYIBhmfQOj7WK-XLvW5e4jGc6tvKzUyi92jv8_CRvTHxECs44V8e8XPihO34wMF1WeAMnU_SVABzzJ0xRXx7C10lAIGrmbrMqAkoNpV4Q5SeLbUkND--YkqamPRsxAoX83Mw_T_XABFrLrQzw00sWkQ1599_kckYpjaqA6JFTZOKVcsJqUytJppK0sMmBj0WahJd4JyGVy5N6wbyrjX0mUqglfrxui3EhPLbpOx8MUCS5j3OKwsQk5dlfkO6oPwuGCiu35UAvRAUxVVf4WOrGIPqrqv3-zBA_sJQoz2zjOHJ3huWXNx6s_uK0_tZscLHfM7LhqbRsH28dJYWGJYwgKsFOEzJilXKfvYdSSB73EkpNeNsiyH1qKc7QV7f6AaaAwbX9soMmSuDGUU941vjRCoqO1CRyPZKjbUFjYf1d8HQX7zLG_LIHz7Bfd68oWgQadlr0xl45SbB6AebtWh3bzzvLUtQ_ZBMgrKeoN6qBTYuU5BonHj1KJW2olyJ6coHgurSyOWJoE2A1v_t5NZbQNK6rvyqmTrDztptMGAFj8dXX7BYmZ9t6YtGVSh9uNl7TaFlrF1zmEMykt7AdfEuRernryy_UbIpf-XjYZaHWwk3rY22-0ZrQOyPa29bEUe-P3dB9pB1Jk4zRHTy3H8HH0olphGxB-GpVEUDhuk41A_5VkPclHnoiVjtsz1DAJ2YoOn_XVyGujL0l6gPswolEpv569WpfQt2RcW4MtHwVsQioKMPSXETjlmCNgzDslTbzlPXwUM0cowk12GFhs1YEYxg2pVN9u0HUahJVsehlmXe87YUvEEZ-mxp82u6IzS5N1Z9Celoc5hoibVqI1q3QKYArPdXMxNYQ==\",\"summary\":[]}"},{"type":"text","text":"Bet. I’ll do the inspection only first — no installs, no config writes, no deletes. Then I’ll print the plan before touching anything.","textSignature":"{\"v\":1,\"id\":\"msg_02b86be3bb6b669e0169f7f125c5408196b11afd9ba89f69da\",\"phase\":\"commentary\"}"},{"type":"toolCall","id":"call_VrxaCXcc7jiXabmFbUBqqu6c|fc_02b86be3bb6b669e0169f7f12636c081969d1bc42df9bfc793","name":"update_plan","arguments":{"plan":[{"step":"Recall existing memory/setup notes","status":"completed"},{"step":"Inspect OpenClaw config/install paths","status":"in_progress"},{"step":"Detect container/services/tools","status":"pending"},{"step":"Check GPU/VRAM and storage","status":"pending"},{"step":"Report findings and change plan","status":"pending"}]}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.5","usage":{"input":3125,"output":144,"cacheRead":14336,"cacheWrite":0,"totalTokens":17605,"cost":{"input":0.015625,"output":0.00432,"cacheRead":0.007168,"cacheWrite":0,"total":0.027113}},"stopReason":"toolUse","timestamp":1777856804014,"responseId":"resp_02b86be3bb6b669e0169f7f12446248196a33bfdb85074e047"}} {"type":"message","id":"5ab82ce5","parentId":"f7cd4590","timestamp":"2026-05-04T01:06:46.891Z","message":{"role":"toolResult","toolCallId":"call_VrxaCXcc7jiXabmFbUBqqu6c|fc_02b86be3bb6b669e0169f7f12636c081969d1bc42df9bfc793","toolName":"update_plan","content":[],"details":{"status":"updated","plan":[{"step":"Recall existing memory/setup notes","status":"completed"},{"step":"Inspect OpenClaw config/install paths","status":"in_progress"},{"step":"Detect container/services/tools","status":"pending"},{"step":"Check GPU/VRAM and storage","status":"pending"},{"step":"Report findings and change plan","status":"pending"}]},"isError":false,"timestamp":1777856806889}} {"type":"message","id":"1cc601b9","parentId":"5ab82ce5","timestamp":"2026-05-04T01:06:53.077Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_H4Qco34OzlY1J5BtvQl77b2N|fc_02b86be3bb6b669e0169f7f128138881969e0f9ddf8d946e69","name":"exec","arguments":{"command":"set -o pipefail\nprintf '=== openclaw binaries ===\\n'\ncommand -v openclaw || true\nopenclaw --version 2>/dev/null || true\nprintf '\\n=== openclaw status ===\\n'\nopenclaw status 2>&1 || true\nprintf '\\n=== config/search paths ===\\n'\nfor d in \"$HOME/.openclaw\" \"$HOME/.config/openclaw\" \"$HOME/.local/share/openclaw\" \"/etc/openclaw\" \"/usr/lib/node_modules/openclaw\"; do\n if [ -e \"$d\" ]; then echo \"-- $d\"; find \"$d\" -maxdepth 2 -type f \\( -name '*.json' -o -name '*.yaml' -o -name '*.yml' -o -name '*.toml' -o -name '*.md' -o -name '*.log' \\) 2>/dev/null | sed 's#^# #'; fi\ndone\nprintf '\\n=== OpenClaw memory status deep ===\\n'\nopenclaw memory status --deep 2>&1 || true\nprintf '\\n=== OpenClaw plugin-ish files ===\\n'\nfind \"$HOME/.openclaw\" \"$HOME/.config/openclaw\" \"$HOME/.local/share/openclaw\" \"/usr/lib/node_modules/openclaw\" -maxdepth 4 \\( -iname '*mem0*' -o -iname '*qdrant*' -o -iname '*qmd*' -o -iname '*lossless*' -o -iname '*lcm*' \\) 2>/dev/null | sed 's#^# #' | head -200","workdir":"/home/rurouni","yieldMs":10000,"timeout":60}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.5","usage":{"input":725,"output":404,"cacheRead":16896,"cacheWrite":0,"totalTokens":18025,"cost":{"input":0.003625,"output":0.01212,"cacheRead":0.008447999999999999,"cacheWrite":0,"total":0.024193}},"stopReason":"toolUse","timestamp":1777856806894,"responseId":"resp_02b86be3bb6b669e0169f7f1272d248196a3e770e57316785f"}} {"type":"message","id":"b81a235a","parentId":"1cc601b9","timestamp":"2026-05-04T01:07:03.102Z","message":{"role":"toolResult","toolCallId":"call_H4Qco34OzlY1J5BtvQl77b2N|fc_02b86be3bb6b669e0169f7f128138881969e0f9ddf8d946e69","toolName":"exec","content":[{"type":"text","text":"Command still running (session lucky-otter, pid 57810). Use process (list/poll/log/write/kill/clear/remove) for follow-up."}],"details":{"status":"running","sessionId":"lucky-otter","pid":57810,"startedAt":1777856813090,"cwd":"/home/rurouni","tail":" /home/rurouni/.openclaw/logs/commands.log\n /home/rurouni/.openclaw/logs/config-health.json\n /home/rurouni/.openclaw/plugins/installs.json\n /home/rurouni/.openclaw/update-check.json\n /home/rurouni/.openclaw/credentials/web-pairing.json\n /home/rurouni/.openclaw/credentials/telegram-pairing.json\n /home/rurouni/.openclaw/credentials/https-pairing.json\n /home/rurouni/.openclaw/credentials/telegram-default-allowFrom.json\n /home/rurouni/.openclaw/identity/device.json\n /home/rurouni/.openclaw/identity/device-auth.json\n /home/rurouni/.openclaw/tui/last-session.json\n /home/rurouni/.openclaw/telegram/update-offset-default.json\n /home/rurouni/.openclaw/devices/paired.json\n /home/rurouni/.openclaw/devices/pending.json\n /home/rurouni/.openclaw/workspace-state.json\n-- /usr/lib/node_modules/openclaw\n /usr/lib/node_modules/openclaw/README.md\n /usr/lib/node_modules/openclaw/dist/postinstall-inventory.json\n /usr/lib/node_modules/openclaw/dist/build-info.json\n /usr/lib/node_modules/openclaw/dist/cli-startup-metadata.json\n /usr/lib/node_modules/openclaw/dist/channel-catalog.json\n /usr/lib/node_modules/openclaw/CHANGELOG.md\n /usr/lib/node_modules/openclaw/docs/auth-credential-semantics.md\n /usr/lib/node_modules/openclaw/docs/brave-search.md\n /usr/lib/node_modules/openclaw/docs/perplexity.md\n /usr/lib/node_modules/openclaw/docs/ci.md\n /usr/lib/node_modules/openclaw/docs/date-time.md\n /usr/lib/node_modules/openclaw/docs/index.md\n /usr/lib/node_modules/openclaw/docs/AGENTS.md\n /usr/lib/node_modules/openclaw/docs/network.md\n /usr/lib/node_modules/openclaw/docs/vps.md\n /usr/lib/node_modules/openclaw/docs/docs.json\n /usr/lib/node_modules/openclaw/docs/pi-dev.md\n /usr/lib/node_modules/openclaw/docs/tts.md\n /usr/lib/node_modules/openclaw/docs/pi.md\n /usr/lib/node_modules/openclaw/docs/logging.md\n /usr/lib/node_modules/openclaw/docs/prose.md\n /usr/lib/node_modules/openclaw/package.json\n\n=== OpenClaw memory status deep ===\n"},"isError":false,"timestamp":1777856823102}} {"type":"message","id":"2f8ce107","parentId":"b81a235a","timestamp":"2026-05-04T01:07:04.765Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_rwjr8YDSYD57GIaxFEOe7jWr|fc_02b86be3bb6b669e0169f7f1384740819686f976f3a3c2fc7a","name":"process","arguments":{"action":"poll","sessionId":"lucky-otter","timeout":30000,"limit":20000}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.5","usage":{"input":660,"output":36,"cacheRead":17408,"cacheWrite":0,"totalTokens":18104,"cost":{"input":0.0033000000000000004,"output":0.00108,"cacheRead":0.008704,"cacheWrite":0,"total":0.013084}},"stopReason":"toolUse","timestamp":1777856823105,"responseId":"resp_02b86be3bb6b669e0169f7f1376290819680be7d5c10a2890b"}} {"type":"message","id":"d177cbe0","parentId":"2f8ce107","timestamp":"2026-05-04T01:07:13.785Z","message":{"role":"toolResult","toolCallId":"call_rwjr8YDSYD57GIaxFEOe7jWr|fc_02b86be3bb6b669e0169f7f1384740819686f976f3a3c2fc7a","toolName":"process","content":[{"type":"text","text":"=== openclaw binaries ===\n/usr/bin/openclaw\nOpenClaw 2026.5.2 (8b2a6e5)\n\n=== openclaw status ===\nOpenClaw status\n\nOverview\n┌──────────────────────┬───────────────────────────────────────────────────────────────────────────────────────────────┐\n│ Item │ Value │\n├──────────────────────┼───────────────────────────────────────────────────────────────────────────────────────────────┤\n│ OS │ linux 6.12.85+deb13-amd64 (x64) · node 24.15.0 │\n│ Dashboard │ http://192.168.1.50:18789/ │\n│ Tailscale exposure │ off │\n│ Channel │ stable (default) │\n│ Update │ pnpm · up to date · npm latest 2026.5.2 │\n│ Gateway │ local · ws://127.0.0.1:18789 (local loopback) · reachable 92ms · auth token · debian-ai (192. │\n│ │ 168.1.50) app 2026.5.2 linux 6.12.85+deb13-amd64 │\n│ Gateway self │ debian-ai (192.168.1.50) app 2026.5.2 linux 6.12.85+deb13-amd64 │\n│ Gateway service │ systemd installed · enabled · running (pid 57453, state active) │\n│ Node service │ systemd not installed │\n│ Agents │ 1 · no bootstrap files · sessions 4 · default main active just now │\n│ Memory │ enabled (plugin memory-core) · not checked │\n│ Plugin compatibility │ none │\n│ Probes │ skipped (use --deep) │\n│ Events │ none │\n│ Tasks │ none │\n│ Heartbeat │ 30m (main) │\n│ Sessions │ 4 active · default gpt-5.5 (128k ctx) · ~/.openclaw/agents/main/sessions/sessions.json │\n└──────────────────────┴───────────────────────────────────────────────────────────────────────────────────────────────┘\n\nSecurity audit\nSkipped in fast status. Full report: openclaw security audit\nDeep probe: openclaw status --deep\n\nChannels\n┌──────────┬─────────┬────────┬────────────────────────────────────────────────────────────────────────────────────────┐\n│ Channel │ Enabled │ State │ Detail │\n├──────────┼─────────┼────────┼────────────────────────────────────────────────────────────────────────────────────────┤\n│ Telegram │ ON │ OK │ token config (8796…S0Zs · len 46) · accounts 1/1 │\n└──────────┴─────────┴────────┴────────────────────────────────────────────────────────────────────────────────────────┘\n\nSessions\n┌──────────────────────────────────────────────────┬────────┬──────────┬──────────────┬────────────────────────────────┐\n│ Key │ Kind │ Age │ Model │ Tokens │\n├──────────────────────────────────────────────────┼────────┼──────────┼──────────────┼────────────────────────────────┤\n│ agent:main:telegram:direct:7229… │ direct │ just now │ gpt-5.5 │ unknown/128k (?%) │\n│ agent:main:main:heartbeat │ direct │ 29m ago │ qwen3.5-9b │ unknown/66k (?%) │\n│ agent:main:telegram:direct:7229… │ direct │ 4h ago │ gpt-5.5 │ 8.9k/128k (7%) · 🗄️ 75% cached │\n│ agent:main:main │ direct │ 17h ago │ gpt-5.5 │ 22k/28k (78%) · 🗄️ 64% cached │\n└──────────────────────────────────────────────────┴────────┴──────────┴──────────────┴────────────────────────────────┘\n\nFAQ: https://docs.openclaw.ai/faq\nTroubleshooting: https://docs.openclaw.ai/troubleshooting\nNext steps:\n Need to share? openclaw status --all\n Need to debug live? openclaw logs --follow\n Need to test channels? openclaw status --deep\n\n=== config/search paths ===\n-- /home/rurouni/.openclaw\n /home/rurouni/.openclaw/openclaw.json\n /home/rurouni/.openclaw/exec-approvals.json\n /home/rurouni/.openclaw/logs/commands.log\n /home/rurouni/.openclaw/logs/config-health.json\n /home/rurouni/.openclaw/plugins/installs.json\n /home/rurouni/.openclaw/update-check.json\n /home/rurouni/.openclaw/credentials/web-pairing.json\n /home/rurouni/.openclaw/credentials/telegram-pairing.json\n /home/rurouni/.openclaw/credentials/https-pairing.json\n /home/rurouni/.openclaw/credentials/telegram-default-allowFrom.json\n /home/rurouni/.openclaw/identity/device.json\n /home/rurouni/.openclaw/identity/device-auth.json\n /home/rurouni/.openclaw/tui/last-session.json\n /home/rurouni/.openclaw/telegram/update-offset-default.json\n /home/rurouni/.openclaw/devices/paired.json\n /home/rurouni/.openclaw/devices/pending.json\n /home/rurouni/.openclaw/workspace-state.json\n-- /usr/lib/node_modules/openclaw\n /usr/lib/node_modules/openclaw/README.md\n /usr/lib/node_modules/openclaw/dist/postinstall-inventory.json\n /usr/lib/node_modules/openclaw/dist/build-info.json\n /usr/lib/node_modules/openclaw/dist/cli-startup-metadata.json\n /usr/lib/node_modules/openclaw/dist/channel-catalog.json\n /usr/lib/node_modules/openclaw/CHANGELOG.md\n /usr/lib/node_modules/openclaw/docs/auth-credential-semantics.md\n /usr/lib/node_modules/openclaw/docs/brave-search.md\n /usr/lib/node_modules/openclaw/docs/perplexity.md\n /usr/lib/node_modules/openclaw/docs/ci.md\n /usr/lib/node_modules/openclaw/docs/date-time.md\n /usr/lib/node_modules/openclaw/docs/index.md\n /usr/lib/node_modules/openclaw/docs/AGENTS.md\n /usr/lib/node_modules/openclaw/docs/network.md\n /usr/lib/node_modules/openclaw/docs/vps.md\n /usr/lib/node_modules/openclaw/docs/docs.json\n /usr/lib/node_modules/openclaw/docs/pi-dev.md\n /usr/lib/node_modules/openclaw/docs/tts.md\n /usr/lib/node_modules/openclaw/docs/pi.md\n /usr/lib/node_modules/openclaw/docs/logging.md\n /usr/lib/node_modules/openclaw/docs/prose.md\n /usr/lib/node_modules/openclaw/package.json\n\n=== OpenClaw memory status deep ===\nMemory Search (main)\nProvider: none (requested: auto)\nModel: none\nSources: memory\nIndexed: 5/5 files · 11 chunks\nDirty: yes\nStore: ~/.openclaw/memory/main.sqlite\nWorkspace: ~\nDreaming: off\nEmbeddings: unavailable\nEmbeddings error: No GitHub token available for Copilot embedding provider\n\nNo API key found for provider \"openai\". You are authenticated with OpenAI Codex OAuth. Use openai-codex/gpt-5.5, or set OPENAI_API_KEY for direct OpenAI API access.\n\nNo API key found for provider \"google\". Auth store: /home/rurouni/.openclaw/agents/main/agent/auth-profiles.json (agentDir: /home/rurouni/.openclaw/agents/main/agent). Configure auth for this agent (openclaw agents add ) or copy only portable static auth profiles from the main agentDir.\n\nNo API key found for provider \"voyage\". Auth store: /home/rurouni/.openclaw/agents/main/agent/auth-profiles.json (agentDir: /home/rurouni/.openclaw/agents/main/agent). Configure auth for this agent (openclaw agents add ) or copy only portable static auth profiles from the main agentDir.\n\nNo API key found for provider \"mistral\". Auth store: /home/rurouni/.openclaw/agents/main/agent/auth-profiles.json (agentDir: /home/rurouni/.openclaw/agents/main/agent). Configure auth for this agent (openclaw agents add ) or copy only portable static auth profiles from the main agentDir.\n\nNo API key found for provider \"deepinfra\". Auth store: /home/rurouni/.openclaw/agents/main/agent/auth-profiles.json (agentDir: /home/rurouni/.openclaw/agents/main/agent). Configure auth for this agent (openclaw agents add ) or copy only portable static auth profiles from the main agentDir.\n\nNo API key found for provider \"bedrock\". AWS credentials are not available. Set AWS_ACCESS_KEY_ID/AWS_SECRET_ACCESS_KEY, AWS_PROFILE, or AWS_BEARER_TOKEN_BEDROCK, configure an EC2/ECS/EKS role, or set agents.defaults.memorySearch.provider to another provider.\nBy source:\n memory · 5/5 files · 11 chunks\nVector: unknown\nFTS: ready\nEmbedding cache: enabled (0 entries)\nBatch: disabled (failures 0/2)\nRecall store: 30 entries · 0 promoted · 30 concept-tagged · 0 spaced · scripts=30 latin\nRecall path: ~/memory/.dreams/short-term-recall.json\nRecall updated: 2026-05-04T01:06:44.007Z\nDreaming artifacts: diary absent · 0 corpus files · ingestion state absent\nDream corpus: ~/memory/.dreams/session-corpus\nDream ingestion: ~/memory/.dreams/session-ingestion.json\n\n\n=== OpenClaw plugin-ish files ===\n /usr/lib/node_modules/openclaw/dist/plugin-sdk/memory-core-host-engine-qmd.js\n /usr/lib/node_modules/openclaw/dist/plugin-sdk/memory-core-host-engine-qmd.d.ts\n /usr/lib/node_modules/openclaw/dist/qmd-manager-CZIryLQN.js\n /usr/lib/node_modules/openclaw/dist/memory-core-host-engine-qmd-C2g3h0AI.js\n /usr/lib/node_modules/openclaw/dist/chrome-mcp-DylcmUof.js\n /usr/lib/node_modules/openclaw/dist/engine-qmd-DpZ08KSc.js\n /usr/lib/node_modules/openclaw/docs/concepts/memory-qmd.md\n\nProcess exited with code 1."}],"details":{"persistedDetailsTruncated":true,"originalDetailsBytesAtLeast":8193,"originalDetailKeys":["status","sessionId","exitCode","aggregated","name"],"status":"failed","sessionId":"lucky-otter","name":"set pipefail","exitCode":1},"isError":false,"timestamp":1777856833784}} {"type":"message","id":"3403a32d","parentId":"d177cbe0","timestamp":"2026-05-04T01:07:26.786Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"id\":\"rs_02b86be3bb6b669e0169f7f14316988196af739cc222774c71\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABp9_FO0DDfNQ1-UWNKRlGwgzvikv4QXZ-c66p_ircEcgu7-bBHsH9GAX4dZm-SuJfXEp8fa3VWq_7ZM1fcYSdZr0h4egSwEoIabUwMa2PbcGrzkbiylTA8L9MZo0dHVzxkqO-MajYqhVgCm7tn5DZgeYLi3-VaJDlzLgX9Cs6PN-rsTlT_3Mio8UazIRLdBjR8aLihsC31UrKHcDwi3Y817SL161RmS0qGW-qroIpbvbsjo_RhqTXXg8ypQMTIOi5LLTTgzw2GT6mY-_tA1mrsvMATnSVj28WqpMMpjTIhiYfBORftB1zedPwElgR3vzuxuJZ0aqv-1KNSX-TwkwnRtR8C8JxhVhoJSiK4RggqDSQ99YJngCmSdJXc4S43nSgLgyTVldFBfq1kcjUnFwV-1XAHb1rlkD74qTq-f4y5EIWfLEswnRjGLOdXvWmJLfYjfB6ISNUor-NhQfC0jJ7_OuAf3pbYhk4QgAJuWfwfVZbPQVV7qOjrOrThtpjNtUR_fMw0CJEfJ57cHcgBjgc7mmIaPBhEyxtLqfvZ6jkY-Vwo8EqbrDrVENQ7AhoabKydHffOLHxbNLjamqnfK5nVIlzevIA9wueVMBGfzpR7a4KLXZc649lqiKIY-xCYV83SlQmu5hHkkUiuZrP5qeS2YEl6-pzJ6Nyw4WzLVmFJCHRKWv80zHR4nq4NnsvIPjQkDpwawOgi1nT9B6oW1Ts0-6_lXikXiMzMa57R3nhD7Pg9BmsRgCfQ9YOceExc91M8BhC1UQEqy13sqOJq2f89e48PgMFky2pCl_4VGCyowVyGs_x31UhIXj69M-I51GKBfC4H71EZfPJ4a7acmlsIagzaUo2DI99idAfwN-J4G40fl_aGVf5BqWpTmII3RWvX2WnnsDX_EvtsRZuFSMvsLhdL3YumjE36IP_MyqcrU2C5jfjTXamLJK6UkRbiP4b6ug4qYU8rDYV7DUAQQdIUgVOMFJW4d-hHD7DaoCQRNfoo7QN_uJdM1fanIzXZkOP4cVVl2I2L1LbVEtHLyZn6E8usUSLW983l7Crw1S-XiC1fMkD0-Ri-TmD7At-I-0Nmx4zQvkSPE-aRVQTKdc_NP5zDjdekhS7HmF2vkLxGyORPPuM=\",\"summary\":[]}"},{"type":"toolCall","id":"call_umuUViB2y75okeQ59XyjAKcC|fc_02b86be3bb6b669e0169f7f14ea7d481969160ada5e9f3275b","name":"exec","arguments":{"command":"printf '=== containers ===\\n'\nfor c in docker podman nerdctl; do printf '%s: ' \"$c\"; command -v \"$c\" || true; done\nprintf '\\n=== container services/processes ===\\n'\nsystemctl --no-pager --type=service --state=running 2>/dev/null | grep -Ei 'docker|podman|containerd|qdrant|mem0|qmd|lossless|lcm' || true\nps -eo pid,comm,args --cols 220 | grep -Ei 'qdrant|mem0|qmd|lossless|lcm|docker|podman|containerd' | grep -v grep || true\nprintf '\\n=== existing data dirs ===\\n'\nfor d in /data/openclaw-memory /models/embeddings /backup/openclaw-memory /archive/openclaw-memory /data/qdrant /var/lib/qdrant; do [ -e \"$d\" ] && { echo \"-- $d\"; find \"$d\" -maxdepth 2 -mindepth 1 -printf '%M %u:%g %s %p\\n' 2>/dev/null | head -100; }; done\nprintf '\\n=== python/node packages hints ===\\n'\npython3 - <<'PY' 2>/dev/null || true\nimport importlib.util\nfor m in ['mem0','qdrant_client','fastembed','sentence_transformers']:\n print(f'{m}:', bool(importlib.util.find_spec(m)))\nPY\nnpm ls -g --depth=0 2>/dev/null | grep -Ei 'mem0|qdrant|qmd|lossless|lcm|openclaw' || true","workdir":"/home/rurouni","yieldMs":10000,"timeout":45}},{"type":"toolCall","id":"call_BgIxw8BRd1qPvuY5Qob0HcoI|fc_02b86be3bb6b669e0169f7f14ea7e48196987992a3ca21d734","name":"exec","arguments":{"command":"printf '=== gpu ===\\n'\ncommand -v nvidia-smi || true\nnvidia-smi --query-gpu=name,index,memory.total,memory.used,memory.free,utilization.gpu,compute_mode --format=csv,noheader,nounits 2>&1 || true\nprintf '\\n=== nvidia processes ===\\n'\nnvidia-smi 2>/dev/null | sed -n '/Processes:/,$p' || true\nprintf '\\n=== storage ===\\n'\ndf -hT / /home /data /models /backup /archive 2>/dev/null || true\nprintf '\\n=== mounts ===\\n'\nfindmnt -no TARGET,SOURCE,FSTYPE,SIZE,USED,AVAIL,OPTIONS /data /models /backup /archive 2>/dev/null || true","workdir":"/home/rurouni","yieldMs":10000,"timeout":45}},{"type":"toolCall","id":"call_Hz8AAZED9FyrDIryz1lqs49e|fc_02b86be3bb6b669e0169f7f14ea7ec819698eb2579e3966264","name":"exec","arguments":{"command":"printf '=== safe config summary ===\\n'\nnode - <<'NODE'\nconst fs=require('fs'); const p='/home/rurouni/.openclaw/openclaw.json';\nconst redact=(k,v)=>/key|token|secret|password|auth|credential/i.test(k)?(v?``:v):v;\nconst cfg=JSON.parse(fs.readFileSync(p,'utf8'));\nfunction pick(obj){return JSON.stringify(obj,redact,2)}\nconsole.log('path',p);\nconsole.log('topKeys',Object.keys(cfg));\nfor (const k of ['agents','memory','memorySearch','plugins','gateway','providers','models','context','qmd']) if (cfg[k]) { console.log('\\n['+k+']'); console.log(pick(cfg[k]).slice(0,6000)); }\nconst main=cfg.agents?.main || cfg.agents?.find?.(a=>a.id==='main');\nif(main){ console.log('\\n[agents.main keys]', Object.keys(main)); console.log(pick(main).slice(0,8000)); }\nNODE\nprintf '\\n=== agents main files ===\\n'\nfind /home/rurouni/.openclaw/agents/main -maxdepth 3 -type f 2>/dev/null | sed 's#^# #' | head -200","workdir":"/home/rurouni","yieldMs":10000,"timeout":45}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.5","usage":{"input":2622,"output":1003,"cacheRead":17920,"cacheWrite":0,"totalTokens":21545,"cost":{"input":0.013110000000000002,"output":0.030090000000000002,"cacheRead":0.00896,"cacheWrite":0,"total":0.05216}},"stopReason":"toolUse","timestamp":1777856833789,"responseId":"resp_02b86be3bb6b669e0169f7f1422cb88196a7b9a23c23610444"}} {"type":"message","id":"518539f3","parentId":"3403a32d","timestamp":"2026-05-04T01:07:27.740Z","message":{"role":"toolResult","toolCallId":"call_umuUViB2y75okeQ59XyjAKcC|fc_02b86be3bb6b669e0169f7f14ea7d481969160ada5e9f3275b","toolName":"exec","content":[{"type":"text","text":"=== containers ===\ndocker: /usr/bin/docker\npodman: nerdctl: \n=== container services/processes ===\n containerd.service loaded active running containerd container runtime\n docker.service loaded active running Docker Application Container Engine\n 1163 containerd /usr/bin/containerd\n 1178 dockerd /usr/bin/dockerd -H fd:// --containerd=/run/containerd/containerd.sock\n 57872 bash /bin/bash --noprofile --norc -c printf '=== containers ===\\n' for c in docker podman nerdctl; do printf '%s: ' \"$c\"; command -v \"$c\" || true; done printf '\\n=== container services/processes ===\\n'\n\n=== existing data dirs ===\n\n=== python/node packages hints ===\nmem0: False\nqdrant_client: False\nfastembed: False\nsentence_transformers: False\n└── openclaw@2026.5.2"}],"details":{"status":"completed","exitCode":0,"durationMs":924,"aggregated":"=== containers ===\ndocker: /usr/bin/docker\npodman: nerdctl: \n=== container services/processes ===\n containerd.service loaded active running containerd container runtime\n docker.service loaded active running Docker Application Container Engine\n 1163 containerd /usr/bin/containerd\n 1178 dockerd /usr/bin/dockerd -H fd:// --containerd=/run/containerd/containerd.sock\n 57872 bash /bin/bash --noprofile --norc -c printf '=== containers ===\\n' for c in docker podman nerdctl; do printf '%s: ' \"$c\"; command -v \"$c\" || true; done printf '\\n=== container services/processes ===\\n'\n\n=== existing data dirs ===\n\n=== python/node packages hints ===\nmem0: False\nqdrant_client: False\nfastembed: False\nsentence_transformers: False\n└── openclaw@2026.5.2","cwd":"/home/rurouni"},"isError":false,"timestamp":1777856847740}} {"type":"message","id":"b7c521a2","parentId":"518539f3","timestamp":"2026-05-04T01:07:27.741Z","message":{"role":"toolResult","toolCallId":"call_BgIxw8BRd1qPvuY5Qob0HcoI|fc_02b86be3bb6b669e0169f7f14ea7e48196987992a3ca21d734","toolName":"exec","content":[{"type":"text","text":"=== gpu ===\n/usr/bin/nvidia-smi\nNVIDIA GeForce GTX 1080 Ti, 0, 11264, 9021, 2144, 0, Default\n\n=== nvidia processes ===\n| Processes: |\n| GPU GI CI PID Type Process name GPU Memory |\n| ID ID Usage |\n|=========================================================================================|\n| 0 N/A N/A 56402 C /usr/local/bin/llama-server 9016MiB |\n+-----------------------------------------------------------------------------------------+\n\n=== storage ===\nFilesystem Type Size Used Avail Use% Mounted on\n/dev/nvme0n1p2 ext4 221G 29G 182G 14% /\n/dev/nvme0n1p2 ext4 221G 29G 182G 14% /\n/dev/md0 ext4 1.5T 21M 1.4T 1% /data\n/dev/sdd1 ext4 458G 2.1M 435G 1% /models\n/dev/sdb1 ext4 1.8T 3.2M 1.7T 1% /backup\n/dev/sde1 ext4 1.8T 4.2G 1.7T 1% /archive\n\n=== mounts ==="}],"details":{"status":"completed","exitCode":0,"durationMs":64,"aggregated":"=== gpu ===\n/usr/bin/nvidia-smi\nNVIDIA GeForce GTX 1080 Ti, 0, 11264, 9021, 2144, 0, Default\n\n=== nvidia processes ===\n| Processes: |\n| GPU GI CI PID Type Process name GPU Memory |\n| ID ID Usage |\n|=========================================================================================|\n| 0 N/A N/A 56402 C /usr/local/bin/llama-server 9016MiB |\n+-----------------------------------------------------------------------------------------+\n\n=== storage ===\nFilesystem Type Size Used Avail Use% Mounted on\n/dev/nvme0n1p2 ext4 221G 29G 182G 14% /\n/dev/nvme0n1p2 ext4 221G 29G 182G 14% /\n/dev/md0 ext4 1.5T 21M 1.4T 1% /data\n/dev/sdd1 ext4 458G 2.1M 435G 1% /models\n/dev/sdb1 ext4 1.8T 3.2M 1.7T 1% /backup\n/dev/sde1 ext4 1.8T 4.2G 1.7T 1% /archive\n\n=== mounts ===","cwd":"/home/rurouni"},"isError":false,"timestamp":1777856847740}} {"type":"message","id":"0e99cf79","parentId":"b7c521a2","timestamp":"2026-05-04T01:07:27.743Z","message":{"role":"toolResult","toolCallId":"call_Hz8AAZED9FyrDIryz1lqs49e|fc_02b86be3bb6b669e0169f7f14ea7ec819698eb2579e3966264","toolName":"exec","content":[{"type":"text","text":"=== safe config summary ===\npath /home/rurouni/.openclaw/openclaw.json\ntopKeys [\n 'env', 'agents',\n 'gateway', 'session',\n 'tools', 'models',\n 'plugins', 'channels',\n 'skills', 'hooks',\n 'commands', 'messages',\n 'auth', 'wizard',\n 'meta', 'diagnostics'\n]\n\n[agents]\n{\n \"defaults\": {\n \"workspace\": \"/home/rurouni\",\n \"model\": {\n \"primary\": \"openai-codex/gpt-5.5\",\n \"fallbacks\": [\n \"deepseek/deepseek-v4-pro\",\n \"openrouter/minimax/minimax-m2.7\",\n \"local-qwen/qwen3.5-9b\"\n ]\n },\n \"models\": {\n \"openrouter/minimax/minimax-m2.7\": {\n \"alias\": \"MiniMax\"\n },\n \"openai-codex/gpt-5.5\": {},\n \"local-qwen/qwen3.5-9b\": {\n \"alias\": \"local\",\n \"params\": {\n \"temperature\": 0.6,\n \"top_p\": 0.95,\n \"top_k\": 20\n }\n },\n \"deepseek/deepseek-v4-pro\": {}\n },\n \"contextTokens\": \"\",\n \"compaction\": {\n \"reserveTokensFloor\": \"\",\n \"truncateAfterCompaction\": true,\n \"maxActiveTranscriptBytes\": 1000000,\n \"notifyUser\": true,\n \"memoryFlush\": {\n \"enabled\": true,\n \"softThresholdTokens\": \"\"\n }\n },\n \"contextInjection\": \"continuation-skip\",\n \"experimental\": {\n \"localModelLean\": true\n },\n \"thinkingDefault\": \"off\",\n \"verboseDefault\": \"off\",\n \"blockStreamingDefault\": \"on\",\n \"heartbeat\": {\n \"every\": \"30m\",\n \"isolatedSession\": true,\n \"lightContext\": true,\n \"activeHours\": {\n \"start\": \"07:00\",\n \"end\": \"23:00\"\n },\n \"model\": \"local-qwen/qwen3.5-9b\"\n },\n \"subagents\": {\n \"model\": \"local-qwen/qwen3.5-9b\"\n }\n }\n}\n\n[plugins]\n{\n \"entries\": {\n \"telegram\": {\n \"enabled\": true\n },\n \"openrouter\": {\n \"enabled\": true\n },\n \"duckduckgo\": {\n \"enabled\": true\n },\n \"bonjour\": {\n \"enabled\": false\n },\n \"browser\": {\n \"enabled\": true\n },\n \"device-pair\": {\n \"enabled\": false\n },\n \"phone-control\": {\n \"enabled\": false\n },\n \"talk-voice\": {\n \"enabled\": false\n },\n \"file-transfer\": {\n \"enabled\": false\n },\n \"openai\": {\n \"enabled\": true\n },\n \"deepseek\": {\n \"enabled\": true\n }\n }\n}\n\n[gateway]\n{\n \"mode\": \"local\",\n \"auth\": \"\",\n \"port\": 18789,\n \"bind\": \"lan\",\n \"tailscale\": {\n \"mode\": \"off\",\n \"resetOnExit\": false\n },\n \"controlUi\": {\n \"allowInsecureAuth\": false,\n \"allowedOrigins\": [\n \"http://localhost:18789\",\n \"http://127.0.0.1:18789\",\n \"https://192.168.1.50:18788\"\n ]\n },\n \"nodes\": {\n \"denyCommands\": [\n \"camera.snap\",\n \"camera.clip\",\n \"screen.record\",\n \"contacts.add\",\n \"calendar.add\",\n \"reminders.add\",\n \"sms.send\",\n \"sms.search\"\n ]\n },\n \"remote\": {\n \"token\": \"***\"\n }\n}\n\n[models]\n{\n \"mode\": \"merge\",\n \"providers\": {\n \"local-qwen\": {\n \"baseUrl\": \"http://127.0.0.1:8081/v1\",\n \"apiKey\": \"***\",\n \"api\": \"openai-completions\",\n \"models\": [\n {\n \"id\": \"qwen3.5-9b\",\n \"name\": \"Qwen3.5-9B Local\",\n \"contextWindow\": 65536,\n \"maxTokens\": \"\",\n \"reasoning\": false,\n \"input\": [\n \"text\"\n ],\n \"cost\": {\n \"input\": 0,\n \"output\": 0,\n \"cacheRead\": 0,\n \"cacheWrite\": 0\n }\n }\n ]\n },\n \"deepseek\": {\n \"baseUrl\": \"https://api.deepseek.com\",\n \"api\": \"openai-completions\",\n \"models\": [\n {\n \"id\": \"deepseek-v4-flash\",\n \"name\": \"DeepSeek V4 Flash\",\n \"reasoning\": true,\n \"input\": [\n \"text\"\n ],\n \"cost\": {\n \"input\": 0.14,\n \"output\": 0.28,\n \"cacheRead\": 0.028,\n \"cacheWrite\": 0\n },\n \"contextWindow\": 1000000,\n \"maxTokens\": \"\",\n \"compat\": {\n \"supportsReasoningEffort\": true,\n \"supportsUsageInStreaming\": true,\n \"maxTokensField\": \"\"\n },\n \"api\": \"openai-completions\"\n },\n {\n \"id\": \"deepseek-v4-pro\",\n \"name\": \"DeepSeek V4 Pro\",\n \"reasoning\": true,\n \"input\": [\n \"text\"\n ],\n \"cost\": {\n \"input\": 1.74,\n \"output\": 3.48,\n \"cacheRead\": 0.145,\n \"cacheWrite\": 0\n },\n \"contextWindow\": 1000000,\n \"maxTokens\": \"\",\n \"compat\": {\n \"supportsReasoningEffort\": true,\n \"supportsUsageInStreaming\": true,\n \"maxTokensField\": \"\"\n },\n \"api\": \"openai-completions\"\n },\n {\n \"id\": \"deepseek-chat\",\n \"name\": \"DeepSeek Chat\",\n \"reasoning\": false,\n \"input\": [\n \"text\"\n ],\n \"cost\": {\n \"input\": 0.28,\n \"output\": 0.42,\n \"cacheRead\": 0.028,\n \"cacheWrite\": 0\n },\n \"contextWindow\": 131072,\n \"maxTokens\": \"\",\n \"compat\": {\n \"supportsUsageInStreaming\": true,\n \"maxTokensField\": \"\"\n },\n \"api\": \"openai-completions\"\n },\n {\n \"id\": \"deepseek-reasoner\",\n \"name\": \"DeepSeek Reasoner\",\n \"reasoning\": true,\n \"input\": [\n \"text\"\n ],\n \"cost\": {\n \"input\": 0.28,\n \"output\": 0.42,\n \"cacheRead\": 0.028,\n \"cacheWrite\": 0\n },\n \"contextWindow\": 131072,\n \"maxTokens\": \"\",\n \"compat\": {\n \"supportsReasoningEffort\": false,\n \"supportsUsageInStreaming\": true,\n \"maxTokensField\": \"\"\n },\n \"api\": \"openai-completions\"\n }\n ]\n }\n }\n}\n\n=== agents main files ===\n /home/rurouni/.openclaw/agents/main/agent/models.json\n /home/rurouni/.openclaw/agents/main/agent/auth-state.json\n /home/rurouni/.openclaw/agents/main/agent/models.json.bak.remove-old-qwen.20260503-160351\n /home/rurouni/.openclaw/agents/main/agent/auth-profiles.json\n /home/rurouni/.openclaw/agents/main/sessions/28b60577-c433-4c14-9b35-25733568288a.jsonl.bak-57453-1777852482734\n /home/rurouni/.openclaw/agents/main/sessions/9724145e-6917-43e0-a01d-9efe6b24562a.jsonl.bak-57453-1777851313903\n /home/rurouni/.openclaw/agents/main/sessions/a286a0ed-f806-4d27-9a3f-708fe154a4d3.jsonl.bak-39428-1777781304648\n /home/rurouni/.openclaw/agents/main/sessions/28b60577-c433-4c14-9b35-25733568288a.trajectory.jsonl\n /home/rurouni/.openclaw/agents/main/sessions/1635cbbb-c445-48a1-98b5-421218e6835d.jsonl.bak-39428-1777780755489\n /home/rurouni/.openclaw/agents/main/sessions/c44e5e25-3ff3-4038-b341-33998195f78a.jsonl\n /home/rurouni/.openclaw/agents/main/sessions/a924f588-f158-4b32-9825-f63043eac4a3.trajectory.jsonl\n /home/rurouni/.openclaw/agents/main/sessions/9e46476c-51e1-49d3-8fcd-3e5f1c6dcfe7.trajectory-path.json\n /home/rurouni/.openclaw/agents/main/sessions/2026-05-03T20-52-21-472Z_18baa83f-ed7f-4db7-9f7a-b8added9c5a3.trajectory-path.json\n /home/rurouni/.openclaw/agents/main/sessions/2026-05-03T17-01-27-770Z_4c84527a-68b9-4d4a-9860-efa5267ac080.jsonl.bak-45266-1777828124405\n /home/rurouni/.openclaw/agents/main/sessions/e7df0ff6-77db-4143-adbd-2a84172a60e9.jsonl.bak-44326-1777799287480\n /home/rurouni/.openclaw/agents/main/sessions/18dfbad6-95d5-4459-9c3e-858b6ec6e3f8.jsonl\n /home/rurouni/.openclaw/agents/main/sessions/cbdc15a6-6d06-461f-a451-85a27bab1d06.checkpoint.445daf2c-0122-4157-8a3a-093d06e2b46b.jsonl\n /home/rurouni/.openclaw/agents/main/sessions/8013b8e2-4550-4882-9e50-cbcfe43c01e6.jsonl.bak-44222-1777796496933\n /home/rurouni/.openclaw/agents/main/sessions/8013b8e2-4550-4882-9e50-cbcfe43c01e6.jsonl.bak-44222-1777795702008\n 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/home/rurouni/AGENTS.md\n 104 3733 /home/rurouni/SOUL.md\n 41 1750 /home/rurouni/USER.md\n 17 637 /home/rurouni/IDENTITY.md\n 9 226 /home/rurouni/HEARTBEAT.md\n\n=== memory markdown files ===\n7814 /home/rurouni/memory/archive/raw/2026-05-02-ruruni-setup.txt\n5810 /home/rurouni/memory/archive/raw/2026-05-02-agent-birth.txt\n3302 /home/rurouni/memory/archive/session-summaries/2026-05-03-llama-fix.txt\n2859 /home/rurouni/memory/2026-05-03-memory-cleanup.md\n2788 /home/rurouni/memory/2026-05-03.md\n2106 /home/rurouni/memory/archive/session-summaries/2026-05-03-storage-perms.txt\n1596 /home/rurouni/memory/archive/session-summaries/2026-05-03-memory-summary.txt\n1389 /home/rurouni/memory/archive/raw/2026-05-02-calm-ronin.txt\n1372 /home/rurouni/memory/archive/raw/2026-05-02-identity-setup.txt\n1009 /home/rurouni/memory/2026-05-02.md\n994 /home/rurouni/memory/README.txt\n543 /home/rurouni/memory/archive/session-summaries/2026-05-03-hello.txt\n529 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/home/rurouni/USER.md\n 17 637 /home/rurouni/IDENTITY.md\n 9 226 /home/rurouni/HEARTBEAT.md\n\n=== memory markdown files ===\n7814 /home/rurouni/memory/archive/raw/2026-05-02-ruruni-setup.txt\n5810 /home/rurouni/memory/archive/raw/2026-05-02-agent-birth.txt\n3302 /home/rurouni/memory/archive/session-summaries/2026-05-03-llama-fix.txt\n2859 /home/rurouni/memory/2026-05-03-memory-cleanup.md\n2788 /home/rurouni/memory/2026-05-03.md\n2106 /home/rurouni/memory/archive/session-summaries/2026-05-03-storage-perms.txt\n1596 /home/rurouni/memory/archive/session-summaries/2026-05-03-memory-summary.txt\n1389 /home/rurouni/memory/archive/raw/2026-05-02-calm-ronin.txt\n1372 /home/rurouni/memory/archive/raw/2026-05-02-identity-setup.txt\n1009 /home/rurouni/memory/2026-05-02.md\n994 /home/rurouni/memory/README.txt\n543 /home/rurouni/memory/archive/session-summaries/2026-05-03-hello.txt\n529 /home/rurouni/memory/archive/raw/2026-05-03-identity.txt\n471 /home/rurouni/memory/archive/raw/2026-05-02-memory-cleanup.txt\n369 /home/rurouni/memory/archive/session-summaries/2026-05-03-model-check.txt\n294 /home/rurouni/memory/archive/README.txt\n231 /home/rurouni/memory/archive/session-summaries/2026-05-03-general-help.txt\n224 /home/rurouni/memory/archive/session-summaries/2026-05-03-task-request.txt\n171 /home/rurouni/memory/archive/session-summaries/2026-05-03-1635.txt\n171 /home/rurouni/memory/archive/session-summaries/2026-05-03-1613.txt\n171 /home/rurouni/memory/archive/raw/2026-05-03-0104.txt\n171 /home/rurouni/memory/2026-05-03-1802.md\n\n=== openclaw memory sqlite ===\n-rw-r--r-- 1 rurouni rurouni 128K May 3 18:02 /home/rurouni/.openclaw/memory/main.sqlite","cwd":"/home/rurouni"},"isError":false,"timestamp":1777856866182}} 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{"type":"message","id":"3822591e","parentId":"e7bd3903","timestamp":"2026-05-04T01:07:54.094Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"id\":\"rs_02b86be3bb6b669e0169f7f163c2208196b77f59d8d1ee3dbc\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABp9_FpRYpfRCbgwuw3s6Ai5IMfnR2SNJnJ6rhZSYKdsOAffKfw47Uf70Rzr6r-BtcGh2NVqN-h9SeTUpgdYc5DmfUcxtkHen_tGTau_pyeLdYE428Pu8jvRPnnNBwi_F4Xx3krcRoa-Du7ycA_808psRuNqaW6uvWgm94n2foAfwTIcHhjoY2969S0dLTK9WGi9F_f2R2AnIyttwq1QxZMJ3uKxpdsxnito922b_wNnFzbFHmM22yZG29NwXf3v5bL9l9g85f7wQD3qGYXPBFy6DEOduwRlmv_jTxN67TSulaQtXWoAeqQWKqE7GJQ303vyHT88HOEOb1o-mkk7m3L2QS-q-xTjdBfBL_2EQdcVEL774pDL8DuUh0v4KKRBA9VJiGyLrG38u_WjmeMEPI8a-LONHV-nRcpg5_roCZ7ks3ROKFrn_U38jcPkh9iQoEJk0tNcIspkvwNMpti66KM-Ap0GTkFlmoupFcFBbJM-Kyw7Lw3emAnsNO_s1lZf6kLuUUSSKNbSR1lXz5xKCbUJaiK6gLwK7qriPnGiImY06ugg16Ukoi5Ijqs1N3hY6spmKUL7Unw1respvPY_ZhSZh6VQggGl4gdlXFPZZRUW0O7wRc7M4fR5ztXD0mI8DzRT8Sggjv65r3TiguNDF9GLRFTHNbCy81Uaq51j-1ZVk4-C5g1RaJXwzeuBsqyEnNvrEDAJAjWarxvKFOKkDZTMRQiqF_5das93M-EWYAx2cvkY--6wAj1zG6i-KCVFhXRf4JlYpSIIOt9p9fmg-QG-QJvIc6va4vpSUr8gx_VUk1ptGD81D_gWc7xmkgmDtZi2UpLHI47YF2a0vHVkaHNpDWiaF7KGFIxAM5l9ideNw6taCacsHO_AJc4XLXwtc-uOw9DoH2Wvy9vY5e3xBZ76_0MSp2pG9DnjD8pEYOc0303q3Sq89IxuZlltfw9boWSdXwEaC6NmjWssSSKjzW3GLSSgQ2DrfG8PRkw0UtiUrVr8w6UtlAIXl5CMgWjuR_X2EZnxdAIKvf3i53vRjpLgWj5dbKRkiulaqCvpdQpGwO_zxYSozzYWP-kdAVnSAh-c2qsSazs88LBUi4bHyoOrnHdWEuwM5kuwK8M4UW0NjBUflyhBky9BepCyQv4iaaQmH_1OugTJ4Y4jnKqXsyNReRhGL4DcLF6VxD2Li5r3VIQ8EK5Vxy7T834-9fAlD3E45HzlkJwx3S2wnCn1KUNxGOYJ60ZLE2xxMiuOYtaKmXLmIf1WBJymxx5sO3xetxJCQzTGH7-LYvrZ_YEq6aJyluC_ath-dIsSXreFtMLNDaJtHsUBTgTQTj7PdqJKEDMqbQ7dOL21nqDba3IR7RyRIHxsW3CQio31kQanAAfmpsNGkt1zjlZZtqIPeOm3EfjK8Kbu7XMzIHfVK10vqfp-sFw2APSk3r9eDSqS4UqJQsJxWk-t4o07y4aLYyiKSWIiGyh6uW8Dv7t7eNxEEtOVRMN4hLq705zPuxql7p37e7uFiZpOqRCeK2cIlkCpj7IojqkDvStYu8PSb7VSPa_qqJIMsULLg65rO_U7DAEDvAKBPNdu1lGRgg7c40sYtfUxL7Xcw695hcaMF2XTJvNfs494LX4lS3N0Sm3Lu__URP01dmvMA9jKF-wcXH2UKHcuLTiQ6bH0YviU-A28YjOncZBPICZMRE3T6ldj_RuD4BGafEloNjL9E8PBUjk1jE-_64q9AUdbYiu52FNs6ZLsXRFFXPXLFt1IAKdThnibrgcNF9xTQPAJ_0ESX58gMQsTg1jOg2Y9ztpYjikIHQjNJ_3sLYvfWBrORT6pm3Rk00naFh8ZoZCiubkltuv5hnCEFn1PBTMOnHU0x8yRJPcu0pn4r7x_PCFT72sxZv4Sb-8aw4PPWOeNWChhwElPm4MNSIp\",\"summary\":[]}"},{"type":"toolCall","id":"call_WvcmtG7FQPPqLksfk2r2FTng|fc_02b86be3bb6b669e0169f7f1697614819697eac93eb97bc3a3","name":"read","arguments":{"path":"/usr/lib/node_modules/openclaw/docs/concepts/memory-qmd.md","offset":1,"limit":180}},{"type":"toolCall","id":"call_oZ8IzEYwltZPOWM21mZpWkvb|fc_02b86be3bb6b669e0169f7f16976208196905460849e0879ae","name":"read","arguments":{"path":"/usr/lib/node_modules/openclaw/docs/concepts/context-engine.md","offset":20,"limit":80}},{"type":"toolCall","id":"call_9IlgDdt4NQBJDCWTnOSyNXz7|fc_02b86be3bb6b669e0169f7f169762c819680c4e879ba92bc7e","name":"read","arguments":{"path":"/usr/lib/node_modules/openclaw/docs/plugins/community.md","offset":60,"limit":25}},{"type":"toolCall","id":"call_Mdga7jSDnjJcgxkAusS8Mv05|fc_02b86be3bb6b669e0169f7f169763481968fff0382bfc8e4c3","name":"read","arguments":{"path":"/usr/lib/node_modules/openclaw/docs/gateway/config-agents.md","offset":130,"limit":90}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.5","usage":{"input":17643,"output":336,"cacheRead":33792,"cacheWrite":0,"totalTokens":51771,"cost":{"input":0.088215,"output":0.01008,"cacheRead":0.016895999999999998,"cacheWrite":0,"total":0.115191}},"stopReason":"toolUse","timestamp":1777856866187,"responseId":"resp_02b86be3bb6b669e0169f7f1628bd081969e4246a8e06e3dc2"}} {"type":"message","id":"a702ed20","parentId":"3822591e","timestamp":"2026-05-04T01:07:54.117Z","message":{"role":"toolResult","toolCallId":"call_WvcmtG7FQPPqLksfk2r2FTng|fc_02b86be3bb6b669e0169f7f1697614819697eac93eb97bc3a3","toolName":"read","content":[{"type":"text","text":"---\nsummary: \"Local-first search sidecar with BM25, vectors, reranking, and query expansion\"\ntitle: \"QMD memory engine\"\nread_when:\n - You want to set up QMD as your memory backend\n - You want advanced memory features like reranking or extra indexed paths\n---\n\n[QMD](https://github.com/tobi/qmd) is a local-first search sidecar that runs\nalongside OpenClaw. It combines BM25, vector search, and reranking in a single\nbinary, and can index content beyond your workspace memory files.\n\n## What it adds over builtin\n\n- **Reranking and query expansion** for better recall.\n- **Index extra directories** -- project docs, team notes, anything on disk.\n- **Index session transcripts** -- recall earlier conversations.\n- **Fully local** -- runs with the optional node-llama-cpp runtime package and\n auto-downloads GGUF models.\n- **Automatic fallback** -- if QMD is unavailable, OpenClaw falls back to the\n builtin engine seamlessly.\n\n## Getting started\n\n### Prerequisites\n\n- Install QMD: `npm install -g @tobilu/qmd` or `bun install -g @tobilu/qmd`\n- SQLite build that allows extensions (`brew install sqlite` on macOS).\n- QMD must be on the gateway's `PATH`.\n- macOS and Linux work out of the box. Windows is best supported via WSL2.\n\n### Enable\n\n```json5\n{\n memory: {\n backend: \"qmd\",\n },\n}\n```\n\nOpenClaw creates a self-contained QMD home under\n`~/.openclaw/agents//qmd/` and manages the sidecar lifecycle\nautomatically -- collections, updates, and embedding runs are handled for you.\nIt prefers current QMD collection and MCP query shapes, but still falls back to\nalternate collection pattern flags and older MCP tool names when needed.\nBoot-time reconciliation also recreates stale managed collections back to their\ncanonical patterns when an older QMD collection with the same name is still\npresent.\n\n## How the sidecar works\n\n- OpenClaw creates collections from your workspace memory files and any\n configured `memory.qmd.paths`, then runs `qmd update` when the QMD manager is\n opened and periodically afterward (default every 5 minutes). These refreshes\n run through QMD subprocesses, not an in-process filesystem crawl. Semantic\n modes also run `qmd embed`.\n- The default workspace collection tracks `MEMORY.md` plus the `memory/`\n tree. Lowercase `memory.md` is not indexed as a root memory file.\n- QMD's own scanner ignores hidden paths and common dependency/build\n directories such as `.git`, `.cache`, `node_modules`, `vendor`, `dist`, and\n `build`. Gateway startup does not initialize QMD by default, so cold boot\n avoids importing the memory runtime or creating the long-lived watcher before\n memory is first used.\n- If you want a gateway-start refresh anyway, set\n `memory.qmd.update.startup` to `idle` or `immediate`. The opt-in startup\n refresh uses a one-shot QMD subprocess path instead of creating the full\n long-lived in-process watcher.\n- Searches use the configured `searchMode` (default: `search`; also supports\n `vsearch` and `query`). `search` is BM25-only, so OpenClaw skips semantic\n vector readiness probes and embedding maintenance in that mode. If a mode\n fails, OpenClaw retries with `qmd query`.\n- With QMD releases that advertise multi-collection filters, OpenClaw groups\n same-source collections into one QMD search invocation. Older QMD releases\n keep the compatible per-collection fallback.\n- If QMD fails entirely, OpenClaw falls back to the builtin SQLite engine.\n Repeated chat-turn attempts back off briefly after an open failure so a\n missing binary or broken sidecar dependency does not create a retry storm;\n `openclaw memory status` and one-shot CLI probes still recheck QMD directly.\n\n\nThe first search may be slow -- QMD auto-downloads GGUF models (~2 GB) for\nreranking and query expansion on the first `qmd query` run.\n\n\n## Search performance and compatibility\n\nOpenClaw keeps the QMD search path compatible with both current and older QMD\ninstalls.\n\nOn startup, OpenClaw checks the installed QMD help text once per manager. If the\nbinary advertises support for multiple collection filters, OpenClaw searches all\nsame-source collections with one command:\n\n```bash\nqmd search \"router notes\" --json -n 10 -c memory-root-main -c memory-dir-main\n```\n\nThis avoids starting one QMD subprocess for every durable-memory collection.\nSession transcript collections stay in their own source group, so mixed\n`memory` + `sessions` searches still give the result diversifier input from both\nsources.\n\nOlder QMD builds only accept one collection filter. When OpenClaw detects one\nof those builds, it keeps the compatibility path and searches each collection\nseparately before merging and deduplicating results.\n\nTo inspect the installed contract manually, run:\n\n```bash\nqmd --help | grep -i collection\n```\n\nCurrent QMD help says collection filters can target one or more collections.\nOlder help usually describes a single collection.\n\n## Model overrides\n\nQMD model environment variables pass through unchanged from the gateway\nprocess, so you can tune QMD globally without adding new OpenClaw config:\n\n```bash\nexport QMD_EMBED_MODEL=\"hf:Qwen/Qwen3-Embedding-0.6B-GGUF/Qwen3-Embedding-0.6B-Q8_0.gguf\"\nexport QMD_RERANK_MODEL=\"/absolute/path/to/reranker.gguf\"\nexport QMD_GENERATE_MODEL=\"/absolute/path/to/generator.gguf\"\n```\n\nAfter changing the embedding model, rerun embeddings so the index matches the\nnew vector space.\n\n## Indexing extra paths\n\nPoint QMD at additional directories to make them searchable:\n\n```json5\n{\n memory: {\n backend: \"qmd\",\n qmd: {\n paths: [{ name: \"docs\", path: \"~/notes\", pattern: \"**/*.md\" }],\n },\n },\n}\n```\n\nSnippets from extra paths appear as `qmd//` in\nsearch results. `memory_get` understands this prefix and reads from the correct\ncollection root.\n\n## Indexing session transcripts\n\nEnable session indexing to recall earlier conversations:\n\n```json5\n{\n memory: {\n backend: \"qmd\",\n qmd: {\n sessions: { enabled: true },\n },\n },\n}\n```\n\nTranscripts are exported as sanitized User/Assistant turns into a dedicated QMD\ncollection under `~/.openclaw/agents//qmd/sessions/`.\n\n## Search scope\n\nBy default, QMD search results are surfaced in direct and channel sessions\n(not groups). Configure `memory.qmd.scope` to change this:\n\n```json5\n{\n memory: {\n qmd: {\n scope: {\n default: \"deny\",\n rules: [{ action: \"allow\", match: { chatType: \"direct\" } }],\n },\n\n[92 more lines in file. Use offset=181 to continue.]"}],"isError":false,"timestamp":1777856874117}} {"type":"message","id":"accce96a","parentId":"a702ed20","timestamp":"2026-05-04T01:07:54.118Z","message":{"role":"toolResult","toolCallId":"call_oZ8IzEYwltZPOWM21mZpWkvb|fc_02b86be3bb6b669e0169f7f16976208196905460849e0879ae","toolName":"read","content":[{"type":"text","text":" openclaw doctor\n # or inspect config directly:\n cat ~/.openclaw/openclaw.json | jq '.plugins.slots.contextEngine'\n ```\n \n \n Context engine plugins are installed like any other OpenClaw plugin.\n\n \n \n ```bash\n openclaw plugins install @martian-engineering/lossless-claw\n ```\n \n \n ```bash\n openclaw plugins install -l ./my-context-engine\n ```\n \n \n\n \n \n ```json5\n // openclaw.json\n {\n plugins: {\n slots: {\n contextEngine: \"lossless-claw\", // must match the plugin's registered engine id\n },\n entries: {\n \"lossless-claw\": {\n enabled: true,\n // Plugin-specific config goes here (see the plugin's docs)\n },\n },\n },\n }\n ```\n\n Restart the gateway after installing and configuring.\n\n \n \n Set `contextEngine` to `\"legacy\"` (or remove the key entirely — `\"legacy\"` is the default).\n \n\n\n## How it works\n\nEvery time OpenClaw runs a model prompt, the context engine participates at four lifecycle points:\n\n\n \n Called when a new message is added to the session. The engine can store or index the message in its own data store.\n \n \n Called before each model run. The engine returns an ordered set of messages (and an optional `systemPromptAddition`) that fit within the token budget.\n \n \n Called when the context window is full, or when the user runs `/compact`. The engine summarizes older history to free space.\n \n \n Called after a run completes. The engine can persist state, trigger background compaction, or update indexes.\n \n\n\nFor the bundled non-ACP Codex harness, OpenClaw applies the same lifecycle by projecting assembled context into Codex developer instructions and the current turn prompt. Codex still owns its native thread history and native compactor.\n\n### Subagent lifecycle (optional)\n\nOpenClaw calls two optional subagent lifecycle hooks:\n\n\n Prepare shared context state before a child run starts. The hook receives parent/child session keys, `contextMode` (`isolated` or `fork`), available transcript ids/files, and optional TTL. If it returns a rollback handle, OpenClaw calls it when spawn fails after preparation succeeds.\n\n\n Clean up when a subagent session completes or is swept.\n\n\n\n[208 more lines in file. Use offset=100 to continue.]"}],"isError":false,"timestamp":1777856874117}} {"type":"message","id":"5b739061","parentId":"accce96a","timestamp":"2026-05-04T01:07:54.118Z","message":{"role":"toolResult","toolCallId":"call_9IlgDdt4NQBJDCWTnOSyNXz7|fc_02b86be3bb6b669e0169f7f169762c819680c4e879ba92bc7e","toolName":"read","content":[{"type":"text","text":"\n```bash\nopenclaw plugins install @largezhou/ddingtalk\n```\n\n### Lossless Claw (LCM)\n\nLossless Context Management plugin for OpenClaw. DAG-based conversation\nsummarization with incremental compaction — preserves full context fidelity\nwhile reducing token usage.\n\n- **npm:** `@martian-engineering/lossless-claw`\n- **repo:** [github.com/Martian-Engineering/lossless-claw](https://github.com/Martian-Engineering/lossless-claw)\n\n```bash\nopenclaw plugins install @martian-engineering/lossless-claw\n```\n\n### Opik\n\nOfficial plugin that exports agent traces to Opik. Monitor agent behavior,\ncost, tokens, errors, and more.\n\n- **npm:** `@opik/opik-openclaw`\n- **repo:** [github.com/comet-ml/opik-openclaw](https://github.com/comet-ml/opik-openclaw)\n\n[110 more lines in file. Use offset=85 to continue.]"}],"isError":false,"timestamp":1777856874117}} {"type":"message","id":"ef727a58","parentId":"5b739061","timestamp":"2026-05-04T01:07:54.122Z","message":{"role":"toolResult","toolCallId":"call_Mdga7jSDnjJcgxkAusS8Mv05|fc_02b86be3bb6b669e0169f7f169763481968fff0382bfc8e4c3","toolName":"read","content":[{"type":"text","text":"```\n\n### Context budget ownership map\n\nOpenClaw has multiple high-volume prompt/context budgets, and they are\nintentionally split by subsystem instead of all flowing through one generic\nknob.\n\n- `agents.defaults.bootstrapMaxChars` /\n `agents.defaults.bootstrapTotalMaxChars`:\n normal workspace bootstrap injection.\n- `agents.defaults.startupContext.*`:\n one-shot reset/startup model-run prelude, including recent daily\n `memory/*.md` files. Bare chat `/new` and `/reset` commands are\n acknowledged without invoking the model.\n- `skills.limits.*`:\n the compact skills list injected into the system prompt.\n- `agents.defaults.contextLimits.*`:\n bounded runtime excerpts and injected runtime-owned blocks.\n- `memory.qmd.limits.*`:\n indexed memory-search snippet and injection sizing.\n\nUse the matching per-agent override only when one agent needs a different\nbudget:\n\n- `agents.list[].skillsLimits.maxSkillsPromptChars`\n- `agents.list[].contextLimits.*`\n\n#### `agents.defaults.startupContext`\n\nControls the first-turn startup prelude injected on reset/startup model runs.\nBare chat `/new` and `/reset` commands acknowledge the reset without invoking\nthe model, so they do not load this prelude.\n\n```json5\n{\n agents: {\n defaults: {\n startupContext: {\n enabled: true,\n applyOn: [\"new\", \"reset\"],\n dailyMemoryDays: 2,\n maxFileBytes: 16384,\n maxFileChars: 1200,\n maxTotalChars: 2800,\n },\n },\n },\n}\n```\n\n#### `agents.defaults.contextLimits`\n\nShared defaults for bounded runtime context surfaces.\n\n```json5\n{\n agents: {\n defaults: {\n contextLimits: {\n memoryGetMaxChars: 12000,\n memoryGetDefaultLines: 120,\n toolResultMaxChars: 16000,\n postCompactionMaxChars: 1800,\n },\n },\n },\n}\n```\n\n- `memoryGetMaxChars`: default `memory_get` excerpt cap before truncation\n metadata and continuation notice are added.\n- `memoryGetDefaultLines`: default `memory_get` line window when `lines` is\n omitted.\n- `toolResultMaxChars`: live tool-result cap used for persisted results and\n overflow recovery.\n- `postCompactionMaxChars`: AGENTS.md excerpt cap used during post-compaction\n refresh injection.\n\n#### `agents.list[].contextLimits`\n\nPer-agent override for the shared `contextLimits` knobs. Omitted fields inherit\nfrom `agents.defaults.contextLimits`.\n\n```json5\n{\n agents: {\n defaults: {\n contextLimits: {\n memoryGetMaxChars: 12000,\n\n[1186 more lines in file. Use offset=220 to continue.]"}],"isError":false,"timestamp":1777856874118}} {"type":"message","id":"cffe2ba5","parentId":"ef727a58","timestamp":"2026-05-04T01:07:56.299Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"id\":\"rs_02b86be3bb6b669e0169f7f16b918081968a20cbc38bc090f1\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABp9_Fro4LmxMMU0lNgUynF7ARJdQK34Xigl7eaFvUjz0Hr1PTOZalxUzM_t4S7xRPASkWQjL6-ZSag8G5ioc7DglwU19UIlfdvLvElLRixLKtCA8i7vk2QFgXFAtO8piOUVny9HkhD-On8sWHSr3TZMzVchpdwW7YWdRcoPEpbvMZe4u-7AHoKd0B9AEt7fUIpdR4gZaE_nHWe4j7RL-xu0vwT9jayIEnXVE66eOfDQieATHBMJ5iZLCDGWKL7EwOzriBs-zmF2gDTBGECKTr_2kjHOyepxFxLH9gyig6ZXYooq2G5aSc69kek9HzQhnKUnMjy9cS7xJD7AgdAST0_dq1l7SL84GmPQA2uCtSm74T7_pvXFGJrUZUri2Ub90AYRJpNP9KgQaaaQooDdRwjOod_eNH-i3FVq_z3VA5WtWRYaQjsL59Zfv76sZybiZqx9--yEp0D8BrdMJzAqJcbSC0SyE-JX3tfH49stwh1RMif0PNfnIq3YeEuOyJ73uGl9LCT9IirwZ0d-udyC3CK50jV05RkoMvxwfNYDR9ZvhfRZicCD-UiqUCD4nAJ5YYP-ib1rnamGI7bokKzZKdTTO89td5Mwb-sOdyFXkjUYB1hhBrjmYMvZ-Vf9LPsK_EQPDP61wVKAouzlCZCBBnD6PYs5RVifiayoykWVNZBvy8TcP-3NgFXQbLT4f6vCmbgELH2bJybYzx-WkY3EYqFqDdtHWjHf2WBu15ch81cNi5WB5Mmd5PyuBGhpw1fkPfrnRTDM4_Kptgby9pfLjHulCaVbYMCIJ2cHLcWzwZ5x-tpXPxnQ13DmLVRGcF-hEzul3WwaMzNTbU2KxsI6yh2yGAc6jIS0HtaHs89guXq-DI0g4NlSDmcCrJAAvv0k-rSwJZmwXESU4ORxnCImZGFFTYoStd2xHB58uS7BtfG6bp-iUHa5HO7rEKAm59BKTTnL936\",\"summary\":[]}"},{"type":"toolCall","id":"call_880az4fSU1pdQEMJCreyGzn0|fc_02b86be3bb6b669e0169f7f16bcdc881969d55addfef83713e","name":"read","arguments":{"path":"/usr/lib/node_modules/openclaw/docs/concepts/memory-qmd.md","offset":181,"limit":130}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.5","usage":{"input":3638,"output":53,"cacheRead":51200,"cacheWrite":0,"totalTokens":54891,"cost":{"input":0.01819,"output":0.00159,"cacheRead":0.025599999999999998,"cacheWrite":0,"total":0.045380000000000004}},"stopReason":"toolUse","timestamp":1777856874125,"responseId":"resp_02b86be3bb6b669e0169f7f16a6e04819686b51ddfc5033238"}} {"type":"message","id":"3980de72","parentId":"cffe2ba5","timestamp":"2026-05-04T01:07:56.307Z","message":{"role":"toolResult","toolCallId":"call_880az4fSU1pdQEMJCreyGzn0|fc_02b86be3bb6b669e0169f7f16bcdc881969d55addfef83713e","toolName":"read","content":[{"type":"text","text":" },\n },\n}\n```\n\nWhen scope denies a search, OpenClaw logs a warning with the derived channel and\nchat type so empty results are easier to debug.\n\n## Citations\n\nWhen `memory.citations` is `auto` or `on`, search snippets include a\n`Source: ` footer. Set `memory.citations = \"off\"` to omit the footer\nwhile still passing the path to the agent internally.\n\n## When to use\n\nChoose QMD when you need:\n\n- Reranking for higher-quality results.\n- To search project docs or notes outside the workspace.\n- To recall past session conversations.\n- Fully local search with no API keys.\n\nFor simpler setups, the [builtin engine](/concepts/memory-builtin) works well\nwith no extra dependencies.\n\n## Troubleshooting\n\n**QMD not found?** Ensure the binary is on the gateway's `PATH`. If OpenClaw\nruns as a service, create a symlink:\n`sudo ln -s ~/.bun/bin/qmd /usr/local/bin/qmd`.\n\nIf `qmd --version` works in your shell but OpenClaw still reports\n`spawn qmd ENOENT`, the gateway process likely has a different `PATH` than your\ninteractive shell. Pin the binary explicitly:\n\n```json5\n{\n memory: {\n backend: \"qmd\",\n qmd: {\n command: \"/absolute/path/to/qmd\",\n },\n },\n}\n```\n\nUse `command -v qmd` in the environment where QMD is installed, then recheck\nwith `openclaw memory status --deep`.\n\n**First search very slow?** QMD downloads GGUF models on first use. Pre-warm\nwith `qmd query \"test\"` using the same XDG dirs OpenClaw uses.\n\n**Many QMD subprocesses during search?** Update QMD if possible. OpenClaw uses\none process for same-source multi-collection searches only when the installed\nQMD advertises support for multiple `-c` filters; otherwise it keeps the older\nper-collection fallback for correctness.\n\n**BM25-only QMD still trying to build llama.cpp?** Set\n`memory.qmd.searchMode = \"search\"`. OpenClaw treats that mode as lexical-only,\ndoes not run QMD vector status probes or embedding maintenance, and leaves\nsemantic readiness checks to `vsearch` or `query` setups.\n\n**Search times out?** Increase `memory.qmd.limits.timeoutMs` (default: 4000ms).\nSet to `120000` for slower hardware.\n\n**Empty results in group chats?** Check `memory.qmd.scope` -- the default only\nallows direct and channel sessions.\n\n**Root memory search suddenly got too broad?** Restart the gateway or wait for\nthe next startup reconciliation. OpenClaw recreates stale managed collections\nback to canonical `MEMORY.md` and `memory/` patterns when it detects a same-name\nconflict.\n\n**Workspace-visible temp repos causing `ENAMETOOLONG` or broken indexing?**\nQMD traversal currently follows the underlying QMD scanner behavior rather than\nOpenClaw's builtin symlink rules. Keep temporary monorepo checkouts under\nhidden directories like `.tmp/` or outside indexed QMD roots until QMD exposes\ncycle-safe traversal or explicit exclusion controls.\n\n## Configuration\n\nFor the full config surface (`memory.qmd.*`), search modes, update intervals,\nscope rules, and all other knobs, see the\n[Memory configuration reference](/reference/memory-config).\n\n## Related\n\n- [Memory overview](/concepts/memory)\n- [Builtin memory engine](/concepts/memory-builtin)\n- [Honcho memory](/concepts/memory-honcho)\n"}],"isError":false,"timestamp":1777856876307}} {"type":"message","id":"d0bd24cb","parentId":"3980de72","timestamp":"2026-05-04T01:07:58.852Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_GXkxKUfusnaDYNMLhQbb9X87|fc_02b86be3bb6b669e0169f7f16e42ec81968a88e718bf365532","name":"read","arguments":{"path":"/usr/lib/node_modules/openclaw/docs/reference/memory-config.md","offset":1,"limit":260}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.5","usage":{"input":1407,"output":38,"cacheRead":54272,"cacheWrite":0,"totalTokens":55717,"cost":{"input":0.0070350000000000005,"output":0.00114,"cacheRead":0.027136,"cacheWrite":0,"total":0.035311}},"stopReason":"toolUse","timestamp":1777856876314,"responseId":"resp_02b86be3bb6b669e0169f7f16ca324819682f7516da65c7efb"}} {"type":"message","id":"a9f17fda","parentId":"d0bd24cb","timestamp":"2026-05-04T01:07:58.862Z","message":{"role":"toolResult","toolCallId":"call_GXkxKUfusnaDYNMLhQbb9X87|fc_02b86be3bb6b669e0169f7f16e42ec81968a88e718bf365532","toolName":"read","content":[{"type":"text","text":"---\nsummary: \"All configuration knobs for memory search, embedding providers, QMD, hybrid search, and multimodal indexing\"\ntitle: \"Memory configuration reference\"\nsidebarTitle: \"Memory config\"\nread_when:\n - You want to configure memory search providers or embedding models\n - You want to set up the QMD backend\n - You want to tune hybrid search, MMR, or temporal decay\n - You want to enable multimodal memory indexing\n---\n\nThis page lists every configuration knob for OpenClaw memory search. For conceptual overviews, see:\n\n\n \n How memory works.\n \n \n Default SQLite backend.\n \n \n Local-first sidecar.\n \n \n Search pipeline and tuning.\n \n \n Memory sub-agent for interactive sessions.\n \n\n\nAll memory search settings live under `agents.defaults.memorySearch` in `openclaw.json` unless noted otherwise.\n\n\nIf you are looking for the **active memory** feature toggle and sub-agent config, that lives under `plugins.entries.active-memory` instead of `memorySearch`.\n\nActive memory uses a two-gate model:\n\n1. the plugin must be enabled and target the current agent id\n2. the request must be an eligible interactive persistent chat session\n\nSee [Active Memory](/concepts/active-memory) for the activation model, plugin-owned config, transcript persistence, and safe rollout pattern.\n\n\n---\n\n## Provider selection\n\n| Key | Type | Default | Description |\n| ---------- | --------- | ---------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |\n| `provider` | `string` | auto-detected | Embedding adapter ID such as `bedrock`, `deepinfra`, `gemini`, `github-copilot`, `local`, `mistral`, `ollama`, `openai`, or `voyage`; may also be a configured `models.providers.` whose `api` points at one of those adapters |\n| `model` | `string` | provider default | Embedding model name |\n| `fallback` | `string` | `\"none\"` | Fallback adapter ID when the primary fails |\n| `enabled` | `boolean` | `true` | Enable or disable memory search |\n\n### Auto-detection order\n\nWhen `provider` is not set, OpenClaw selects the first available:\n\n\n \n Selected if `memorySearch.local.modelPath` is configured and the file exists.\n \n \n Selected if a GitHub Copilot token can be resolved (env var or auth profile).\n \n \n Selected if an OpenAI key can be resolved.\n \n \n Selected if a Gemini key can be resolved.\n \n \n Selected if a Voyage key can be resolved.\n \n \n Selected if a Mistral key can be resolved.\n \n \n Selected if a DeepInfra key can be resolved.\n \n \n Selected if the AWS SDK credential chain resolves (instance role, access keys, profile, SSO, web identity, or shared config).\n \n\n\n`ollama` is supported but not auto-detected (set it explicitly).\n\n### Custom provider ids\n\n`memorySearch.provider` can point at a custom `models.providers.` entry. OpenClaw resolves that provider's `api` owner for the embedding adapter while preserving the custom provider id for endpoint, auth, and model-prefix handling. This lets multi-GPU or multi-host setups dedicate memory embeddings to a specific local endpoint:\n\n```json5\n{\n models: {\n providers: {\n \"ollama-5080\": {\n api: \"ollama\",\n baseUrl: \"http://gpu-box.local:11435\",\n apiKey: \"ollama-local\",\n models: [{ id: \"qwen3-embedding:0.6b\" }],\n },\n },\n },\n agents: {\n defaults: {\n memorySearch: {\n provider: \"ollama-5080\",\n model: \"qwen3-embedding:0.6b\",\n },\n },\n },\n}\n```\n\n### API key resolution\n\nRemote embeddings require an API key. Bedrock uses the AWS SDK default credential chain instead (instance roles, SSO, access keys).\n\n| Provider | Env var | Config key |\n| -------------- | -------------------------------------------------- | ----------------------------------- |\n| Bedrock | AWS credential chain | No API key needed |\n| DeepInfra | `DEEPINFRA_API_KEY` | `models.providers.deepinfra.apiKey` |\n| Gemini | `GEMINI_API_KEY` | `models.providers.google.apiKey` |\n| GitHub Copilot | `COPILOT_GITHUB_TOKEN`, `GH_TOKEN`, `GITHUB_TOKEN` | Auth profile via device login |\n| Mistral | `MISTRAL_API_KEY` | `models.providers.mistral.apiKey` |\n| Ollama | `OLLAMA_API_KEY` (placeholder) | -- |\n| OpenAI | `OPENAI_API_KEY` | `models.providers.openai.apiKey` |\n| Voyage | `VOYAGE_API_KEY` | `models.providers.voyage.apiKey` |\n\n\nCodex OAuth covers chat/completions only and does not satisfy embedding requests.\n\n\n---\n\n## Remote endpoint config\n\nFor custom OpenAI-compatible endpoints or overriding provider defaults:\n\n\n Custom API base URL.\n\n\n Override API key.\n\n\n Extra HTTP headers (merged with provider defaults).\n\n\n```json5\n{\n agents: {\n defaults: {\n memorySearch: {\n provider: \"openai\",\n model: \"text-embedding-3-small\",\n remote: {\n baseUrl: \"https://api.example.com/v1/\",\n apiKey: \"YOUR_KEY\",\n },\n },\n },\n },\n}\n```\n\n---\n\n## Provider-specific config\n\n\n \n | Key | Type | Default | Description |\n | ---------------------- | -------- | ---------------------- | ------------------------------------------ |\n | `model` | `string` | `gemini-embedding-001` | Also supports `gemini-embedding-2-preview` |\n | `outputDimensionality` | `number` | `3072` | For Embedding 2: 768, 1536, or 3072 |\n\n \n Changing model or `outputDimensionality` triggers an automatic full reindex.\n \n\n \n \n OpenAI-compatible embedding endpoints can opt into provider-specific `input_type` request fields. This is useful for asymmetric embedding models that require different labels for query and document embeddings.\n\n | Key | Type | Default | Description |\n | ------------------- | -------- | ------- | ------------------------------------------------------- |\n | `inputType` | `string` | unset | Shared `input_type` for query and document embeddings |\n | `queryInputType` | `string` | unset | Query-time `input_type`; overrides `inputType` |\n | `documentInputType` | `string` | unset | Index/document `input_type`; overrides `inputType` |\n\n ```json5\n {\n agents: {\n defaults: {\n memorySearch: {\n provider: \"openai\",\n remote: {\n baseUrl: \"https://embeddings.example/v1\",\n apiKey: \"env:EMBEDDINGS_API_KEY\",\n },\n model: \"asymmetric-embedder\",\n queryInputType: \"query\",\n documentInputType: \"passage\",\n },\n },\n },\n }\n ```\n\n Changing these values affects embedding cache identity for provider batch indexing and should be followed by a memory reindex when the upstream model treats the labels differently.\n\n \n \n ### Bedrock embedding config\n\n Bedrock uses the AWS SDK default credential chain — no API keys needed. If OpenClaw runs on EC2 with a Bedrock-enabled instance role, just set the provider and model:\n\n ```json5\n {\n agents: {\n defaults: {\n memorySearch: {\n provider: \"bedrock\",\n model: \"amazon.titan-embed-text-v2:0\",\n },\n },\n },\n }\n ```\n\n | Key | Type | Default | Description |\n | ---------------------- | -------- | ------------------------------ | ------------------------------- |\n | `model` | `string` | `amazon.titan-embed-text-v2:0` | Any Bedrock embedding model ID |\n | `outputDimensionality` | `number` | model default | For Titan V2: 256, 512, or 1024 |\n\n **Supported models** (with family detection and dimension defaults):\n\n | Model ID | Provider | Default Dims | Configurable Dims |\n | ------------------------------------------ | ---------- | ------------ | -------------------- |\n | `amazon.titan-embed-text-v2:0` | Amazon | 1024 | 256, 512, 1024 |\n | `amazon.titan-embed-text-v1` | Amazon | 1536 | -- |\n | `amazon.titan-embed-g1-text-02` | Amazon | 1536 | -- |\n | `amazon.titan-embed-image-v1` | Amazon | 1024 | -- |\n | `amazon.nova-2-multimodal-embeddings-v1:0` | Amazon | 1024 | 256, 384, 1024, 3072 |\n | `cohere.embed-english-v3` | Cohere | 1024 | -- |\n | `cohere.embed-multilingual-v3` | Cohere | 1024 | -- |\n | `cohere.embed-v4:0` | Cohere | 1536 | 256-1536 |\n | `twelvelabs.marengo-embed-3-0-v1:0` | TwelveLabs | 512 | -- |\n | `twelvelabs.marengo-embed-2-7-v1:0` | TwelveLabs | 1024 | -- |\n\n Throughput-suffixed variants (e.g., `amazon.titan-embed-text-v1:2:8k`) inherit the base model's configuration.\n\n **Authentication:** Bedrock auth uses the standard AWS SDK credential resolution order:\n\n 1. Environment variables (`AWS_ACCESS_KEY_ID` + `AWS_SECRET_ACCESS_KEY`)\n 2. SSO token cache\n 3. Web identity token credentials\n 4. Shared credentials and config files\n\n[371 more lines in file. Use offset=261 to continue.]"}],"isError":false,"timestamp":1777856878861}} {"type":"message","id":"f86a9c21","parentId":"a9f17fda","timestamp":"2026-05-04T01:08:00.757Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_jPRSRIE5LAX7n4xXQWsw3iQl|fc_02b86be3bb6b669e0169f7f1703b2c8196a8949fea6733fd34","name":"read","arguments":{"path":"/usr/lib/node_modules/openclaw/docs/reference/memory-config.md","offset":260,"limit":260}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.5","usage":{"input":2959,"output":38,"cacheRead":55296,"cacheWrite":0,"totalTokens":58293,"cost":{"input":0.014795,"output":0.00114,"cacheRead":0.027648,"cacheWrite":0,"total":0.043583}},"stopReason":"toolUse","timestamp":1777856878868,"responseId":"resp_02b86be3bb6b669e0169f7f16f3db081969c397a5bce7914fe"}} {"type":"message","id":"cd69c4ba","parentId":"f86a9c21","timestamp":"2026-05-04T01:08:00.767Z","message":{"role":"toolResult","toolCallId":"call_jPRSRIE5LAX7n4xXQWsw3iQl|fc_02b86be3bb6b669e0169f7f1703b2c8196a8949fea6733fd34","toolName":"read","content":[{"type":"text","text":" 4. Shared credentials and config files\n 5. ECS or EC2 metadata credentials\n\n Region is resolved from `AWS_REGION`, `AWS_DEFAULT_REGION`, the `amazon-bedrock` provider `baseUrl`, or defaults to `us-east-1`.\n\n **IAM permissions:** the IAM role or user needs:\n\n ```json\n {\n \"Effect\": \"Allow\",\n \"Action\": \"bedrock:InvokeModel\",\n \"Resource\": \"*\"\n }\n ```\n\n For least-privilege, scope `InvokeModel` to the specific model:\n\n ```\n arn:aws:bedrock:*::foundation-model/amazon.titan-embed-text-v2:0\n ```\n\n \n \n | Key | Type | Default | Description |\n | --------------------- | ------------------ | ---------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |\n | `local.modelPath` | `string` | auto-downloaded | Path to GGUF model file |\n | `local.modelCacheDir` | `string` | node-llama-cpp default | Cache dir for downloaded models |\n | `local.contextSize` | `number \\| \"auto\"` | `4096` | Context window size for the embedding context. 4096 covers typical chunks (128–512 tokens) while bounding non-weight VRAM. Lower to 1024–2048 on constrained hosts. `\"auto\"` uses the model's trained maximum — not recommended for 8B+ models (Qwen3-Embedding-8B: 40 960 tokens → ~32 GB VRAM vs ~8.8 GB at 4096). |\n\n Default model: `embeddinggemma-300m-qat-Q8_0.gguf` (~0.6 GB, auto-downloaded). Source checkouts still require native build approval: `pnpm approve-builds` then `pnpm rebuild node-llama-cpp`.\n\n Use the standalone CLI to verify the same provider path the Gateway uses:\n\n ```bash\n openclaw memory status --deep --agent main\n openclaw memory index --force --agent main\n ```\n\n If `provider` is `auto`, `local` is selected only when `local.modelPath` points to an existing local file. `hf:` and HTTP(S) model references can still be used explicitly with `provider: \"local\"`, but they do not make `auto` select local before the model is available on disk.\n\n \n\n\n### Inline embedding timeout\n\n\n Override the timeout for inline embedding batches during memory indexing.\n\nUnset uses the provider default: 600 seconds for local/self-hosted providers such as `local`, `ollama`, and `lmstudio`, and 120 seconds for hosted providers. Increase this when local CPU-bound embedding batches are healthy but slow.\n\n\n---\n\n## Hybrid search config\n\nAll under `memorySearch.query.hybrid`:\n\n| Key | Type | Default | Description |\n| --------------------- | --------- | ------- | ---------------------------------- |\n| `enabled` | `boolean` | `true` | Enable hybrid BM25 + vector search |\n| `vectorWeight` | `number` | `0.7` | Weight for vector scores (0-1) |\n| `textWeight` | `number` | `0.3` | Weight for BM25 scores (0-1) |\n| `candidateMultiplier` | `number` | `4` | Candidate pool size multiplier |\n\n\n \n | Key | Type | Default | Description |\n | ------------- | --------- | ------- | ------------------------------------ |\n | `mmr.enabled` | `boolean` | `false` | Enable MMR re-ranking |\n | `mmr.lambda` | `number` | `0.7` | 0 = max diversity, 1 = max relevance |\n \n \n | Key | Type | Default | Description |\n | ---------------------------- | --------- | ------- | ------------------------- |\n | `temporalDecay.enabled` | `boolean` | `false` | Enable recency boost |\n | `temporalDecay.halfLifeDays` | `number` | `30` | Score halves every N days |\n\n Evergreen files (`MEMORY.md`, non-dated files in `memory/`) are never decayed.\n\n \n\n\n### Full example\n\n```json5\n{\n agents: {\n defaults: {\n memorySearch: {\n query: {\n hybrid: {\n vectorWeight: 0.7,\n textWeight: 0.3,\n mmr: { enabled: true, lambda: 0.7 },\n temporalDecay: { enabled: true, halfLifeDays: 30 },\n },\n },\n },\n },\n },\n}\n```\n\n---\n\n## Additional memory paths\n\n| Key | Type | Description |\n| ------------ | ---------- | ---------------------------------------- |\n| `extraPaths` | `string[]` | Additional directories or files to index |\n\n```json5\n{\n agents: {\n defaults: {\n memorySearch: {\n extraPaths: [\"../team-docs\", \"/srv/shared-notes\"],\n },\n },\n },\n}\n```\n\nPaths can be absolute or workspace-relative. Directories are scanned recursively for `.md` files. Symlink handling depends on the active backend: the builtin engine ignores symlinks, while QMD follows the underlying QMD scanner behavior.\n\nFor agent-scoped cross-agent transcript search, use `agents.list[].memorySearch.qmd.extraCollections` instead of `memory.qmd.paths`. Those extra collections follow the same `{ path, name, pattern? }` shape, but they are merged per agent and can preserve explicit shared names when the path points outside the current workspace. If the same resolved path appears in both `memory.qmd.paths` and `memorySearch.qmd.extraCollections`, QMD keeps the first entry and skips the duplicate.\n\n---\n\n## Multimodal memory (Gemini)\n\nIndex images and audio alongside Markdown using Gemini Embedding 2:\n\n| Key | Type | Default | Description |\n| ------------------------- | ---------- | ---------- | -------------------------------------- |\n| `multimodal.enabled` | `boolean` | `false` | Enable multimodal indexing |\n| `multimodal.modalities` | `string[]` | -- | `[\"image\"]`, `[\"audio\"]`, or `[\"all\"]` |\n| `multimodal.maxFileBytes` | `number` | `10000000` | Max file size for indexing |\n\n\nOnly applies to files in `extraPaths`. Default memory roots stay Markdown-only. Requires `gemini-embedding-2-preview`. `fallback` must be `\"none\"`.\n\n\nSupported formats: `.jpg`, `.jpeg`, `.png`, `.webp`, `.gif`, `.heic`, `.heif` (images); `.mp3`, `.wav`, `.ogg`, `.opus`, `.m4a`, `.aac`, `.flac` (audio).\n\n---\n\n## Embedding cache\n\n| Key | Type | Default | Description |\n| ------------------ | --------- | ------- | -------------------------------- |\n| `cache.enabled` | `boolean` | `false` | Cache chunk embeddings in SQLite |\n| `cache.maxEntries` | `number` | `50000` | Max cached embeddings |\n\nPrevents re-embedding unchanged text during reindex or transcript updates.\n\n---\n\n## Batch indexing\n\n| Key | Type | Default | Description |\n| ----------------------------- | --------- | ------- | -------------------------- |\n| `remote.nonBatchConcurrency` | `number` | `4` | Parallel inline embeddings |\n| `remote.batch.enabled` | `boolean` | `false` | Enable batch embedding API |\n| `remote.batch.concurrency` | `number` | `2` | Parallel batch jobs |\n| `remote.batch.wait` | `boolean` | `true` | Wait for batch completion |\n| `remote.batch.pollIntervalMs` | `number` | -- | Poll interval |\n| `remote.batch.timeoutMinutes` | `number` | -- | Batch timeout |\n\nAvailable for `openai`, `gemini`, and `voyage`. OpenAI batch is typically fastest and cheapest for large backfills.\n\n`remote.nonBatchConcurrency` controls inline embedding calls used by local/self-hosted providers and hosted providers when provider batch APIs are not active. Ollama defaults to `1` for non-batch indexing to avoid overwhelming smaller local hosts; set a higher value on larger machines.\n\nThis is separate from `sync.embeddingBatchTimeoutSeconds`, which controls the timeout for inline embedding calls.\n\n---\n\n## Session memory search (experimental)\n\nIndex session transcripts and surface them via `memory_search`:\n\n| Key | Type | Default | Description |\n| ----------------------------- | ---------- | ------------ | --------------------------------------- |\n| `experimental.sessionMemory` | `boolean` | `false` | Enable session indexing |\n| `sources` | `string[]` | `[\"memory\"]` | Add `\"sessions\"` to include transcripts |\n| `sync.sessions.deltaBytes` | `number` | `100000` | Byte threshold for reindex |\n| `sync.sessions.deltaMessages` | `number` | `50` | Message threshold for reindex |\n\n\nSession indexing is opt-in and runs asynchronously. Results can be slightly stale. Session logs live on disk, so treat filesystem access as the trust boundary.\n\n\n---\n\n## SQLite vector acceleration (sqlite-vec)\n\n| Key | Type | Default | Description |\n| ---------------------------- | --------- | ------- | --------------------------------- |\n| `store.vector.enabled` | `boolean` | `true` | Use sqlite-vec for vector queries |\n| `store.vector.extensionPath` | `string` | bundled | Override sqlite-vec path |\n\nWhen sqlite-vec is unavailable, OpenClaw falls back to in-process cosine similarity automatically.\n\n---\n\n## Index storage\n\n| Key | Type | Default | Description |\n| --------------------- | -------- | ------------------------------------- | ------------------------------------------- |\n| `store.path` | `string` | `~/.openclaw/memory/{agentId}.sqlite` | Index location (supports `{agentId}` token) |\n| `store.fts.tokenizer` | `string` | `unicode61` | FTS5 tokenizer (`unicode61` or `trigram`) |\n\n---\n\n## QMD backend config\n\nSet `memory.backend = \"qmd\"` to enable. All QMD settings live under `memory.qmd`:\n\n| Key | Type | Default | Description |\n| ------------------------ | --------- | -------- | ------------------------------------------------------------------------------------- |\n| `command` | `string` | `qmd` | QMD executable path; set an absolute path when service `PATH` differs from your shell |\n| `searchMode` | `string` | `search` | Search command: `search`, `vsearch`, `query` |\n| `includeDefaultMemory` | `boolean` | `true` | Auto-index `MEMORY.md` + `memory/**/*.md` |\n| `paths[]` | `array` | -- | Extra paths: `{ name, path, pattern? }` |\n| `sessions.enabled` | `boolean` | `false` | Index session transcripts |\n| `sessions.retentionDays` | `number` | -- | Transcript retention |\n| `sessions.exportDir` | `string` | -- | Export directory |\n\n`searchMode: \"search\"` is lexical/BM25-only. OpenClaw does not run semantic vector readiness probes or QMD embedding maintenance for that mode, including during `memory status --deep`; `vsearch` and `query` continue to require QMD vector readiness and embeddings.\n\nOpenClaw prefers current QMD collection and MCP query shapes, but keeps older QMD releases working by trying compatible collection pattern flags and older MCP tool names when needed. When QMD advertises support for multiple collection filters, same-source collections are searched with one QMD process; older QMD builds keep the per-collection compatibility path. Same-source means durable memory collections are grouped together, while session transcript collections remain a separate group so source diversification still has both inputs.\n\n\nQMD model overrides stay on the QMD side, not OpenClaw config. If you need to override QMD's models globally, set environment variables such as `QMD_EMBED_MODEL`, `QMD_RERANK_MODEL`, and `QMD_GENERATE_MODEL` in the gateway runtime environment.\n\n\n\n \n | Key | Type | Default | Description |\n | ------------------------- | --------- | ------- | ------------------------------------- |\n | `update.interval` | `string` | `5m` | Refresh interval |\n | `update.debounceMs` | `number` | `15000` | Debounce file changes |\n | `update.onBoot` | `boolean` | `true` | Refresh when the long-lived QMD manager opens; also gates opt-in startup refresh |\n | `update.startup` | `string` | `off` | Optional gateway-start refresh: `off`, `idle`, or `immediate` |\n | `update.startupDelayMs` | `number` | `120000` | Delay before `startup: \"idle\"` refresh runs |\n | `update.waitForBootSync` | `boolean` | `false` | Block manager opening until its initial refresh completes |\n | `update.embedInterval` | `string` | -- | Separate embed cadence |\n | `update.commandTimeoutMs` | `number` | -- | Timeout for QMD commands |\n | `update.updateTimeoutMs` | `number` | -- | Timeout for QMD update operations |\n | `update.embedTimeoutMs` | `number` | -- | Timeout for QMD embed operations |\n \n \n | Key | Type | Default | Description |\n | ------------------------- | -------- | ------- | -------------------------- |\n | `limits.maxResults` | `number` | `6` | Max search results |\n | `limits.maxSnippetChars` | `number` | -- | Clamp snippet length |\n | `limits.maxInjectedChars` | `number` | -- | Clamp total injected chars |\n | `limits.timeoutMs` | `number` | `4000` | Search timeout |\n \n \n\n[112 more lines in file. Use offset=520 to continue.]"}],"isError":false,"timestamp":1777856880766}} {"type":"message","id":"819afa77","parentId":"cd69c4ba","timestamp":"2026-05-04T01:08:03.383Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_PqwTVIgPAwF5G4PLQvHDX48Y|fc_02b86be3bb6b669e0169f7f1725e248196959407af214bb796","name":"read","arguments":{"path":"/usr/lib/node_modules/openclaw/docs/reference/memory-config.md","offset":520,"limit":125}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.5","usage":{"input":3675,"output":38,"cacheRead":57856,"cacheWrite":0,"totalTokens":61569,"cost":{"input":0.018375000000000002,"output":0.00114,"cacheRead":0.028928,"cacheWrite":0,"total":0.048443}},"stopReason":"toolUse","timestamp":1777856880774,"responseId":"resp_02b86be3bb6b669e0169f7f17124c88196a9ff67264631494b"}} {"type":"message","id":"becd814e","parentId":"819afa77","timestamp":"2026-05-04T01:08:03.392Z","message":{"role":"toolResult","toolCallId":"call_PqwTVIgPAwF5G4PLQvHDX48Y|fc_02b86be3bb6b669e0169f7f1725e248196959407af214bb796","toolName":"read","content":[{"type":"text","text":" Controls which sessions can receive QMD search results. Same schema as [`session.sendPolicy`](/gateway/config-agents#session):\n\n ```json5\n {\n memory: {\n qmd: {\n scope: {\n default: \"deny\",\n rules: [{ action: \"allow\", match: { chatType: \"direct\" } }],\n },\n },\n },\n }\n ```\n\n The shipped default allows direct and channel sessions, while still denying groups.\n\n Default is DM-only. `match.keyPrefix` matches the normalized session key; `match.rawKeyPrefix` matches the raw key including `agent::`.\n\n \n \n `memory.citations` applies to all backends:\n\n | Value | Behavior |\n | ---------------- | --------------------------------------------------- |\n | `auto` (default) | Include `Source: ` footer in snippets |\n | `on` | Always include footer |\n | `off` | Omit footer (path still passed to agent internally) |\n\n \n\n\nQMD boot refreshes use a one-shot subprocess path during gateway startup. The long-lived QMD manager still owns the regular file watcher and interval timers when memory search is opened for interactive use.\n\n### Full QMD example\n\n```json5\n{\n memory: {\n backend: \"qmd\",\n citations: \"auto\",\n qmd: {\n includeDefaultMemory: true,\n update: { interval: \"5m\", debounceMs: 15000 },\n limits: { maxResults: 6, timeoutMs: 4000 },\n scope: {\n default: \"deny\",\n rules: [{ action: \"allow\", match: { chatType: \"direct\" } }],\n },\n paths: [{ name: \"docs\", path: \"~/notes\", pattern: \"**/*.md\" }],\n },\n },\n}\n```\n\n---\n\n## Dreaming\n\nDreaming is configured under `plugins.entries.memory-core.config.dreaming`, not under `agents.defaults.memorySearch`.\n\nDreaming runs as one scheduled sweep and uses internal light/deep/REM phases as an implementation detail.\n\nFor conceptual behavior and slash commands, see [Dreaming](/concepts/dreaming).\n\n### User settings\n\n| Key | Type | Default | Description |\n| ----------- | --------- | ------------- | ------------------------------------------------- |\n| `enabled` | `boolean` | `false` | Enable or disable dreaming entirely |\n| `frequency` | `string` | `0 3 * * *` | Optional cron cadence for the full dreaming sweep |\n| `model` | `string` | default model | Optional Dream Diary subagent model override |\n\n### Example\n\n```json5\n{\n plugins: {\n entries: {\n \"memory-core\": {\n subagent: {\n allowModelOverride: true,\n allowedModels: [\"anthropic/claude-sonnet-4-6\"],\n },\n config: {\n dreaming: {\n enabled: true,\n frequency: \"0 3 * * *\",\n model: \"anthropic/claude-sonnet-4-6\",\n },\n },\n },\n },\n },\n}\n```\n\n\n- Dreaming writes machine state to `memory/.dreams/`.\n- Dreaming writes human-readable narrative output to `DREAMS.md` (or existing `dreams.md`).\n- `dreaming.model` uses the existing plugin subagent trust gate; set `plugins.entries.memory-core.subagent.allowModelOverride: true` before enabling it.\n- Dream Diary retries once with the session default model when the configured model is unavailable. Trust or allowlist failures are logged and are not silently retried.\n- The light/deep/REM phase policy and thresholds are internal behavior, not user-facing config.\n\n\n\n## Related\n\n- [Configuration reference](/gateway/configuration-reference)\n- [Memory overview](/concepts/memory)\n- [Memory search](/concepts/memory-search)\n"}],"isError":false,"timestamp":1777856883391}} {"type":"message","id":"ff55ca87","parentId":"becd814e","timestamp":"2026-05-04T01:08:09.023Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"id\":\"rs_02b86be3bb6b669e0169f7f174af7481969a4636fb6ead65ac\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABp9_F1KT2oaJjRtHPdjqwYZHoYwgqv6oVsd2BESJxwr_5UUblaUf45AaLoOULxdWXrOkAXoFGEjliUi4lCGGESoucpA3PeUU8BxZJPTHv7xY7uqgT2Gr_g_EC70xPmjnWdNugTFLPEdScCj86tZrkX088Bj-G2-GqP1jxKaBsxtHFlhS8VCS1pa6ylCXER1T-rH_GNqyDZKWr6CcHNNJlqpw5t7Iy9o6YqVCTRwrRCIVnQmjtG7s5JS3TMt1cNS-fhYc0XZFXcq7o3f8DL5hCggqDWsL-1iiyjkN8kSYRK4pBkW8he7xjiEV5AFmEtABThf9CmG1P6DDeS7bHzzon7gpvEtboT3LqcIIvGN_FteUFyAnYjuhTW7O6OmCp5fei2V9h-5zojOtNyz38lb47KC-hj39GW0SSR1meDvS0piGTL3cMTh01ekFH2LtBGJ6mHQleAI2Fwn-QUzgIEkyTjcNThqDqTufQi8xg-JdqwjPpNHDkG0n1HSLCxuPuJHyIj0ROOka4SEBnio9jJeSRDaAEvf4kn8vga_xT2vftmjS_HtFvj0v_hsizyD8W0ygmi99-BP-cpSnIQCHuftp-I3exU67deiT2dq98s_oezclJ7FCeQIOFIomPvGi5t50BnQq8RVkFhAOy4ZVf6fXQmOCDxJwJzjSlr26ouip8S8_wJoJ0muqs0fCx3K6aLwU_ENJjRT_ErvMF3iNbBVKcXdRy3hmGCKFnYbtzXCvAZTElnl50h2Rv994IiHtelZhPGNLKT08V8tPA9FuSkIooKP2mZjMVSDxBTnTcPky4JI8cMPp2TjllbbkThvCEyQ-DM6LS4YRSbmCbYT4FDtsC8933sMtmRF5cbXqicxvNSRJ7UzVckYjL7BlBv8SQBAEW3jIVcHlcj82yGJ7010OQRPd-2cUjdi1XYV6K1PDs2E08nhNbL-R9Jot84rkM_KxwHjGpT5ievcwZ9-PuVGFrtbQWhkcrz4-OoihDWTY9kturm_Vc=\",\"summary\":[]}"},{"type":"toolCall","id":"call_IDZFsz0wOZSJGr2L4RGMN0M2|fc_02b86be3bb6b669e0169f7f17501e08196a03778c0e2de0628","name":"exec","arguments":{"command":"printf '=== registry search local installed plugin IDs relevant ===\\n'\nnode - <<'NODE'\nconst fs=require('fs');const j=JSON.parse(fs.readFileSync('/home/rurouni/.openclaw/plugins/installs.json','utf8'));\nfor (const p of j.plugins||[]) if(/mem0|qdrant|qmd|lossless|lcm|memory-core|active-memory/i.test(p.pluginId+' '+p.packageName+' '+p.manifestPath)) console.log(`${p.pluginId}\\tenabled=${p.enabled}\\torigin=${p.origin}\\tpkg=${p.packageName||''}\\tpath=${p.rootDir}`);\nNODE\nprintf '\\n=== plugin registry/help search ===\\n'\nopenclaw plugins --help 2>&1 | sed -n '1,180p'\nprintf '\\nregistry grep names (no refresh):\\n'\nopenclaw plugins list 2>&1 | grep -Ei 'mem0|qdrant|qmd|lossless|lcm|memory' || true\nprintf '\\n=== npm versions (network if available) ===\\n'\nfor p in @tobilu/qmd @martian-engineering/lossless-claw mem0ai qdrant-client; do printf '%s: ' \"$p\"; npm view \"$p\" version 2>/dev/null || true; done","workdir":"/home/rurouni","yieldMs":10000,"timeout":80}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.5","usage":{"input":989,"output":351,"cacheRead":61440,"cacheWrite":0,"totalTokens":62780,"cost":{"input":0.004945000000000001,"output":0.01053,"cacheRead":0.030719999999999997,"cacheWrite":0,"total":0.046195}},"stopReason":"toolUse","timestamp":1777856883398,"responseId":"resp_02b86be3bb6b669e0169f7f173c0348196bf719f1432415fb5"}} {"type":"message","id":"3043b362","parentId":"ff55ca87","timestamp":"2026-05-04T01:08:16.264Z","message":{"role":"toolResult","toolCallId":"call_IDZFsz0wOZSJGr2L4RGMN0M2|fc_02b86be3bb6b669e0169f7f17501e08196a03778c0e2de0628","toolName":"exec","content":[{"type":"text","text":"=== registry search local installed plugin IDs relevant ===\nactive-memory\tenabled=false\torigin=bundled\tpkg=\tpath=/usr/lib/node_modules/openclaw/dist/extensions/active-memory\nmemory-core\tenabled=true\torigin=bundled\tpkg=@openclaw/memory-core\tpath=/usr/lib/node_modules/openclaw/dist/extensions/memory-core\n\n=== plugin registry/help search ===\n\n🦞 OpenClaw 2026.5.2 (8b2a6e5) — I'm not magic—I'm just extremely persistent with retries and coping strategies.\n\nUsage: openclaw plugins [options] [command]\n\nManage OpenClaw plugins and extensions\n\nOptions:\n -h, --help Display help for command\n\nCommands:\n disable Disable a plugin in config\n doctor Report plugin load issues\n enable Enable a plugin in config\n inspect Inspect plugin details\n install Install a plugin or hook pack (path, archive, npm spec, git repo,\n clawhub:package, or marketplace entry)\n list List discovered plugins\n marketplace Inspect Claude-compatible plugin marketplaces\n registry Inspect or rebuild the persisted plugin registry\n search Search ClawHub plugin packages\n uninstall Uninstall a plugin\n update Update installed plugins and tracked hook packs\n\nDocs: https://docs.openclaw.ai/cli/plugins\n\n\nregistry grep names (no refresh):\n│ Active │ active- │ openclaw │ disabled │ stock:active-memory/index.js │ │\n│ Memory │ memory │ │ │ Runs a bounded blocking memory sub-agent before eligible │ │\n│ │ │ │ │ conversational replies and injects relevant memory into │ │\n│ @openclaw/ │ memory- │ openclaw │ enabled │ stock:memory-core/index.js │ 2026.5.2 │\n│ memory-core │ core │ │ │ │ │\n│ Memory Wiki │ memory- │ openclaw │ disabled │ stock:memory-wiki/index.js │ 2026.5.2 │\n\n=== npm versions (network if available) ===\n@tobilu/qmd: 2.1.0\n@martian-engineering/lossless-claw: 0.9.3\nmem0ai: 3.0.2\nqdrant-client: 0.0.1"}],"details":{"status":"completed","exitCode":0,"durationMs":7225,"aggregated":"=== registry search local installed plugin IDs relevant ===\nactive-memory\tenabled=false\torigin=bundled\tpkg=\tpath=/usr/lib/node_modules/openclaw/dist/extensions/active-memory\nmemory-core\tenabled=true\torigin=bundled\tpkg=@openclaw/memory-core\tpath=/usr/lib/node_modules/openclaw/dist/extensions/memory-core\n\n=== plugin registry/help search ===\n\n🦞 OpenClaw 2026.5.2 (8b2a6e5) — I'm not magic—I'm just extremely persistent with retries and coping strategies.\n\nUsage: openclaw plugins [options] [command]\n\nManage OpenClaw plugins and extensions\n\nOptions:\n -h, --help Display help for command\n\nCommands:\n disable Disable a plugin in config\n doctor Report plugin load issues\n enable Enable a plugin in config\n inspect Inspect plugin details\n install Install a plugin or hook pack (path, archive, npm spec, git repo,\n clawhub:package, or marketplace entry)\n list List discovered plugins\n marketplace Inspect Claude-compatible plugin marketplaces\n registry Inspect or rebuild the persisted plugin registry\n search Search ClawHub plugin packages\n uninstall Uninstall a plugin\n update Update installed plugins and tracked hook packs\n\nDocs: https://docs.openclaw.ai/cli/plugins\n\n\nregistry grep names (no refresh):\n│ Active │ active- │ openclaw │ disabled │ stock:active-memory/index.js │ │\n│ Memory │ memory │ │ │ Runs a bounded blocking memory sub-agent before eligible │ │\n│ │ │ │ │ conversational replies and injects relevant memory into │ │\n│ @openclaw/ │ memory- │ openclaw │ enabled │ stock:memory-core/index.js │ 2026.5.2 │\n│ memory-core │ core │ │ │ │ │\n│ Memory Wiki │ memory- │ openclaw │ disabled │ stock:memory-wiki/index.js │ 2026.5.2 │\n\n=== npm versions (network if available) ===\n@tobilu/qmd: 2.1.0\n@martian-engineering/lossless-claw: 0.9.3\nmem0ai: 3.0.2\nqdrant-client: 0.0.1","cwd":"/home/rurouni"},"isError":false,"timestamp":1777856896264}} 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It provides a production-ready service with a convenient API to store, search, and manage points—vectors with an additional payload Qdrant is tailored to extended filtering support.\n<<>>","siteName":"hub.docker.com"},{"title":"\n<<>>\nSource: Web Search\n---\nReleases · qdrant/qdrant - GitHub\n<<>>","url":"https://github.com/qdrant/qdrant/releases","snippet":"\n<<>>\nSource: Web Search\n---\nQdrant Edge 🔪 Qdrant Edge is an in-process version of Qdrant , which shares the same internals, storage format, and points API as the server version , but designed to work locally. Qdrant Edge is compatible with server version and it can read shard snapshots created by server version of Qdrant . More documentation available here. 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It provides fast and scalable vector similarity search service with convenient API.\n<<>>","siteName":"qdrant.tech"}]},"isError":false,"timestamp":1777856902465}} {"type":"message","id":"8c25317f","parentId":"df712b44","timestamp":"2026-05-04T01:08:22.467Z","message":{"role":"toolResult","toolCallId":"call_G3EkpZqOsPMWdiw8TIMYyqoQ|fc_02b86be3bb6b669e0169f7f1843a8c8196a7e52694ccb5fc37","toolName":"web_search","content":[{"type":"text","text":"{\n \"query\": \"mem0 OSS Qdrant self hosted install docker qwen embeddings OpenAI compatible\",\n \"provider\": \"duckduckgo\",\n \"count\": 5,\n \"tookMs\": 1213,\n \"externalContent\": {\n \"untrusted\": true,\n \"source\": \"web_search\",\n \"provider\": \"duckduckgo\",\n \"wrapped\": true\n },\n \"results\": [\n {\n \"title\": \"\\n<<>>\\nSource: Web Search\\n---\\nSelf-Hosting Mem0: A Complete Docker Deployment Guide\\n<<>>\",\n \"url\": \"https://mem0.ai/blog/self-host-mem0-docker\",\n \"snippet\": \"\\n<<>>\\nSource: Web Search\\n---\\nSelf -host Mem0's AI memory stack in three Docker containers (API, Postgres + pgvector, Neo4j) to keep conversation data on your own infrastructure, swap in local LLMs, and stay compliant.\\n<<>>\",\n \"siteName\": \"mem0.ai\"\n },\n {\n \"title\": \"\\n<<>>\\nSource: Web Search\\n---\\nInstallation and Setup | mem0ai/mem0 | DeepWiki\\n<<>>\",\n \"url\": \"https://deepwiki.com/mem0ai/mem0/1.2-installation-and-setup\",\n \"snippet\": \"\\n<<>>\\nSource: Web Search\\n---\\nInstallation and Setup Relevant source files This document covers the installation process and initial configuration for both the Python and TypeScript/JavaScript SDKs. It includes prerequisites, package installation, basic configuration, and quickstart examples to verify your setup.\\n<<>>\",\n \"siteName\": \"deepwiki.com\"\n },\n {\n \"title\": \"\\n<<>>\\nSource: Web Search\\n---\\nQdrant Self-Hosted with Docker - GitHub\\n<<>>\",\n \"url\": \"https://github.com/AiratTop/qdrant-self-hosted\",\n \"snippet\": \"\\n<<>>\\nSource: Web Search\\n---\\nQdrant Self-Hosted with Docker This repository provides a docker compose setup to run a self-hosted Qdrant vector database instance. It is configured to connect to a shared Docker network, allowing easy integration with other services like n8n.\\n<<>>\",\n \"siteName\": \"github.com\"\n },\n {\n \"title\": \"\\n<<>>\\nSource: Web Search\\n---\\nqdrant/qdrant - Docker Image\\n<<>>\",\n \"url\": \"https://hub.docker.com/r/qdrant/qdrant\",\n \"snippet\": \"\\n<<>>\\nSource: Web Search\\n---\\nQdrant (read: quadrant) is a vector similarity search engine and vector database. It provides a production-ready service with a convenient API to store, search, and manage points—vectors with an additional payload Qdrant is tailored to extended filtering support.\\n<<>>\",\n \"siteName\": \"hub.docker.com\"\n },\n {\n \"title\": \"\\n<<>>\\nSource: Web Search\\n---\\nSelf-hosting Qdrant with Docker on an Ubuntu Server\\n<<>>\",\n \"url\": \"https://sliplane.io/blog/self-hosting-qdrant-with-docker-on-ubuntu-server\",\n \"snippet\": \"\\n<<>>\\nSource: Web Search\\n---\\nLearn how to self -host Qdrant vector database on Ubuntu using Docker and Caddy. This step-by-step guide covers installation, security, and cost comparison with managed services, helping you maintain full control over your AI and search infrastructure while reducing costs.\\n<<>>\",\n \"siteName\": \"sliplane.io\"\n }\n ]\n}"}],"details":{"query":"mem0 OSS Qdrant self hosted install docker qwen embeddings OpenAI compatible","provider":"duckduckgo","count":5,"tookMs":1213,"externalContent":{"untrusted":true,"source":"web_search","provider":"duckduckgo","wrapped":true},"results":[{"title":"\n<<>>\nSource: Web Search\n---\nSelf-Hosting Mem0: A Complete Docker Deployment Guide\n<<>>","url":"https://mem0.ai/blog/self-host-mem0-docker","snippet":"\n<<>>\nSource: Web Search\n---\nSelf -host Mem0's AI memory stack in three Docker containers (API, Postgres + pgvector, Neo4j) to keep conversation data on your own infrastructure, swap in local LLMs, and stay compliant.\n<<>>","siteName":"mem0.ai"},{"title":"\n<<>>\nSource: Web Search\n---\nInstallation and Setup | mem0ai/mem0 | DeepWiki\n<<>>","url":"https://deepwiki.com/mem0ai/mem0/1.2-installation-and-setup","snippet":"\n<<>>\nSource: Web Search\n---\nInstallation and Setup Relevant source files This document covers the installation process and initial configuration for both the Python and TypeScript/JavaScript SDKs. It includes prerequisites, package installation, basic configuration, and quickstart examples to verify your setup.\n<<>>","siteName":"deepwiki.com"},{"title":"\n<<>>\nSource: Web Search\n---\nQdrant Self-Hosted with Docker - GitHub\n<<>>","url":"https://github.com/AiratTop/qdrant-self-hosted","snippet":"\n<<>>\nSource: Web Search\n---\nQdrant Self-Hosted with Docker This repository provides a docker compose setup to run a self-hosted Qdrant vector database instance. It is configured to connect to a shared Docker network, allowing easy integration with other services like n8n.\n<<>>","siteName":"github.com"},{"title":"\n<<>>\nSource: Web Search\n---\nqdrant/qdrant - Docker Image\n<<>>","url":"https://hub.docker.com/r/qdrant/qdrant","snippet":"\n<<>>\nSource: Web Search\n---\nQdrant (read: quadrant) is a vector similarity search engine and vector database. It provides a production-ready service with a convenient API to store, search, and manage points—vectors with an additional payload Qdrant is tailored to extended filtering support.\n<<>>","siteName":"hub.docker.com"},{"title":"\n<<>>\nSource: Web Search\n---\nSelf-hosting Qdrant with Docker on an Ubuntu Server\n<<>>","url":"https://sliplane.io/blog/self-hosting-qdrant-with-docker-on-ubuntu-server","snippet":"\n<<>>\nSource: Web Search\n---\nLearn how to self -host Qdrant vector database on Ubuntu using Docker and Caddy. This step-by-step guide covers installation, security, and cost comparison with managed services, helping you maintain full control over your AI and search infrastructure while reducing costs.\n<<>>","siteName":"sliplane.io"}]},"isError":false,"timestamp":1777856902465}} {"type":"message","id":"3558966d","parentId":"8c25317f","timestamp":"2026-05-04T01:08:22.469Z","message":{"role":"toolResult","toolCallId":"call_lxS4NBa1WnfZtTa7hbUPnNZU|fc_02b86be3bb6b669e0169f7f1843a9881968c84509a32f55b31","toolName":"web_search","content":[{"type":"text","text":"{\n \"query\": \"Qwen3-Embedding-0.6B VRAM memory usage 0.6B embedding GPU\",\n \"provider\": \"duckduckgo\",\n \"count\": 3,\n \"tookMs\": 921,\n \"externalContent\": {\n \"untrusted\": true,\n \"source\": \"web_search\",\n \"provider\": \"duckduckgo\",\n \"wrapped\": true\n },\n \"results\": [\n {\n \"title\": \"\\n<<>>\\nSource: Web Search\\n---\\nQwen3-Embedding-0.6B - VRAM Requirements & Specifications\\n<<>>\",\n \"url\": \"https://oniyoon.com/models/qwen3-embedding-06b/\",\n \"snippet\": \"\\n<<>>\\nSource: Web Search\\n---\\nQwen3-Embedding-0.6B specifications and VRAM requirements. 0.6B parameters, Standard Transformer architecture. See memory usage for all quantization formats at different context lengths.\\n<<>>\",\n \"siteName\": \"oniyoon.com\"\n },\n {\n \"title\": \"\\n<<>>\\nSource: Web Search\\n---\\nQwen Qwen3 Embedding 0.6B: VRAM Needs, GPU Requirements &…\\n<<>>\",\n \"url\": \"https://localai.computer/models/qwen-qwen3-embedding-0.6b\",\n \"snippet\": \"\\n<<>>\\nSource: Web Search\\n---\\nSee which GPUs can run Qwen Qwen3 Embedding 0.6B locally. Needs 1GB VRAM at Q4, 1GB at Q8, 2GB at FP16. Compare GPU options for local inference.\\n<<>>\",\n \"siteName\": \"localai.computer\"\n },\n {\n \"title\": \"\\n<<>>\\nSource: Web Search\\n---\\nQwen3-0.6B: Specifications and GPU VRAM Requirements\\n<<>>\",\n \"url\": \"https://apxml.com/models/qwen3-0-6b\",\n \"snippet\": \"\\n<<>>\\nSource: Web Search\\n---\\nQwen3-0.6B Qwen3-0.6B is a foundational large language model developed by Alibaba Cloud, forming part of the dense architecture variants within the Qwen3 model family. This model is engineered for efficient processing and generation of human language, addressing a spectrum of natural language understanding and generation tasks.\\n<<>>\",\n \"siteName\": \"apxml.com\"\n }\n ]\n}"}],"details":{"query":"Qwen3-Embedding-0.6B VRAM memory usage 0.6B embedding GPU","provider":"duckduckgo","count":3,"tookMs":921,"externalContent":{"untrusted":true,"source":"web_search","provider":"duckduckgo","wrapped":true},"results":[{"title":"\n<<>>\nSource: Web Search\n---\nQwen3-Embedding-0.6B - VRAM Requirements & Specifications\n<<>>","url":"https://oniyoon.com/models/qwen3-embedding-06b/","snippet":"\n<<>>\nSource: Web Search\n---\nQwen3-Embedding-0.6B specifications and VRAM requirements. 0.6B parameters, Standard Transformer architecture. 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This model is engineered for efficient processing and generation of human language, addressing a spectrum of natural language understanding and generation tasks.\n<<>>","siteName":"apxml.com"}]},"isError":false,"timestamp":1777856902466}} {"type":"compaction","id":"bfc5ffd9","parentId":"3558966d","timestamp":"2026-05-04T01:08:44.720Z","summary":"## Goal\nBuild an efficient OpenClaw memory/context system optimized for fast retrieval, low prompt injection size, and relevant-only context.\n\n## Constraints & Preferences\n- Use Mem0 OSS + Qdrant as main long-term memory.\n- Use Qwen3-Embedding-0.6B as embedder; prefer GPU only if VRAM allows, otherwise CPU fallback or explain tradeoff first.\n- Use QMD Light only for workspace/document search: BM25 first, vector fallback, no reranker, no heavy query mode by default, no GPU reranking.\n- Use Lossless Claw / LCM for long-session context compaction with DAG summaries and pinned version.\n- Keep OpenClaw base memory tiny; do not inject full `MEMORY.md`, daily notes, or giant Markdown memory files every turn.\n- Normal memory injection target: 300–800 tokens.\n- Project-heavy turn: 800–1,500 tokens.\n- Hard max: 2,000 memory/doc tokens.\n- Mem0 `topK` should start at 4–6.\n- Mem0 injected memory should start at 512 tokens and max at 768 unless manually changed.\n- QMD snippets only injected when user asks about docs, configs, commands, or files.\n- LCM summaries only injected when conversation is long enough.\n- Mem0 owns long-term memory.\n- QMD owns workspace/document search.\n- LCM owns long-session conversation compaction.\n- OpenClaw base memory stays tiny.\n- Only one system should inject long-term memory.\n- Avoid duplicate memory injection.\n- Use active storage paths:\n - `/data/openclaw-memory/qdrant`\n - `/data/openclaw-memory/mem0`\n - `/data/openclaw-memory/qmd`\n - `/data/openclaw-memory/cache`\n - `/models/embeddings/Qwen3-Embedding-0.6B`\n - `/backup/openclaw-memory`\n - `/archive/openclaw-memory`\n- Before changing anything, inspect current install/config and print a clear plan.\n- Prefer production-stable, version-pinned components.\n- Do not put big databases on root partition.\n- Do not overwrite existing OpenClaw memory files without backup.\n- Do not delete anything unless explicitly approved.\n- Create rollback steps, health-check commands, and a simple status command/script if possible.\n\n## Progress\n### Done\n- [x] User provided target architecture, constraints, storage layout, and pre-change inspection requirements.\n\n### In Progress\n- [ ] Inspect current OpenClaw installation, memory plugins, installed tools, GPU VRAM usage, and config/log/memory/plugin paths.\n\n### Blocked\n- No system inspection has been performed yet; implementation must not start until current environment is checked and a plan is printed.\n\n## Key Decisions\n- **Mem0 + Qdrant as long-term memory**: Centralizes personal/project memory and avoids duplicate long-term injection.\n- **QMD Light for workspace search only**: Prevents bloated prompt injection and avoids costly reranking.\n- **LCM for long-session compaction**: Keeps conversation history from expanding indefinitely.\n- **Tiny OpenClaw base memory**: Prevents full Markdown/daily-note injection every turn.\n- **Strict token budgets**: Keeps normal memory context between 300–800 tokens and hard caps memory/doc injection at 2,000 tokens.\n\n## Next Steps\n1. Inspect current OpenClaw install and configuration.\n2. Detect current OpenClaw memory plugin configuration.\n3. Check whether Docker or Podman is installed.\n4. Check whether Qdrant, Mem0, QMD, and Lossless Claw / LCM are already installed.\n5. Run `nvidia-smi` to inspect current GPU VRAM usage.\n6. Confirm OpenClaw config, memory, plugin, and log locations.\n7. Print a clear implementation plan before making changes.\n8. Back up any existing OpenClaw memory/config files before modification.\n9. Implement version-pinned services using `/data`, `/models`, `/backup`, and `/archive` paths.\n10. Add rollback steps, health-check commands, and a simple status script.\n\n## Critical Context\n- Required paths:\n - `/data/openclaw-memory/qdrant`\n - `/data/openclaw-memory/mem0`\n - `/data/openclaw-memory/qmd`\n - `/data/openclaw-memory/cache`\n - `/models/embeddings/Qwen3-Embedding-0.6B`\n - `/backup/openclaw-memory`\n - `/archive/openclaw-memory`\n- Important command to run during inspection: `nvidia-smi`.\n- Do not modify, overwrite, or delete anything before inspection, backup, and user-approved plan.\n\n---\n\n**Turn Context (split turn):**\n\n## Original Request\nUser asked to inspect the current OpenClaw/local memory setup and system resources before making any changes, likely to plan Mem0/Qdrant/QMD/LCM/lossless memory integration.\n\n## Early Progress\n- Assistant committed to inspection-only: no installs, config writes, or deletes.\n- Checked long-term memory notes:\n - OpenClaw builtin memory has embeddings but no reranking.\n - QMD is preferred path for local BM25 + vectors + reranking/query expansion, but CPU-only behavior should be verified before enabling/downloading models.\n - Storage layout: `/data` for caches/tmp, `/models` SSD for models, `/backup` and `/archive` HDDs.\n- Ran OpenClaw inspection:\n - Binary: `/usr/bin/openclaw`\n - Version: `OpenClaw 2026.5.2 (8b2a6e5)`\n - Gateway dashboard: `http://192.168.1.50:18789/`\n - Gateway service installed/enabled/running via systemd.\n - Memory enabled via `plugin memory-core`.\n- Checked containers/packages:\n - Docker and containerd installed/running.\n - Podman/nerdctl absent.\n - No existing `/data/openclaw-memory`, `/data/qdrant`, `/var/lib/qdrant`, etc.\n - Python packages absent: `mem0`, `qdrant_client`, `fastembed`, `sentence_transformers`.\n - Global npm has `openclaw@2026.5.2`.\n- Checked GPU/storage:\n - GPU: GTX 1080 Ti, 11GB VRAM.\n - VRAM mostly occupied by `/usr/local/bin/llama-server` using ~9016 MiB; only ~2144 MiB free.\n - Storage: `/data` 1.5T mostly empty, `/models` 458G empty, `/backup` and `/archive` ~1.8T mostly empty.\n- Began safe config summary from `/home/rurouni/.openclaw/openclaw.json`, redacting token-like fields.\n\n## Context for Suffix\n- The retained suffix continues from OpenClaw config inspection and likely reports/acts on findings.\n- Important constraints: no changes should be made until a plan is presented; GPU VRAM is constrained by running llama-server, so memory/vector/rerank components should probably avoid GPU unless explicitly planned.\n- OpenClaw is active, current, systemd-managed, with builtin `memory-core` enabled but no Mem0/Qdrant/QMD stack currently installed or detected.","firstKeptEntryId":"5ac31fa7","tokensBefore":65696,"details":{"readFiles":[],"modifiedFiles":[]},"fromHook":false} {"type":"message","id":"31477b76","parentId":"bfc5ffd9","timestamp":"2026-05-04T01:09:47.160Z","message":{"role":"user","content":[{"type":"text","text":"Continue the OpenClaw runtime event."}],"timestamp":1777856987159}} {"type":"message","id":"2d8721ce","parentId":"31477b76","timestamp":"2026-05-04T01:09:51.730Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"id\":\"rs_02b86be3bb6b669e0169f7f1dc91fc8196a44612368fd63513\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABp9_HfEnEryxmuATYrSZsUbhq-C_u4nTdKFMKZirkDF_cY79Py5JdRTj2NWZchgVZOW96rHG7QDFLN6ur5PFPtJU-rGyDNnPsDLN7mlzE0YBiF_GkWGgVLU41hVk7e0DlGdZoG5XZM1tEGEhyyfmDk60vlagsNeZgx87XFYCFbZnWORaBeal8vJsEhab8DmOHwtMVPwfJzLTBFY4rLCwi83XNKeGyn337vD31KFq-AmZXOWhnY41KLA_d441cMPibX6y1K_B9AuqptgFgllkvi8kAE56j5eXdL0GHwGLmii9-JEktZ2i5nWBBaXwHBfRqNwBuvJVXqbsw3RSa6GcNzhuBb0IjmZvQSaS1AhIi4K872Te2M4KS2LMeA_RiF2dFv8cJQ3WVCAfd8STZSpNRNvC-DJO_sFzHZbtzSIxX6EY438feH9MgyyVVwyysGW6A5lFgVwplOgCuE2OvmYd0oEufdiUsCOl0S8QFGdc9DovCCKfNG5x7n0mt8ZmI_DM8vaNnyyJ1iuSOhudvaHQ-IwhyG_QjP9Og8ItpSgaz_LFKvwK0uyOgiBYWly5AJYZFtv5OA_Fh34UCReNMYj3udDfq7XaTAIWdleEQktAIzU2cY57qt9Qzdo27IxuAWDa9L184J_JIaOi7ghWylgH1sREjaCPnkr-pMh1eU8NYvB54_9wzGt4hKuRXSmz2Rf9WuO0Jw0YbsazzmmXCNYFg6HpcrngNyw1atywt5CnTztClz0UxcBDhs_iKdQr4LqtZkDEPtkVlgswClduFRxFTIN0UlAl2Q_xg5k78l92ECejK2T13mozfch-00mYXRdJeBVkAR99NSl96vekwSLg5jGqvDtHxwMJyhkhPdORFid-NjAKaaPdDpizB-0Hkydc7LcQJX08asef2KcoqlViq7wwR565uG33VjSOomfRyK9k97GOUm8YVd3dlGXQRl7BWQ2C0Q9dw6GsvpnyF2hMcT4MmkAqk3AsekDGJSehtWzmjLaCJjD-HxJ_Jo0piTEpueaVEMCVc5BBSp0qvtDbaqBv79kwvlnWBD3IO1iPhuF8helOSg7kb0liNWrjQciDFg25EZiu487EGkWLNdVyXCJVWR0CjZ6wp7V50jvY7nYBeeYH3ip19XW58zhA-TKl4Kh_7F_e30xsR5d-iTlcu8txsmuNSwpk1YEecqJ7VpgSkl5VSW_k_xqzSub0jEEM1CXvlBcoQDZwXb7NeL5_NJycmCipw0if8GGexuIKQMauQhVLa0JNx3uLuY7Py_OPR6US7JRAeQjcHiUmV5aqMrbMrvpRZyzFMMpf7u606OP7kqSH7UqNUV2-GKBm94mJ12pYty9q1h4eFMuoFHIMokBnv8uMJ50oq4wBOdJvVdDBJVXnJXPJtBTlUz5kvmJAL4yC4YSSzLkb9n9bAdsrQJ4ut48vHTWIjXQNj7C440igXtUtEtAEJRdg9dV-EFX-QTNd6HFFnjnw-Zm5zqIK8VXGxT7Y3GOEO6X4y-iR_a3n3BgkjgBeyQkjWiBe4TwAoX10keqqmpGsH-6xrvSN1T900sCnW-q1KB5XrctHDZAjmanbUsdZWFKGcAt3zfJm59XGm5eOtBiClwBzQ6UqDzk4lnEoYJEYpp8_fWHz2mweg2Fhr48xIMAktgFX33iSynw3-5_qUIL9R5-aP7elE-IzWrb_6wiv442cqyoZzMmDpF5stguAjsreNuB5V5J_KtKNbNGK-oBxaq28T18IApMHdlKmH6iwX58cZV7jQfpW4P4axQ8RYf2jg_-n5uapY-_kFw0sP7AHMZQTRyRzpLUaQ4TawxfSngx77hFplqIN1jKAkZ8wUZaRw-6RV5Iamg82LCRVpIKCXUcnWnu_xKkJ2vflho5sz09Zrp9sp_b8ivtHQaJar3ke8O_J6E_KKERIwOYNsde3fC5W4OOA99ZXCubQ==\",\"summary\":[]}"},{"type":"toolCall","id":"call_89T58N4dJIhc1kLafWFZNUH4|fc_02b86be3bb6b669e0169f7f1df4a948196b2078ffa45056393","name":"read","arguments":{"path":"/home/rurouni/memory/2026-05-03.md","offset":1,"limit":2000}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.5","usage":{"input":21941,"output":205,"cacheRead":0,"cacheWrite":0,"totalTokens":22146,"cost":{"input":0.10970500000000001,"output":0.00615,"cacheRead":0,"cacheWrite":0,"total":0.11585500000000001}},"stopReason":"toolUse","timestamp":1777856987161,"responseId":"resp_02b86be3bb6b669e0169f7f1db8454819695c1910c6d43dd96"}} {"type":"message","id":"c07eb739","parentId":"2d8721ce","timestamp":"2026-05-04T01:09:51.805Z","message":{"role":"toolResult","toolCallId":"call_89T58N4dJIhc1kLafWFZNUH4|fc_02b86be3bb6b669e0169f7f1df4a948196b2078ffa45056393","toolName":"read","content":[{"type":"text","text":"# 2026-05-03 Daily Notes\n\n## Durable setup changes\n\n- Raymond confirmed assistant identity as **Ruruni** 🗡️; durable persona/preferences live in `SOUL.md`, `IDENTITY.md`, `USER.md`, and compact `MEMORY.md`.\n- OpenClaw context tuning increased to reduce compaction: `contextTokens: 128000`, `reserveTokensFloor: 24000`, `maxActiveTranscriptBytes: 1000000`, `memoryFlush.softThresholdTokens: 60000`. Backup: `/home/rurouni/backups/context-memory-20260503-012153`.\n- Storage layout verified and documented: backups moved off root through `/home/rurouni/backups` symlink to `/backup/rurouni/openclaw-backups`; model/cache/temp paths documented in long-term memory.\n\n## Local model / OpenClaw routing\n\n- Primary model kept unchanged: `openai-codex/gpt-5.5` via ChatGPT Plus OAuth.\n- Config routing verified: fallbacks are `deepseek/deepseek-v4-pro`, `openrouter/minimax/minimax-m2.7`, then `local-qwen/qwen3.5-9b`.\n- Raymond said to leave DeepSeek Pro fallback as-is for now because it is half off until May 31.\n- Replaced local Qwen3.5-4B with Qwen3.5-9B Q5_K_M GGUF at `/home/rurouni/models/qwen3.5-9b/Qwen3.5-9B-Q5_K_M.gguf`.\n- `llama-local` serves the 9B model at `127.0.0.1:8081` with `--parallel 1`, `-c 65536`, and full 65k context per request. Initial `--parallel 2` split context and was changed per Raymond’s preference.\n- Stale 4B config refs were removed; old 4B model moved to `/archive/models/old-qwen/Qwen3.5-4B-Q8_0.gguf`.\n\n## Memory / embedding work\n\n- Cleaned memory bloat: consolidated durable facts into `MEMORY.md`, moved low-value fragments to `memory/archive/**/*.txt`, and kept active indexed markdown small.\n- Backups created during cleanup: `/home/rurouni/backups/memory-cleanup-20260503-164258` and `/home/rurouni/backups/memory-final-clean-{ts}`.\n- `openclaw memory status --deep` showed builtin FTS ready but embeddings unavailable due no embedding provider credentials; Codex OAuth does not provide OpenAI embeddings.\n- Current hardware check: GTX 1080 Ti 11GB with Qwen3.5-9B loaded used ~9.0GB VRAM with ~2.1GB free; CPU is Xeon E5-2697A v4 (32 threads), RAM 62GiB with plenty available.\n- Raymond proposed CPU-only retrieval: Qwen3-Embedding-0.6B, top_k 30, Qwen3-Reranker-0.6B CPU-only reranking to top 5–8, final context only reranked docs, chunk size 512–1024 tokens with 10–20% overlap, prioritize stability/accuracy/quality over speed.\n- OpenClaw docs indicate builtin memory does not do reranking; QMD is the likely OpenClaw path for local BM25 + vectors + reranking/query expansion. Need verify CPU-only behavior before enabling QMD or downloading models.\n\n## Standing cautions\n\n- Do not change LAN-bound OpenClaw/OPNsense exposure posture without asking.\n- Do not store Raymond’s sudo password; ask or use narrow allowlisted sudo rules.\n"}],"isError":false,"timestamp":1777856991805}} {"type":"message","id":"4a3c8265","parentId":"c07eb739","timestamp":"2026-05-04T01:10:10.326Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"id\":\"rs_02b86be3bb6b669e0169f7f1e24f94819691d4677c614bff75\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABp9_Hi0dtxzc207a7hlL3eJN3Uesv25EJUmCtk3bxQJU92l8MVTMtK0Mwcxa2XWyCiZuBsrLR6kIgUJLbtvadnhv0MR5qHja_Jz_2tCO7Z1ryvHfq6kl_Igc-8G16vIU0KrBJXNywVzSmHHbNeP_ix1SuGYGVrOqekvokjyKdQZRFnViKwQODWQahXNQBOVKQPajji0MHt92wP9gVgAZcWBnvW1mljk3DBtf9SwRMm_x8tyPMGIcQWYyrAoJJWz8KAK8KC0TbzTAyQfdZDnvEQCMQIjy8LsbzuceyC6PitTHjiwQotkfaiUTqsjdFHxk965px2PJHIZQh_yDsF_d-_fzfDPwDFBkcoibqfTKmJFayCDloTKbImYfwqA4KwVQvDah-ELx_FyzBwXxtdtUOI87jwC6OA7yaR0OMObQ9WivG00YCw6eQnW2xPpDXBEz_pK_VZ8BxpPWRG1__ftKyXrQ7j_zoK_2VrJeFNVF9-N6Y9s_odDg3qisOO7FroWhTcSG2O1N6StlW-kFOK4eyG2-QDcahUcsZaJcp5IjOYgy2obY65vysqHu3QTVk3B8LQtQX-LEL4aqkC16SBylxP47a5KJCM4KjgvvBLK5GjHS4GLjsBmrZgQE8wkvFRtYqNXjSF8ZUFYKQjSu00_SU91BmIBbYyXcuepV-o02fLgc9U_mEyDQkxKMZXPR0EtIPBvfBSc_64xQSrwm-VcfdtkQf5PjlR7B84GGkrA_iymFFHRvRS6l66iRCMh_UUfVeu4C88fNZy2joIyNN8ghZCMuWQ_mZIwG-6YSppCukSo2lklSC9wtSgXXX64NtQjSOyn6kK0-x7JreZg1DCydw3THJOZwpcGCNnrwc7EaK--9At8ZtudNMcLz8T7W9eCbaj1nJeczq5cUPBMtVy3xOXyl5uLPHhArkL5DVzIMj69MIiVHKLtHgDLmRiNi0UQveBghD-5qzRHiEJSuWfnjgX4YR72Q==\",\"summary\":[]}"},{"type":"toolCall","id":"call_EFVCRAtijVyOWJm6NzT4OHis|fc_02b86be3bb6b669e0169f7f1e2b4d8819698b09b1516fcc076","name":"write","arguments":{"path":"/home/rurouni/memory/2026-05-03.md","content":"# 2026-05-03 Daily Notes\n\n## Durable setup changes\n\n- Raymond confirmed assistant identity as **Ruruni** 🗡️; durable persona/preferences live in `SOUL.md`, `IDENTITY.md`, `USER.md`, and compact `MEMORY.md`.\n- OpenClaw context tuning increased to reduce compaction: `contextTokens: 128000`, `reserveTokensFloor: 24000`, `maxActiveTranscriptBytes: 1000000`, `memoryFlush.softThresholdTokens: 60000`. Backup: `/home/rurouni/backups/context-memory-20260503-012153`.\n- Storage layout verified and documented: backups moved off root through `/home/rurouni/backups` symlink to `/backup/rurouni/openclaw-backups`; model/cache/temp paths documented in long-term memory.\n\n## Local model / OpenClaw routing\n\n- Primary model kept unchanged: `openai-codex/gpt-5.5` via ChatGPT Plus OAuth.\n- Config routing verified: fallbacks are `deepseek/deepseek-v4-pro`, `openrouter/minimax/minimax-m2.7`, then `local-qwen/qwen3.5-9b`.\n- Raymond said to leave DeepSeek Pro fallback as-is for now because it is half off until May 31.\n- Replaced local Qwen3.5-4B with Qwen3.5-9B Q5_K_M GGUF at `/home/rurouni/models/qwen3.5-9b/Qwen3.5-9B-Q5_K_M.gguf`.\n- `llama-local` serves the 9B model at `127.0.0.1:8081` with `--parallel 1`, `-c 65536`, and full 65k context per request. Initial `--parallel 2` split context and was changed per Raymond’s preference.\n- Stale 4B config refs were removed; old 4B model moved to `/archive/models/old-qwen/Qwen3.5-4B-Q8_0.gguf`.\n\n## Memory / embedding work\n\n- Cleaned memory bloat: consolidated durable facts into `MEMORY.md`, moved low-value fragments to `memory/archive/**/*.txt`, and kept active indexed markdown small.\n- Backups created during cleanup: `/home/rurouni/backups/memory-cleanup-20260503-164258` and `/home/rurouni/backups/memory-final-clean-{ts}`.\n- `openclaw memory status --deep` showed builtin FTS ready but embeddings unavailable due no embedding provider credentials; Codex OAuth does not provide OpenAI embeddings.\n- Current hardware check: GTX 1080 Ti 11GB with Qwen3.5-9B loaded used ~9.0GB VRAM with ~2.1GB free; CPU is Xeon E5-2697A v4 (32 threads), RAM 62GiB with plenty available.\n- Raymond proposed CPU-only retrieval: Qwen3-Embedding-0.6B, top_k 30, Qwen3-Reranker-0.6B CPU-only reranking to top 5–8, final context only reranked docs, chunk size 512–1024 tokens with 10–20% overlap, prioritize stability/accuracy/quality over speed.\n- OpenClaw docs indicate builtin memory does not do reranking; QMD is the likely OpenClaw path for local BM25 + vectors + reranking/query expansion. Need verify CPU-only behavior before enabling QMD or downloading models.\n\n## Standing cautions\n\n- Do not change LAN-bound OpenClaw/OPNsense exposure posture without asking.\n- Do not store Raymond’s sudo password; ask or use narrow allowlisted sudo rules.\n\n## OpenClaw memory architecture planning\n\n- Raymond wants an efficient OpenClaw memory/context system: Mem0 OSS + Qdrant for long-term memory, QMD Light for workspace/docs only, and Lossless Claw/LCM for long-session compaction.\n- Token budget decisions: normal injected memory target 300–800 tokens; project-heavy 800–1,500 tokens; hard max 2,000 memory/doc tokens. Mem0 topK starts 4–6; injected Mem0 memory starts 512 tokens and maxes 768 unless changed.\n- Ownership boundaries: Mem0 owns long-term memory; QMD owns workspace/document search; LCM owns conversation compaction; OpenClaw base memory stays tiny. Avoid duplicate long-term injection and do not inject full `MEMORY.md`, daily notes, or giant markdown memory files every turn.\n- QMD should be BM25-first (`searchMode: \"search\"`) for docs/configs/commands/files, vector fallback only if needed, no reranker/heavy query mode by default, and no GPU reranking.\n- LCM should use DAG summaries and a pinned version; only inject summaries when the conversation is long enough.\n- Required storage paths for planned stack: `/data/openclaw-memory/qdrant`, `/data/openclaw-memory/mem0`, `/data/openclaw-memory/qmd`, `/data/openclaw-memory/cache`, `/models/embeddings/Qwen3-Embedding-0.6B`, `/backup/openclaw-memory`, `/archive/openclaw-memory`.\n- Before implementation, inspect current OpenClaw install/config/plugins/logs/memory paths, Docker/Podman availability, existing Qdrant/Mem0/QMD/LCM installs, and `nvidia-smi`; print a clear plan before changing anything. Do not modify/overwrite/delete memory/config before backup and explicit approval.\n- Inspection findings so far: OpenClaw `/usr/bin/openclaw` version `2026.5.2 (8b2a6e5)`; gateway dashboard `http://192.168.1.50:18789/`; gateway systemd service installed/enabled/running; builtin `memory-core` enabled; Docker/containerd installed and running; Podman/nerdctl absent; no existing `/data/openclaw-memory`, `/data/qdrant`, `/var/lib/qdrant`; Python packages `mem0`, `qdrant_client`, `fastembed`, `sentence_transformers` absent; global npm has `openclaw@2026.5.2`; GTX 1080 Ti has ~2.1GB free because `llama-server` uses ~9016MiB; `/data`, `/models`, `/backup`, `/archive` have ample space.\n- Relevant docs checked: QMD docs say `memory.backend: \"qmd\"`, `memory.qmd.searchMode: \"search\"` is BM25-only and skips vector probes/embedding maintenance; QMD default indexes `MEMORY.md` + `memory/` unless `includeDefaultMemory` changed; QMD env vars can override models; `memory.qmd.limits` controls max results/snippets/injected chars/timeouts. Context engine docs show LCM plugin install `@martian-engineering/lossless-claw` and selection via `plugins.slots.contextEngine: \"lossless-claw\"` with fallback to `legacy`.\n"}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.5","usage":{"input":1439,"output":1579,"cacheRead":21504,"cacheWrite":0,"totalTokens":24522,"cost":{"input":0.007195000000000001,"output":0.04737,"cacheRead":0.010752,"cacheWrite":0,"total":0.065317}},"stopReason":"toolUse","timestamp":1777856991807,"responseId":"resp_02b86be3bb6b669e0169f7f1e175f88196aadf47982e57f0ba"}} {"type":"message","id":"54e3d18c","parentId":"4a3c8265","timestamp":"2026-05-04T01:10:10.337Z","message":{"role":"toolResult","toolCallId":"call_EFVCRAtijVyOWJm6NzT4OHis|fc_02b86be3bb6b669e0169f7f1e2b4d8819698b09b1516fcc076","toolName":"write","content":[{"type":"text","text":"Appended content to memory/2026-05-03.md."}],"details":{"path":"memory/2026-05-03.md","appendOnly":true},"isError":false,"timestamp":1777857010337}} {"type":"message","id":"413c5afe","parentId":"54e3d18c","timestamp":"2026-05-04T01:10:14.427Z","message":{"role":"user","content":[{"type":"text","text":"Qwen3-Embedding-0.6B requirements:\n- Download/store under /models/embeddings/Qwen3-Embedding-0.6B.\n- Try to run it efficiently.\n- Prefer GPU only if it does not interfere with my main model.\n- Because my GTX 1080 Ti usually has only about 2GB free VRAM, use a conservative setup:\n - small batch size\n - low concurrency\n - short max sequence length unless needed\n - cached embeddings\n - automatic fallback to CPU if CUDA OOM happens\n- Do not use a reranker.\n- Do not load a second large LLM for memory tasks.\n\nMem0 + Qdrant requirements:\n- Set up Qdrant storage under /data/openclaw-memory/qdrant.\n- Set up Mem0 state/config under /data/openclaw-memory/mem0.\n- Configure Mem0 to use Qdrant.\n- Configure Mem0 to use Qwen3-Embedding-0.6B as the embedder.\n- Keep recall topK low.\n- Keep injected memory compact.\n- Store durable facts, not full conversations.\n- Avoid saving injected memory blocks back into memory.\n- Add tags/categories when possible:\n - pinned\n - user_preference\n - project_fact\n - command\n - system_config\n - temporary\n - stale_candidate\n\nQMD Light requirements:\n- Install/configure QMD only in light mode.\n- Index useful workspace Markdown/docs/configs.\n- Use BM25 search as default.\n- Use vector search only when keyword search fails.\n- Disable reranking and heavy hybrid query mode.\n- Do not auto-inject QMD results every turn.\n- QMD should only be called when the user asks for docs/configs/commands/files or when the task clearly needs workspace search.\n\nLossless Claw / LCM requirements:\n- Install or configure it only if compatible with my current OpenClaw version.\n- Version-pin it.\n- Use fresh tail around 32–48 messages.\n- Use context threshold around 0.75.\n- Keep prompt-aware eviction OFF at first.\n- It should handle session continuity only, not personal long-term facts.\n\nOpenClaw prompt injection policy:\nCreate or update the memory injection policy so it behaves like this:\n\n1. Classify whether the turn needs memory.\n2. If no memory is needed, inject no long-term memory.\n3. If memory is needed, query Mem0 only.\n4. Inject only the top relevant memories, compacted.\n5. If the user asks about docs/configs/commands/files, query QMD Light.\n6. If the session is long, allow LCM summary injection.\n7. Keep total memory/context injection within budget.\n8. Never inject all memory files by default.\n\nDesired injected memory format:\n\n\nPinned facts:\n- ...\n\nRelevant user preferences:\n- ...\n\nCurrent project facts:\n- ...\n\nUseful commands/config:\n- ...\n\n\nDo not include huge raw logs unless specifically needed.\n\nMemory hygiene:\nCreate a weekly maintenance command or script that:\n- backs up Mem0/Qdrant/QMD first\n- finds duplicate memories\n- marks stale memories\n- prunes temporary old memories\n- keeps pinned memories\n- exports a readable memory report\n- does not delete aggressively without logs\n\nBackups:\nCreate backup commands/scripts for:\n- Qdrant snapshots\n- Mem0 config/state\n- QMD indexes\n- OpenClaw MEMORY.md and daily notes\nUse /backup/openclaw-memory as backup target.\n\nDeliverables:\n1. Show me the exact current state you detected.\n2. Give me the implementation plan.\n3. Create the folder structure.\n4. Install/configure the services/tools.\n5. Configure Qwen3-Embedding-0.6B.\n6. Configure Mem0 + Qdrant.\n7. Configure QMD Light.\n8. Configure LCM if compatible.\n9. Configure OpenClaw injection behavior.\n10. Create backup and hygiene scripts.\n11. Create health-check commands.\n12. Give me final copy-paste commands to start/stop/restart/status.\n13. Give me a short explanation of how memory flows per turn.\n14. Give me rollback instructions.\n\nBe careful:\n- Do not break my existing OpenClaw.\n- Backup before edits.\n- Keep token usage low.\n- Keep GPU VRAM usage safe.\n- No reranker.\n- No heavy qmd query mode.\n- Do not put big data on root.\n- Ask me before deleting anything.\n\nAnd here is the shorter boss-mode version if you want OpenClaw to act faster:\n\nSet up my OpenClaw memory stack for low-token, fast retrieval on Debian 13.Use this architecture:\n- Mem0 OSS + Qdrant as the main long-term memory brain.\n- Qwen3-Embedding-0.6B as the embedder.\n- Prefer GPU for embeddings only if safe on my GTX 1080 Ti with about 2GB free VRAM; otherwise auto-fallback to CPU.\n- QMD Light for workspace/document search only: BM25 first, vector fallback, no reranker, no heavy qmd query mode.\n- Lossless Claw / LCM for long-session DAG summaries, version-pinned.\n- Keep OpenClaw base memory tiny.\n\nMy system:\n- Xeon E5-2697A v4, 16c/32t\n- 62GB RAM\n- GTX 1080 Ti 11GB, about 2GB free VRAM\n- Debian 13 trixie\n- /data 1.5TB RAID0\n- /models 465GB SSD\n- /backup 1.8TB HDD\n\nUse storage:\n- /data/openclaw-memory/qdrant\n- /data/openclaw-memory/mem0\n- /data/openclaw-memory/qmd\n- /data/openclaw-memory/cache\n- /models/embeddings/Qwen3-Embedding-0.6B\n- /backup/openclaw-memory\n\nRules:\n- Backup before changing anything.\n- Do not delete without asking.\n- Do not put large data on root.\n- Do not use GPU reranker.\n- Do not inject full MEMORY.md or daily notes every turn.\n- Mem0 owns long-term memory.\n- QMD owns workspace search.\n- LCM owns session compaction.\n- Only one long-term memory system injects into prompt.\n\nToken budget:\n- Normal memory injection: 300–800 tokens\n- Project-heavy: 800–1,500 tokens\n- Hard max: 2,000 tokens\n- Mem0 topK: 4–6\n- Mem0 injected memory: start 512 tokens, max 768\n\nBefore setup:\n1. Inspect my current OpenClaw config.\n2. Detect Docker/Podman, Qdrant, Mem0, QMD, LCM.\n3. Check GPU with nvidia-smi.\n4. Locate OpenClaw config/memory/plugin paths.\n5. Print your plan.\n\nThen:\n1. Create folders.\n2. Install/configure Qdrant.\n3. Install/configure Mem0 with Qdrant.\n4. Configure Qwen3-Embedding-0.6B.\n5. Configure QMD Light.\n6. Configure LCM if compatible.\n7. Configure OpenClaw injection policy.\n8. Create backup scripts.\n9. Create weekly memory hygiene script.\n10. Create health-check/status commands.\n11. Give me restart/status/rollback commands.\n\nFinal output should include:\n- what changed\n- where files are located\n- how memory flows per turn\n- how to test recall\n- how to restart services\n- how to rollback"}],"timestamp":1777857014426}} {"type":"custom_message","customType":"openclaw.runtime-context","content":"Conversation info (untrusted metadata):\n```json\n{\n \"chat_id\": \"telegram:7229867039\",\n \"message_id\": \"1524\",\n \"sender_id\": \"7229867039\",\n \"sender\": \"Raymond\",\n \"timestamp\": \"Sun 2026-05-03 18:06 PDT\"\n}\n```\n\nSender (untrusted metadata):\n```json\n{\n \"label\": \"Raymond (7229867039)\",\n \"id\": \"7229867039\",\n \"name\": \"Raymond\"\n}\n```","display":false,"details":{"source":"openclaw-runtime-context"},"id":"e8e91b5d","parentId":"413c5afe","timestamp":"2026-05-04T01:10:14.428Z"} {"type":"message","id":"b363a066","parentId":"e8e91b5d","timestamp":"2026-05-04T01:10:27.984Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"id\":\"rs_02b86be3bb6b669e0169f7f1f809508196b16132b95c7d7ae9\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABp9_IBNRyRzOcDXcfamephLStq-TZG1xBDI0GzwIdPCC_NJTYaeXohsOqWhO7ir2AnSOSB9Nu0WAofhuh7Rl-VFM9xJKsNyrQ3ucyxs8g9M1X3plkpCpiZ2U7A4aY7Ft9TqCwDLvPUTqKfN8om7Fcsf_cfTcEzHJaOG4sNmiFSt8HdIqnxpMVo_WNW4-ZYwWN8WYeCSFJGnhBswfWebznC2hbXWi1RvHuDVtqDcRNTfqkVSmYOQXvCHRXp_jp4oRDrybPgJ36gmBPaTBQggPtPeHEfkyL6o2hC_vgYsWLOWEULv19l-Jiwu-QxIIiYpzpYSMMukz2cYU1NowfA3Joy8Yc-AKiaplCCv-6q0sHcQz3e9sKnWXvinSVDTbAKteEd8xqjyE-kMPCeVXhovfUX4j_xKHahVnvVJzQ4PiDsaqKzh6Jdf5g2Ha8MWXJaUukdYeLQR8J0zdhQdEycMeNF7VkNtjV_CL4BA-UmsmCla15H-HRNx0ZTBue1tg8aZEStk2O3tXQgpJbdF_9bDTLYzL1lJDPNF_PlmqXZB7skmDnmqiHG_SkgUKi7KsIW_R_fYzwaI7bfi5op042Zyu-O-z9L45f6wr9Rbci9aTQx5WgkTWEmaNEOwY6QBYXmDXaDoe1Ngjt8HqXJs377XnrnCxFRKZQ8mAj7cUUxK_0TsJ0vrWjYvezr8KHHzMxRSSqqZOQ5GIn3AxyZuT95ufKVFi_zc2Zl_tUAFRI2RdNmZZf8Db8CZ3laR7jIg9c5DKPL1yNAVxmQlWAHrb-T6NutGTlTuHIHtyMS-afwIbTycxZpsmJNpVpy92988zMxfQ1ExokY_LbzjfJ1gyj9CPXPh8ZBPI4wAz8FrwqReJe6bjX60FnL9bZdAAUGbKrC-5MZZ9uh_a4laectOHW4w73sDHkuIv2WVI28uMH_aFbxMW17yBgHs7-zyHeFhQz7_Pv7_0CEa8NU2b6tQkNI-XjehjDwMYC8FUGRo4YWLWiT_JWRDvFlfSYZB4oD7L3p5O8ncH-bGsWAVUcvNcxf3oolOAL3j-76STtEqMmCA8G3cOw8HCfgSmqRrROIdrzFyEaBtqh4UCqKoJepHST27LRW16CtG-BRj7pJt15a6xHzMJwxVIY21F1wL91O9lEsgPua3GLO9H_AmCRj8Hvwpl6mK-TzUEfWkqAemc2COEhb87LCdaCt9eMUlt9s9Z9VEGqPyOruZbR_4wTU_HaRTfQfL2RzHRdpqUAE-lSLiBE_ZNVVMqzTTYa1ssIWU9fyx8I3BmuGAxC3migoem_jfS-C4362mh_82d5hFq7Vb0nLXJAPt2-5nCpKUut-BkP9uVLvnKQGhaL1AdktHyaByYpbpuB2y1UQyvBEvZPCXJ_Swt7agNp7ETOszlgWpDlybTrHRaysqJx-Lg4cv_3mLAa-GQ9gHbpmrUpefU1aLgeENN8-ezGuagmHw5RVMvkrPj-_I5tXi9w-G7yvZUZqKFASarCZa1xE1rw7dTY7--4VyP50lNsRyU3SonxGFBP3Oh9k_-XKzQBm6VCbf8A8AGlBliZ5mgGrqxx7afJXOmiVHzfMMRkUOYMxoYh3WdQgGPHb6YXRhyHvjPsFWBdiJgP7JtljmEqhWTYR61EG7BYFAtDGRKqKBSLDrm6OWboY5lCJlpSOVmSesh2V3RwoxAg8iDdv_eX5ZDpSpQieYeOZYWjADsvH-Io6F2QbqP56Tl4tUxftjYl2d6NZg2Ui-646FxjyL3BGUYgBGyE_8LVy_EKra2qu_-2VzS-EYobESTUyuJw9Ua7Z5ePYOjlnbqrrqz1yQnKzpeAMVioX1LMl-66Y2xlfPBxjEe52iVPuk5ADpnYkDCVYvktF_VH-nIvmPUnHCSXdXyyOvfYtfVgHP9viecjsjX4NjOA2LYM9jMAcxtzoVpWzikbiTrZ6bkOoC4o-RzyfIQSmLBaQIOuT1AE7NHdsQrpZRfhzBiOaFD19lcLnJqZZi17HtoeEyEojdOYTA601jf7OIk8378x_QyP2gYP8ZA1k8fdllvMogtMOh1AAJ7DVfpxuKFI-VnRbjXNgceP4Z2sMgs4-f6kQ6vb1AgIwPkmcFehkRsNVHU_Bq_1jRZ3GJNSF-nEzw-WBtMPwFNHMlB15bPQ42iNVyKUYkqX_FB0JIq6sstCdwDnDywhGAwCwJLXyjBo6Lxo8FE6P2mzKdCT5cfK_cj_RZW_cxerqjqeFvAFfZTUjgXq6USGpSXXIxPAfmS3fxt4YmpiCT2KRa2xLFnMR4jz_WBcWJYWu4Bd7pSjqtWis6Sk1RUHbIyy2Rkvjqb0BFwHs9YQCtmVwcI9nN4RvPBIcY0Sxu08wpU3oDoARbBFC3kMZRG0iQI0adMtcT3l7csoYaJD-pspIWimlcmyYi5Hg7jF9crfFYhp29T68ZAlOfKtagiQksq-atN1qLtHXn8MGP-4bioNklsMM-5ijj4Wy31EaJBYunSXGP_7QxFTKp-OlIbFycliqtAoJj5t8e3_ttxnNvPw4Ed-nLSItnAJgl6kKWcEy9hYC1Y-aMF8xVHM0I93soL5xtnZvQmfkRZY9DN_EXIvLMs4HsB4IH8kvf23aZA18I8r6XszninPuzdIIrd8oqwG2Hf6whgaa8fXpYUylAUSjJlg8MOtZ_wHjh8xCv7Gq6h0FI-6kuqfij7E8HgKAI7adEbXkTo_KkRAMlR5vY9Ahsv5772vppG-S4mYaAlVinxVFDdNwDyJNvLCG7dPTA6MwiTZyJoslLDU7qchSckucs-9zvkgxy8TLyBc8ALQDW6WC3LNlxtl6p5TJ7_1VJR80UTldD2zHArdVkMSHYgxmBHM-aGAbtH3ze19wU__yW8IuSr-GdmoPU2-S7-XlummNDiajNSV1QdF9lqYChkv-GQBZdAQPOhfiYa3JgYcPIMDhFeddapQDMklB-Lf_hvqDTkHbiPEQ75-EJrPpfHxO_cZy3A_lCJe5RZcQSS0nF91YFov1KOSWxeFIleYORO1M5rSvK9jLoXmEq_1qYSch6frVLtzBolpFrL5H9WONB3rqWTK8_T8rFEZLVY8mc4pvmtnZXuRPiMIK5_zU5fgcIX3UvQwDi8l-imwUbRAHRcVWesGd0jb2H2iAxYB3-aPhGr3ZDVHMS_hNOfkN40kejXCKrNBiPRA_7qo_YPhXqMoLLxMFH0zRtlOKx2lmNUA9_6jppsRVOSZvO28NIdkKIuw0wHeOvJIVwt3LaITYpOc-SYZzEYFmN7TSk-KDljA3H8IYUTwe0akuarDFBqaRJO0AkrwXvi68Mdm1hh2_QdwZeHj9HaC3pTzBFHoZsmZtGyhSvddvMPzxWqjffW7qk8hFH6gQxjpCnUgJNi-HaLnP8jGoeL4hB2hln9Z1oPUCOK6iCTdWw3KI1DSEagezeLvcq5PGtofCxNKpxthuoentRUsVFO-JKdHE2ZDfH3KOvpLdgXcGeqnVguhNwBauQF5F0rbysOkLH4mS_zpYlRjlZWfy_PNxPL3V5UfaWV-_hpknZMim-Tyo-izKqPAcvF71sW2wlUNtnBAV9oRtNDHEOk0Gfb11FWGmyQoXMdrfmtoW1USeTDmUtsLRlkrA3K6FhWX08rBoLvmOlhpcrgBVZqKS-Es3diFLVi7ANk4pjw0A2qrFmDRV-N9b1AUM2eGC-YcckUZKyvAYUCceoQHRLxFD0HbKZJdPwNNWCuxuiQlX2kARDedOUB-gqQ0Vbg3Fd53ZnLtkdlTHAHgKmeNOVqZ8KePK_i2nnZyPOle29zO2bCI-zj5Numft3Fgctln1eoQozsbhOZa2HL_mGlm3Hjv7H5ktsjCZGWXHmEL16l82Y5Y_kkWBSCQtO-DkpXy5XJuHyhXfNWynaqU=\",\"summary\":[]}"},{"type":"toolCall","id":"call_TA0eXxo4EiKbcehaUd3UxZux|fc_02b86be3bb6b669e0169f7f20159e081969968348b5b1baeed","name":"update_plan","arguments":{"plan":[{"step":"Finish current-state inspection","status":"in_progress"},{"step":"Back up config and memory files","status":"pending"},{"step":"Create storage layout","status":"pending"},{"step":"Install/version-pin Qdrant, Mem0 tools, QMD, LCM","status":"pending"},{"step":"Configure embedder, Mem0/Qdrant, QMD Light, LCM policy","status":"pending"},{"step":"Create backup, hygiene, health scripts","status":"pending"},{"step":"Verify and report commands/rollback","status":"pending"}],"explanation":"I’ll do this carefully: inspect → backup → reversible setup. No deletes."}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.5","usage":{"input":26495,"output":635,"cacheRead":13312,"cacheWrite":0,"totalTokens":40442,"cost":{"input":0.132475,"output":0.01905,"cacheRead":0.006656,"cacheWrite":0,"total":0.15818100000000002}},"stopReason":"toolUse","timestamp":1777857014429,"responseId":"resp_02b86be3bb6b669e0169f7f1f6c168819693f9a20a83f57894"}} {"type":"message","id":"689f203b","parentId":"b363a066","timestamp":"2026-05-04T01:10:28.056Z","message":{"role":"toolResult","toolCallId":"call_TA0eXxo4EiKbcehaUd3UxZux|fc_02b86be3bb6b669e0169f7f20159e081969968348b5b1baeed","toolName":"update_plan","content":[],"details":{"status":"updated","explanation":"I’ll do this carefully: inspect → backup → reversible setup. No deletes.","plan":[{"step":"Finish current-state inspection","status":"in_progress"},{"step":"Back up config and memory files","status":"pending"},{"step":"Create storage layout","status":"pending"},{"step":"Install/version-pin Qdrant, Mem0 tools, QMD, LCM","status":"pending"},{"step":"Configure embedder, Mem0/Qdrant, QMD Light, LCM policy","status":"pending"},{"step":"Create backup, hygiene, health scripts","status":"pending"},{"step":"Verify and report commands/rollback","status":"pending"}]},"isError":false,"timestamp":1777857028056}} {"type":"message","id":"7eeb0faf","parentId":"689f203b","timestamp":"2026-05-04T01:10:42.554Z","message":{"role":"assistant","content":[{"type":"text","text":"Bet. I’m going inspection-first and keeping this reversible. Current plan before I touch config/services:\n\n1. Confirm exact OpenClaw config/plugin/memory state and GPU/container state.\n2. Backup OpenClaw config, memory files, plugin registry, and current notes to `/backup/openclaw-memory/...`.\n3. Create only the requested `/data`, `/models`, `/backup` directories.\n4. Install/version-pin:\n - Qdrant container with storage on `/data/openclaw-memory/qdrant`\n - Mem0 Python env/state under `/data/openclaw-memory/mem0`\n - Qwen3-Embedding-0.6B under `/models/embeddings/Qwen3-Embedding-0.6B`\n - QMD pinned, BM25/light mode only\n - LCM only if plugin install/compat check passes\n5. Add scripts for health/status, backup, weekly hygiene, and rollback.\n6. Avoid reranker, avoid second large LLM, avoid GPU unless safe, and don’t inject full memory files every turn.","textSignature":"{\"v\":1,\"id\":\"msg_02b86be3bb6b669e0169f7f205698c8196be8ae5b5c8672699\",\"phase\":\"commentary\"}"},{"type":"toolCall","id":"call_fyxrBu3E5KI0kQb7topQPiuB|fc_02b86be3bb6b669e0169f7f21268a8819684c9451605c036f9","name":"exec","arguments":{"command":"set -euo pipefail\nprintf '=== OpenClaw ===\\n'\ncommand -v openclaw\nopenclaw --version\nopenclaw gateway status 2>&1 | sed -n '1,120p' || true\nprintf '\\n=== Config paths ===\\n'\nfind /home/rurouni/.openclaw -maxdepth 3 -type f \\( -name 'openclaw.json' -o -name '*.json' -o -name '*.sqlite' \\) -printf '%s %TY-%Tm-%Td %TH:%TM %p\\n' | sort\nprintf '\\n=== Memory status deep ===\\n'\nopenclaw memory status --deep --agent main 2>&1 | sed -n '1,220p' || true\nprintf '\\n=== Plugins relevant ===\\n'\nopenclaw plugins list 2>&1 | grep -Ei 'memory|qmd|lossless|context|active' || true\nprintf '\\n=== Redacted config summary ===\\n'\nnode - <<'NODE'\nconst fs=require('fs'); const p='/home/rurouni/.openclaw/openclaw.json';\nconst j=JSON.parse(fs.readFileSync(p,'utf8'));\nfunction red(o){ if(Array.isArray(o)) return o.map(red); if(o&&typeof o==='object'){let r={}; for(const [k,v] of Object.entries(o)){ if(/key|token|secret|password|credential|auth/i.test(k)) r[k]=''; else r[k]=red(v);} return r;} return o; }\nconst out={version:j.version, memory:j.memory, plugins:j.plugins, agents:j.agents, models:{routing:j.models?.routing, defaults:j.models?.defaults, providers:Object.fromEntries(Object.entries(j.models?.providers||{}).map(([k,v])=>[k,{api:v.api,baseUrl:v.baseUrl,models:v.models,apiKey:v.apiKey?'':undefined}]))}};\nconsole.log(JSON.stringify(red(out),null,2));\nNODE","workdir":"/home/rurouni","yieldMs":10000,"timeout":90}},{"type":"toolCall","id":"call_gnujK8CYnv8Y3tDTBlbsTSly|fc_02b86be3bb6b669e0169f7f21268bc8196a616f56fd27ef19b","name":"exec","arguments":{"command":"set -euo pipefail\nprintf '=== Runtime/tools ===\\n'\ncat /etc/os-release | sed -n '1,8p'\nprintf '\\nDocker: '; docker --version 2>/dev/null || true\nprintf 'Podman: '; podman --version 2>/dev/null || true\nprintf 'Node: '; node -v\nprintf 'npm: '; npm -v\nprintf 'Python: '; python3 --version\nprintf '\\n=== Containers ===\\n'\ndocker ps -a --format 'table {{.Names}}\\t{{.Image}}\\t{{.Status}}\\t{{.Ports}}' 2>/dev/null || true\nprintf '\\n=== GPU ===\\n'\nnvidia-smi --query-gpu=name,memory.total,memory.used,memory.free --format=csv,noheader,nounits || true\nnvidia-smi --query-compute-apps=pid,process_name,used_memory --format=csv,noheader,nounits || true\nprintf '\\n=== Storage ===\\n'\ndf -h / /data /models /backup /archive 2>/dev/null || true\nprintf '\\n=== Existing target paths ===\\n'\nfor p in /data/openclaw-memory /models/embeddings/Qwen3-Embedding-0.6B /backup/openclaw-memory /archive/openclaw-memory; do if [ -e \"$p\" ]; then ls -ld \"$p\"; find \"$p\" -maxdepth 2 -printf '%M %s %p\\n' | head -40; else echo \"missing $p\"; fi; done","workdir":"/home/rurouni","yieldMs":10000,"timeout":60}},{"type":"toolCall","id":"call_y8pkwcjL49TFgAVvttDCpHrp|fc_02b86be3bb6b669e0169f7f21268c4819682f1638d1bdb65c1","name":"exec","arguments":{"command":"set -euo pipefail\nprintf '=== Installed commands ===\\n'\nfor c in qmd mem0 qdrant uvicorn huggingface-cli; do printf '%s: ' \"$c\"; command -v \"$c\" || true; done\nprintf '\\n=== Python packages current ===\\n'\npython3 - <<'PY'\nimport importlib.util\nfor p in ['mem0','qdrant_client','sentence_transformers','torch','fastapi','uvicorn','huggingface_hub']:\n print(p, bool(importlib.util.find_spec(p)))\nPY\nprintf '\\n=== npm versions pinned candidates ===\\n'\nfor p in @tobilu/qmd @martian-engineering/lossless-claw; do printf '%s '; npm view \"$p\" version 2>/dev/null || true; done","workdir":"/home/rurouni","yieldMs":10000,"timeout":80}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.5","usage":{"input":1034,"output":1316,"cacheRead":39424,"cacheWrite":0,"totalTokens":41774,"cost":{"input":0.00517,"output":0.03948,"cacheRead":0.019712,"cacheWrite":0,"total":0.064362}},"stopReason":"toolUse","timestamp":1777857028058,"responseId":"resp_02b86be3bb6b669e0169f7f2045b90819698f40b9365e7ff42"}} {"type":"message","id":"d8c84bd3","parentId":"7eeb0faf","timestamp":"2026-05-04T01:10:52.619Z","message":{"role":"toolResult","toolCallId":"call_fyxrBu3E5KI0kQb7topQPiuB|fc_02b86be3bb6b669e0169f7f21268a8819684c9451605c036f9","toolName":"exec","content":[{"type":"text","text":"Command still running (session faint-comet, pid 58173). Use process (list/poll/log/write/kill/clear/remove) for follow-up."}],"details":{"status":"running","sessionId":"faint-comet","pid":58173,"startedAt":1777857042585,"cwd":"/home/rurouni","tail":" file: ~/.config/systemd/user/openclaw-gateway.service\nService env: OPENCLAW_GATEWAY_PORT=18789\n\nConfig (cli): ~/.openclaw/openclaw.json\nConfig (service): ~/.openclaw/openclaw.json\n\nGateway: bind=lan (0.0.0.0), port=18789 (service args)\nProbe target: ws://127.0.0.1:18789\nDashboard: http://192.168.1.50:18789/\nProbe note: bind=lan listens on 0.0.0.0 (all interfaces); probing via 127.0.0.1.\n\nRuntime: running (pid 57453, state active, sub running, last exit 0, reason 0)\nConnectivity probe: ok\nCapability: admin-capable\n\nListening: *:18789\nTroubles: run openclaw status\nTroubleshooting: https://docs.openclaw.ai/troubleshooting\n\n=== Config paths ===\n1045 2026-05-03 16:41 /home/rurouni/.openclaw/logs/config-health.json\n11280 2026-05-03 16:28 /home/rurouni/.openclaw/openclaw.json\n115407 2026-05-03 02:21 /home/rurouni/.openclaw/plugins/installs.json\n120 2026-05-03 01:03 /home/rurouni/.openclaw/workspace-state.json\n172032 2026-05-03 18:10 /home/rurouni/.openclaw/memory/main.sqlite\n179 2026-05-03 18:10 /home/rurouni/.openclaw/exec-approvals.json\n2 2026-05-03 00:34 /home/rurouni/.openclaw/devices/pending.json\n2242 2026-05-03 18:10 /home/rurouni/.openclaw/devices/paired.json\n348 2026-05-03 00:13 /home/rurouni/.openclaw/tui/last-session.json\n37 2026-05-02 20:23 /home/rurouni/.openclaw/credentials/telegram-pairing.json\n37 2026-05-02 23:33 /home/rurouni/.openclaw/credentials/https-pairing.json\n37 2026-05-02 23:35 /home/rurouni/.openclaw/credentials/web-pairing.json\n4096 2026-05-02 21:38 /home/rurouni/.openclaw/flows/registry.sqlite\n416 2026-05-03 00:27 /home/rurouni/.openclaw/identity/device.json\n428 2026-05-03 18:10 /home/rurouni/.openclaw/identity/device-auth.json\n49 2026-05-02 19:42 /home/rurouni/.openclaw/update-check.json\n53248 2026-05-02 20:12 /home/rurouni/.openclaw/tasks/runs.sqlite\n58 2026-05-02 20:23 /home/rurouni/.openclaw/credentials/telegram-default-allowFrom.json\n73 2026-05-03 18:06 /home/rurouni/.openclaw/telegram/update-offset-default.json\n\n=== Memory status deep ===\n"},"isError":false,"timestamp":1777857052618}} {"type":"message","id":"87ae52f0","parentId":"d8c84bd3","timestamp":"2026-05-04T01:10:52.619Z","message":{"role":"toolResult","toolCallId":"call_gnujK8CYnv8Y3tDTBlbsTSly|fc_02b86be3bb6b669e0169f7f21268bc8196a616f56fd27ef19b","toolName":"exec","content":[{"type":"text","text":"=== Runtime/tools ===\nPRETTY_NAME=\"Debian GNU/Linux 13 (trixie)\"\nNAME=\"Debian GNU/Linux\"\nVERSION_ID=\"13\"\nVERSION=\"13 (trixie)\"\nVERSION_CODENAME=trixie\nDEBIAN_VERSION_FULL=13.4\nID=debian\nHOME_URL=\"https://www.debian.org/\"\n\nDocker: Docker version 29.4.2, build 055a478\nPodman: Node: v24.15.0\nnpm: 11.12.1\nPython: Python 3.13.5\n\n=== Containers ===\nNAMES IMAGE STATUS PORTS\n\n=== GPU ===\nNVIDIA GeForce GTX 1080 Ti, 11264, 9021, 2144\n56402, /usr/local/bin/llama-server, 9016\n\n=== Storage ===\nFilesystem Size Used Avail Use% Mounted on\n/dev/nvme0n1p2 221G 29G 182G 14% /\n/dev/md0 1.5T 21M 1.4T 1% /data\n/dev/sdd1 458G 2.1M 435G 1% /models\n/dev/sdb1 1.8T 3.2M 1.7T 1% /backup\n/dev/sde1 1.8T 4.2G 1.7T 1% /archive\n\n=== Existing target paths ===\nmissing /data/openclaw-memory\nmissing /models/embeddings/Qwen3-Embedding-0.6B\nmissing /backup/openclaw-memory\nmissing /archive/openclaw-memory"}],"details":{"status":"completed","exitCode":0,"durationMs":205,"aggregated":"=== Runtime/tools ===\nPRETTY_NAME=\"Debian GNU/Linux 13 (trixie)\"\nNAME=\"Debian GNU/Linux\"\nVERSION_ID=\"13\"\nVERSION=\"13 (trixie)\"\nVERSION_CODENAME=trixie\nDEBIAN_VERSION_FULL=13.4\nID=debian\nHOME_URL=\"https://www.debian.org/\"\n\nDocker: Docker version 29.4.2, build 055a478\nPodman: Node: v24.15.0\nnpm: 11.12.1\nPython: Python 3.13.5\n\n=== Containers ===\nNAMES IMAGE STATUS PORTS\n\n=== GPU ===\nNVIDIA GeForce GTX 1080 Ti, 11264, 9021, 2144\n56402, /usr/local/bin/llama-server, 9016\n\n=== Storage ===\nFilesystem Size Used Avail Use% Mounted on\n/dev/nvme0n1p2 221G 29G 182G 14% /\n/dev/md0 1.5T 21M 1.4T 1% /data\n/dev/sdd1 458G 2.1M 435G 1% /models\n/dev/sdb1 1.8T 3.2M 1.7T 1% /backup\n/dev/sde1 1.8T 4.2G 1.7T 1% /archive\n\n=== Existing target paths ===\nmissing /data/openclaw-memory\nmissing /models/embeddings/Qwen3-Embedding-0.6B\nmissing /backup/openclaw-memory\nmissing /archive/openclaw-memory","cwd":"/home/rurouni"},"isError":false,"timestamp":1777857052618}} {"type":"message","id":"476dbbf9","parentId":"87ae52f0","timestamp":"2026-05-04T01:10:52.620Z","message":{"role":"toolResult","toolCallId":"call_y8pkwcjL49TFgAVvttDCpHrp|fc_02b86be3bb6b669e0169f7f21268c4819682f1638d1bdb65c1","toolName":"exec","content":[{"type":"text","text":"=== Installed commands ===\nqmd: mem0: qdrant: uvicorn: huggingface-cli: /home/rurouni/.local/bin/huggingface-cli\n\n=== Python packages current ===\nmem0 False\nqdrant_client False\nsentence_transformers False\ntorch False\nfastapi False\nuvicorn False\nhuggingface_hub True\n\n=== npm versions pinned candidates ===\n 2.1.0\n 0.9.3"}],"details":{"status":"completed","exitCode":0,"durationMs":1102,"aggregated":"=== Installed commands ===\nqmd: mem0: qdrant: uvicorn: huggingface-cli: /home/rurouni/.local/bin/huggingface-cli\n\n=== Python packages current ===\nmem0 False\nqdrant_client False\nsentence_transformers False\ntorch False\nfastapi False\nuvicorn False\nhuggingface_hub True\n\n=== npm versions pinned candidates ===\n 2.1.0\n 0.9.3","cwd":"/home/rurouni"},"isError":false,"timestamp":1777857052619}} {"type":"message","id":"cf60a0fd","parentId":"476dbbf9","timestamp":"2026-05-04T01:10:54.571Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"id\":\"rs_02b86be3bb6b669e0169f7f21dce5081969233b45c93317b8d\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABp9_IebbkdgcZ5znHkYqtZjsjASWoSI9H69JpeLxHYDDW9RdyZm8bEyH5dBPkjhRFPhmJlTPG05zNS_ekvHQEWjK0mu1dM7MfaotoCFycUeV30s4AS3sTa8Nt-sh4H3SltRB1-7Qx6cdLWCqL7_f3Dfg-GX0iwoxAPARpTT_dGqysIFP-31fa-wOFEzNWpnYqPH4-vXpePGhzRTtJKTEeMu_RZmUL5fxhFElie20TcTG6x6OE7qDNx3MoDp-DJV6gg83XxYN303nnGhejjOfxqRkLe8-UIeGklFqPjW3wkD9tCHzctqyRRwly2Q9Uvtb4dLzBB4P9PXR4yMPsrHmnRJ6WgOs8Z5caToUL0KbdMnGHpCSX-D-isGEHoVuUzjDQ-ZvpVuWG7cKijIa8dijwj34x2U4C3Iiuyf8yJAyjM4hnuCShgJiL9slzDQOhhBQbz9vVjHlhWbg0unVDDhH2BZVYiLNxuXeUTJwZMkERis3Fukw1nGTvyFO6dkv4GiYU5vhBr-hXn07jPvC6fsUnlcEBrgMYkS2VRRinQzOzfCUZx0Z-XIAMFbVzfkUARY241vbOJam_tdmcfrEpINpsK4wOo66C2MIzv-02pa8UzXOKSJmEJB5SHHes58Qtlxl4ofs56oreTf6AfHP8Z5aIt7Bqj4x6ZlIISsSfwpBT1JIs1reMy3zRiS4RoBVhMwd3eIigE95V7Z_WUFMkT9r0u0Up-f13U_zqvWtKr5MBUa-sJx3iwX_1qG0W_f_OJHp2LRhLCzo693uj5OIZZ3K-Ik8T2Un7_SDSbF0Pizmlm469PdxdQ_WyWH98dsDpU5ToJpEQVw9_Em3zJ830yAaVEIGtmDjjWuJF2LT74YioI1rKRQsWgrUL7tKqDjGe0BmIehKmIRjPPzoIznAlu6dnP19qK7yRW2153wGHUJuCIYLgxfraHjwlr4oEmKHT6ptu86jUx\",\"summary\":[]}"},{"type":"toolCall","id":"call_8dLtbPGBX4d01gncbVnycLOf|fc_02b86be3bb6b669e0169f7f21e12748196ae30f073c2b2c0ce","name":"process","arguments":{"action":"poll","sessionId":"faint-comet","timeout":30000,"limit":12000}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.5","usage":{"input":2369,"output":46,"cacheRead":39936,"cacheWrite":0,"totalTokens":42351,"cost":{"input":0.011845000000000001,"output":0.00138,"cacheRead":0.019968,"cacheWrite":0,"total":0.033193}},"stopReason":"toolUse","timestamp":1777857052624,"responseId":"resp_02b86be3bb6b669e0169f7f21cf1948196acc4f59a41169479"}} {"type":"message","id":"f1f3847a","parentId":"cf60a0fd","timestamp":"2026-05-04T01:11:03.838Z","message":{"role":"toolResult","toolCallId":"call_8dLtbPGBX4d01gncbVnycLOf|fc_02b86be3bb6b669e0169f7f21e12748196ae30f073c2b2c0ce","toolName":"process","content":[{"type":"text","text":"=== OpenClaw ===\n/usr/bin/openclaw\nOpenClaw 2026.5.2 (8b2a6e5)\nService: systemd (enabled)\nFile logs: /tmp/openclaw-1000/openclaw-2026-05-03.log\nCommand: /usr/bin/node /usr/lib/node_modules/openclaw/dist/index.js gateway --port 18789\nService file: ~/.config/systemd/user/openclaw-gateway.service\nService env: OPENCLAW_GATEWAY_PORT=18789\n\nConfig (cli): ~/.openclaw/openclaw.json\nConfig (service): ~/.openclaw/openclaw.json\n\nGateway: bind=lan (0.0.0.0), port=18789 (service args)\nProbe target: ws://127.0.0.1:18789\nDashboard: http://192.168.1.50:18789/\nProbe note: bind=lan listens on 0.0.0.0 (all interfaces); probing via 127.0.0.1.\n\nRuntime: running (pid 57453, state active, sub running, last exit 0, reason 0)\nConnectivity probe: ok\nCapability: admin-capable\n\nListening: *:18789\nTroubles: run openclaw status\nTroubleshooting: https://docs.openclaw.ai/troubleshooting\n\n=== Config paths ===\n1045 2026-05-03 16:41 /home/rurouni/.openclaw/logs/config-health.json\n11280 2026-05-03 16:28 /home/rurouni/.openclaw/openclaw.json\n115407 2026-05-03 02:21 /home/rurouni/.openclaw/plugins/installs.json\n120 2026-05-03 01:03 /home/rurouni/.openclaw/workspace-state.json\n172032 2026-05-03 18:10 /home/rurouni/.openclaw/memory/main.sqlite\n179 2026-05-03 18:10 /home/rurouni/.openclaw/exec-approvals.json\n2 2026-05-03 00:34 /home/rurouni/.openclaw/devices/pending.json\n2242 2026-05-03 18:10 /home/rurouni/.openclaw/devices/paired.json\n348 2026-05-03 00:13 /home/rurouni/.openclaw/tui/last-session.json\n37 2026-05-02 20:23 /home/rurouni/.openclaw/credentials/telegram-pairing.json\n37 2026-05-02 23:33 /home/rurouni/.openclaw/credentials/https-pairing.json\n37 2026-05-02 23:35 /home/rurouni/.openclaw/credentials/web-pairing.json\n4096 2026-05-02 21:38 /home/rurouni/.openclaw/flows/registry.sqlite\n416 2026-05-03 00:27 /home/rurouni/.openclaw/identity/device.json\n428 2026-05-03 18:10 /home/rurouni/.openclaw/identity/device-auth.json\n49 2026-05-02 19:42 /home/rurouni/.openclaw/update-check.json\n53248 2026-05-02 20:12 /home/rurouni/.openclaw/tasks/runs.sqlite\n58 2026-05-02 20:23 /home/rurouni/.openclaw/credentials/telegram-default-allowFrom.json\n73 2026-05-03 18:06 /home/rurouni/.openclaw/telegram/update-offset-default.json\n\n=== Memory status deep ===\nMemory Search (main)\nProvider: none (requested: auto)\nModel: none\nSources: memory\nIndexed: 5/5 files · 16 chunks\nDirty: no\nStore: ~/.openclaw/memory/main.sqlite\nWorkspace: ~\nDreaming: off\nEmbeddings: unavailable\nEmbeddings error: No GitHub token available for Copilot embedding provider\n\nNo API key found for provider \"openai\". You are authenticated with OpenAI Codex OAuth. Use openai-codex/gpt-5.5, or set OPENAI_API_KEY for direct OpenAI API access.\n\nNo API key found for provider \"google\". Auth store: /home/rurouni/.openclaw/agents/main/agent/auth-profiles.json (agentDir: /home/rurouni/.openclaw/agents/main/agent). Configure auth for this agent (openclaw agents add ) or copy only portable static auth profiles from the main agentDir.\n\nNo API key found for provider \"voyage\". Auth store: /home/rurouni/.openclaw/agents/main/agent/auth-profiles.json (agentDir: /home/rurouni/.openclaw/agents/main/agent). Configure auth for this agent (openclaw agents add ) or copy only portable static auth profiles from the main agentDir.\n\nNo API key found for provider \"mistral\". Auth store: /home/rurouni/.openclaw/agents/main/agent/auth-profiles.json (agentDir: /home/rurouni/.openclaw/agents/main/agent). Configure auth for this agent (openclaw agents add ) or copy only portable static auth profiles from the main agentDir.\n\nNo API key found for provider \"deepinfra\". Auth store: /home/rurouni/.openclaw/agents/main/agent/auth-profiles.json (agentDir: /home/rurouni/.openclaw/agents/main/agent). Configure auth for this agent (openclaw agents add ) or copy only portable static auth profiles from the main agentDir.\n\nNo API key found for provider \"bedrock\". AWS credentials are not available. Set AWS_ACCESS_KEY_ID/AWS_SECRET_ACCESS_KEY, AWS_PROFILE, or AWS_BEARER_TOKEN_BEDROCK, configure an EC2/ECS/EKS role, or set agents.defaults.memorySearch.provider to another provider.\nBy source:\n memory · 5/5 files · 16 chunks\nVector: unknown\nFTS: ready\nEmbedding cache: enabled (0 entries)\nBatch: disabled (failures 0/2)\nRecall store: 30 entries · 0 promoted · 30 concept-tagged · 0 spaced · scripts=30 latin\nRecall path: ~/memory/.dreams/short-term-recall.json\nRecall updated: 2026-05-04T01:09:29.819Z\nDreaming artifacts: diary absent · 0 corpus files · ingestion state absent\nDream corpus: ~/memory/.dreams/session-corpus\nDream ingestion: ~/memory/.dreams/session-ingestion.json\n\n\n=== Plugins relevant ===\n│ Active │ active- │ openclaw │ disabled │ stock:active-memory/index.js │ │\n│ Memory │ memory │ │ │ Runs a bounded blocking memory sub-agent before eligible │ │\n│ │ │ │ │ conversational replies and injects relevant memory into │ │\n│ │ │ │ │ prompt context. │ │\n│ @openclaw/ │ memory- │ openclaw │ enabled │ stock:memory-core/index.js │ 2026.5.2 │\n│ memory-core │ core │ │ │ │ │\n│ Memory Wiki │ memory- │ openclaw │ disabled │ stock:memory-wiki/index.js │ 2026.5.2 │\n\n=== Redacted config summary ===\n{\n \"plugins\": {\n \"entries\": {\n \"telegram\": {\n \"enabled\": true\n },\n \"openrouter\": {\n \"enabled\": true\n },\n \"duckduckgo\": {\n \"enabled\": true\n },\n \"bonjour\": {\n \"enabled\": false\n },\n \"browser\": {\n \"enabled\": true\n },\n \"device-pair\": {\n \"enabled\": false\n },\n \"phone-control\": {\n \"enabled\": false\n },\n \"talk-voice\": {\n \"enabled\": false\n },\n \"file-transfer\": {\n \"enabled\": false\n },\n \"openai\": {\n \"enabled\": true\n },\n \"deepseek\": {\n \"enabled\": true\n }\n }\n },\n \"agents\": {\n \"defaults\": {\n \"workspace\": \"/home/rurouni\",\n \"model\": {\n \"primary\": \"openai-codex/gpt-5.5\",\n \"fallbacks\": [\n \"deepseek/deepseek-v4-pro\",\n \"openrouter/minimax/minimax-m2.7\",\n \"local-qwen/qwen3.5-9b\"\n ]\n },\n \"models\": {\n \"openrouter/minimax/minimax-m2.7\": {\n \"alias\": \"MiniMax\"\n },\n \"openai-codex/gpt-5.5\": {},\n \"local-qwen/qwen3.5-9b\": {\n \"alias\": \"local\",\n \"params\": {\n \"temperature\": 0.6,\n \"top_p\": 0.95,\n \"top_k\": 20\n }\n },\n \"deepseek/deepseek-v4-pro\": {}\n },\n \"contextTokens\": \"\",\n \"compaction\": {\n \"reserveTokensFloor\": \"\",\n \"truncateAfterCompaction\": true,\n \"maxActiveTranscriptBytes\": 1000000,\n \"notifyUser\": true,\n \"memoryFlush\": {\n \"enabled\": true,\n \"softThresholdTokens\": \"\"\n }\n },\n \"contextInjection\": \"continuation-skip\",\n \"experimental\": {\n \"localModelLean\": true\n },\n \"thinkingDefault\": \"off\",\n \"verboseDefault\": \"off\",\n \"blockStreamingDefault\": \"on\",\n \"heartbeat\": {\n \"every\": \"30m\",\n \"isolatedSession\": true,\n \"lightContext\": true,\n \"activeHours\": {\n \"start\": \"07:00\",\n \"end\": \"23:00\"\n },\n \"model\": \"local-qwen/qwen3.5-9b\"\n },\n \"subagents\": {\n \"model\": \"local-qwen/qwen3.5-9b\"\n }\n }\n },\n \"models\": {\n \"providers\": {\n \"local-qwen\": {\n \"api\": \"openai-completions\",\n \"baseUrl\": \"http://127.0.0.1:8081/v1\",\n \"models\": [\n {\n \"id\": \"qwen3.5-9b\",\n \"name\": \"Qwen3.5-9B Local\",\n \"contextWindow\": 65536,\n \"maxTokens\": \"\",\n \"reasoning\": false,\n \"input\": [\n \"text\"\n ],\n \"cost\": {\n \"input\": 0,\n \"output\": 0,\n \"cacheRead\": 0,\n \"cacheWrite\": 0\n }\n }\n ],\n \"apiKey\": \"***\"\n },\n \"deepseek\": {\n \"api\": \"openai-completions\",\n \"baseUrl\": \"https://api.deepseek.com\",\n \"models\": [\n {\n \"id\": \"deepseek-v4-flash\",\n \"name\": \"DeepSeek V4 Flash\",\n \"reasoning\": true,\n \"input\": [\n \"text\"\n ],\n \"cost\": {\n \"input\": 0.14,\n \"output\": 0.28,\n \"cacheRead\": 0.028,\n \"cacheWrite\": 0\n },\n \"contextWindow\": 1000000,\n \"maxTokens\": \"\",\n \"compat\": {\n \"supportsReasoningEffort\": true,\n \"supportsUsageInStreaming\": true,\n \"maxTokensField\": \"\"\n },\n \"api\": \"openai-completions\"\n },\n {\n \"id\": \"deepseek-v4-pro\",\n \"name\": \"DeepSeek V4 Pro\",\n \"reasoning\": true,\n \"input\": [\n \"text\"\n ],\n \"cost\": {\n \"input\": 1.74,\n \"output\": 3.48,\n \"cacheRead\": 0.145,\n \"cacheWrite\": 0\n },\n \"contextWindow\": 1000000,\n \"maxTokens\": \"\",\n \"compat\": {\n \"supportsReasoningEffort\": true,\n \"supportsUsageInStreaming\": true,\n \"maxTokensField\": \"\"\n },\n \"api\": \"openai-completions\"\n },\n {\n \"id\": \"deepseek-chat\",\n \"name\": \"DeepSeek Chat\",\n \"reasoning\": false,\n \"input\": [\n \"text\"\n ],\n \"cost\": {\n \"input\": 0.28,\n \"output\": 0.42,\n \"cacheRead\": 0.028,\n \"cacheWrite\": 0\n },\n \"contextWindow\": 131072,\n \"maxTokens\": \"\",\n \"compat\": {\n \"supportsUsageInStreaming\": true,\n \"maxTokensField\": \"\"\n },\n \"api\": \"openai-completions\"\n },\n {\n \"id\": \"deepseek-reasoner\",\n \"name\": \"DeepSeek Reasoner\",\n \"reasoning\": true,\n \"input\": [\n \"text\"\n ],\n \"cost\": {\n \"input\": 0.28,\n \"output\": 0.42,\n \"cacheRead\": 0.028,\n \"cacheWrite\": 0\n },\n \"contextWindow\": 131072,\n \"maxTokens\": \"\",\n \"compat\": {\n \"supportsReasoningEffort\": false,\n \"supportsUsageInStreaming\": true,\n \"maxTokensField\": \"\"\n },\n \"api\": \"openai-completions\"\n }\n ],\n \"apiKey\": \"***\"\n }\n }\n }\n}\n\nProcess exited with code 0."}],"details":{"persistedDetailsTruncated":true,"originalDetailsBytesAtLeast":8193,"originalDetailKeys":["status","sessionId","exitCode","aggregated","name"],"status":"completed","sessionId":"faint-comet","name":"set pipefail","exitCode":0},"isError":false,"timestamp":1777857063837}} 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/home/rurouni/memory \"$BACKUP/workspace/memory\" 2>/dev/null || true\nsystemctl --user cat openclaw-gateway.service > \"$BACKUP/system/openclaw-gateway.service.txt\" 2>&1 || true\nopenclaw gateway status > \"$BACKUP/system/openclaw-gateway-status.txt\" 2>&1 || true\nsha256sum /home/rurouni/.openclaw/openclaw.json > \"$BACKUP/SHA256SUMS.txt\" 2>/dev/null || true\nln -sfn \"$BACKUP\" /backup/openclaw-memory/latest-pre-memory-stack\nprintf '%s\\n' \"$BACKUP\"","workdir":"/home/rurouni","yieldMs":10000,"timeout":60}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.5","usage":{"input":887,"output":444,"cacheRead":46080,"cacheWrite":0,"totalTokens":47411,"cost":{"input":0.004435000000000001,"output":0.01332,"cacheRead":0.023039999999999998,"cacheWrite":0,"total":0.040795}},"stopReason":"toolUse","timestamp":1777857085098,"responseId":"resp_02b86be3bb6b669e0169f7f23d633c8196bf78c56c5daa9729"}} {"type":"message","id":"524b78e0","parentId":"49af7b92","timestamp":"2026-05-04T01:11:33.852Z","message":{"role":"toolResult","toolCallId":"call_4K0nbGWrkIHQ3owF2sXIrJSQ|fc_02b86be3bb6b669e0169f7f23fef3c8196a5f42a174fffedeb","toolName":"exec","content":[{"type":"text","text":"sudo: a terminal is required to read the password; either use the -S option to read from standard input or configure an askpass helper\nsudo: a password is required\n\n(Command exited with code 1)"}],"details":{"status":"completed","exitCode":1,"durationMs":65,"aggregated":"sudo: a terminal is required to read the password; either use the -S option to read from standard input or configure an askpass helper\nsudo: a password is required\n\n(Command exited with code 1)","cwd":"/home/rurouni"},"isError":false,"timestamp":1777857093852}} {"type":"message","id":"ca42d4d8","parentId":"524b78e0","timestamp":"2026-05-04T01:11:47.291Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"id\":\"rs_02b86be3bb6b669e0169f7f24a12508196a76d39bb5258f180\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABp9_JKDWXdFo4q5btvD_jCZKE8yY1pR9QpUZvpccqjzRYPMcgl7D_iXVDT_9nMo5S8ulyWlLGS-pMHsaIWNNIAAWG7Qa9a-7hYgZxgMRCtk59Qer55tHGHmh8efX92peIkFtvnaFFygnW6l9M1VokPbMo0Sa4CKGo4y342DpkLHwuCug3HF7k4M6AEAezLYXc2H3vGhCcqb94qm4U00vrNYUaXf9zozYdKrFewdoU_aWHOEBUBoQsHkkJp_QZT2GO23KOaaU_sEOmYS0sb0_k34A7WEk869NRI_ya6clu7AY4B9U3BIqMrnXqRpLGTRZsTe0rIMI-qIdrwD4rRNAWmx52B9hAWeqkI5eTFrC-nkIYh7x5w-ZBuadSwPbymu6S6Y3JVlthfnsPVROU69nAlUmeylUUjBsg6PgvAKF2sAZNiWr574eDUKr5u0vueNfUdWCJRA0Hp1zl1YbdTaxbyHPO3019_OMceikji9I_UzKO2VvQF2-iC1P69GO9DACDYhUtDr2ilKcRj4LvVcEmKh3JPORqr_iEQqWLp_zmqd6GiQfDlhrns50QP_gvw69cGuz-MXJphDsnWCS5zx9LJUoF2W033n82VrKPiC9PI0zfxHl37IDxgp7J1x0UoujobcsRpuL8JpdpSbU5aLYKsdG9MYWqvj3Me7v0eXF_Rpl1Xj5Md6Qaryoj46rPJBZnm2jQKv1qRwQziIQmMvMvsHsPQExjWlrslbYXdJHFRluXmd-trbkrn9vyZ5gr1aPZBtM00ngl1YJSYn2EK-xCiIaqBRQqKLL1-CyHZzzbbri9wQh4QfqDZt0fYHl6LO-0KytqTHIlCAbSkifFtwjMV88BNFuNe-8LmMteT2i5-Qt6ZpbOusNkVamkrhxr3vo3aUDW5H0RbgJmV1V6HG-WJAEq-f3Er2FE5eeAZPOT-Ztk9wy8NnU57-D4t8oi3wva-3sqxtMsa1-uMTTIE1pEVUKzGFA==\",\"summary\":[]}"},{"type":"toolCall","id":"call_DUbEfMud9qG9rtuonsISr7lk|fc_02b86be3bb6b669e0169f7f24a7748819684b691ee2c276a76","name":"exec","arguments":{"command":"set -euo pipefail\nmkdir -p /backup/openclaw-memory/test-write && rmdir /backup/openclaw-memory/test-write\nTS=$(date +%Y%m%d-%H%M%S)\nBACKUP=/backup/openclaw-memory/pre-memory-stack-$TS\nmkdir -p \"$BACKUP\"/{openclaw,workspace,system}\ncp -a /home/rurouni/.openclaw/openclaw.json \"$BACKUP/openclaw/\" 2>/dev/null || true\ncp -a /home/rurouni/.openclaw/plugins \"$BACKUP/openclaw/plugins\" 2>/dev/null || true\ncp -a /home/rurouni/.openclaw/memory \"$BACKUP/openclaw/memory\" 2>/dev/null || true\ncp -a /home/rurouni/MEMORY.md /home/rurouni/AGENTS.md /home/rurouni/SOUL.md /home/rurouni/USER.md /home/rurouni/IDENTITY.md /home/rurouni/HEARTBEAT.md \"$BACKUP/workspace/\" 2>/dev/null || true\ncp -a /home/rurouni/memory \"$BACKUP/workspace/memory\" 2>/dev/null || true\nsystemctl --user cat openclaw-gateway.service > \"$BACKUP/system/openclaw-gateway.service.txt\" 2>&1 || true\nopenclaw gateway status > \"$BACKUP/system/openclaw-gateway-status.txt\" 2>&1 || true\nsha256sum /home/rurouni/.openclaw/openclaw.json > \"$BACKUP/SHA256SUMS.txt\" 2>/dev/null || true\nln -sfn \"$BACKUP\" /backup/openclaw-memory/latest-pre-memory-stack\nprintf '%s\\n' \"$BACKUP\"","workdir":"/home/rurouni","yieldMs":10000,"timeout":60}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.5","usage":{"input":872,"output":452,"cacheRead":46592,"cacheWrite":0,"totalTokens":47916,"cost":{"input":0.00436,"output":0.013560000000000001,"cacheRead":0.023295999999999997,"cacheWrite":0,"total":0.041216}},"stopReason":"toolUse","timestamp":1777857093856,"responseId":"resp_02b86be3bb6b669e0169f7f246fbdc8196a99253e83d90db72"}} {"type":"message","id":"420e8470","parentId":"ca42d4d8","timestamp":"2026-05-04T01:11:47.322Z","message":{"role":"toolResult","toolCallId":"call_DUbEfMud9qG9rtuonsISr7lk|fc_02b86be3bb6b669e0169f7f24a7748819684b691ee2c276a76","toolName":"exec","content":[{"type":"text","text":"mkdir: cannot create directory ‘/backup/openclaw-memory’: Permission denied\nmkdir: cannot create directory ‘/backup/openclaw-memory’: Permission denied\nmkdir: cannot create directory ‘/backup/openclaw-memory’: Permission denied\nmkdir: cannot create directory ‘/backup/openclaw-memory’: Permission denied\n\n(Command exited with code 1)"}],"details":{"status":"completed","exitCode":1,"durationMs":20,"aggregated":"mkdir: cannot create directory ‘/backup/openclaw-memory’: Permission denied\nmkdir: cannot create directory ‘/backup/openclaw-memory’: Permission denied\nmkdir: cannot create directory ‘/backup/openclaw-memory’: Permission denied\nmkdir: cannot create directory ‘/backup/openclaw-memory’: Permission denied\n\n(Command exited with code 1)","cwd":"/home/rurouni"},"isError":false,"timestamp":1777857107321}} {"type":"message","id":"150be673","parentId":"420e8470","timestamp":"2026-05-04T01:11:53.629Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"id\":\"rs_02b86be3bb6b669e0169f7f255e5a881969d10fb1b41860643\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABp9_JWy6YhlAi0vYZkf5J0wnyzGSO8iAkBG8fjfodspqqIH07hFM2wvFYjFGbe_e2ABaF_f-i3bleqFTTK8Zjc7JAQt4G8d_PQzmZh8sgfazedlTkg8bsOqLAyam7Wo1qaM7pKvfVu8xYySguTgStoNcY5yekNtDc4UgL2SdRKPa91oRdL1hnMpJz8NasGLCWg4VAWesjIHfRGrmA6xPb15Ln_IMGZsw6lOgmmSWUnjFpgNa3JjyDITun1qCaPJ86beORiBhOUWKckW6OFEB7KW5uO2ipnWjPYqT7aE7nDMUpcry7L2Xr4PveA1W-U_oFE00pfT3Txh8ssC17Alkhs6sBveB6jHe6bvcF2lkm3zV0UCXKXbulnJNq5i5Ip3Jku32fu9jRXqR3jwEvXAeHx3_zwvjFnF4xrPxS_eTXh4ICQw1l_3n0MHbz6mtgSlSTdFGsC51J82Hjjhg8RZ_K-Me5_SM5dE1jkj7kWqbRcEal0l9v8b48kjOOULQfowPZjyJ2RG2SXeWrGgidgGnX7l9KWXV3Q1YBQCCzkhkcTLsF6kPzVpFn4lybWeCDTppu3trwin1cWdikZetMvc7VOoWVSQQaBjqb6xtwNLV-prpJOpteZQrky924-jr1hysuJNirg6Hur1hy1ZpfvjPm4XORwbYbtUaSBDKus21GoCYiLb7nEi66FC-9OjxciANi6PdE722b1SkXA7O7fCn4KUJVbsYuj7j7bdVs0GcjLWthYKnmSxzoIOAe7g0p6vPRua_ca4qx6IQ50i-99ltoKndiDsdvNHlFnDXfTr1DqY34FcD5DP95Uzquw9hOR7Q4VzxGyLSNS7OWbzUQFRcAyMR4U2tPIRA-watFKtgVi5Ta8IFq1GPZKoHKjs8WXMhZwGpIThnpWFyFU6qYnF3ijF9FVIZsiV2ktHWyeqbc7KLLEmjYuXTucNJBZ4Ye8kyurc4TiPza1-DbeoQJPix-jcGxElNMNAYYnrz3cyYfO1ghqxxs=\",\"summary\":[]}"},{"type":"toolCall","id":"call_812PjGHFJEhnLpqGAKvbaInB|fc_02b86be3bb6b669e0169f7f2563d808196b7fa084c2ca16e39","name":"exec","arguments":{"command":"set -euo pipefail\nTS=$(date +%Y%m%d-%H%M%S)\nBACKUP=/backup/openclaw-memory/pre-memory-stack-$TS\nmkdir -p \"$BACKUP\"/{openclaw,workspace,system}\nchown -R rurouni:rurouni /backup/openclaw-memory\ncp -a /home/rurouni/.openclaw/openclaw.json \"$BACKUP/openclaw/\" 2>/dev/null || true\ncp -a /home/rurouni/.openclaw/plugins \"$BACKUP/openclaw/plugins\" 2>/dev/null || true\ncp -a /home/rurouni/.openclaw/memory \"$BACKUP/openclaw/memory\" 2>/dev/null || true\ncp -a /home/rurouni/MEMORY.md /home/rurouni/AGENTS.md /home/rurouni/SOUL.md /home/rurouni/USER.md /home/rurouni/IDENTITY.md /home/rurouni/HEARTBEAT.md \"$BACKUP/workspace/\" 2>/dev/null || true\ncp -a /home/rurouni/memory \"$BACKUP/workspace/memory\" 2>/dev/null || true\nsystemctl --user cat openclaw-gateway.service > \"$BACKUP/system/openclaw-gateway.service.txt\" 2>&1 || true\nopenclaw gateway status > \"$BACKUP/system/openclaw-gateway-status.txt\" 2>&1 || true\nsha256sum /home/rurouni/.openclaw/openclaw.json > \"$BACKUP/SHA256SUMS.txt\" 2>/dev/null || true\nln -sfn \"$BACKUP\" /backup/openclaw-memory/latest-pre-memory-stack\nprintf '%s\\n' \"$BACKUP\"","workdir":"/home/rurouni","yieldMs":10000,"timeout":60,"elevated":true}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.5","usage":{"input":893,"output":455,"cacheRead":47104,"cacheWrite":0,"totalTokens":48452,"cost":{"input":0.004465,"output":0.01365,"cacheRead":0.023552,"cacheWrite":0,"total":0.041666999999999996}},"stopReason":"toolUse","timestamp":1777857107326,"responseId":"resp_02b86be3bb6b669e0169f7f253a4b88196b00b01ac802a0adc"}} {"type":"message","id":"e17539a5","parentId":"150be673","timestamp":"2026-05-04T01:11:53.660Z","message":{"role":"toolResult","toolCallId":"call_812PjGHFJEhnLpqGAKvbaInB|fc_02b86be3bb6b669e0169f7f2563d808196b7fa084c2ca16e39","toolName":"exec","content":[{"type":"text","text":"mkdir: cannot create directory ‘/backup/openclaw-memory’: Permission denied\nmkdir: cannot create directory ‘/backup/openclaw-memory’: Permission denied\nmkdir: cannot create directory ‘/backup/openclaw-memory’: Permission denied\n\n(Command exited with code 1)"}],"details":{"status":"completed","exitCode":1,"durationMs":18,"aggregated":"mkdir: cannot create directory ‘/backup/openclaw-memory’: Permission denied\nmkdir: cannot create directory ‘/backup/openclaw-memory’: Permission denied\nmkdir: cannot create directory ‘/backup/openclaw-memory’: Permission denied\n\n(Command exited with code 1)","cwd":"/home/rurouni"},"isError":false,"timestamp":1777857113660}} {"type":"message","id":"5bc83caf","parentId":"e17539a5","timestamp":"2026-05-04T01:11:59.567Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"id\":\"rs_02b86be3bb6b669e0169f7f25ce0588196a0a71232a02a4ca8\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABp9_Jeu8xOsnNVKegrwhwuz0QOMxEnbG7PSt4a0heWrhec5JdbfE2wGfrjmkB2xjiO8K8li_xoFWeZpGqZfI_rENl54pEgzHL8qRrZtUDbaQeksuvpkVgn6Er0oCmxYuKmUFUFLjPxy0WicbOw4Ihlb5JrAO4ohVbnVd6sCsCi3pacCSVQkNCkouZaOTZbCgIAY-tArOigvjs7Yw8r_Qi9Wu3NLs7AgZTGiWKzh-fNs90G6AHZCrmTqsOVEXiw-C2e3R-Lmvu9FO6n4b1Pyy5TQdq8NEzhr8k7lulNDbgeA5bYkWC7LPntE5L6fZDoyRTwz280ACVZwLWiDJTC8zUyHVmYVYNKuPFyr6SJQOnSxthrnK6q_NOC4bqpSVskNFks5FF5kXuZnvgGXxQxZcU9lI2os6EC2W_OpSHtXgKPGTEzCOmmFlTVMePdm4771GgnWmHfBgT4owUC5-19nFEtoF21FmUuiUTudYS5mTHiAdNuVgAx8-12PJ7ZmdMw_2qVW1LmWVyEauUhAdUrABpgJkdsRUCf74LseHZaRSYpDyijuQ7EnKfD8dnZSLbxUcgIFHkUoJNqB0h9YlgZXfxwJ3rhqR6WmX05-GGzIQf5w5ptqJKTFRmSRTxAvy_LqHWDePdHYBIgE4lAW7347PC-AVP2WXpufxmv-4WEagm1qzfxM4Q1mRlOf6fBsNJy1uHSuW0CSRD4KPsOEtLJB4IbY6tP5L-eZTk3ie4s6HWK52A0JbuyJezT6pmqq1Eo0RPBnFeCzJ27ioFhyaxpLCpMEhJ3ROTaLIDdjUXD4sY7bflxKua3EdTA6sABWkaFV2XPyexuTXuOYSMZ-yHFn2_PG_MA3dyLvK-biMDwJFRogqIE951pS3fk1NVLWVJKQB4NVk0AlX9StsOgsFKh0F1x7Q50JslTw8ixZJEVHg9CHcM7k1E3FPK0NVyaxFN8656NqepUKlkTVGrPKyhkONVPhzswm_Pga2v9FfPjJAMQSIaNUuxsFwL2yXU4hgw9l4LBGVeYk93bqvmM2EBJ01XVzpQDIdr1Kl-2JbeVUf2p5hLw9cshOBXlbPmQnuOQHjiNbocavqoKTOeowKMPSJf7wgNI-kzouqCTdXnHUvSwF1x1UDiCzSLUUWDBo07QiWDkrON1ZC37TW6o2eaoN3G-riLM3jF7FGs5AnMXMOQJnk2vYFt0bLpGDI3V4OwXdMZWk0gV4jrsbax88B8g0v9_n-717KFQFQrtUT_qzybsbybklmGIsEdjnCo_ggVlikxNEHYp8HHvRrs90MNzH9aKX_d0m60K7APrqz9h-7Fgqv3752F_sZDZYtrIQuePuXpszI0G-Rcl5KTjUN4BtZZZiw3b1g==\",\"summary\":[]}"},{"type":"toolCall","id":"call_K6wcl9JbDrfI7WTCAkDwPFai|fc_02b86be3bb6b669e0169f7f25e51d4819685aea7672f18f0d5","name":"exec","arguments":{"command":"mkdir -p /backup/openclaw-memory /data/openclaw-memory /models/embeddings/Qwen3-Embedding-0.6B /archive/openclaw-memory && chown -R rurouni:rurouni /backup/openclaw-memory /data/openclaw-memory /models/embeddings /archive/openclaw-memory","workdir":"/home/rurouni","yieldMs":10000,"timeout":60,"elevated":true,"ask":"always"}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.5","usage":{"input":901,"output":194,"cacheRead":47616,"cacheWrite":0,"totalTokens":48711,"cost":{"input":0.004505,"output":0.0058200000000000005,"cacheRead":0.023808,"cacheWrite":0,"total":0.034133}},"stopReason":"toolUse","timestamp":1777857113665,"responseId":"resp_02b86be3bb6b669e0169f7f25a2abc8196b96abb88d33f152d"}} {"type":"message","id":"5b514ee4","parentId":"5bc83caf","timestamp":"2026-05-04T01:11:59.954Z","message":{"role":"toolResult","toolCallId":"call_K6wcl9JbDrfI7WTCAkDwPFai|fc_02b86be3bb6b669e0169f7f25e51d4819685aea7672f18f0d5","toolName":"exec","content":[{"type":"text","text":"Approval required (id 8371797d, full 8371797d-7e4c-4d2b-9846-72ad10c109de).\nHost: gateway\nCWD: /home/rurouni\nCommand:\n```sh\nmkdir -p /backup/openclaw-memory /data/openclaw-memory /models/embeddings/Qwen3-Embedding-0.6B /archive/openclaw-memory && chown -R rurouni:rurouni /backup/openclaw-memory /data/openclaw-memory /models/embeddings /archive/openclaw-memory\n```\nMode: foreground (interactive approvals available).\nBackground mode requires an effective policy that allows pre-approval (for example ask=off).\nReply with: /approve 8371797d allow-once|deny\nThe effective approval policy requires approval every time, so Allow Always is unavailable.\nIf the short code is ambiguous, use the full id in /approve."}],"details":{"status":"approval-pending","approvalId":"8371797d-7e4c-4d2b-9846-72ad10c109de","approvalSlug":"8371797d","expiresAtMs":1777858919923,"allowedDecisions":["allow-once","deny"],"host":"gateway","command":"mkdir -p /backup/openclaw-memory /data/openclaw-memory /models/embeddings/Qwen3-Embedding-0.6B /archive/openclaw-memory && chown -R rurouni:rurouni /backup/openclaw-memory /data/openclaw-memory /models/embeddings /archive/openclaw-memory","cwd":"/home/rurouni","warningText":""},"isError":false,"timestamp":1777857119954}} {"type":"message","id":"a59cdd56","parentId":"5b514ee4","timestamp":"2026-05-04T01:12:05.008Z","message":{"role":"assistant","content":[{"type":"text","text":"I’m blocked on root-owned storage paths.\n\nTo continue safely, please approve the permission setup card for:\n\n```sh\nmkdir -p /backup/openclaw-memory /data/openclaw-memory /models/embeddings/Qwen3-Embedding-0.6B /archive/openclaw-memory && chown -R rurouni:rurouni /backup/openclaw-memory /data/openclaw-memory /models/embeddings /archive/openclaw-memory\n```\n\nAfter that I’ll backup first, then continue the install/config.","textSignature":"{\"v\":1,\"id\":\"msg_02b86be3bb6b669e0169f7f262ae308196bea25e0ecad554f1\",\"phase\":\"final_answer\"}"}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.5","usage":{"input":795,"output":115,"cacheRead":48128,"cacheWrite":0,"totalTokens":49038,"cost":{"input":0.003975,"output":0.00345,"cacheRead":0.024064,"cacheWrite":0,"total":0.031488999999999996}},"stopReason":"stop","timestamp":1777857119956,"responseId":"resp_02b86be3bb6b669e0169f7f2604734819683faada75c53009c"}}