760 lines
117 KiB
JSON
760 lines
117 KiB
JSON
{
|
||
"session_id": "7f2d3130ad72",
|
||
"title": "Rose Memory Sync Nachtversion",
|
||
"workspace": "/Users/rose/.hermes",
|
||
"model": "@minimax:MiniMax-M2.7",
|
||
"messages": [
|
||
{
|
||
"role": "user",
|
||
"content": "Rose Memory Sync (Nightly) funktioniert das ? iste s funktions fähig und was macht es",
|
||
"timestamp": 1776371909
|
||
},
|
||
{
|
||
"role": "assistant",
|
||
"content": "Ich check das schnell.\n",
|
||
"tool_calls": [
|
||
{
|
||
"id": "call_function_fb8ydnzs6704_1",
|
||
"call_id": "call_function_fb8ydnzs6704_1",
|
||
"response_item_id": "fc_function_fb8ydnzs6704_1",
|
||
"type": "function",
|
||
"function": {
|
||
"name": "cronjob",
|
||
"arguments": "{\"action\": \"list\"}"
|
||
}
|
||
},
|
||
{
|
||
"id": "call_function_fb8ydnzs6704_2",
|
||
"call_id": "call_function_fb8ydnzs6704_2",
|
||
"response_item_id": "fc_function_fb8ydnzs6704_2",
|
||
"type": "function",
|
||
"function": {
|
||
"name": "search_files",
|
||
"arguments": "{\"pattern\": \"rose-memory-chromadb-sync|memory.*sync|chromadb.*sync\", \"target\": \"content\", \"path\": \"/Users/rose/.hermes\", \"output_mode\": \"files_only\"}"
|
||
}
|
||
}
|
||
],
|
||
"timestamp": 1776371909
|
||
},
|
||
{
|
||
"role": "tool",
|
||
"content": "{\n \"success\": true,\n \"count\": 5,\n \"jobs\": [\n {\n \"job_id\": \"9de5e64d03ef\",\n \"name\": \"Memory Health Check\",\n \"skill\": null,\n \"skills\": [],\n \"prompt_preview\": \"Laufe_Memory_Health_Check\",\n \"model\": null,\n \"provider\": null,\n \"base_url\": null,\n \"schedule\": \"every 15m\",\n \"repeat\": \"forever\",\n \"deliver\": \"local\",\n \"next_run_at\": \"2026-04-16T15:17:20.064915+02:00\",\n \"last_run_at\": \"2026-04-16T15:02:20.064915+02:00\",\n \"last_status\": \"ok\",\n \"last_delivery_error\": null,\n \"enabled\": true,\n \"state\": \"scheduled\",\n \"paused_at\": null,\n \"paused_reason\": null,\n \"script\": \"memory_health_wrapper.py\"\n },\n {\n \"job_id\": \"15f90ee7af94\",\n \"name\": \"Analytics Daily Report\",\n \"skill\": null,\n \"skills\": [],\n \"prompt_preview\": \"Daily Analytics Report\",\n \"model\": null,\n \"provider\": null,\n \"base_url\": null,\n \"schedule\": \"0 9 * * *\",\n \"repeat\": \"forever\",\n \"deliver\": \"local\",\n \"next_run_at\": null,\n \"last_run_at\": \"2026-04-16T09:01:18.242577+02:00\",\n \"last_status\": \"ok\",\n \"last_delivery_error\": null,\n \"enabled\": true,\n \"state\": \"scheduled\",\n \"paused_at\": null,\n \"paused_reason\": null,\n \"script\": \"analytics_report.py\"\n },\n {\n \"job_id\": \"56b0be860bf8\",\n \"name\": \"Hermes Housekeeping\",\n \"skill\": null,\n \"skills\": [],\n \"prompt_preview\": \"Run the Hermes Housekeeping script: ~/.hermes/scripts/housekeeping.py\\nExecute: python3 ~/.hermes/scr...\",\n \"model\": null,\n \"provider\": null,\n \"base_url\": null,\n \"schedule\": \"every 15m\",\n \"repeat\": \"forever\",\n \"deliver\": \"local\",\n \"next_run_at\": \"2026-04-16T15:19:43.256364+02:00\",\n \"last_run_at\": \"2026-04-16T15:04:43.256364+02:00\",\n \"last_status\": \"ok\",\n \"last_delivery_error\": null,\n \"enabled\": true,\n \"state\": \"scheduled\",\n \"paused_at\": null,\n \"paused_reason\": null\n },\n {\n \"job_id\": \"ecd1da0f1d95\",\n \"name\": \"Rose Memory Sync (Nightly)\",\n \"skill\": \"hermes-housekeeping-maintenance\",\n \"skills\": [\n \"hermes-housekeeping-maintenance\"\n ],\n \"prompt_preview\": \"# Rose's Memory - Nightly Full-Flow Pipeline\\n\\nF\\u00fchre den kompletten Memory-Pipeline aus:\\n\\n## Schritt ...\",\n \"model\": null,\n \"provider\": null,\n \"base_url\": null,\n \"schedule\": \"0 2 * * *\",\n \"repeat\": \"999 times\",\n \"deliver\": \"telegram\",\n \"next_run_at\": \"2026-04-17T02:00:00+02:00\",\n \"last_run_at\": null,\n \"last_status\": null,\n \"last_delivery_error\": null,\n \"enabled\": true,\n \"state\": \"scheduled\",\n \"paused_at\": null,\n \"paused_reason\": null\n },\n {\n \"job_id\": \"90031c503f0b\",\n \"name\": \"hermes-housekeeping\",\n \"skill\": null,\n \"skills\": [],\n \"prompt_preview\": \"Run the Hermes housekeeping script to keep all services alive. Execute: python3 ~/.hermes/scripts/ho...\",\n \"model\": null,\n \"provider\": null,\n \"base_url\": null,\n \"schedule\": \"*/15 * * * *\",\n \"repeat\": \"forever\",\n \"deliver\": \"local\",\n \"next_run_at\": \"2026-04-16T15:30:00+02:00\",\n \"last_run_at\": \"2026-04-16T15:00:34.035954+02:00\",\n \"last_status\": \"ok\",\n \"last_delivery_error\": null,\n \"enabled\": true,\n \"state\": \"scheduled\",\n \"paused_at\": null,\n \"paused_reason\": null,\n \"script\": \"housekeeping.py\"\n }\n ]\n}",
|
||
"tool_call_id": "call_function_fb8ydnzs6704_1",
|
||
"timestamp": 1776371909
|
||
},
|
||
{
|
||
"role": "tool",
|
||
"content": "{\"total_count\": 50, \"files\": [\"/Users/rose/.hermes/cron/jobs.json\", \"/Users/rose/.hermes/sessions/session_cron_90031c503f0b_20260416_081551.json\", \"/Users/rose/.hermes/sessions/session_20260416_165318_1a751b.json\", \"/Users/rose/.hermes/sessions/session_4f5b77b3ce7e.json\", \"/Users/rose/.hermes/sessions/request_dump_20260416_131535_9d38a1_20260416_131536_735782.json\", \"/Users/rose/.hermes/sessions/session_cron_56b0be860bf8_20260416_140512.json\", \"/Users/rose/.hermes/sessions/session_20260416_101717_53925a.json\", \"/Users/rose/.hermes/sessions/session_20260416_125046_7c397c.json\", \"/Users/rose/.hermes/sessions/session_cron_90031c503f0b_20260416_083129.json\", \"/Users/rose/.hermes/sessions/session_20260416_163943_d75717.json\", \"/Users/rose/.hermes/sessions/session_20260416_163914_2d199b.json\", \"/Users/rose/.hermes/sessions-archive/session_20260414_184534_e262b9.json\", \"/Users/rose/.hermes/sessions/session_cron_56b0be860bf8_20260416_081031.json\", \"/Users/rose/.hermes/sessions/session_20260416_131542_c4953a21.json\", \"/Users/rose/.hermes/sessions/session_cron_90031c503f0b_20260416_150026.json\", \"/Users/rose/.hermes/sessions-archive/session_20260415_115041_c13be2.json\", \"/Users/rose/.hermes/sessions/session_3b85e2e5ea50.json\", \"/Users/rose/.hermes/sessions/session_cron_9de5e64d03ef_20260416_080821.json\", \"/Users/rose/.hermes/sessions-archive/session_cron_7adbbd79b6c0_20260414_165547.json\", \"/Users/rose/.hermes/sessions/session_bac18e5a0628.json\", \"/Users/rose/.hermes/sessions/session_20260416_150440_99437e.json\", \"/Users/rose/.hermes/sessions-archive/session_20260416_093031_7664e5.json\", \"/Users/rose/.hermes/sessions/request_dump_20260416_123403_71dc71_20260416_123404_990287.json\", \"/Users/rose/.hermes/sessions-archive/session_20260415_102315_fcdf51.json\", \"/Users/rose/.hermes/sessions/session_20260416_134253_136b61.json\", \"/Users/rose/.hermes/sessions/session_20260416_113858_99717e.json\", \"/Users/rose/.hermes/sessions/session_20260416_122345_bd6998.json\", \"/Users/rose/.hermes/sessions-archive/session_940e100e2d8c.json\", \"/Users/rose/.hermes/sessions/session_cron_ecd1da0f1d95_20260416_111713.json\", \"/Users/rose/.hermes/sessions/session_cron_90031c503f0b_20260416_134557.json\", \"/Users/rose/.hermes/sessions-archive/session_20260415_083207_fd6c43.json\", \"/Users/rose/.hermes/sessions/session_20260416_123134_58f5b3.json\", \"/Users/rose/.hermes/sessions-archive/session_20260415_192055_0f876f.json\", \"/Users/rose/.hermes/sessions/session_cron_90031c503f0b_20260416_093247.json\", \"/Users/rose/.hermes/sessions-archive/session_20260415_100552_deaac3.json\", \"/Users/rose/.hermes/sessions-archive/session_20260414_152504_dd2345.json\", \"/Users/rose/.hermes/sessions/session_20260416_150621_4f567f.json\", \"/Users/rose/.hermes/sessions-archive/20260414_152504_dd2345.jsonl\", \"/Users/rose/.hermes/sessions-archive/session_20260415_125702_5eb6e3ab.json\", \"/Users/rose/.hermes/sessions-archive/request_dump_c3822d5c457b_20260415_185302_372229.json\", \"/Users/rose/.hermes/sessions-archive/session_20260414_202501_23bb23.json\", \"/Users/rose/.hermes/sessions/session_20260416_144210_4f068e.json\", \"/Users/rose/.hermes/sessions/session_cron_90031c503f0b_20260416_114535.json\", \"/Users/rose/.hermes/sessions-archive/request_dump_ac9d2423e751_20260415_161454_373422.json\", \"/Users/rose/.hermes/sessions-archive/session_20260415_075745_d1bbba.json\", \"/Users/rose/.hermes/sessions/session_20260416_121900_91b4fb.json\", \"/Users/rose/.hermes/sessions-archive/session_20260414_165047_8ed9d1.json\", \"/Users/rose/.hermes/sessions/session_20260416_114231_2b3a42.json\", \"/Users/rose/.hermes/sessions-archive/20260415_122237_562f82.jsonl\", \"/Users/rose/.hermes/sessions-archive/session_20260415_131600_be3637.json\"]}",
|
||
"tool_call_id": "call_function_fb8ydnzs6704_2",
|
||
"timestamp": 1776371909
|
||
},
|
||
{
|
||
"role": "assistant",
|
||
"content": "",
|
||
"tool_calls": [
|
||
{
|
||
"id": "call_function_boxj3d29c1q9_1",
|
||
"call_id": "call_function_boxj3d29c1q9_1",
|
||
"response_item_id": "fc_function_boxj3d29c1q9_1",
|
||
"type": "function",
|
||
"function": {
|
||
"name": "read_file",
|
||
"arguments": "{\"path\": \"/Users/rose/.hermes/sessions/session_cron_ecd1da0f1d95_20260416_111713.json\", \"limit\": 100}"
|
||
}
|
||
}
|
||
],
|
||
"timestamp": 1776371909
|
||
},
|
||
{
|
||
"role": "tool",
|
||
"content": "{\"content\": \" 1|{\\n 2| \\\"session_id\\\": \\\"cron_ecd1da0f1d95_20260416_111713\\\",\\n 3| \\\"model\\\": \\\"qwen/qwen3.5-35b-a3b\\\",\\n 4| \\\"base_url\\\": \\\"http://localhost:1234/v1\\\",\\n 5| \\\"platform\\\": \\\"cron\\\",\\n 6| \\\"session_start\\\": \\\"2026-04-16T11:17:13.767486\\\",\\n 7| \\\"last_updated\\\": \\\"2026-04-16T11:26:10.531391\\\",\\n 8| \\\"system_prompt\\\": \\\"You are Hermes Agent, an intelligent AI assistant created by Nous Research. You are helpful, knowledgeable, and direct. You assist users with a wide range of tasks including answering questions, writing and editing code, analyzing information, creative work, and executing actions via your tools. You communicate clearly, admit uncertainty when appropriate, and prioritize being genuinely useful over being verbose unless otherwise directed below. Be targeted and efficient in your exploration and investigations.\\\\n\\\\nYou have persistent memory across sessions. Save durable facts using the memory tool: user preferences, environment details, tool quirks, and stable conventions. Memory is injected into every turn, so keep it compact and focused on facts that will still matter later.\\\\nPrioritize what reduces future user steering — the most valuable memory is one that prevents the user from having to correct or remind you again. User preferences and recurring corrections matter more than procedural task details.\\\\nDo NOT save task progress, session outcomes, completed-work logs, or temporary TODO state to memory; use session_search to recall those from past transcripts. If you've discovered a new way to do something, solved a problem that could be necessary later, save it as a skill with the skill tool. When the user references something from a past conversation or you suspect relevant cross-session context exists, use session_search to recall it before asking them to repeat themselves. After completing a complex task (5+ tool calls), fixing a tricky error, or discovering a non-trivial workflow, save the approach as a skill with skill_manage so you can reuse it next time.\\\\nWhen using a skill and finding it outdated, incomplete, or wrong, patch it immediately with skill_manage(action='patch') — don't wait to be asked. Skills that aren't maintained become liabilities.\\\\n\\\\n## Skills (mandatory)\\\\nBefore replying, scan the skills below. If a skill matches or is ev... [truncated]\\n 9| \\\"tools\\\": [\\n 10| {\\n 11| \\\"type\\\": \\\"function\\\",\\n 12| \\\"function\\\": {\\n 13| \\\"name\\\": \\\"browser_back\\\",\\n 14| \\\"description\\\": \\\"Navigate back to the previous page in browser history. Requires browser_navigate to be called first.\\\",\\n 15| \\\"parameters\\\": {\\n 16| \\\"type\\\": \\\"object\\\",\\n 17| \\\"properties\\\": {},\\n 18| \\\"required\\\": []\\n 19| }\\n 20| }\\n 21| },\\n 22| {\\n 23| \\\"type\\\": \\\"function\\\",\\n 24| \\\"function\\\": {\\n 25| \\\"name\\\": \\\"browser_click\\\",\\n 26| \\\"description\\\": \\\"Click on an element identified by its ref ID from the snapshot (e.g., '@e5'). The ref IDs are shown in square brackets in the snapshot output. Requires browser_navigate and browser_snapshot to be called first.\\\",\\n 27| \\\"parameters\\\": {\\n 28| \\\"type\\\": \\\"object\\\",\\n 29| \\\"properties\\\": {\\n 30| \\\"ref\\\": {\\n 31| \\\"type\\\": \\\"string\\\",\\n 32| \\\"description\\\": \\\"The element reference from the snapshot (e.g., '@e5', '@e12')\\\"\\n 33| }\\n 34| },\\n 35| \\\"required\\\": [\\n 36| \\\"ref\\\"\\n 37| ]\\n 38| }\\n 39| }\\n 40| },\\n 41| {\\n 42| \\\"type\\\": \\\"function\\\",\\n 43| \\\"function\\\": {\\n 44| \\\"name\\\": \\\"browser_console\\\",\\n 45| \\\"description\\\": \\\"Get browser console output and JavaScript errors from the current page. Returns console.log/warn/error/info messages and uncaught JS exceptions. Use this to detect silent JavaScript errors, failed API calls, and application warnings. Requires browser_navigate to be called first. When 'expression' is provided, evaluates JavaScript in the page context and returns the result — use this for DOM inspection, reading page state, or extracting data programmatically.\\\",\\n 46| \\\"parameters\\\": {\\n 47| \\\"type\\\": \\\"object\\\",\\n 48| \\\"properties\\\": {\\n 49| \\\"clear\\\": {\\n 50| \\\"type\\\": \\\"boolean\\\",\\n 51| \\\"default\\\": false,\\n 52| \\\"description\\\": \\\"If true, clear the message buffers after reading\\\"\\n 53| },\\n 54| \\\"expression\\\": {\\n 55| \\\"type\\\": \\\"string\\\",\\n 56| \\\"description\\\": \\\"JavaScript expression to evaluate in the page context. Runs in the browser like DevTools console — full access to DOM, window, document. Return values are serialized to JSON. Example: 'document.title' or 'document.querySelectorAll(\\\\\\\"a\\\\\\\").length'\\\"\\n 57| }\\n 58| },\\n 59| \\\"required\\\": []\\n 60| }\\n 61| }\\n 62| },\\n 63| {\\n 64| \\\"type\\\": \\\"function\\\",\\n 65| \\\"function\\\": {\\n 66| \\\"name\\\": \\\"browser_get_images\\\",\\n 67| \\\"description\\\": \\\"Get a list of all images on the current page with their URLs and alt text. Useful for finding images to analyze with the vision tool. Requires browser_navigate to be called first.\\\",\\n 68| \\\"parameters\\\": {\\n 69| \\\"type\\\": \\\"object\\\",\\n 70| \\\"properties\\\": {},\\n 71| \\\"required\\\": []\\n 72| }\\n 73| }\\n 74| },\\n 75| {\\n 76| \\\"type\\\": \\\"function\\\",\\n 77| \\\"function\\\": {\\n 78| \\\"name\\\": \\\"browser_navigate\\\",\\n 79| \\\"description\\\": \\\"Navigate to a URL in the browser. Initializes the session and loads the page. Must be called before other browser tools. Use browser tools when you need to interact with a page (click, fill forms, dynamic content). Returns a compact page snapshot with interactive elements and ref IDs — no need to call browser_snapshot separately after navigating.\\\",\\n 80| \\\"parameters\\\": {\\n 81| \\\"type\\\": \\\"object\\\",\\n 82| \\\"properties\\\": {\\n 83| \\\"url\\\": {\\n 84| \\\"type\\\": \\\"string\\\",\\n 85| \\\"description\\\": \\\"The URL to navigate to (e.g., 'https://example.com')\\\"\\n 86| }\\n 87| },\\n 88| \\\"required\\\": [\\n 89| \\\"url\\\"\\n 90| ]\\n 91| }\\n 92| }\\n 93| },\\n 94| {\\n 95| \\\"type\\\": \\\"function\\\",\\n 96| \\\"function\\\": {\\n 97| \\\"name\\\": \\\"browser_press\\\",\\n 98| \\\"description\\\": \\\"Press a keyboard key. Useful for submitting forms (Enter), navigating (Tab), or keyboard shortcuts. Requires browser_navigate to be called first.\\\",\\n 99| \\\"parameters\\\": {\\n 100| \\\"type\\\": \\\"object\\\",\\n 101|\", \"total_lines\": 945, \"file_size\": 84301, \"truncated\": true, \"hint\": \"Use offset=101 to continue reading (showing 1-100 of 945 lines)\", \"is_binary\": false, \"is_image\": false}",
|
||
"tool_call_id": "call_function_boxj3d29c1q9_1",
|
||
"timestamp": 1776371909
|
||
},
|
||
{
|
||
"role": "assistant",
|
||
"content": "",
|
||
"tool_calls": [
|
||
{
|
||
"id": "call_function_0frc39idxb60_1",
|
||
"call_id": "call_function_0frc39idxb60_1",
|
||
"response_item_id": "fc_function_0frc39idxb60_1",
|
||
"type": "function",
|
||
"function": {
|
||
"name": "read_file",
|
||
"arguments": "{\"offset\": 800, \"limit\": 150, \"path\": \"/Users/rose/.hermes/sessions/session_cron_ecd1da0f1d95_20260416_111713.json\"}"
|
||
}
|
||
}
|
||
],
|
||
"timestamp": 1776371909
|
||
},
|
||
{
|
||
"role": "tool",
|
||
"content": "{\"content\": \" 800| ],\\n 801| \\\"description\\\": \\\"Current status\\\"\\n 802| }\\n 803| },\\n 804| \\\"required\\\": [\\n 805| \\\"id\\\",\\n 806| \\\"content\\\",\\n 807| \\\"status\\\"\\n 808| ]\\n 809| }\\n 810| },\\n 811| \\\"merge\\\": {\\n 812| \\\"type\\\": \\\"boolean\\\",\\n 813| \\\"description\\\": \\\"true: update existing items by id, add new ones. false (default): replace the entire list.\\\",\\n 814| \\\"default\\\": false\\n 815| }\\n 816| },\\n 817| \\\"required\\\": []\\n 818| }\\n 819| }\\n 820| },\\n 821| {\\n 822| \\\"type\\\": \\\"function\\\",\\n 823| \\\"function\\\": {\\n 824| \\\"name\\\": \\\"vision_analyze\\\",\\n 825| \\\"description\\\": \\\"Analyze images using AI vision. Provides a comprehensive description and answers a specific question about the image content.\\\",\\n 826| \\\"parameters\\\": {\\n 827| \\\"type\\\": \\\"object\\\",\\n 828| \\\"properties\\\": {\\n 829| \\\"image_url\\\": {\\n 830| \\\"type\\\": \\\"string\\\",\\n 831| \\\"description\\\": \\\"Image URL (http/https) or local file path to analyze.\\\"\\n 832| },\\n 833| \\\"question\\\": {\\n 834| \\\"type\\\": \\\"string\\\",\\n 835| \\\"description\\\": \\\"Your specific question or request about the image to resolve. The AI will automatically provide a complete image description AND answer your specific question.\\\"\\n 836| }\\n 837| },\\n 838| \\\"required\\\": [\\n 839| \\\"image_url\\\",\\n 840| \\\"question\\\"\\n 841| ]\\n 842| }\\n 843| }\\n 844| },\\n 845| {\\n 846| \\\"type\\\": \\\"function\\\",\\n 847| \\\"function\\\": {\\n 848| \\\"name\\\": \\\"write_file\\\",\\n 849| \\\"description\\\": \\\"Write content to a file, completely replacing existing content. Use this instead of echo/cat heredoc in terminal. Creates parent directories automatically. OVERWRITES the entire file — use 'patch' for targeted edits.\\\",\\n 850| \\\"parameters\\\": {\\n 851| \\\"type\\\": \\\"object\\\",\\n 852| \\\"properties\\\": {\\n 853| \\\"path\\\": {\\n 854| \\\"type\\\": \\\"string\\\",\\n 855| \\\"description\\\": \\\"Path to the file to write (will be created if it doesn't exist, overwritten if it does)\\\"\\n 856| },\\n 857| \\\"content\\\": {\\n 858| \\\"type\\\": \\\"string\\\",\\n 859| \\\"description\\\": \\\"Complete content to write to the file\\\"\\n 860| }\\n 861| },\\n 862| \\\"required\\\": [\\n 863| \\\"path\\\",\\n 864| \\\"content\\\"\\n 865| ]\\n 866| }\\n 867| }\\n 868| }\\n 869| ],\\n 870| \\\"message_count\\\": 7,\\n 871| \\\"messages\\\": [\\n 872| {\\n 873| \\\"role\\\": \\\"user\\\",\\n 874| \\\"content\\\": \\\"[SYSTEM: The user has invoked the \\\\\\\"hermes-housekeeping-maintenance\\\\\\\" skill, indicating they want you to follow its instructions. The full skill content is loaded below.]\\\\n\\\\n---\\\\nname: hermes-housekeeping-maintenance\\\\ndescription: Automated Hermes maintenance via cronjob - ChromaDB keepalive, session cleanup, DB vacuum, log rotation, backup cleanup. Handles macOS 26 launchd limitations.\\\\nversion: 1.0\\\\ncreated: 2026-04-15\\\\n---\\\\n\\\\n# Hermes Housekeeping Maintenance\\\\n\\\\nAutomated maintenance script that runs every 15 minutes via Hermes cronjob.\\\\n\\\\n## What It Does\\\\n\\\\n1. **ChromaDB Keepalive** - Checks if ChromaDB server is running on port 8000, restarts if down\\\\n2. **Gateway Health Check + Auto-Restart** - Monitors Hermes Gateway process, auto-restarts via nohup if down\\\\n3. **WebUI Health Check + Auto-Restart** - Monitors Hermes WebUI on port 8787, auto-restarts via start.sh if down\\\\n3. **Session Cleanup** - Removes session JSONL files older than 30 days from `~/.hermes/sessions/`\\\\n4. **state.db Vacuum** - SQLite VACUUM when state.db exceeds 100MB\\\\n5. **Cron Output Cleanup** - Removes stale cron output files older than 7 days\\\\n6. **Empty DB Cleanup** - Removes 0-byte database files\\\\n7. **Log Rotation** - Rotates individual log files exceeding 10MB\\\\n8. **Backup Cleanup** - Removes old `sessions.backup_*` and `migration/` dirs older than 7 days\\\\n\\\\n## Script Location\\\\n\\\\n`~/.hermes/scripts/housekeeping.py`\\\\n\\\\n## Cronjob\\\\n\\\\n- **Name:** Hermes Housekeeping\\\\n- **Schedule:** every 15m\\\\n- **Deliver:** local (report saved to `~/.hermes/cron/output/housekeeping-latest.json`)\\\\n- **Job ID:** 90031c503f0b (updated April 2026)\\\\n\\\\n## Manual Run\\\\n\\\\n```bash\\\\npython3 ~/.hermes/scripts/housekeeping.py\\\\n```\\\\n\\\\n## Gateway Auto-Restart Details\\\\n\\\\n- Check: `pgrep -f \\\\\\\"hermes gateway run\\\\\\\"`\\\\n- Start: `/Users/rose/.hermes/hermes-agent/venv/bin/python3 /Users/rose/.local/bin/hermes gateway run`\\\\n- Runs in background via `subprocess.Popen(start_new_session=True)`\\\\n- Verifies restar... [truncated]\\n 875| },\\n 876| {\\n 877| \\\"role\\\": \\\"assistant\\\",\\n 878| \\\"content\\\": \\\"<think>The user wants me to run the full Memory Pipeline (extract → promote → sync), so I'll execute each step in sequence with proper error handling and logging.\\\\n</think>\\\\nI'll execute the complete memory pipeline as specified. Let me run each step sequentially.\\\",\\n 879| \\\"reasoning\\\": \\\"The user wants me to run the full Memory Pipeline (extract → promote → sync), so I'll execute each step in sequence with proper error handling and logging.\\\",\\n 880| \\\"finish_reason\\\": \\\"tool_calls\\\",\\n 881| \\\"tool_calls\\\": [\\n 882| {\\n 883| \\\"id\\\": \\\"715314722\\\",\\n 884| \\\"call_id\\\": \\\"715314722\\\",\\n 885| \\\"response_item_id\\\": \\\"fc_715314722\\\",\\n 886| \\\"type\\\": \\\"function\\\",\\n 887| \\\"function\\\": {\\n 888| \\\"name\\\": \\\"execute_code\\\",\\n 889| \\\"arguments\\\": \\\"{\\\\\\\"code\\\\\\\":\\\\\\\"from hermes_tools import terminal, read_file, write_file\\\\\\\\nimport json\\\\\\\\nfrom datetime import datetime\\\\\\\\n\\\\\\\\n# Step 1: Extract Sessions\\\\\\\\nprint(\\\\\\\\\\\\\\\"=\\\\\\\\\\\\\\\" * 60)\\\\\\\\nprint(\\\\\\\\\\\\\\\"STEP 1: Extracting Sessions\\\\\\\\\\\\\\\")\\\\\\\\nprint(\\\\\\\\\\\\\\\"=\\\\\\\\\\\\\\\" * 60)\\\\\\\\n\\\\\\\\nresult = terminal(\\\\\\\\n command=\\\\\\\\\\\\\\\"cd /Users/rose/.hermes/hermes-agent && source venv/bin/activate && python tools/memory_pipeline.py --extract\\\\\\\\\\\\\\\",\\\\\\\\n timeout=120,\\\\\\\\n workdir=\\\\\\\\\\\\\\\"/Users/rose\\\\\\\\\\\\\\\"\\\\\\\\n)\\\\\\\\n\\\\\\\\nif result[\\\\\\\\\\\\\\\"exit_code\\\\\\\\\\\\\\\"] == 0:\\\\\\\\n print(\\\\\\\\\\\\\\\"✓ Extraction successful\\\\\\\\\\\\\\\")\\\\\\\\nelse:\\\\\\\\n print(f\\\\\\\\\\\\\\\"✗ Extraction failed with exit code {result['exit_code']}\\\\\\\\\\\\\\\")\\\\\\\\n \\\\\\\\nprint(\\\\\\\\\\\\\\\"\\\\\\\\\\\\\\\\nOutput:\\\\\\\\\\\\\\\")\\\\\\\\nprint(result[\\\\\\\\\\\\\\\"output\\\\\\\\\\\\\\\"])\\\\\\\\n\\\\\\\\n# Save results for later analysis\\\\\\\\nextraction_result = json.loads(result[\\\\\\\\\\\\\\\"output\\\\\\\\\\\\\\\"].split('\\\\\\\\\\\\\\\\n')[-1]) if result[\\\\\\\\\\\\\\\"output\\\\\\\\\\\\\\\"].strip() else {}\\\\\\\\nsession_count = extraction_result.get(\\\\\\\\\\\\\\\"processed_sessions\\\\\\\\\\\\\\\", 0) if extraction_result else 0\\\\\\\\nnew_facts = extraction_result.get(\\\\\\\\\\\\\\\"extracted_facts\\\\\\\\\\\\\\\", 0) if extraction_result else 0\\\\\\\\n\\\\\\\\nprint(f\\\\\\\\\\\\\\\"\\\\\\\\\\\\\\\\nExtracted: {extraction_result}\\\\\\\\\\\\\\\")\\\\\\\\n\\\\\\\"}\\\"\\n 890| }\\n 891| }\\n 892| ]\\n 893| },\\n 894| {\\n 895| \\\"role\\\": \\\"tool\\\",\\n 896| \\\"content\\\": \\\"{\\\\\\\"status\\\\\\\": \\\\\\\"error\\\\\\\", \\\\\\\"output\\\\\\\": \\\\\\\"============================================================\\\\\\\\nSTEP 1: Extracting Sessions\\\\\\\\n============================================================\\\\\\\\n✗ Extraction failed with exit code 124\\\\\\\\n\\\\\\\\nOutput:\\\\\\\\n============================================================\\\\\\\\nSTEP 1: Session → ChromaDB Extraktion (Batch Mode)\\\\\\\\n============================================================\\\\\\\\nLoading embedding model...\\\\\\\\n\\\\\\\\nLoading weights: 0%| | 0/103 [00:00<?, ?it/s]\\\\\\\\nLoading weights: 100%|██████████| 103/103 [00:00<00:00, 11807.84it/s]\\\\\\\\nBertModel LOAD REPORT from: sentence-transformers/all-MiniLM-L6-v2\\\\\\\\nKey | Status | | \\\\\\\\n------------------------+------------+--+-\\\\\\\\nembeddings.position_ids | UNEXPECTED | | \\\\\\\\n\\\\\\\\nNotes:\\\\\\\\n- UNEXPECTED:\\\\\\\\tcan be ignored when loading from different task/architecture; not ok if you expect identical arch.\\\\\\\\nWarning: You are sending unauthenticated requests to the HF Hub. Please set a HF_TOKEN to enable higher rate limits and faster downloads.\\\\\\\\n/Users/rose/.local/share/uv/python/cpython-3.11.15-macos-aarch64-none/lib/python3.11/multiprocessing/resource_tracker.py:254: UserWarning: resource_tracker: There appear to be 1 leaked semaphore objects to clean up at shutdown\\\\\\\\n warnings.warn('resource_tracker: There appear to be %d '\\\\\\\\n\\\\\\\\n[Command timed out after 120s]\\\\\\\\n\\\\\\\\n--- stderr ---\\\\\\\\nTraceback (most recent call last):\\\\\\\\n File \\\\\\\\\\\\\\\"/private/var/folders/84/v4lq2y417wv_q_1dcmnh7dtr0000gn/T/hermes_sandbox_2d4_yuk3/script.py\\\\\\\\\\\\\\\", line 25, in <module>\\\\\\\\n extraction_result = json.loads(result[\\\\\\\\\\\\\\\"output\\\\\\\\\\\\\\\"].split('\\\\\\\\\\\\\\\\n')[-1]) if result[\\\\\\\\\\\\\\\"output\\\\\\\\\\\\\\\"].strip() else {}\\\\\\\\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\\\\\\\\n File \\\\\\\\\\\\\\\"/Users/rose/.local/share/uv/python/cpython-3.11.15-macos-aarch64-none/lib/python3.11/json/__init__.py\\\\\\\\\\\\\\\", line 346, in loads\\\\\\\\n return _default_decoder.decode(s)\\\\\\\\n ^^^^^^^^^^^^^^^^^^^^^^^... [truncated]\\n 897| \\\"tool_call_id\\\": \\\"715314722\\\"\\n 898| },\\n 899| {\\n 900| \\\"role\\\": \\\"assistant\\\",\\n 901| \\\"content\\\": \\\"<think>The extraction command timed out after 120 seconds, so I need to retry with a longer timeout and fix the JSON parsing that failed because there was no output.\\\\n</think>\\\\nThe extraction timed out at 120 seconds. Let me increase the timeout and try again:\\\",\\n 902| \\\"reasoning\\\": \\\"The extraction command timed out after 120 seconds, so I need to retry with a longer timeout and fix the JSON parsing that failed because there was no output.\\\",\\n 903| \\\"finish_reason\\\": \\\"tool_calls\\\",\\n 904| \\\"tool_calls\\\": [\\n 905| {\\n 906| \\\"id\\\": \\\"169140197\\\",\\n 907| \\\"call_id\\\": \\\"169140197\\\",\\n 908| \\\"response_item_id\\\": \\\"fc_169140197\\\",\\n 909| \\\"type\\\": \\\"function\\\",\\n 910| \\\"function\\\": {\\n 911| \\\"name\\\": \\\"execute_code\\\",\\n 912| \\\"arguments\\\": \\\"{\\\\\\\"code\\\\\\\":\\\\\\\"from hermes_tools import terminal, write_file\\\\\\\\nimport json\\\\\\\\n\\\\\\\\n# Step 1: Extract Sessions (with longer timeout)\\\\\\\\nprint(\\\\\\\\\\\\\\\"=\\\\\\\\\\\\\\\" * 60)\\\\\\\\nprint(\\\\\\\\\\\\\\\"STEP 1: Extracting Sessions\\\\\\\\\\\\\\\")\\\\\\\\nprint(\\\\\\\\\\\\\\\"=\\\\\\\\\\\\\\\" * 60)\\\\\\\\n\\\\\\\\nresult = terminal(\\\\\\\\n command=\\\\\\\\\\\\\\\"cd /Users/rose/.hermes/hermes-agent && source venv/bin/activate && python tools/memory_pipeline.py --extract\\\\\\\\\\\\\\\",\\\\\\\\n timeout=300,\\\\\\\\n workdir=\\\\\\\\\\\\\\\"/Users/rose\\\\\\\\\\\\\\\"\\\\\\\\n)\\\\\\\\n\\\\\\\\nif result[\\\\\\\\\\\\\\\"exit_code\\\\\\\\\\\\\\\"] == 0:\\\\\\\\n print(\\\\\\\\\\\\\\\"✓ Extraction successful\\\\\\\\\\\\\\\")\\\\\\\\nelse:\\\\\\\\n print(f\\\\\\\\\\\\\\\"✗ Extraction failed with exit code {result['exit_code']}\\\\\\\\\\\\\\\")\\\\\\\\n \\\\\\\\nprint(\\\\\\\\\\\\\\\"\\\\\\\\\\\\\\\\n--- Output ---\\\\\\\\\\\\\\\\n\\\\\\\\\\\\\\\")\\\\\\\\nprint(result[\\\\\\\\\\\\\\\"output\\\\\\\\\\\\\\\"])\\\\\\\\n\\\\\\\"}\\\"\\n 913| }\\n 914| }\\n 915| ]\\n 916| },\\n 917| {\\n 918| \\\"role\\\": \\\"tool\\\",\\n 919| \\\"content\\\": \\\"{\\\\\\\"status\\\\\\\": \\\\\\\"error\\\\\\\", \\\\\\\"output\\\\\\\": \\\\\\\"============================================================\\\\\\\\nSTEP 1: Extracting Sessions\\\\\\\\n============================================================\\\\\\\\n\\\\\\\\n--- stderr ---\\\\\\\\nTraceback (most recent call last):\\\\\\\\n File \\\\\\\\\\\\\\\"/private/var/folders/84/v4lq2y417wv_q_1dcmnh7dtr0000gn/T/hermes_sandbox_a4ge8s3w/script.py\\\\\\\\\\\\\\\", line 9, in <module>\\\\\\\\n result = terminal(\\\\\\\\n ^^^^^^^^^\\\\\\\\n File \\\\\\\\\\\\\\\"/private/var/folders/84/v4lq2y417wv_q_1dcmnh7dtr0000gn/T/hermes_sandbox_a4ge8s3w/hermes_tools.py\\\\\\\\\\\\\\\", line 85, in terminal\\\\\\\\n return _call('terminal', {\\\\\\\\\\\\\\\"command\\\\\\\\\\\\\\\": command, \\\\\\\\\\\\\\\"timeout\\\\\\\\\\\\\\\": timeout, \\\\\\\\\\\\\\\"workdir\\\\\\\\\\\\\\\": workdir})\\\\\\\\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\\\\\\\\n File \\\\\\\\\\\\\\\"/private/var/folders/84/v4lq2y417wv_q_1dcmnh7dtr0000gn/T/hermes_sandbox_a4ge8s3w/hermes_tools.py\\\\\\\\\\\\\\\", line 56, in _call\\\\\\\\n chunk = conn.recv(65536)\\\\\\\\n ^^^^^^^^^^^^^^^^\\\\\\\\nTimeoutError: timed out\\\\\\\\n\\\\\\\", \\\\\\\"tool_calls_made\\\\\\\": 1, \\\\\\\"duration_seconds\\\\\\\": 300.22, \\\\\\\"error\\\\\\\": \\\\\\\"Traceback (most recent call last):\\\\\\\\n File \\\\\\\\\\\\\\\"/private/var/folders/84/v4lq2y417wv_q_1dcmnh7dtr0000gn/T/hermes_sandbox_a4ge8s3w/script.py\\\\\\\\\\\\\\\", line 9, in <module>\\\\\\\\n result = terminal(\\\\\\\\n ^^^^^^^^^\\\\\\\\n File \\\\\\\\\\\\\\\"/private/var/folders/84/v4lq2y417wv_q_1dcmnh7dtr0000gn/T/hermes_sandbox_a4ge8s3w/hermes_tools.py\\\\\\\\\\\\\\\", line 85, in terminal\\\\\\\\n return _call('terminal', {\\\\\\\\\\\\\\\"command\\\\\\\\\\\\\\\": command, \\\\\\\\\\\\\\\"timeout\\\\\\\\\\\\\\\": timeout, \\\\\\\\\\\\\\\"workdir\\\\\\\\\\\\\\\": workdir})\\\\\\\\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\\\\\\\\n File \\\\\\\\\\\\\\\"/private/var/folders/84/v4lq2y417wv_q_1dcmnh7dtr0000gn/T/hermes_sandbox_a4ge8s3w/hermes_tools.py\\\\\\\\\\\\\\\", line 56, in _call\\\\\\\\n chunk = conn.recv(65536)\\\\\\\\n ^^^^^^^^^^^^^^^^\\\\\\\\nTimeoutError: timed out\\\\\\\\n\\\\\\\"}\\\",\\n 920| \\\"tool_call_id\\\": \\\"169140197\\\"\\n 921| },\\n 922| {\\n 923| \\\"role\\\": \\\"assistant\\\",\\n 924| \\\"content\\\": \\\"<think>The extraction is timing out due to embedding model loading, so I need to run it as a background process and poll for completion instead of waiting synchronously.\\\\n</think>\\\\nThe command is still timing out during embedding model loading. Let me check if ChromaDB is running first (as required), then try the extraction in background mode:\\\",\\n 925| \\\"reasoning\\\": \\\"The extraction is timing out due to embedding model loading, so I need to run it as a background process and poll for completion instead of waiting synchronously.\\\",\\n 926| \\\"finish_reason\\\": \\\"tool_calls\\\",\\n 927| \\\"tool_calls\\\": [\\n 928| {\\n 929| \\\"id\\\": \\\"542880581\\\",\\n 930| \\\"call_id\\\": \\\"542880581\\\",\\n 931| \\\"response_item_id\\\": \\\"fc_542880581\\\",\\n 932| \\\"type\\\": \\\"function\\\",\\n 933| \\\"function\\\": {\\n 934| \\\"name\\\": \\\"execute_code\\\",\\n 935| \\\"arguments\\\": \\\"{\\\\\\\"code\\\\\\\":\\\\\\\"from hermes_tools import terminal, write_file\\\\\\\\nimport time\\\\\\\\n\\\\\\\\n# First, verify ChromaDB is running on port 8000\\\\\\\\nprint(\\\\\\\\\\\\\\\"Checking ChromaDB status...\\\\\\\\\\\\\\\")\\\\\\\\nresult = terminal(\\\\\\\\n command=\\\\\\\\\\\\\\\"curl -s http://127.0.0.1:8000/api/v2/heartbeat\\\\\\\\\\\\\\\",\\\\\\\\n timeout=10\\\\\\\\n)\\\\\\\\n\\\\\\\\nif result[\\\\\\\\\\\\\\\"exit_code\\\\\\\\\\\\\\\"] == 0:\\\\\\\\n print(f\\\\\\\\\\\\\\\"✓ ChromaDB is running: {result['output']}\\\\\\\\\\\\\\\")\\\\\\\\nelse:\\\\\\\\n print(f\\\\\\\\\\\\\\\"✗ ChromaDB not responding. Trying to start...\\\\\\\\\\\\\\\")\\\\\\\\n # Try to start ChromaDB in background\\\\\\\\n chroma_result = terminal(\\\\\\\\n command=\\\\\\\\\\\\\\\"chroma run --path /Users/rose/.hermes/chroma_db > ~/.hermes/chroma_db/server.log 2>&1 &\\\\\\\\\\\\\\\",\\\\\\\\n timeout=5,\\\\\\\\n workdir=\\\\\\\\\\\\\\\"/Users/rose\\\\\\\\\\\\\\\"\\\\\\\\n )\\\\\\\\n print(f\\\\\\\\\\\\\\\"ChromaDB start attempt: {chroma_result['output']}\\\\\\\\\\\\\\\")\\\\\\\\n\\\\\\\\n# Now try running the extraction in background mode with progress tracking\\\\\\\\nprint(\\\\\\\\\\\\\\\"\\\\\\\\\\\\\\\\nStarting memory pipeline extraction (background)...\\\\\\\\\\\\\\\")\\\\\\\\n\\\\\\\\nresult = terminal(\\\\\\\\n command=\\\\\\\\\\\\\\\"cd /Users/rose/.hermes/hermes-agent && source venv/bin/activate && timeout 300 python tools/memory_pipeline.py --extract\\\\\\\\\\\\\\\",\\\\\\\\n timeout=420, # Give extra time for timeout wrapper\\\\\\\\n workdir=\\\\\\\\\\\\\\\"/Users/rose\\\\\\\\\\\\\\\"\\\\\\\\n)\\\\\\\\n\\\\\\\\nprint(\\\\\\\\\\\\\\\"\\\\\\\\\\\\\\\\n--- Extraction Output ---\\\\\\\\\\\\\\\\n\\\\\\\\\\\\\\\")\\\\\\\\nprint(result[\\\\\\\\\\\\\\\"output\\\\\\\\\\\\\\\"])\\\\\\\\nprint(f\\\\\\\\\\\\\\\"\\\\\\\\\\\\\\\\nExit code: {result['exit_code']}\\\\\\\\\\\\\\\")\\\\\\\\n\\\\\\\"}\\\"\\n 936| }\\n 937| }\\n 938| ]\\n 939| },\\n 940| {\\n 941| \\\"role\\\": \\\"tool\\\",\\n 942| \\\"content\\\": \\\"{\\\\\\\"status\\\\\\\": \\\\\\\"success\\\\\\\", \\\\\\\"output\\\\\\\": \\\\\\\"Checking ChromaDB status...\\\\\\\\n✓ ChromaDB is running: {\\\\\\\\\\\\\\\"nanosecond heartbeat\\\\\\\\\\\\\\\":1776331569833849000}\\\\\\\\n\\\\\\\\nStarting memory pipeline extraction (background)...\\\\\\\\n\\\\\\\\n--- Extraction Output ---\\\\\\\\n\\\\\\\\n/bin/bash: line 2: timeout: command not found\\\\\\\\n\\\\\\\\nExit code: 127\\\\\\\\n\\\\\\\", \\\\\\\"tool_calls_made\\\\\\\": 2, \\\\\\\"duration_seconds\\\\\\\": 1.06}\\\",\\n 943| \\\"tool_call_id\\\": \\\"542880581\\\"\\n 944| }\\n 945| ]\\n 946|}\", \"total_lines\": 945, \"file_size\": 84301, \"truncated\": false, \"is_binary\": false, \"is_image\": false}",
|
||
"tool_call_id": "call_function_0frc39idxb60_1",
|
||
"timestamp": 1776371909
|
||
},
|
||
{
|
||
"role": "assistant",
|
||
"content": "**Rose Memory Sync (Nightly)** — der Cron Job existiert, aber:\n\n**Status: ✗ Noch nie erfolgreich gelaufen** (`last_run_at: null`)\n\n**Was es machen soll:**\nDer Job führt jeden Nacht um 2:00 Uhr den kompletten Memory-Pipeline aus:\n1. **Extract** — Sessions auswerten und Fakten extrahieren\n2. **Promote** — wichtige Infos ins ChromaDB-semantische Memory schieben\n3. **Sync** — Vault-Memory mit ChromaDB synchronisieren\n\n**Warum es aktuell nicht läuft:**\n\nDie Logs zeigen zwei Probleme:\n1. **Embedding-Modell** (MiniLM-L6-v2) braucht zu lange zum Laden — 300s reichen nicht\n2. **macOS hat keinen `timeout`-Befehl** — der Pipeline-Skript nutzt `timeout 300 python ...` was auf Linux funktioniert, aber nicht auf macOS\n\nDer Job ist korrekt konfiguriert und liefert nach Telegram, aber er braucht:\n- Einen Fix für den `timeout`-Befehl (durch `gtimeout` oder via Python `signal.SIGALRM`)\n- Mehr Zeit für die Embedding-Initialisierung\n\nSoll ich den Fix einbauen und den Pipeline jetzt manuell ausführen?",
|
||
"timestamp": 1776371909
|
||
},
|
||
{
|
||
"role": "user",
|
||
"content": "benutze doch lmstudio qwen 3.5",
|
||
"timestamp": 1776371909
|
||
},
|
||
{
|
||
"role": "assistant",
|
||
"content": "",
|
||
"tool_calls": [
|
||
{
|
||
"id": "call_function_g5ez9tktykr5_1",
|
||
"call_id": "call_function_g5ez9tktykr5_1",
|
||
"response_item_id": "fc_function_g5ez9tktykr5_1",
|
||
"type": "function",
|
||
"function": {
|
||
"name": "search_files",
|
||
"arguments": "{\"pattern\": \"memory_pipeline.py\", \"output_mode\": \"files_only\"}"
|
||
}
|
||
}
|
||
],
|
||
"timestamp": 1776371909
|
||
},
|
||
{
|
||
"role": "tool",
|
||
"content": "{\"total_count\": 0}",
|
||
"tool_call_id": "call_function_g5ez9tktykr5_1",
|
||
"timestamp": 1776371909
|
||
},
|
||
{
|
||
"role": "assistant",
|
||
"content": "",
|
||
"tool_calls": [
|
||
{
|
||
"id": "call_function_abaoo1h2ylmi_1",
|
||
"call_id": "call_function_abaoo1h2ylmi_1",
|
||
"response_item_id": "fc_function_abaoo1h2ylmi_1",
|
||
"type": "function",
|
||
"function": {
|
||
"name": "search_files",
|
||
"arguments": "{\"pattern\": \"memory_pipeline\", \"output_mode\": \"files_only\"}"
|
||
}
|
||
}
|
||
],
|
||
"timestamp": 1776371909
|
||
},
|
||
{
|
||
"role": "tool",
|
||
"content": "{\"total_count\": 0}",
|
||
"tool_call_id": "call_function_abaoo1h2ylmi_1",
|
||
"timestamp": 1776371909
|
||
},
|
||
{
|
||
"role": "assistant",
|
||
"content": "",
|
||
"tool_calls": [
|
||
{
|
||
"id": "call_function_ladkumh4bf96_1",
|
||
"call_id": "call_function_ladkumh4bf96_1",
|
||
"response_item_id": "fc_function_ladkumh4bf96_1",
|
||
"type": "function",
|
||
"function": {
|
||
"name": "skill_view",
|
||
"arguments": "{\"name\": \"hermes-housekeeping-maintenance\"}"
|
||
}
|
||
}
|
||
],
|
||
"timestamp": 1776371909
|
||
},
|
||
{
|
||
"role": "tool",
|
||
"content": "{\"success\": true, \"name\": \"hermes-housekeeping-maintenance\", \"description\": \"Automated Hermes maintenance via cronjob - ChromaDB keepalive, session cleanup, DB vacuum, log rotation, backup cleanup. Handles macOS 26 launchd limitations.\", \"tags\": [], \"related_skills\": [], \"content\": \"---\\nname: hermes-housekeeping-maintenance\\ndescription: Automated Hermes maintenance via cronjob - ChromaDB keepalive, session cleanup, DB vacuum, log rotation, backup cleanup. Handles macOS 26 launchd limitations.\\nversion: 1.0\\ncreated: 2026-04-15\\n---\\n\\n# Hermes Housekeeping Maintenance\\n\\nAutomated maintenance script that runs every 15 minutes via Hermes cronjob.\\n\\n## What It Does\\n\\n1. **ChromaDB Keepalive** - Checks if ChromaDB server is running on port 8000, restarts if down\\n2. **Gateway Health Check + Auto-Restart** - Monitors Hermes Gateway process, auto-restarts via nohup if down\\n3. **WebUI Health Check + Auto-Restart** - Monitors Hermes WebUI on port 8787, auto-restarts via start.sh if down\\n3. **Session Cleanup** - Removes session JSONL files older than 30 days from `~/.hermes/sessions/`\\n4. **state.db Vacuum** - SQLite VACUUM when state.db exceeds 100MB\\n5. **Cron Output Cleanup** - Removes stale cron output files older than 7 days\\n6. **Empty DB Cleanup** - Removes 0-byte database files\\n7. **Log Rotation** - Rotates individual log files exceeding 10MB\\n8. **Backup Cleanup** - Removes old `sessions.backup_*` and `migration/` dirs older than 7 days\\n\\n## Script Location\\n\\n`~/.hermes/scripts/housekeeping.py`\\n\\n## Cronjob\\n\\n- **Name:** Hermes Housekeeping\\n- **Schedule:** every 15m\\n- **Deliver:** local (report saved to `~/.hermes/cron/output/housekeeping-latest.json`)\\n- **Job ID:** 90031c503f0b (updated April 2026)\\n\\n## Manual Run\\n\\n```bash\\npython3 ~/.hermes/scripts/housekeeping.py\\n```\\n\\n## Gateway Auto-Restart Details\\n\\n- Check: `pgrep -f \\\"hermes gateway run\\\"`\\n- Start: `/Users/rose/.hermes/hermes-agent/venv/bin/python3 /Users/rose/.local/bin/hermes gateway run`\\n- Runs in background via `subprocess.Popen(start_new_session=True)`\\n- Verifies restart success after 5 second wait\\n\\n## WebUI Auto-Restart Details\\n\\n- Check: `curl http://localhost:8787/health` (fallback: `lsof -i :8787`)\\n- Start: `bash start.sh` in `~/.hermes/hermes-webui/`\\n- Requires `.env` with `HERMES_WEBUI_HOST=0.0.0.0` and `HERMES_WEBUI_PORT=8787`\\n- Verifies restart success after 5 second wait\\n\\n## Report Format\\n\\nJSON report saved to `housekeeping-latest.json`:\\n```json\\n{\\n \\\"timestamp\\\": \\\"2026-04-15T08:52:38\\\",\\n \\\"actions\\\": [\\\"ChromaDB: running\\\", \\\"state.db: 186 MB - OK\\\"],\\n \\\"errors\\\": [],\\n \\\"status\\\": \\\"ok\\\"\\n}\\n```\\n\\nStatus can be `ok` or `degraded` (if ChromaDB down or Gateway missing).\\n\\n## macOS 26 launchd Workaround\\n\\nmacOS 26 (Tahoe) has a bug where `launchctl bootstrap/load/kickstart` fails with exit 125/134 for ALL new LaunchAgents. The housekeeping script works around this by:\\n\\n1. Starting services via `nohup` + `subprocess.Popen(start_new_session=True)`\\n2. Checking process health every 15 minutes\\n3. Auto-restarting ChromaDB if it goes down\\n\\n## ChromaDB Details\\n\\n- Binary: `/opt/homebrew/bin/chroma`\\n- Data path: `~/.hermes/chroma_db/`\\n- Port: 8000\\n- Host: 127.0.0.1\\n- Health endpoint: `http://127.0.0.1:8000/api/v2/heartbeat`\\n\\n## Cleanup: Dead/Obsolete Files in .hermes\\n\\nSession cleanup also targets these specific file patterns:\\n\\n| Pattern | Reason | Typical Size |\\n|---------|--------|-------------|\\n| `state.db.corrupt` | Gateway crash leftover from WAL corruption | 200+ MB |\\n| `state.db.corrupt-backup` | Backup of corrupt file | 200+ MB |\\n| `state.db.bak.*` | Old timestamped backups | 5 MB |\\n| `chroma/chroma.sqlite3` | Dummy/empty DB (real DB is in `chroma_db/`) | <1 MB |\\n\\n**SIP-protected paths:** On macOS, `cron/output/` files may be protected by SIP (System Integrity Protection) and cannot be deleted even as root. This is normal — skip these in cleanup scripts.\\n\\n**Also clean these empty/dead directories if present:**\\n- `pairing/`, `plans/`, `images/`, `output/`, `templates/` (often left empty after setup)\\n- `webui-mvp/` (superseded by `webui/`)\\n- `chroma/` (empty after dummy DB removal)\\n- `forget_me_not/` vs `forget-me-not/` — only ONE should exist; delete the older one\\n\\n**Manual cleanup command (TOTALLY SAFE — dry-run first):**\\n```bash\\n# Check first\\nls -la ~/.hermes/state.db.corrupt* 2>/dev/null\\nls -d ~/.hermes/{pairing,plans,images,output,templates,webui-mvp,chroma} 2>/dev/null\\n# Remove corrupt DBs\\nrm ~/.hermes/state.db.corrupt ~/.hermes/state.db.corrupt-backup\\n# Remove empty dirs\\nfor d in pairing plans images output templates webui-mvp chroma; do [ -d \\\"$HOME/.hermes/$d\\\" ] && rmdir \\\"$HOME/.hermes/$d\\\" 2>/dev/null; done\\n```\\n\\n## Known Issue: Gateway pgrep False Negative (macOS)\\n\\nThe Gateway health check (`check_hermes_gateway()`) uses `pgrep -f 'hermes gateway run'` to detect the running process. On macOS, `pgrep` intermittently returns exit code 1 (no match) even when the process IS running and visible via `ps aux`. This causes:\\n\\n1. Housekeeping reports \\\"Gateway: DOWN - restart failed\\\" → **false negative**\\n2. Restart attempt fails because `hermes gateway run` correctly detects the existing instance and refuses to start a duplicate\\n\\n**Diagnosis:** If housekeeping reports Gateway DOWN, always verify with:\\n```bash\\nps aux | grep 'hermes gateway run' | grep -v grep\\n```\\nIf the process appears in `ps` output but `pgrep` returns 1, it's a false negative — Gateway is healthy.\\n\\n**Fix for housekeeping.py:** Replace the `pgrep` check in `check_hermes_gateway()` with:\\n```python\\nresult = subprocess.run(\\n [\\\"ps\\\", \\\"aux\\\"], capture_output=True, text=True, timeout=5\\n)\\nif \\\"hermes gateway run\\\" in result.stdout and \\\"grep\\\" not in [line for line in result.stdout.split('\\\\n') if 'hermes gateway run' in line]:\\n # Gateway is running\\n```\\nOr add a retry with `ps aux | grep` as fallback after the initial `pgrep` attempt.\\n\\n## Troubleshooting\\n\\n- **Gateway reported DOWN but actually running:** See \\\"Known Issue: Gateway pgrep False Negative\\\" above\\n- **ChromaDB won't start:** Check `~/.hermes/chroma_db/server.log` and `server_error.log`\\n- **state.db won't shrink:** VACUUM requires no active connections; stop gateway first\\n- **Housekeeping cronjob not running:** Check `hermes cron list` and verify job is enabled\\n\", \"path\": \"devops/hermes-housekeeping-maintenance/SKILL.md\", \"skill_dir\": \"/Users/rose/.hermes/skills/devops/hermes-housekeeping-maintenance\", \"linked_files\": null, \"usage_hint\": null, \"required_environment_variables\": [], \"required_commands\": [], \"missing_required_environment_variables\": [], \"missing_credential_files\": [], \"missing_required_commands\": [], \"setup_needed\": false, \"setup_skipped\": false, \"readiness_status\": \"available\"}",
|
||
"tool_call_id": "call_function_ladkumh4bf96_1",
|
||
"timestamp": 1776371909
|
||
},
|
||
{
|
||
"role": "assistant",
|
||
"content": "",
|
||
"tool_calls": [
|
||
{
|
||
"id": "call_function_ludukrcv8aer_1",
|
||
"call_id": "call_function_ludukrcv8aer_1",
|
||
"response_item_id": "fc_function_ludukrcv8aer_1",
|
||
"type": "function",
|
||
"function": {
|
||
"name": "skill_view",
|
||
"arguments": "{\"name\": \"rose-memory-chromadb-sync\"}"
|
||
}
|
||
}
|
||
],
|
||
"timestamp": 1776371909
|
||
},
|
||
{
|
||
"role": "tool",
|
||
"content": "{\"success\": true, \"name\": \"rose-memory-chromadb-sync\", \"description\": \"Vollständiges autonomes Memory-System: ChromaDB (Index) + Vault (Source of Truth) + Session Extraktion\", \"tags\": [], \"related_skills\": [], \"content\": \"---\\nname: rose-memory-chromadb-sync\\ncategory: memory-system\\ndescription: \\\"Vollständiges autonomes Memory-System: ChromaDB (Index) + Vault (Source of Truth) + Session Extraktion\\\"\\nauthor: Rose\\nversion: 2.0\\ncreated: 2026-04-13T15:00:00Z\\nupdated: 2026-04-15T12:15:00Z\\n---\\n\\n# Rose's Memory - Vollständiges Autonomes System\\n\\n## Architektur: 3-Tier Biomimetisches Gedächtnis\\n\\n```\\n┌─────────────────────────────────────────────────────────────┐\\n│ TIER 1: KURZZEIT (Built-in Memory) │\\n│ ~2200 chars, in jeden Prompt injiziert │\\n│ Aktuelle, wichtige Fakten │\\n├─────────────────────────────────────────────────────────────┤\\n│ TIER 2: MITTELFRISTIG (ChromaDB) │\\n│ Port 8000, Vektor-Datenbank │\\n│ SEMANTISCHER INDEX — zeigt WO im Vault die Info ist │\\n├─────────────────────────────────────────────────────────────┤\\n│ TIER 3: LANGFRISTIG (Vault) │\\n│ ~/.hermes/memory/topics/*.md │\\n│ SOURCE OF TRUTH — echte Fakten, git-tracked │\\n└─────────────────────────────────────────────────────────────┘\\n```\\n\\n**WICHTIG:** ChromaDB ist der INDEX (wo?), Vault ist die SOURCE OF TRUTH (was?). Suche geht IMMER über ChromaDB, liest dann Content aus Vault.\\n\\n## Komponenten\\n\\n### 1. memory_pipeline.py (NEU - Vollständiger Autonomous Flow)\\n**Pfad:** `~/.hermes/hermes-agent/tools/memory_pipeline.py`\\n\\n```bash\\n# Die 3 Schritte:\\npython tools/memory_pipeline.py --extract # Session → ChromaDB\\npython tools/memory_pipeline.py --promote # ChromaDB → Vault \\npython tools/memory_pipeline.py --sync # Vault → ChromaDB\\npython tools/memory_pipeline.py --full-flow # Alle 3 zusammen\\npython tools/memory_pipeline.py --search \\\"query\\\" # Semantische Suche\\n```\\n\\n### 2. sync_memory_to_chromadb.py (älter, nur Sync)\\n**Pfad:** `~/.hermes/hermes-agent/tools/sync_memory_to_chromadb.py`\\n\\nNur Vault → ChromaDB Sync. Für neue Installationen preferiere memory_pipeline.py.\\n\\n## File Locations\\n\\n```\\n~/.hermes/chroma_db/ # ChromaDB Persistent Storage (NICHT ~/.hermes/memory/)\\n~/.hermes/memory/ # Markdown Vault\\n ├── topics/*.md # Fakten als Markdown\\n ├── config.yaml # Such-Konfiguration\\n └── MEMORY_ARCHITECTURE.md # Architektur-Dokumentation\\n~/.hermes/hermes-agent/tools/\\n ├── memory_pipeline.py # NEU: Vollständiger Pipeline\\n ├── sync_memory_to_chromadb.py # Sync Script\\n └── search_memory_tool.py # Hermes Tool Integration\\n~/.hermes/sessions/ # Session Files (für Extraktion)\\n```\\n\\n## Autonomer Flow (Alle 4 Stunden via Cron)\\n\\n```\\nSESSIONS → [Qwen LLM Extraktion] → CHROMADB\\n ↓\\n [confidence > 0.85]\\n ↓\\n VAULT (Markdown)\\n ↓\\n VAULT → CHROMADB Sync\\n```\\n\\n## CRITICAL: Qwen Thinking Mode Problem\\n\\n**Problem (FIXED):** Qwen 3.5 35B produziert Thinking Blocks die das JSON unterbrechen.\\n\\n**Solution (implemented):**\\n1. `strip_qwen_thinking_block()` — entfernt `<think>...</think>` XML Tags UND \\\"Thinking Process:\\\" Text\\n2. `extract_json_flexible()` — parst Qwen's malformed JSON (erstes Item oft ohne `{topic}` Wrapper)\\n3. ChromaDB Fix — leere Listen `[]` schlagen fehl, müssen `[\\\"\\\"]` sein\\n4. Batch-Modus — 10 Sessions pro LLM-Call, ~3.5s/Session (vs 44-116s einzeln)\\n\\n**Batch-Extraktion funktioniert stabil!**\\n- 10 Sessions pro API-Call\\n- ~3.5s pro Session\\n- 340 Sessions = ~20 Minuten\\n\\n## Such-Flow (Korrekt)\\n\\n```\\nUser Query → ChromaDB (semantisch) → Vault Path → Lese Vault Content → Zeige\\n```\\n\\n**WICHTIG:** Suche MUSS tatsächlichen Vault Content lesen, nicht nur ChromaDB Document. Das Document in ChromaDB ist nur der searchable Text (aliases + content). Der volle Content kommt aus dem Vault File.\\n\\n## Qwen Thinking Mode — Technische Fixes\\n\\n**Problem:** Qwen 3.5 hat Thinking HARDCODED — keine API-Parameter schalten es ab.\\n\\n**Symptom:** LLM Antwort beginnt mit `<think> ...Thinking Process... $]` BLOCK, JSON kommt erst DANACH am Ende. Bei `max_tokens=2000` wird JSON abgeschnitten.\\n\\n**Fix 1 — Thinking Stripping:**\\n```python\\n# Entfernt XML <think> Tags\\ncontent = re.sub(r'<think>.*?</think>', '', raw, flags=re.DOTALL).strip()\\n\\n# Entfernt \\\"Thinking Process:\\\" Text davor\\ncontent = re.sub(\\n r'^Thinking Process:.*?(?=\\\\n(?:Now let me|\\\\[\\\\s*\\\\{))',\\n '', content, flags=re.DOTALL | re.MULTILINE\\n).strip()\\n```\\n\\n**Fix 2 — Robuster JSON Parser (`extract_json_flexible`):**\\n\\nQwen produziert oft MALFORMED JSON:\\n```json\\n[\\n \\\"content\\\": \\\"Some text without topic wrapper...\\\", // ← INVALID\\n },\\n {\\n \\\"topic\\\": \\\"Valid Object\\\", // ← Nur Objekte MIT \\\"topic\\\" sind gültig\\n ...\\n }\\n]\\n```\\n\\nDer Parser sucht alle `\\\"topic\\\": \\\"...\\\"` Patterns und extrahiert das umschliessende `{ ... }` Objekt:\\n```python\\ntopic_pattern = re.compile(r'\\\"topic\\\":\\\\s*\\\"([^\\\"]+)\\\"')\\nfor topic_match in topic_pattern.finditer(content):\\n # Finde öffnendes { das dieses \\\"topic\\\" einschliesst\\n # Parse das { ... } Block als JSON\\n```\\n\\n**Fix 3 — ChromaDB Metadata Bug:**\\n\\nChromaDB akzeptiert KEINE leeren Listen in Metadata:\\n```python\\n# SCHLECHT — HTTP 400 Error\\n\\\"aliases\\\": []\\n\\n# GUT — funktioniert\\n\\\"aliases\\\": [\\\"\\\"] if aliases else [\\\"\\\"]\\n\\\"tags\\\": [\\\"\\\"] if tags else [\\\"\\\"]\\n```\\n\\n## Batch-Extraktion — Performance\\n\\n**Problem:** 146 Sessions × 44-116s = 2+ Stunden (zu langsam)\\n\\n**Lösung:** 10 Sessions pro LLM-Call:\\n- Rate: ~3.5s/Session statt 44-116s\\n- 340 Sessions = ~20 Minuten\\n\\n**Prompt (kurz halten für Qwen):**\\n```\\nExtract facts from this conversation. JSON array only.\\nFormat: [{\\\"topic\\\": \\\"...\\\", \\\"content\\\": \\\"...\\\", \\\"tags\\\": [], \\\"aliases\\\": [], \\\"confidence\\\": 0.9}]\\n\\n{Sessions}\\n\\nJSON:\\n```\\n\\n## search_memory_tool Registration — Bug Fixes\\n\\n**Problem:** `search_memory` war nicht als Tool verfügbar obwohl Code existierte.\\n\\n**Ursache 1:** Nicht in `toolsets.py` `_HERMES_CORE_TOOLS`:\\n```python\\n\\\"search_memory\\\", # Fehlte!\\n```\\n\\n**Ursache 2:** Nicht in `model_tools.py` Import-Liste:\\n```python\\n\\\"tools.search_memory_tool\\\", # Fehlte!\\n```\\n\\n**Ursache 3:** `@registry.command` Decorator in `search_memory_tool.py` war INVALID (existiert nicht im Registry) — mussten wir entfernen.\\n\\n**Achtung:** Nach Änderungen an `toolsets.py` oder `model_tools.py` → Hermes neustarten.\\n\\n## Pitfalls & Notes\\n\\n**DO:**\\n- ChromaDB läuft auf Port 8000\\n- Health Check nutzt `~/.hermes/chroma_db/` (NICHT `~/.hermes/memory/`)\\n- Suche liest Vault Content für vollständige Info\\n- Confidence > 0.85 für Vault Promotion\\n- Cron-Job nutzt `--full-flow` (nicht nur `--extract`!)\\n\\n**DON'T:**\\n- Niemals Vault Files direkt editieren ohne Sync hinterher\\n- ChromaDB nicht manuell editieren (nur via API)\\n- Extraktion mit Qwen Thinking Mode (timeouts)\\n- Keine leeren Listen `[]` in ChromaDB Metadata — immer `[\\\"\\\"]` fallback\\n\\n## Gefundene Bugs (Trial & Error)\\n\\n### 1. search_memory Tool nicht registriert\\n**Symptom:** Tool existiert aber `/search` funktioniert nicht\\n**Ursachen:**\\n- Nicht in `toolsets.py` → `_HERMES_CORE_TOOLS` (fehlte in Liste)\\n- Nicht in `model_tools.py` → Import-Liste (fehlte)\\n- `@registry.command` Decorator in `search_memory_tool.py` war INVALID → Import brach ab\\n\\n**Fix in toolsets.py:**\\n```python\\n#search_memory in _HERMES_CORE_TOOLS hinzufügen\\n\\\"search_memory\\\",\\n```\\n\\n**Fix in model_tools.py:**\\n```python\\n#In _discover_tools() Import-Liste:\\n\\\"tools.search_memory_tool\\\",\\n```\\n\\n**Fix in search_memory_tool.py:**\\n```python\\n# Den @registry.command Decorator + search_memory_command entfernen\\n# (war fehlerhaft und wird nicht gebraucht)\\n```\\n\\n### 2. Cron-Job speichert nicht in Vault\\n**Symptom:** ChromaDB hat Facts aber Vault bleibt leer\\n**Ursache:** `--extract` macht NUR Extraktion, kein Promotion\\n**Fix:** `--full-flow` nutzen (Extraktion + Promotion + Sync)\\n\\n### 3. ChromaDB Upsert HTTP 400\\n**Symptom:** `chromadb.errors.InvalidArgumentException: empty list not allowed`\\n**Ursache:** ChromaDB akzeptiert keine leeren Listen in Metadata\\n**Fix in memory_pipeline.py:**\\n```python\\nmetadata = {\\n \\\"tags\\\": tags if tags else [\\\"\\\"], # Nie []\\n \\\"aliases\\\": aliases if aliases else [\\\"\\\"], # Nie []\\n ...\\n}\\n```\\n\\n### 4. Qwen Thinking produziert malformed JSON\\n**Symptom:** JSON Parser findet keine Facts obwohl LLM welche extrahiert hat\\n**Ursache:** Qwen 3.5 hat HARDCODED Thinking — kein API-Parameter schaltet es ab\\n**Fix:** `extract_json_flexible()` sucht nach `\\\"topic\\\": \\\"...\\\"` Patterns und extrahiert das umschliessende `{...}` Objekt\\n\\n## Gefundene Bugs (Trial & Error) — April 2026 Update\\n\\n### 5. Promotion nutzt fact_id statt meta.topic\\n**Symptom:** Facts werden nicht promoted obwohl confidence > 0.85\\n**Ursache:** Promotion nutzte `fact_id` (z.B. \\\"fact-docker-server\\\") statt `meta.get(\\\"topic\\\")` (\\\"docker-server\\\") um Vault-Path zu prüfen\\n**Fix in memory_pipeline.py:**\\n```python\\n# FALSCH:\\ntopic = fact_id\\nvault_path = TOPICS_PATH / f\\\"{topic}.md\\\"\\n\\n# RICHTIG:\\ntopic = meta.get(\\\"topic\\\", fact_id)\\nvault_path = TOPICS_PATH / f\\\"{topic}.md\\\"\\n```\\n\\n### 6. HTTP 400 Retry Logic\\n**Symptom:** Extraktion bricht bei HTTP 400 ab, keine Facts werden extrahiert\\n**Ursache:** Keine Retry-Logik bei transienten LM Studio Fehlern\\n**Fix in extract_batch_facts():**\\n```python\\nmax_retries = 3\\nretry_delay = 5\\nfor attempt in range(max_retries):\\n try:\\n # API call...\\n except urllib.error.HTTPError as e:\\n if e.code == 400 and attempt < max_retries - 1:\\n print(f\\\" Retry {attempt+1}/{max_retries}...\\\")\\n time.sleep(retry_delay)\\n continue\\n```\\n\\n### 7. Vault Promotion schreibt nur Frontmatter ohne Content\\n**Symptom:** Vault Files existieren aber haben nur YAML Frontmatter, kein Content\\n**Ursache:** `promote_high_confidence_facts()` schrieb nur `frontmatter` Variable, nicht den extrahierten `content`\\n**Fix:**\\n```python\\nfull_content = f\\\"\\\"\\\"{frontmatter}\\n\\n{content}\\n\\\"\\\"\\\"\\nwith open(vault_path, \\\"w\\\") as f:\\n f.write(full_content) # Nicht nur frontmatter!\\n```\\n\\n## Nightly Pipeline — Operational Runbook (April 2026)\\n\\n### CRITICAL: Don't use `--full-flow` in Cron Jobs\\n\\n`--full-flow` runs all 3 steps in one process. This reliably **times out after 5 minutes** because the embedding model (`all-MiniLM-L6-v2`) takes ~30s to load and extraction can be slow with many sessions.\\n\\n**Instead, run steps individually with proper timeouts:**\\n\\n```bash\\n# Step 1: Extract (allow 120s)\\ncd /Users/rose/.hermes/hermes-agent && source venv/bin/activate\\npython tools/memory_pipeline.py --extract\\n\\n# Step 2: Promote (allow 60s)\\npython tools/memory_pipeline.py --promote\\n\\n# Step 3: Sync (allow 180s — embedding model loading)\\npython tools/memory_pipeline.py --sync\\n```\\n\\n### Before Running: Kill Stuck Processes\\n\\nOld `memory_pipeline.py --extract` processes can accumulate and block new runs:\\n```bash\\npkill -f \\\"memory_pipeline.py\\\"\\n# Verify:\\nps aux | grep memory_pipeline | grep -v grep\\n```\\n\\n### Step 2 Fails Silently on Missing Directories\\n\\n**Symptom:** Promotion reports 0 facts promoted despite high-confidence facts existing.\\n**Cause:** Pipeline tries to write files like `topics/mission-control-ui/ux.md` but the parent directory doesn't exist.\\n**Fix:** Create missing topic directories before promotion:\\n```bash\\nmkdir -p ~/.hermes/memory/topics/<topic-name>\\n```\\nThe pipeline does NOT auto-create parent directories. After fixing dirs, re-run `--promote`.\\n\\n### ChromaDB Collection Name\\n\\nThe collection is **`rose_memory`**, NOT `facts`. Using `get_collection(name='facts')` throws `NotFoundError`:\\n```python\\n# CORRECT:\\ncollection = client.get_collection(name='rose_memory')\\nprint(collection.count()) # Should show ~351+\\n```\\n\\n### Vault File Count vs ChromaDB Count\\n\\n- Vault has ~349 markdown files (flat `topics/*.md` + subdirectories)\\n- ChromaDB `rose_memory` collection has ~351 items\\n- Discrepancy is normal — promotion adds facts to ChromaDB before writing to vault\\n- After `--sync`, vault files are re-synced to ChromaDB (345 files)\\n\\n### Step-by-Step Execution via execute_code\\n\\nWhen running via Hermes `execute_code`, use individual `terminal()` calls per step with appropriate timeouts:\\n```python\\nfrom hermes_tools import terminal\\n\\n# Step 1 (timeout=120)\\nterminal(command=\\\"cd ... && python tools/memory_pipeline.py --extract\\\", timeout=120)\\n\\n# Step 2 (timeout=60)\\nterminal(command=\\\"cd ... && python tools/memory_pipeline.py --promote\\\", timeout=60)\\n\\n# Step 3 (timeout=180 — model loading takes time)\\nterminal(command=\\\"cd ... && python tools/memory_pipeline.py --sync\\\", timeout=180)\\n```\\n\\n## Cron-Jobs Übersicht\\n\\n| Job ID | Schedule | Script | Status |\\n|--------|---------|--------|--------|\\n| ecd1da0f1d95 | `0 0 * * *` | `memory_pipeline.py --full-flow` | ⚠️ Use step-by-step instead |\\n| Memory Health Check | `*/15 * * * *` | `housekeeping.py` | ✅ Aktiv |\\n| Housekeeping | `90031c503f0b` | every 15m | ✅ Aktiv |\\n\", \"path\": \"rose-memory-chromadb-sync/SKILL.md\", \"skill_dir\": \"/Users/rose/.hermes/skills/rose-memory-chromadb-sync\", \"linked_files\": {\"scripts\": [\"scripts/sync_memory_to_chromadb.py\", \"scripts/search_memory.py\"]}, \"usage_hint\": \"To view linked files, call skill_view(name, file_path) where file_path is e.g. 'references/api.md' or 'assets/config.yaml'\", \"required_environment_variables\": [], \"required_commands\": [], \"missing_required_environment_variables\": [], \"missing_credential_files\": [], \"missing_required_commands\": [], \"setup_needed\": false, \"setup_skipped\": false, \"readiness_status\": \"available\"}",
|
||
"tool_call_id": "call_function_ludukrcv8aer_1",
|
||
"timestamp": 1776371909
|
||
},
|
||
{
|
||
"role": "assistant",
|
||
"content": "",
|
||
"tool_calls": [
|
||
{
|
||
"id": "call_function_8t2tuffsyzzx_1",
|
||
"call_id": "call_function_8t2tuffsyzzx_1",
|
||
"response_item_id": "fc_function_8t2tuffsyzzx_1",
|
||
"type": "function",
|
||
"function": {
|
||
"name": "search_files",
|
||
"arguments": "{\"output_mode\": \"files_only\", \"pattern\": \"memory_pipeline.py\"}"
|
||
}
|
||
}
|
||
],
|
||
"timestamp": 1776371909
|
||
},
|
||
{
|
||
"role": "tool",
|
||
"content": "{\"total_count\": 0}",
|
||
"tool_call_id": "call_function_8t2tuffsyzzx_1",
|
||
"timestamp": 1776371909
|
||
},
|
||
{
|
||
"role": "assistant",
|
||
"content": "",
|
||
"tool_calls": [
|
||
{
|
||
"id": "call_function_ts4m4pgdwxml_1",
|
||
"call_id": "call_function_ts4m4pgdwxml_1",
|
||
"response_item_id": "fc_function_ts4m4pgdwxml_1",
|
||
"type": "function",
|
||
"function": {
|
||
"name": "search_files",
|
||
"arguments": "{\"output_mode\": \"files_only\", \"pattern\": \"memory_pipeline\"}"
|
||
}
|
||
}
|
||
],
|
||
"timestamp": 1776371909
|
||
},
|
||
{
|
||
"role": "tool",
|
||
"content": "{\"total_count\": 0}",
|
||
"tool_call_id": "call_function_ts4m4pgdwxml_1",
|
||
"timestamp": 1776371909
|
||
},
|
||
{
|
||
"role": "assistant",
|
||
"content": "",
|
||
"tool_calls": [
|
||
{
|
||
"id": "call_function_2makxfp4zfqt_1",
|
||
"call_id": "call_function_2makxfp4zfqt_1",
|
||
"response_item_id": "fc_function_2makxfp4zfqt_1",
|
||
"type": "function",
|
||
"function": {
|
||
"name": "terminal",
|
||
"arguments": "{\"command\": \"find /Users/rose/.hermes -name \\\"memory_pipeline.py\\\" 2>/dev/null; find /Users/rose -name \\\"memory_pipeline.py\\\" 2>/dev/null | head -5\"}"
|
||
}
|
||
}
|
||
],
|
||
"timestamp": 1776371909
|
||
},
|
||
{
|
||
"role": "tool",
|
||
"content": "{\"output\": \"\", \"exit_code\": 0, \"error\": null}",
|
||
"tool_call_id": "call_function_2makxfp4zfqt_1",
|
||
"timestamp": 1776371909
|
||
},
|
||
{
|
||
"role": "assistant",
|
||
"content": "",
|
||
"tool_calls": [
|
||
{
|
||
"id": "call_function_43o45yltc25w_1",
|
||
"call_id": "call_function_43o45yltc25w_1",
|
||
"response_item_id": "fc_function_43o45yltc25w_1",
|
||
"type": "function",
|
||
"function": {
|
||
"name": "terminal",
|
||
"arguments": "{\"command\": \"ls -la /Users/rose/.hermes/hermes-agent/tools/ 2>/dev/null | head -30\"}"
|
||
}
|
||
}
|
||
],
|
||
"timestamp": 1776371909
|
||
},
|
||
{
|
||
"role": "tool",
|
||
"content": "{\"output\": \"total 3120\\n-rw-r--r-- 1 rose staff 726 Apr 3 11:55 __init__.py\\ndrwxr-xr-x 55 rose staff 1760 Apr 16 13:42 __pycache__\\ndrwxr-xr-x 61 rose staff 1952 Apr 16 13:42 .\\ndrwxr-xr-x 83 rose staff 2656 Apr 16 13:42 ..\\n-rw-r--r-- 1 rose staff 1784 Apr 3 11:55 ansi_strip.py\\n-rw-r--r-- 1 rose staff 37911 Apr 15 15:21 approval.py\\n-rw-r--r-- 1 rose staff 1561 Apr 8 21:16 binary_extensions.py\\n-rw-r--r-- 1 rose staff 1588 Apr 3 11:55 browser_camofox_state.py\\n-rw-r--r-- 1 rose staff 21410 Apr 16 13:42 browser_camofox.py\\ndrwxr-xr-x 8 rose staff 256 Apr 14 20:35 browser_providers\\n-rw-r--r-- 1 rose staff 95227 Apr 16 13:42 browser_tool.py\\n-rw-r--r-- 1 rose staff 2032 Apr 8 21:16 budget_config.py\\n-rw-r--r-- 1 rose staff 22604 Apr 12 14:29 checkpoint_manager.py\\n-rw-r--r-- 1 rose staff 4955 Apr 8 11:10 clarify_tool.py\\n-rw-r--r-- 1 rose staff 53126 Apr 16 13:42 code_execution_tool.py\\n-rw-r--r-- 1 rose staff 14938 Apr 12 14:29 credential_files.py\\n-rw-r--r-- 1 rose staff 20752 Apr 15 15:21 cronjob_tools.py\\n-rw-r--r-- 1 rose staff 3701 Apr 8 11:10 debug_helpers.py\\n-rw-r--r-- 1 rose staff 48235 Apr 16 13:42 delegate_tool.py\\n-rw-r--r-- 1 rose staff 3550 Apr 14 09:40 env_passthrough.py\\ndrwxr-xr-x 14 rose staff 448 Apr 16 13:42 environments\\n-rw-r--r-- 1 rose staff 47687 Apr 14 09:40 file_operations.py\\n-rw-r--r-- 1 rose staff 37374 Apr 14 09:40 file_tools.py\\n-rw-r--r-- 1 rose staff 21031 Apr 12 14:29 fuzzy_match.py\\n-rw-r--r-- 1 rose staff 18000 Apr 14 09:40 homeassistant_tool.py\\n-rw-r--r-- 1 rose staff 27252 Apr 14 09:40 image_generation_tool.py\\n-rw-r--r-- 1 rose staff 2638 Apr 12 14:29 interrupt.py\\n-rw-r--r-- 1 rose staff 5424 Apr 3 11:55 managed_tool_gateway.py\\n-rw-r--r-- 1 rose staff 17356 Apr 12 14:29 mcp_oauth.py\", \"exit_code\": 0, \"error\": null}\n\n[Subdirectory context discovered: hermes-agent/AGENTS.md]\n# Hermes Agent - Development Guide\n\nInstructions for AI coding assistants and developers working on the hermes-agent codebase.\n\n## Development Environment\n\n```bash\nsource venv/bin/activate # ALWAYS activate before running Python\n```\n\n## Project Structure\n\n```\nhermes-agent/\n├── run_agent.py # AIAgent class — core conversation loop\n├── model_tools.py # Tool orchestration, discover_builtin_tools(), handle_function_call()\n├── toolsets.py # Toolset definitions, _HERMES_CORE_TOOLS list\n├── cli.py # HermesCLI class — interactive CLI orchestrator\n├── hermes_state.py # SessionDB — SQLite session store (FTS5 search)\n├── agent/ # Agent internals\n│ ├── prompt_builder.py # System prompt assembly\n│ ├── context_compressor.py # Auto context compression\n│ ├── prompt_caching.py # Anthropic prompt caching\n│ ├── auxiliary_client.py # Auxiliary LLM client (vision, summarization)\n│ ├── model_metadata.py # Model context lengths, token estimation\n│ ├── models_dev.py # models.dev registry integration (provider-aware context)\n│ ├── display.py # KawaiiSpinner, tool preview formatting\n│ ├── skill_commands.py # Skill slash commands (shared CLI/gateway)\n│ └── trajectory.py # Trajectory saving helpers\n├── hermes_cli/ # CLI subcommands and setup\n│ ├── main.py # Entry point — all `hermes` subcommands\n│ ├── config.py # DEFAULT_CONFIG, OPTIONAL_ENV_VARS, migration\n│ ├── commands.py # Slash command definitions + SlashCommandCompleter\n│ ├── callbacks.py # Terminal callbacks (clarify, sudo, approval)\n│ ├── setup.py # Interactive setup wizard\n│ ├── skin_engine.py # Skin/theme engine — CLI visual customization\n│ ├── skills_config.py # `hermes skills` — enable/disable skills per platform\n│ ├── tools_config.py # `hermes tools` — enable/disable tools per platform\n│ ├── skills_hub.py # `/skills` slash command (search, browse, install)\n│ ├── models.py # Model catalog, provider model lists\n│ ├── model_switch.py # Shared /model switch pipeline (CLI + gateway)\n│ └── auth.py # Provider credential resolution\n├── tools/ # Tool implementations (one file per tool)\n│ ├── registry.py # Central tool registry (schemas, handlers, dispatch)\n│ ├── approval.py # Dangerous command detection\n│ ├── terminal_tool.py # Terminal orchestration\n│ ├── process_registry.py # Background process management\n│ ├── file_tools.py # File read/write/search/patch\n│ ├── web_tools.py # Web search/extract (Parallel + Firecrawl)\n│ ├── browser_tool.py # Browserbase browser automation\n│ ├── code_execution_tool.py # execute_code sandbox\n│ ├── delegate_tool.py # Subagent delegation\n│ ├── mcp_tool.py # MCP client (~1050 lines)\n│ └── environments/ # Terminal backends (local, docker, ssh, modal, daytona, singularity)\n├── gateway/ # Messaging platform gateway\n│ ├── run.py # Main loop, slash commands, message dispatch\n│ ├── session.py # SessionStore — conversation persistence\n│ └── platforms/ # Adapters: telegram, discord, slack, whatsapp, homeassistant, signal, qqbot\n├── acp_adapter/ # ACP server (VS Code / Zed / JetBrains integration)\n├── cron/ # Scheduler (jobs.py, scheduler.py)\n├── environments/ # RL training environments (Atropos)\n├── tests/ # Pytest suite (~3000 tests)\n└── batch_runner.py # Parallel batch processing\n```\n\n**User config:** `~/.hermes/config.yaml` (settings), `~/.hermes/.env` (API keys)\n\n## File Dependency Chain\n\n```\ntools/registry.py (no deps — imported by all tool files)\n ↑\ntools/*.py (each calls registry.register() at import time)\n ↑\nmodel_tools.py (imports tools/registry + triggers tool discovery)\n ↑\nrun_agent.py, cli.py, batch_runner.py, environments/\n```\n\n---\n\n## AIAgent Class (run_agent.py)\n\n```python\nclass AIAgent:\n def __init__(self,\n model: str = \"anthropic/claude-opus-4.6\",\n max_iterations: int = 90,\n enabled_toolsets: list = None,\n disabled_toolsets: list = None,\n quiet_mode: bool = False,\n save_trajectories: bool = False,\n platform: str = None, # \"cli\", \"telegram\", etc.\n session_id: str = None,\n skip_context_files: bool = False,\n skip_memory: bool = False,\n # ... plus provider, api_mode, callbacks, routing params\n ): ...\n\n def chat(self, message: str) -> str:\n \"\"\"Simple interface — returns final response string.\"\"\"\n\n def run_conversation(self, user_message: str, system_message: str = None,\n conversation_history: list = None, task_id: str = None) -> dict:\n \"\"\"Full interface — returns dict with final_response + messages.\"\"\"\n```\n\n### Agent Loop\n\nThe core loop is inside `run_conversation()` — entirely synchronous:\n\n```python\nwhile api_call_count < self.max_iterations and self.iteration_budget.remaining > 0:\n response = client.chat.completions.create(model=model, messages=messages, tools=tool_schemas)\n if response.tool_calls:\n for tool_call in response.tool_calls:\n result = handle_function_call(tool_call.name, tool_call.args, task_id)\n messages.append(tool_result_message(result))\n api_call_count += 1\n else:\n return response.content\n```\n\nMessages follow OpenAI format: `{\"role\": \"system/user/assistant/tool\", ...}`. Reasoning content is stored in `assistant_msg[\"reasoning\"]`.\n\n---\n\n## CLI Architecture (cli.py)\n\n- **Rich** for banner/panels, **prompt_toolkit** for input with autocomplete\n- **KawaiiSpinner** (`agent/display.py`) — animated faces during API calls, `┊` activity feed for tool results\n- `load_cli_config()` in cli.py merges hardcoded defaults + user config YAML\n- **Skin engine** (`hermes_cli/skin_engine.py`) — data-driven CLI theming; initialized from `display.skin` config key at startup; skins customize banner colors, spinner faces/verbs/wings, tool prefix, response box, branding text\n- `process_command()` is a method on `HermesCLI` — dispatches on canonical command name resolved via `resolve_command()` from the central registry\n- Skill slash commands: `agent/skill_commands.py` scans `~/.hermes/skills/`, injects as **user message** (not system prompt) to preserve prompt caching\n\n### Slash Command Registry (`hermes_cli/commands.py`)\n\nAll slash commands are defined in a central `COMMAND_REGISTRY` list of `CommandDef` objects. Every downstream consumer derives from this registry automatically:\n\n- **CLI** — `process_command()` resolves aliases via `resolve_command()`, dispatches on canonical name\n- **Gateway** — `GATEWAY_KNOWN_COMMANDS` frozenset for hook emission, `resolve_command()` for dispatch\n- **Gateway help** — `gateway_help_lines()` generates `/help` output\n- **Telegram** — `telegram_bot_commands()` generates the BotCommand menu\n- **Slack** — `slack_subcommand_map()` generates `/hermes` subcommand routing\n- **Autocomplete** — `COMMANDS` flat dict feeds `SlashCommandCompleter`\n- **CLI help** — `COMMANDS_BY_CATEGORY` dict feeds `show_help()`\n\n### Adding a Slash Command\n\n1. Add a `CommandDef` entry to `COMMAND_REGISTRY` in `hermes_cli/commands.py`:\n```python\nCommandDef(\"mycommand\", \"Description of what it does\", \"Session\",\n aliases=(\"mc\",), args_hint=\"[arg]\"),\n```\n2. Add handler in `HermesCLI.process_command()` in `cli.py`:\n```python\nelif canonical == \"mycommand\":\n self._handle_mycommand(cmd_original)\n```\n3. If the command is available in the gateway, add a handler in `gateway/run.py`:\n```python\nif canonical == \"mycommand\":\n return await self._handle_mycommand(event)\n```\n4. For persistent settings, use `save_config_value()` in `cli.py`\n\n**CommandDef fields:**\n- `name` — canonical name without slash (e.g. `\"background\"`)\n- `description` — human-readable description\n- `category` — one of `\"Sess\n\n[...truncated AGENTS.md: 20,441 chars total]",
|
||
"tool_call_id": "call_function_43o45yltc25w_1",
|
||
"timestamp": 1776371909
|
||
},
|
||
{
|
||
"role": "assistant",
|
||
"content": "",
|
||
"tool_calls": [
|
||
{
|
||
"id": "call_function_bevw0i3i7upv_1",
|
||
"call_id": "call_function_bevw0i3i7upv_1",
|
||
"response_item_id": "fc_function_bevw0i3i7upv_1",
|
||
"type": "function",
|
||
"function": {
|
||
"name": "terminal",
|
||
"arguments": "{\"command\": \"ls -la /Users/rose/.hermes/scripts/ | grep -i memory\"}"
|
||
}
|
||
}
|
||
],
|
||
"timestamp": 1776371909
|
||
},
|
||
{
|
||
"role": "tool",
|
||
"content": "{\"output\": \"-rw-r--r-- 1 rose staff 6406 Apr 15 13:20 agent_memory.py\\n-rw-r--r-- 1 rose staff 877 Apr 13 15:45 memory_health_wrapper.py\", \"exit_code\": 0, \"error\": null}",
|
||
"tool_call_id": "call_function_bevw0i3i7upv_1",
|
||
"timestamp": 1776371909
|
||
},
|
||
{
|
||
"role": "assistant",
|
||
"content": "",
|
||
"tool_calls": [
|
||
{
|
||
"id": "call_function_mac3uryp0bz0_1",
|
||
"call_id": "call_function_mac3uryp0bz0_1",
|
||
"response_item_id": "fc_function_mac3uryp0bz0_1",
|
||
"type": "function",
|
||
"function": {
|
||
"name": "read_file",
|
||
"arguments": "{\"path\": \"/Users/rose/.hermes/scripts/agent_memory.py\"}"
|
||
}
|
||
}
|
||
],
|
||
"timestamp": 1776371909
|
||
},
|
||
{
|
||
"role": "tool",
|
||
"content": "{\"content\": \" 1|#!/usr/bin/env python3\\n 2|\\\"\\\"\\\"\\n 3|Rose Life-OS — Agent Memory Management\\n 4|======================================\\n 5|Each Tier-2 agent has persistent memory via memory.md files.\\n 6|\\n 7|Usage:\\n 8| python3 agent_memory.py --agent lotus --read\\n 9| python3 agent_memory.py --agent sunflower --add \\\"User prefers index funds over ETFs\\\"\\n 10| python3 agent_memory.py --agent lotus --search \\\"injury\\\"\\n 11| python3 agent_memory.py --agent lotus --clear\\n 12| python3 agent_memory.py --agent lotus --list\\n 13|\\\"\\\"\\\"\\n 14|\\n 15|import argparse\\n 16|import json\\n 17|import os\\n 18|import sys\\n 19|import re\\n 20|from datetime import datetime\\n 21|from pathlib import Path\\n 22|from typing import Optional\\n 23|\\n 24|HERMES_HOME = Path.home() / \\\".hermes\\\"\\n 25|AGENTS_DIR = HERMES_HOME / \\\"agents\\\"\\n 26|\\n 27|def get_memory_path(agent: str) -> Path:\\n 28| \\\"\\\"\\\"Get the memory file path for an agent.\\\"\\\"\\\"\\n 29| return AGENTS_DIR / agent / \\\"memory.md\\\"\\n 30|\\n 31|def read_memory(agent: str) -> dict:\\n 32| \\\"\\\"\\\"Read memory for an agent and parse into structured format.\\\"\\\"\\\"\\n 33| mem_path = get_memory_path(agent)\\n 34| if not mem_path.exists():\\n 35| return {\\\"agent\\\": agent, \\\"entries\\\": [], \\\"last_updated\\\": None}\\n 36| \\n 37| content = mem_path.read_text(encoding=\\\"utf-8\\\")\\n 38| return parse_memory_content(content, agent)\\n 39|\\n 40|def parse_memory_content(content: str, agent: str) -> dict:\\n 41| \\\"\\\"\\\"Parse memory.md content into structured dict.\\\"\\\"\\\"\\n 42| entries = []\\n 43| last_updated = None\\n 44| \\n 45| # Simple format: each non-header line starting with \\\"- \\\" is an entry\\n 46| lines = content.split(\\\"\\\\n\\\")\\n 47| for line in lines:\\n 48| line = line.strip()\\n 49| if line.startswith(\\\"- \\\"):\\n 50| entry = line[2:]\\n 51| # Extract timestamp if present [YYYY-MM-DD]\\n 52| match = re.match(r\\\"\\\\[(\\\\d{4}-\\\\d{2}-\\\\d{2})\\\\] (.+)\\\", entry)\\n 53| if match:\\n 54| entries.append({\\\"date\\\": match.group(1), \\\"fact\\\": match.group(2), \\\"raw\\\": entry})\\n 55| else:\\n 56| entries.append({\\\"date\\\": None, \\\"fact\\\": entry, \\\"raw\\\": entry})\\n 57| \\n 58| # Try to find last_updated\\n 59| update_match = re.search(r\\\"Last updated: (.+)\\\", content)\\n 60| if update_match:\\n 61| last_updated = update_match.group(1)\\n 62| \\n 63| return {\\\"agent\\\": agent, \\\"entries\\\": entries, \\\"last_updated\\\": last_updated}\\n 64|\\n 65|def write_memory(agent: str, entries: list) -> None:\\n 66| \\\"\\\"\\\"Write entries back to memory.md.\\\"\\\"\\\"\\n 67| mem_path = get_memory_path(agent)\\n 68| mem_path.parent.mkdir(parents=True, exist_ok=True)\\n 69| \\n 70| lines = [\\n 71| f\\\"# {agent.title()} — Agent Memory\\\",\\n 72| \\\"\\\",\\n 73| f\\\"Last updated: {datetime.now().strftime('%Y-%m-%d %H:%M')}\\\",\\n 74| \\\"\\\",\\n 75| \\\"## Facts\\\",\\n 76| \\\"\\\"\\n 77| ]\\n 78| \\n 79| for entry in entries:\\n 80| date_str = f\\\"[{entry['date']}] \\\" if entry.get('date') else \\\"\\\"\\n 81| lines.append(f\\\"- {date_str}{entry['fact']}\\\")\\n 82| \\n 83| lines.append(\\\"\\\")\\n 84| mem_path.write_text(\\\"\\\\n\\\".join(lines), encoding=\\\"utf-8\\\")\\n 85|\\n 86|def add_fact(agent: str, fact: str, date: str = None) -> None:\\n 87| \\\"\\\"\\\"Add a new fact to agent's memory.\\\"\\\"\\\"\\n 88| if date is None:\\n 89| date = datetime.now().strftime(\\\"%Y-%m-%d\\\")\\n 90| \\n 91| mem = read_memory(agent)\\n 92| \\n 93| # Check for duplicate\\n 94| for entry in mem[\\\"entries\\\"]:\\n 95| if entry[\\\"fact\\\"] == fact:\\n 96| print(f\\\"Fact already exists: {fact[:50]}...\\\")\\n 97| return\\n 98| \\n 99| mem[\\\"entries\\\"].append({\\\"date\\\": date, \\\"fact\\\": fact, \\\"raw\\\": f\\\"[{date}] {fact}\\\"})\\n 100| write_memory(agent, mem[\\\"entries\\\"])\\n 101| print(f\\\"✓ Added to {agent} memory: {fact[:60]}...\\\")\\n 102|\\n 103|def search_memory(agent: str, query: str) -> list:\\n 104| \\\"\\\"\\\"Search agent's memory for matching entries.\\\"\\\"\\\"\\n 105| mem = read_memory(agent)\\n 106| query_lower = query.lower()\\n 107| results = []\\n 108| \\n 109| for entry in mem[\\\"entries\\\"]:\\n 110| if query_lower in entry[\\\"fact\\\"].lower():\\n 111| results.append(entry)\\n 112| \\n 113| return results\\n 114|\\n 115|def list_memory(agent: str) -> None:\\n 116| \\\"\\\"\\\"List all memory entries for an agent.\\\"\\\"\\\"\\n 117| mem = read_memory(agent)\\n 118| \\n 119| if not mem[\\\"entries\\\"]:\\n 120| print(f\\\" {agent}: No memory entries\\\")\\n 121| return\\n 122| \\n 123| print(f\\\"\\\\n 📋 {agent.upper()} MEMORY ({len(mem['entries'])} entries)\\\")\\n 124| print(f\\\" Last updated: {mem.get('last_updated', 'never')}\\\\n\\\")\\n 125| \\n 126| for i, entry in enumerate(mem[\\\"entries\\\"], 1):\\n 127| date_str = entry.get(\\\"date\\\", \\\"?\\\")\\n 128| print(f\\\" {i}. [{date_str}] {entry['fact']}\\\")\\n 129| print()\\n 130|\\n 131|def clear_memory(agent: str, confirm: bool = False) -> None:\\n 132| \\\"\\\"\\\"Clear all memory for an agent.\\\"\\\"\\\"\\n 133| if not confirm:\\n 134| print(f\\\" Use --confirm to actually clear {agent} memory\\\")\\n 135| return\\n 136| \\n 137| mem_path = get_memory_path(agent)\\n 138| if mem_path.exists():\\n 139| mem_path.unlink()\\n 140| print(f\\\" ✓ Cleared {agent} memory\\\")\\n 141|\\n 142|def export_json(agent: str) -> None:\\n 143| \\\"\\\"\\\"Export memory as JSON.\\\"\\\"\\\"\\n 144| mem = read_memory(agent)\\n 145| print(json.dumps(mem, indent=2, ensure_ascii=False))\\n 146|\\n 147|def main():\\n 148| parser = argparse.ArgumentParser(description=\\\"Rose Agent Memory Management\\\")\\n 149| parser.add_argument(\\\"--agent\\\", \\\"-a\\\", required=True, help=\\\"Agent name\\\")\\n 150| parser.add_argument(\\\"--read\\\", \\\"-r\\\", action=\\\"store_true\\\", help=\\\"Read all memory\\\")\\n 151| parser.add_argument(\\\"--add\\\", help=\\\"Add a fact to memory\\\")\\n 152| parser.add_argument(\\\"--search\\\", \\\"-s\\\", help=\\\"Search memory\\\")\\n 153| parser.add_argument(\\\"--list\\\", \\\"-l\\\", action=\\\"store_true\\\", help=\\\"List all entries\\\")\\n 154| parser.add_argument(\\\"--clear\\\", action=\\\"store_true\\\", help=\\\"Clear all memory\\\")\\n 155| parser.add_argument(\\\"--confirm\\\", action=\\\"store_true\\\", help=\\\"Confirm dangerous actions\\\")\\n 156| parser.add_argument(\\\"--export\\\", \\\"-e\\\", action=\\\"store_true\\\", help=\\\"Export as JSON\\\")\\n 157| parser.add_argument(\\\"--date\\\", \\\"-d\\\", help=\\\"Date for entry (default: today)\\\")\\n 158| \\n 159| args = parser.parse_args()\\n 160| \\n 161| if args.clear:\\n 162| clear_memory(args.agent, args.confirm)\\n 163| elif args.read:\\n 164| mem = read_memory(args.agent)\\n 165| if mem[\\\"entries\\\"]:\\n 166| list_memory(args.agent)\\n 167| else:\\n 168| print(f\\\" {args.agent}: No memory entries\\\")\\n 169| elif args.list:\\n 170| list_memory(args.agent)\\n 171| elif args.add:\\n 172| add_fact(args.agent, args.add, args.date)\\n 173| elif args.search:\\n 174| results = search_memory(args.agent, args.search)\\n 175| if results:\\n 176| print(f\\\"\\\\n 🔍 Search results for '{args.search}':\\\\n\\\")\\n 177| for entry in results:\\n 178| print(f\\\" [{entry.get('date', '?')}] {entry['fact']}\\\")\\n 179| print()\\n 180| else:\\n 181| print(f\\\" No entries matching: {args.search}\\\")\\n 182| elif args.export:\\n 183| export_json(args.agent)\\n 184| else:\\n 185| parser.print_help()\\n 186|\\n 187|if __name__ == \\\"__main__\\\":\\n 188| main()\\n 189|\", \"total_lines\": 188, \"file_size\": 6406, \"truncated\": false, \"is_binary\": false, \"is_image\": false}",
|
||
"tool_call_id": "call_function_mac3uryp0bz0_1",
|
||
"timestamp": 1776371909
|
||
},
|
||
{
|
||
"role": "assistant",
|
||
"content": "",
|
||
"tool_calls": [
|
||
{
|
||
"id": "call_function_ekrs57cb6pb0_1",
|
||
"call_id": "call_function_ekrs57cb6pb0_1",
|
||
"response_item_id": "fc_function_ekrs57cb6pb0_1",
|
||
"type": "function",
|
||
"function": {
|
||
"name": "read_file",
|
||
"arguments": "{\"limit\": 50, \"path\": \"/Users/rose/.hermes/cron/jobs.json\"}"
|
||
}
|
||
}
|
||
],
|
||
"timestamp": 1776371909
|
||
},
|
||
{
|
||
"role": "tool",
|
||
"content": "{\"content\": \" 1|{\\n 2| \\\"jobs\\\": [\\n 3| {\\n 4| \\\"id\\\": \\\"9de5e64d03ef\\\",\\n 5| \\\"name\\\": \\\"Memory Health Check\\\",\\n 6| \\\"prompt\\\": \\\"Laufe_Memory_Health_Check\\\",\\n 7| \\\"skills\\\": [],\\n 8| \\\"skill\\\": null,\\n 9| \\\"model\\\": null,\\n 10| \\\"provider\\\": null,\\n 11| \\\"base_url\\\": null,\\n 12| \\\"script\\\": \\\"memory_health_wrapper.py\\\",\\n 13| \\\"schedule\\\": {\\n 14| \\\"kind\\\": \\\"interval\\\",\\n 15| \\\"minutes\\\": 15,\\n 16| \\\"display\\\": \\\"every 15m\\\"\\n 17| },\\n 18| \\\"schedule_display\\\": \\\"every 15m\\\",\\n 19| \\\"repeat\\\": {\\n 20| \\\"times\\\": null,\\n 21| \\\"completed\\\": 154\\n 22| },\\n 23| \\\"enabled\\\": true,\\n 24| \\\"state\\\": \\\"scheduled\\\",\\n 25| \\\"paused_at\\\": null,\\n 26| \\\"paused_reason\\\": null,\\n 27| \\\"created_at\\\": \\\"2026-04-13T11:55:33.117356+02:00\\\",\\n 28| \\\"next_run_at\\\": \\\"2026-04-16T15:17:20.064915+02:00\\\",\\n 29| \\\"last_run_at\\\": \\\"2026-04-16T15:02:20.064915+02:00\\\",\\n 30| \\\"last_status\\\": \\\"ok\\\",\\n 31| \\\"last_error\\\": null,\\n 32| \\\"last_delivery_error\\\": null,\\n 33| \\\"deliver\\\": \\\"local\\\",\\n 34| \\\"origin\\\": {\\n 35| \\\"platform\\\": \\\"telegram\\\",\\n 36| \\\"chat_id\\\": \\\"1446513575\\\",\\n 37| \\\"chat_name\\\": \\\"Sabo Mera_Mera\\\",\\n 38| \\\"thread_id\\\": null\\n 39| }\\n 40| },\\n 41| {\\n 42| \\\"id\\\": \\\"15f90ee7af94\\\",\\n 43| \\\"name\\\": \\\"Analytics Daily Report\\\",\\n 44| \\\"prompt\\\": \\\"Daily Analytics Report\\\",\\n 45| \\\"skills\\\": [],\\n 46| \\\"skill\\\": null,\\n 47| \\\"model\\\": null,\\n 48| \\\"provider\\\": null,\\n 49| \\\"base_url\\\": null,\\n 50| \\\"script\\\": \\\"analytics_report.py\\\",\\n 51|\", \"total_lines\": 181, \"file_size\": 5896, \"truncated\": true, \"hint\": \"Use offset=51 to continue reading (showing 1-50 of 181 lines)\", \"is_binary\": false, \"is_image\": false}",
|
||
"tool_call_id": "call_function_ekrs57cb6pb0_1",
|
||
"timestamp": 1776371909
|
||
},
|
||
{
|
||
"role": "assistant",
|
||
"content": "",
|
||
"tool_calls": [
|
||
{
|
||
"id": "call_function_bd8v6vbl4lx0_1",
|
||
"call_id": "call_function_bd8v6vbl4lx0_1",
|
||
"response_item_id": "fc_function_bd8v6vbl4lx0_1",
|
||
"type": "function",
|
||
"function": {
|
||
"name": "read_file",
|
||
"arguments": "{\"limit\": 100, \"offset\": 80, \"path\": \"/Users/rose/.hermes/cron/jobs.json\"}"
|
||
}
|
||
}
|
||
],
|
||
"timestamp": 1776371909
|
||
},
|
||
{
|
||
"role": "tool",
|
||
"content": "{\"content\": \" 80| \\\"model\\\": null,\\n 81| \\\"provider\\\": null,\\n 82| \\\"base_url\\\": null,\\n 83| \\\"script\\\": null,\\n 84| \\\"schedule\\\": {\\n 85| \\\"kind\\\": \\\"interval\\\",\\n 86| \\\"minutes\\\": 15,\\n 87| \\\"display\\\": \\\"every 15m\\\"\\n 88| },\\n 89| \\\"schedule_display\\\": \\\"every 15m\\\",\\n 90| \\\"repeat\\\": {\\n 91| \\\"times\\\": null,\\n 92| \\\"completed\\\": 44\\n 93| },\\n 94| \\\"enabled\\\": true,\\n 95| \\\"state\\\": \\\"scheduled\\\",\\n 96| \\\"paused_at\\\": null,\\n 97| \\\"paused_reason\\\": null,\\n 98| \\\"created_at\\\": \\\"2026-04-15T08:48:39.151194+02:00\\\",\\n 99| \\\"next_run_at\\\": \\\"2026-04-16T15:19:43.256364+02:00\\\",\\n 100| \\\"last_run_at\\\": \\\"2026-04-16T15:04:43.256364+02:00\\\",\\n 101| \\\"last_status\\\": \\\"ok\\\",\\n 102| \\\"last_error\\\": null,\\n 103| \\\"last_delivery_error\\\": null,\\n 104| \\\"deliver\\\": \\\"local\\\",\\n 105| \\\"origin\\\": null\\n 106| },\\n 107| {\\n 108| \\\"id\\\": \\\"ecd1da0f1d95\\\",\\n 109| \\\"name\\\": \\\"Rose Memory Sync (Nightly)\\\",\\n 110| \\\"prompt\\\": \\\"# Rose's Memory - Nightly Full-Flow Pipeline\\\\n\\\\nF\\\\u00fchre den kompletten Memory-Pipeline aus:\\\\n\\\\n## Schritt 1: Sessions extrahieren\\\\ncd /Users/rose/.hermes/hermes-agent && source venv/bin/activate && python tools/memory_pipeline.py --extract\\\\n\\\\n## Schritt 2: High-Confidence Fakten \\\\u2192 Vault (Markdown)\\\\npython tools/memory_pipeline.py --promote\\\\n\\\\n## Schritt 3: Vault \\\\u2192 ChromaDB Sync\\\\npython tools/memory_pipeline.py --sync\\\\n\\\\n## WICHTIG:\\\\n- Wenn ein Schritt fehlschl\\\\u00e4gt, den Fehler loggen aber mit dem n\\\\u00e4chsten weitermachen\\\\n- Am Ende eine kurze Zusammenfassung: wie viele Sessions verarbeitet, wie viele neue Fakten extrahiert, wie viele promoted\\\\n- ChromaDB muss auf Port 8000 laufen (housekeeping stellt das sicher)\\\",\\n 111| \\\"skills\\\": [\\n 112| \\\"hermes-housekeeping-maintenance\\\"\\n 113| ],\\n 114| \\\"skill\\\": \\\"hermes-housekeeping-maintenance\\\",\\n 115| \\\"model\\\": null,\\n 116| \\\"provider\\\": null,\\n 117| \\\"base_url\\\": null,\\n 118| \\\"script\\\": null,\\n 119| \\\"schedule\\\": {\\n 120| \\\"kind\\\": \\\"cron\\\",\\n 121| \\\"expr\\\": \\\"0 2 * * *\\\",\\n 122| \\\"display\\\": \\\"0 2 * * *\\\"\\n 123| },\\n 124| \\\"schedule_display\\\": \\\"0 2 * * *\\\",\\n 125| \\\"repeat\\\": {\\n 126| \\\"times\\\": 999,\\n 127| \\\"completed\\\": 0\\n 128| },\\n 129| \\\"enabled\\\": true,\\n 130| \\\"state\\\": \\\"scheduled\\\",\\n 131| \\\"paused_at\\\": null,\\n 132| \\\"paused_reason\\\": null,\\n 133| \\\"created_at\\\": \\\"2026-04-15T13:16:16.409232+02:00\\\",\\n 134| \\\"next_run_at\\\": \\\"2026-04-17T02:00:00+02:00\\\",\\n 135| \\\"last_run_at\\\": null,\\n 136| \\\"last_status\\\": null,\\n 137| \\\"last_error\\\": null,\\n 138| \\\"last_delivery_error\\\": null,\\n 139| \\\"deliver\\\": \\\"telegram\\\",\\n 140| \\\"origin\\\": {\\n 141| \\\"platform\\\": \\\"telegram\\\",\\n 142| \\\"chat_id\\\": \\\"1446513575\\\",\\n 143| \\\"chat_name\\\": \\\"Sabo Mera_Mera\\\",\\n 144| \\\"thread_id\\\": null\\n 145| }\\n 146| },\\n 147| {\\n 148| \\\"id\\\": \\\"90031c503f0b\\\",\\n 149| \\\"name\\\": \\\"hermes-housekeeping\\\",\\n 150| \\\"prompt\\\": \\\"Run the Hermes housekeeping script to keep all services alive. Execute: python3 ~/.hermes/scripts/housekeeping.py\\\\nReport any services that failed to start or restart.\\\",\\n 151| \\\"skills\\\": [],\\n 152| \\\"skill\\\": null,\\n 153| \\\"model\\\": null,\\n 154| \\\"provider\\\": null,\\n 155| \\\"base_url\\\": null,\\n 156| \\\"script\\\": \\\"housekeeping.py\\\",\\n 157| \\\"schedule\\\": {\\n 158| \\\"kind\\\": \\\"cron\\\",\\n 159| \\\"expr\\\": \\\"*/15 * * * *\\\",\\n 160| \\\"display\\\": \\\"*/15 * * * *\\\"\\n 161| },\\n 162| \\\"schedule_display\\\": \\\"*/15 * * * *\\\",\\n 163| \\\"repeat\\\": {\\n 164| \\\"times\\\": null,\\n 165| \\\"completed\\\": 18\\n 166| },\\n 167| \\\"enabled\\\": true,\\n 168| \\\"state\\\": \\\"scheduled\\\",\\n 169| \\\"paused_at\\\": null,\\n 170| \\\"paused_reason\\\": null,\\n 171| \\\"created_at\\\": \\\"2026-04-15T22:08:14.148485+02:00\\\",\\n 172| \\\"next_run_at\\\": \\\"2026-04-16T15:30:00+02:00\\\",\\n 173| \\\"last_run_at\\\": \\\"2026-04-16T15:00:34.035954+02:00\\\",\\n 174| \\\"last_status\\\": \\\"ok\\\",\\n 175| \\\"last_error\\\": null,\\n 176| \\\"last_delivery_error\\\": null,\\n 177| \\\"deliver\\\": \\\"local\\\",\\n 178| \\\"origin\\\": null\\n 179| }\\n 180|\", \"total_lines\": 181, \"file_size\": 5896, \"truncated\": true, \"hint\": \"Use offset=180 to continue reading (showing 80-179 of 181 lines)\", \"is_binary\": false, \"is_image\": false}",
|
||
"tool_call_id": "call_function_bd8v6vbl4lx0_1",
|
||
"timestamp": 1776371909
|
||
},
|
||
{
|
||
"role": "assistant",
|
||
"content": "",
|
||
"tool_calls": [
|
||
{
|
||
"id": "call_function_9xfh2s4iw25e_1",
|
||
"call_id": "call_function_9xfh2s4iw25e_1",
|
||
"response_item_id": "fc_function_9xfh2s4iw25e_1",
|
||
"type": "function",
|
||
"function": {
|
||
"name": "terminal",
|
||
"arguments": "{\"command\": \"ls -la /Users/rose/.hermes/scripts/\"}"
|
||
}
|
||
}
|
||
],
|
||
"timestamp": 1776371909
|
||
},
|
||
{
|
||
"role": "tool",
|
||
"content": "{\"output\": \"total 112\\ndrwxr-xr-x 4 rose staff 128 Apr 15 14:19 __pycache__\\ndrwxr-xr-x 10 rose staff 320 Apr 15 14:18 .\\ndrwx------ 62 rose staff 1984 Apr 16 22:31 ..\\n-rw-r--r-- 1 rose staff 6406 Apr 15 13:20 agent_memory.py\\n-rw-r--r-- 1 rose staff 2494 Apr 13 12:07 analytics_report.py\\n-rw-r--r-- 1 rose staff 9652 Apr 15 22:08 housekeeping.py\\n-rw-r--r-- 1 rose staff 877 Apr 13 15:45 memory_health_wrapper.py\\n-rw-r--r-- 1 rose staff 6849 Apr 15 12:37 message_bus.py\\n-rwxr-xr-x 1 rose staff 10348 Apr 15 15:50 research_search.py\\n-rw-r--r-- 1 rose staff 7141 Apr 15 13:15 searxng_search.py\", \"exit_code\": 0, \"error\": null}",
|
||
"tool_call_id": "call_function_9xfh2s4iw25e_1",
|
||
"timestamp": 1776371909
|
||
},
|
||
{
|
||
"role": "assistant",
|
||
"content": "",
|
||
"tool_calls": [
|
||
{
|
||
"id": "call_function_fddrhqx6z5oh_1",
|
||
"call_id": "call_function_fddrhqx6z5oh_1",
|
||
"response_item_id": "fc_function_fddrhqx6z5oh_1",
|
||
"type": "function",
|
||
"function": {
|
||
"name": "read_file",
|
||
"arguments": "{\"path\": \"/Users/rose/.hermes/scripts/memory_health_wrapper.py\"}"
|
||
}
|
||
}
|
||
],
|
||
"timestamp": 1776371909
|
||
},
|
||
{
|
||
"role": "tool",
|
||
"content": "{\"content\": \" 1|#!/usr/bin/env python3\\n 2|\\\"\\\"\\\"\\n 3|Memory Health Check Wrapper - suppress output on success, alert on failure.\\n 4|This script is executed by the cron job via hermes cron --script flag.\\n 5|\\\"\\\"\\\"\\n 6|import sys\\n 7|from pathlib import Path\\n 8|\\n 9|# CRITICAL: Add ~/.hermes/tools to Python path for module resolution\\n 10|tools_path = str(Path.home() / \\\".hermes\\\" / \\\"tools\\\")\\n 11|sys.path.insert(0, tools_path)\\n 12|\\n 13|try:\\n 14| # Import and run the health check logic directly\\n 15| from memory_health_check import main as health_main\\n 16| health_main()\\n 17|except ModuleNotFoundError as e:\\n 18| print(f\\\"ERROR: Failed to import memory_health_check module: {e}\\\", file=sys.stderr)\\n 19| sys.exit(1)\\n 20|except SystemExit as e:\\n 21| if e.code == 1:\\n 22| print(\\\"⚠️ MEMORY HEALTH CHECK FAILED - ISSUES DETECTED\\\", file=sys.stderr)\\n 23| raise\\n 24|finally:\\n 25| pass\\n 26|\\n 27|# Normal exit (code 0) - output already suppressed during success\\n 28|sys.exit(0)\\n 29|\", \"total_lines\": 28, \"file_size\": 877, \"truncated\": false, \"is_binary\": false, \"is_image\": false}",
|
||
"tool_call_id": "call_function_fddrhqx6z5oh_1",
|
||
"timestamp": 1776371909
|
||
},
|
||
{
|
||
"role": "assistant",
|
||
"content": "",
|
||
"tool_calls": [
|
||
{
|
||
"id": "call_function_8ja9e0ifkpd7_1",
|
||
"call_id": "call_function_8ja9e0ifkpd7_1",
|
||
"response_item_id": "fc_function_8ja9e0ifkpd7_1",
|
||
"type": "function",
|
||
"function": {
|
||
"name": "terminal",
|
||
"arguments": "{\"command\": \"ls -la /Users/rose/.hermes/memory/ 2>/dev/null | head -20; ls /Users/rose/.hermes/chroma_db/ 2>/dev/null | head -10\"}"
|
||
}
|
||
}
|
||
],
|
||
"timestamp": 1776371909
|
||
},
|
||
{
|
||
"role": "tool",
|
||
"content": "{\"output\": \"total 544\\ndrwxr-xr-x 3 rose staff 96 Apr 12 15:49 _templates\\ndrwxr-xr-x 19 rose staff 608 Apr 15 15:46 .\\ndrwx------ 62 rose staff 1984 Apr 16 22:31 ..\\ndrwxr-xr-x 12 rose staff 384 Apr 12 17:56 .git\\ndrwxr-xr-x 2 rose staff 64 Apr 12 15:48 1-Inbox\\n-rw-r--r-- 1 rose staff 188416 Apr 15 15:46 chroma.sqlite3\\n-rw-r--r-- 1 rose staff 2991 Apr 12 21:29 config.yaml\\n-rw-r--r-- 1 rose staff 2431 Apr 15 13:48 Index.md\\n-rw-r--r-- 1 rose staff 4069 Apr 15 09:13 MEMORY_ARCHITECTURE.md\\n-rw-r--r-- 1 rose staff 9890 Apr 15 14:56 MEMORY_SYSTEM.md\\n-rw-r--r-- 1 rose staff 8645 Apr 13 12:12 memory-system-design.md\\n-rw-r--r-- 1 rose staff 3013 Apr 12 19:29 PHASE_3_COMPLETION.md\\n-rw-r--r-- 1 rose staff 6574 Apr 12 19:49 phase_3_testing_report.md\\n-rw-r--r-- 1 rose staff 10136 Apr 12 21:20 PROJECT_PLAN.md\\n-rw-r--r-- 1 rose staff 5950 Apr 12 18:05 PROJECT_SEARCH_TOOL.md\\n-rw-r--r-- 1 rose staff 8501 Apr 12 17:47 README_SEARCH_TOOL.md\\n-rw-r--r-- 1 rose staff 7380 Apr 15 14:25 SCRIPTS_REFERENCE.md\\ndrwxr-xr-x 2 rose staff 64 Apr 12 15:48 tags\\ndrwxr-xr-x 351 rose staff 11232 Apr 15 22:54 topics\\n3bdbac12-9d5a-4bf8-8f20-3d6c8f9fa890\\n63f68406-9543-4e04-a905-d4ebb20c7275\\nchroma.sqlite3\\nserver.log\", \"exit_code\": 0, \"error\": null}",
|
||
"tool_call_id": "call_function_8ja9e0ifkpd7_1",
|
||
"timestamp": 1776371909
|
||
},
|
||
{
|
||
"role": "assistant",
|
||
"content": "**Erkenntnis:** Das Pipeline-Skript `tools/memory_pipeline.py` existiert nicht — der Cron-Job referenziert es, aber die Datei wurde nie angelegt (oder ist weg).\n\n**Was aber FUNKTIONIERT:**\n- **ChromaDB** läuft auf Port 8000 ✓\n- **Vault** hat 351 Themen-Dateien ✓\n- **Such-Tool** funktioniert (Chromadb + Vault Integration) ✓\n\n**Was der Nightly-Job machen SOLL:**\n```\nStep 1: Sessions → Fakten extrahieren (Qwen 3.5 via LM Studio)\nStep 2: High-Confidence Fakten → Vault Markdown promoten \nStep 3: Vault → ChromaDB synchronisieren\n```\n\n**Das Problem:** `memory_pipeline.py` fehlt komplett. Der Cron-Job würde sowieso mit dem Embedding-Modell (MiniLM) timeouten — laut Skill-Doku sollte er Qwen 3.5 für Extraktion nutzen.\n\n**Soll ich:**\n1. **Das Pipeline-Skript bauen** mit Qwen 3.5 (LM Studio) für Extraktion + die bekannten Fixes aus der Skill-Doku?\n2. **Oder erstmal prüfen** ob die 351 Vault-Dateien bereits in ChromaDB indexiert sind?",
|
||
"timestamp": 1776371909
|
||
},
|
||
{
|
||
"role": "user",
|
||
"content": "funktiinert der qwen 3.5 m,odell lokale llm?",
|
||
"timestamp": 1776371909
|
||
},
|
||
{
|
||
"role": "assistant",
|
||
"content": "",
|
||
"reasoning": "The user is asking if the Qwen 3.5 model works locally via LLM. Let me check if LM Studio is running and if Qwen 3.5 is available.",
|
||
"finish_reason": "tool_calls",
|
||
"reasoning_details": [
|
||
{
|
||
"signature": "bc885f79f53bc60f8af4e7710dd665967910f000ca611b08f5d7d22c47f51f8d",
|
||
"thinking": "The user is asking if the Qwen 3.5 model works locally via LLM. Let me check if LM Studio is running and if Qwen 3.5 is available.",
|
||
"type": "thinking"
|
||
}
|
||
],
|
||
"tool_calls": [
|
||
{
|
||
"id": "call_function_vawvpcib8r6y_1",
|
||
"call_id": "call_function_vawvpcib8r6y_1",
|
||
"response_item_id": "fc_function_vawvpcib8r6y_1",
|
||
"type": "function",
|
||
"function": {
|
||
"name": "terminal",
|
||
"arguments": "{\"command\": \"curl -s http://localhost:1234/v1/models 2>/dev/null | python3 -c \\\"import sys,json; d=json.load(sys.stdin); [print(m['id']) for m in d.get('data',[])]\\\" 2>/dev/null || echo \\\"LM Studio nicht erreichbar auf Port 1234\\\"\"}"
|
||
}
|
||
}
|
||
],
|
||
"timestamp": 1776371909
|
||
},
|
||
{
|
||
"role": "tool",
|
||
"content": "{\"output\": \"qwen/qwen3.5-35b-a3b\\ngoogle_gemma-4-31b-it\\ntext-embedding-nomic-embed-text-v1.5\", \"exit_code\": 0, \"error\": null, \"approval\": \"Command required approval (Security scan — [HIGH] Pipe to interpreter: curl | python3: Command pipes output from 'curl' directly to interpreter 'python3'. Downloaded content will be executed without inspection.\\n Safer: tirith run http://localhost:1234/v1/models — or: vet http://localhost:1234/v1/models (https://getvet.sh)) and was approved by the user.\"}",
|
||
"tool_call_id": "call_function_vawvpcib8r6y_1",
|
||
"timestamp": 1776371909
|
||
},
|
||
{
|
||
"role": "assistant",
|
||
"content": "",
|
||
"reasoning": "Qwen 3.5 35B is available on LM Studio (localhost:1234). Let me also check if I can actually make a chat completion to verify it works end-to-end.",
|
||
"finish_reason": "tool_calls",
|
||
"reasoning_details": [
|
||
{
|
||
"signature": "49ab68cc89a717cfe3f90a93c5fa2ce641e3f9cae82afba21dff3a936627ec4c",
|
||
"thinking": "Qwen 3.5 35B is available on LM Studio (localhost:1234). Let me also check if I can actually make a chat completion to verify it works end-to-end.",
|
||
"type": "thinking"
|
||
}
|
||
],
|
||
"tool_calls": [
|
||
{
|
||
"id": "call_function_0l0sh2g7dbyw_1",
|
||
"call_id": "call_function_0l0sh2g7dbyw_1",
|
||
"response_item_id": "fc_function_0l0sh2g7dbyw_1",
|
||
"type": "function",
|
||
"function": {
|
||
"name": "terminal",
|
||
"arguments": "{\"command\": \"curl -s -X POST http://localhost:1234/v1/chat/completions \\\\\\n -H \\\"Content-Type: application/json\\\" \\\\\\n -d '{\\\"model\\\":\\\"qwen/qwen3.5-35b-a3b\\\",\\\"messages\\\":[{\\\"role\\\":\\\"user\\\",\\\"content\\\":\\\"Sag nur: OK\\\"}],\\\"max_tokens\\\":20}' \\\\\\n --max-time 30 2>&1\"}"
|
||
}
|
||
}
|
||
],
|
||
"timestamp": 1776371909
|
||
},
|
||
{
|
||
"role": "tool",
|
||
"content": "{\"output\": \"{\\n \\\"id\\\": \\\"chatcmpl-b9863j63h4e4sy6w87ahlr\\\",\\n \\\"object\\\": \\\"chat.completion\\\",\\n \\\"created\\\": 1776371898,\\n \\\"model\\\": \\\"qwen/qwen3.5-35b-a3b\\\",\\n \\\"choices\\\": [\\n {\\n \\\"index\\\": 0,\\n \\\"message\\\": {\\n \\\"role\\\": \\\"assistant\\\",\\n \\\"content\\\": \\\"Thinking Process:\\\\n\\\\n1. **Analyze the Request:** The user is asking me to\\\",\\n \\\"tool_calls\\\": []\\n },\\n \\\"logprobs\\\": null,\\n \\\"finish_reason\\\": \\\"length\\\"\\n }\\n ],\\n \\\"usage\\\": {\\n \\\"prompt_tokens\\\": 15,\\n \\\"completion_tokens\\\": 20,\\n \\\"total_tokens\\\": 35\\n },\\n \\\"stats\\\": {},\\n \\\"system_fingerprint\\\": \\\"qwen/qwen3.5-35b-a3b\\\"\\n}\", \"exit_code\": 0, \"error\": null}",
|
||
"tool_call_id": "call_function_0l0sh2g7dbyw_1",
|
||
"timestamp": 1776371909
|
||
},
|
||
{
|
||
"role": "assistant",
|
||
"content": "**Ja, Qwen 3.5 funktioniert lokal.** LM Studio auf Port 1234:\n\n```\nqwen/qwen3.5-35b-a3b ← 35B Parameter Modell\n```\n\nEs antwortet — aber mit einem bekannten Issue: Qwen 3.5 hat **Thinking HARDCODED** aktiv, die Antwort beginnt mit `Thinking Process:\\n\\n1. **Analyze...` vor dem eigentlichen Text. Das lässt sich nicht per API abschalten.\n\nFür den Memory Pipeline wäre das aber kein Problem — wir strippen das Thinking mit Regex vorher.\n\n**Frage:** Soll ich jetzt das `memory_pipeline.py` Skript bauen das:\n1. Qwen 3.5 für Extraktion nutzt (kein externes Embedding-Modell nötig)\n2. Batch-Modus (10 Sessions pro Call für Speed)\n3. Thinking-Stripping + robuste JSON-Parsierung\n4. Die 3 Steps: Extract → Promote → Sync",
|
||
"reasoning": "Qwen 3.5 is working but it has the \"Thinking Process:\" prefix issue. Let me check a few more things quickly - is it generating actual responses without the thinking mode, and is the 35B model fully loaded (not quantized to oblivion)? Also the user asked if it works \"lokal\" - the answer is yes, it works on localhost:1234 via LM Studio.\n\nThe thinking process issue means Qwen 3.5 has hardcoded thinking. The model responds but prepends thinking. This is a known issue.\n\nLet me just give a quick status.",
|
||
"finish_reason": "stop",
|
||
"reasoning_details": [
|
||
{
|
||
"signature": "83be7d3da6e9d114d6efaf5f14f0c9dbf5feaba21f124106613ba70bbef5190b",
|
||
"thinking": "Qwen 3.5 is working but it has the \"Thinking Process:\" prefix issue. Let me check a few more things quickly - is it generating actual responses without the thinking mode, and is the 35B model fully loaded (not quantized to oblivion)? Also the user asked if it works \"lokal\" - the answer is yes, it works on localhost:1234 via LM Studio.\n\nThe thinking process issue means Qwen 3.5 has hardcoded thinking. The model responds but prepends thinking. This is a known issue.\n\nLet me just give a quick status.",
|
||
"type": "thinking"
|
||
}
|
||
],
|
||
"timestamp": 1776371909
|
||
}
|
||
],
|
||
"tool_calls": [
|
||
{
|
||
"name": "cronjob",
|
||
"snippet": "{\n \"success\": true,\n \"count\": 5,\n \"jobs\": [\n {\n \"job_id\": \"9de5e64d03ef\",\n \"name\": \"Memory Health Check\",\n \"skill\": null,\n \"skills\": [],\n \"prompt_preview\": \"Laufe_Memory",
|
||
"tid": "call_function_fb8ydnzs6704_1",
|
||
"assistant_msg_idx": 1,
|
||
"args": {
|
||
"action": "list"
|
||
}
|
||
},
|
||
{
|
||
"name": "search_files",
|
||
"snippet": "{\"total_count\": 50, \"files\": [\"/Users/rose/.hermes/cron/jobs.json\", \"/Users/rose/.hermes/sessions/session_cron_90031c503f0b_20260416_081551.json\", \"/Users/rose/.hermes/sessions/session_20260416_165318",
|
||
"tid": "call_function_fb8ydnzs6704_2",
|
||
"assistant_msg_idx": 1,
|
||
"args": {
|
||
"pattern": "rose-memory-chromadb-sync|memory.*sync|chromadb.*sync",
|
||
"target": "content",
|
||
"path": "/Users/rose/.hermes",
|
||
"output_mode": "files_only"
|
||
}
|
||
},
|
||
{
|
||
"name": "read_file",
|
||
"snippet": "{\"content\": \" 1|{\\n 2| \\\"session_id\\\": \\\"cron_ecd1da0f1d95_20260416_111713\\\",\\n 3| \\\"model\\\": \\\"qwen/qwen3.5-35b-a3b\\\",\\n 4| \\\"base_url\\\": \\\"http://localhost:1234/v1\\\",\\n 5| \\\"",
|
||
"tid": "call_function_boxj3d29c1q9_1",
|
||
"assistant_msg_idx": 4,
|
||
"args": {
|
||
"path": "/Users/rose/.hermes/sessions/session_cron_ecd1da0f1d95_20260416_111713.json",
|
||
"limit": "100"
|
||
}
|
||
},
|
||
{
|
||
"name": "read_file",
|
||
"snippet": "{\"content\": \" 800| ],\\n 801| \\\"description\\\": \\\"Current status\\\"\\n 802| }\\n 803| },\\n 804| \\\"required\\\": ",
|
||
"tid": "call_function_0frc39idxb60_1",
|
||
"assistant_msg_idx": 6,
|
||
"args": {
|
||
"offset": "800",
|
||
"limit": "150",
|
||
"path": "/Users/rose/.hermes/sessions/session_cron_ecd1da0f1d95_20260416_111713.json"
|
||
}
|
||
},
|
||
{
|
||
"name": "search_files",
|
||
"snippet": "{\"total_count\": 0}",
|
||
"tid": "call_function_g5ez9tktykr5_1",
|
||
"assistant_msg_idx": 10,
|
||
"args": {
|
||
"pattern": "memory_pipeline.py",
|
||
"output_mode": "files_only"
|
||
}
|
||
},
|
||
{
|
||
"name": "search_files",
|
||
"snippet": "{\"total_count\": 0}",
|
||
"tid": "call_function_abaoo1h2ylmi_1",
|
||
"assistant_msg_idx": 12,
|
||
"args": {
|
||
"pattern": "memory_pipeline",
|
||
"output_mode": "files_only"
|
||
}
|
||
},
|
||
{
|
||
"name": "skill_view",
|
||
"snippet": "{\"success\": true, \"name\": \"hermes-housekeeping-maintenance\", \"description\": \"Automated Hermes maintenance via cronjob - ChromaDB keepalive, session cleanup, DB vacuum, log rotation, backup cleanup. Ha",
|
||
"tid": "call_function_ladkumh4bf96_1",
|
||
"assistant_msg_idx": 14,
|
||
"args": {
|
||
"name": "hermes-housekeeping-maintenance"
|
||
}
|
||
},
|
||
{
|
||
"name": "skill_view",
|
||
"snippet": "{\"success\": true, \"name\": \"rose-memory-chromadb-sync\", \"description\": \"Vollständiges autonomes Memory-System: ChromaDB (Index) + Vault (Source of Truth) + Session Extraktion\", \"tags\": [], \"related_ski",
|
||
"tid": "call_function_ludukrcv8aer_1",
|
||
"assistant_msg_idx": 16,
|
||
"args": {
|
||
"name": "rose-memory-chromadb-sync"
|
||
}
|
||
},
|
||
{
|
||
"name": "search_files",
|
||
"snippet": "{\"total_count\": 0}",
|
||
"tid": "call_function_8t2tuffsyzzx_1",
|
||
"assistant_msg_idx": 18,
|
||
"args": {
|
||
"output_mode": "files_only",
|
||
"pattern": "memory_pipeline.py"
|
||
}
|
||
},
|
||
{
|
||
"name": "search_files",
|
||
"snippet": "{\"total_count\": 0}",
|
||
"tid": "call_function_ts4m4pgdwxml_1",
|
||
"assistant_msg_idx": 20,
|
||
"args": {
|
||
"output_mode": "files_only",
|
||
"pattern": "memory_pipeline"
|
||
}
|
||
},
|
||
{
|
||
"name": "terminal",
|
||
"snippet": "{\"output\": \"\", \"exit_code\": 0, \"error\": null}",
|
||
"tid": "call_function_2makxfp4zfqt_1",
|
||
"assistant_msg_idx": 22,
|
||
"args": {
|
||
"command": "find /Users/rose/.hermes -name \"memory_pipeline.py\" 2>/dev/null; find /Users/rose -name \"memory_pipeline.py\" 2>/dev/null..."
|
||
}
|
||
},
|
||
{
|
||
"name": "terminal",
|
||
"snippet": "{\"output\": \"total 3120\\n-rw-r--r-- 1 rose staff 726 Apr 3 11:55 __init__.py\\ndrwxr-xr-x 55 rose staff 1760 Apr 16 13:42 __pycache__\\ndrwxr-xr-x 61 rose staff 1952 Apr 16 13:42 .\\ndrw",
|
||
"tid": "call_function_43o45yltc25w_1",
|
||
"assistant_msg_idx": 24,
|
||
"args": {
|
||
"command": "ls -la /Users/rose/.hermes/hermes-agent/tools/ 2>/dev/null | head -30"
|
||
}
|
||
},
|
||
{
|
||
"name": "terminal",
|
||
"snippet": "-rw-r--r-- 1 rose staff 6406 Apr 15 13:20 agent_memory.py\n-rw-r--r-- 1 rose staff 877 Apr 13 15:45 memory_health_wrapper.py",
|
||
"tid": "call_function_bevw0i3i7upv_1",
|
||
"assistant_msg_idx": 26,
|
||
"args": {
|
||
"command": "ls -la /Users/rose/.hermes/scripts/ | grep -i memory"
|
||
}
|
||
},
|
||
{
|
||
"name": "read_file",
|
||
"snippet": "{\"content\": \" 1|#!/usr/bin/env python3\\n 2|\\\"\\\"\\\"\\n 3|Rose Life-OS — Agent Memory Management\\n 4|======================================\\n 5|Each Tier-2 agent has persistent memory ",
|
||
"tid": "call_function_mac3uryp0bz0_1",
|
||
"assistant_msg_idx": 28,
|
||
"args": {
|
||
"path": "/Users/rose/.hermes/scripts/agent_memory.py"
|
||
}
|
||
},
|
||
{
|
||
"name": "read_file",
|
||
"snippet": "{\"content\": \" 1|{\\n 2| \\\"jobs\\\": [\\n 3| {\\n 4| \\\"id\\\": \\\"9de5e64d03ef\\\",\\n 5| \\\"name\\\": \\\"Memory Health Check\\\",\\n 6| \\\"prompt\\\": \\\"Laufe_Memory_Health_Check",
|
||
"tid": "call_function_ekrs57cb6pb0_1",
|
||
"assistant_msg_idx": 30,
|
||
"args": {
|
||
"limit": "50",
|
||
"path": "/Users/rose/.hermes/cron/jobs.json"
|
||
}
|
||
},
|
||
{
|
||
"name": "read_file",
|
||
"snippet": "{\"content\": \" 80| \\\"model\\\": null,\\n 81| \\\"provider\\\": null,\\n 82| \\\"base_url\\\": null,\\n 83| \\\"script\\\": null,\\n 84| \\\"schedule\\\": {\\n 85| \\\"kind\\\": \\",
|
||
"tid": "call_function_bd8v6vbl4lx0_1",
|
||
"assistant_msg_idx": 32,
|
||
"args": {
|
||
"limit": "100",
|
||
"offset": "80",
|
||
"path": "/Users/rose/.hermes/cron/jobs.json"
|
||
}
|
||
},
|
||
{
|
||
"name": "terminal",
|
||
"snippet": "total 112\ndrwxr-xr-x 4 rose staff 128 Apr 15 14:19 __pycache__\ndrwxr-xr-x 10 rose staff 320 Apr 15 14:18 .\ndrwx------ 62 rose staff 1984 Apr 16 22:31 ..\n-rw-r--r-- 1 rose staff 640",
|
||
"tid": "call_function_9xfh2s4iw25e_1",
|
||
"assistant_msg_idx": 34,
|
||
"args": {
|
||
"command": "ls -la /Users/rose/.hermes/scripts/"
|
||
}
|
||
},
|
||
{
|
||
"name": "read_file",
|
||
"snippet": "{\"content\": \" 1|#!/usr/bin/env python3\\n 2|\\\"\\\"\\\"\\n 3|Memory Health Check Wrapper - suppress output on success, alert on failure.\\n 4|This script is executed by the cron job via hermes",
|
||
"tid": "call_function_fddrhqx6z5oh_1",
|
||
"assistant_msg_idx": 36,
|
||
"args": {
|
||
"path": "/Users/rose/.hermes/scripts/memory_health_wrapper.py"
|
||
}
|
||
},
|
||
{
|
||
"name": "terminal",
|
||
"snippet": "total 544\ndrwxr-xr-x 3 rose staff 96 Apr 12 15:49 _templates\ndrwxr-xr-x 19 rose staff 608 Apr 15 15:46 .\ndrwx------ 62 rose staff 1984 Apr 16 22:31 ..\ndrwxr-xr-x 12 rose staff",
|
||
"tid": "call_function_8ja9e0ifkpd7_1",
|
||
"assistant_msg_idx": 38,
|
||
"args": {
|
||
"command": "ls -la /Users/rose/.hermes/memory/ 2>/dev/null | head -20; ls /Users/rose/.hermes/chroma_db/ 2>/dev/null | head -10"
|
||
}
|
||
},
|
||
{
|
||
"name": "terminal",
|
||
"snippet": "qwen/qwen3.5-35b-a3b\ngoogle_gemma-4-31b-it\ntext-embedding-nomic-embed-text-v1.5",
|
||
"tid": "call_function_vawvpcib8r6y_1",
|
||
"assistant_msg_idx": 42,
|
||
"args": {
|
||
"command": "curl -s http://localhost:1234/v1/models 2>/dev/null | python3 -c \"import sys,json; d=json.load(sys.stdin); [print(m['id'..."
|
||
}
|
||
},
|
||
{
|
||
"name": "terminal",
|
||
"snippet": "{\n \"id\": \"chatcmpl-b9863j63h4e4sy6w87ahlr\",\n \"object\": \"chat.completion\",\n \"created\": 1776371898,\n \"model\": \"qwen/qwen3.5-35b-a3b\",\n \"choices\": [\n {\n \"index\": 0,\n \"message\": {\n ",
|
||
"tid": "call_function_0l0sh2g7dbyw_1",
|
||
"assistant_msg_idx": 44,
|
||
"args": {
|
||
"command": "curl -s -X POST http://localhost:1234/v1/chat/completions \\\n -H \"Content-Type: application/json\" \\\n -d '{\"model\":\"qwen..."
|
||
}
|
||
}
|
||
],
|
||
"created_at": 1776371554.1609,
|
||
"updated_at": 1776371909.011453,
|
||
"pinned": false,
|
||
"archived": false,
|
||
"project_id": null,
|
||
"profile": "default",
|
||
"input_tokens": 717037,
|
||
"output_tokens": 3692,
|
||
"estimated_cost": null,
|
||
"personality": null,
|
||
"active_stream_id": null,
|
||
"pending_user_message": null,
|
||
"pending_attachments": [],
|
||
"pending_started_at": null,
|
||
"llm_title_generated": true
|
||
} |