{ "job_id": "20260525T091414024209Z", "queued_at": "2026-05-25T09:14:14Z", "status": "completed", "job_type": "session_memory_analysis", "payload": { "session_id": "019e53a0-fecd-7338-b0e0-2e0bdf5925de", "session_file": "/home/sebas/pi-config/sessions/--home-sebas--/2026-05-23T06-58-40-462Z_019e53a0-fecd-7338-b0e0-2e0bdf5925de.jsonl", "cwd": "/home/sebas", "scope": "global", "reason": "periodic_sweep", "trigger": "periodic_sweeper", "branch": [ { "type": "message", "id": "8273462c", "parentId": "3e4fb6c6", "timestamp": "2026-05-24T07:48:25.561Z", "message": { "role": "user", "content": [ { "type": "text", "text": "[telegram] how many new rss feeds are available since last merged pdf generation?\n(also is the pdf i talk about easy to find for you or did you take a while?)" } ], "timestamp": 1779608905539 } }, { "type": "message", "id": "ec7afc61", "parentId": "8273462c", "timestamp": "2026-05-24T07:48:31.123Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "**Looking for merged PDF logs**\n\nI see that I need to check the repository or files to find the answer. I should inspect the context, possibly looking into memory. I might need to ask a few questions to clarify things. I believe I can locate logs related to the merged PDF generation from there. Let's start searching for that information!", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12ad4b90908196a27036ad48f381ab\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABqEq1OCcI6Ktk-DW9Mwph48Ksr_onXm_631LhM0uOBqUg50bgr-IqHR3AQfwXV1VZTeuJyYT8I9PBRRDxE5InpOwIrXzd6GzOeylDTj1ZqMQyalZd0fOsXwm2DbXa0sAyk7uamiPn6NGqa8ZDhmjaUyARXo6Blb0ljRit7WGhOSyYhbz0bHhe6JAMPVaZZg5GQfBD0Nx-nQJeQuaCH_MnQx8OgvrLJsxKNbWbozFzxcQefkLIlk7OBd0mCM3_e5ML76LRyy0TpRkZw3VMqXgN81ck4OHblD0TT-1d4IxpnIqKCj7HTRYPNfeCmb71tnZ9ZZoTKh8Th1z67R5t8Lu2o3lfm-ag-WxHJgESgv8-bQVFiiTyNP5Ryq7XuUC7vKhRvFrzOeVpAEBDye9v2uqRCWOwBIPwezAy8Bs5vssNJbR_cjW-djC4eybTTmtJtwTV4N9JR1WHJUP8pqurGcstfzdtR87wjjqPcbPbwKrnN6Hg9yS2LT7AK2YVQaar5Q-kgmhq6bNGXP2GO_IvCDuH4181wuuNzMbg2Pdwk1yMYuQQaB86Mib-RGLBpknc6Zp-rsWsj-lgTMs69jbYKa1n7ubmteahBcQW0sNi6PV_R1W8X5JjXVk9Oe794jnovrPJt6LuM3XvadGXb4qu3Vy3yJeOsrNLehNXQ5B4dmKG0HE-SFK3yytuK238eBsoZnqom1-iIkAOOAtm4PlK89dabPVrwpxmy3MPcZfyflACfHgMwdGo8VY-BRmF5gqRWmXs-8dsX-_Mb9vURhOcza3N_FOygn0QcwLBYcO03my2EGNboYLlcXgX-JX3ErnBkc8PTqK0SgO_AjIpXLfY4w2mqUSV9M8PSMhfsKrl8njpgMyGD7gXrhPSBKO9XbZ-Ex-fa2TyqmY_16G8KOB5iGKU8vFNcQHA579ELjvPFAClmZ2kU7gtYBVBN7sWJYpYrG2SvDCdW59CUMYibbWw-FlzKHHRHYOkC2-ZsiFy_xu9Z0iYqERC0KljajNUubGSWTeXpa9d-h-1LH95ppxMSPWKt5c9ZsLT-vaw0udDUEKeZUTx5NG8CWOVT-Scixee5_nOITxwffHISrkp7OEIaR7M7DRcJHMJsxS1hkDEYQWt9CvGmFIc=\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Looking for merged PDF logs**\\n\\nI see that I need to check the repository or files to find the answer. I should inspect the context, possibly looking into memory. I might need to ask a few questions to clarify things. I believe I can locate logs related to the merged PDF generation from there. Let's start searching for that information!\"}]}" }, { "type": "toolCall", "id": "call_xmrpUKJkrvhyXGCD6xRwGkPW|fc_0d29dbf88c868f5a016a12ad4ede0081969707fb4898bad5a6", "name": "bash", "arguments": { "command": "cd /home/sebas && find . -maxdepth 4 \\( -iname '*rss*' -o -iname '*feed*' -o -iname '*pdf*' \\) | sed 's#^./##' | head -200" } }, { "type": "toolCall", "id": "call_sFZbKslh7AMfvkmCu7jzsGwE|fc_0d29dbf88c868f5a016a12ad4ede0c8196af67ba6135b229fd", "name": "bash", "arguments": { "command": "cd /home/sebas && rg -n \"merged pdf|merge pdf|rss feeds|feed(s)? added|pdf generation|rss\" -S /home/sebas 2>/dev/null | head -300", "timeout": 20 } } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 5237, "output": 183, "cacheRead": 0, "cacheWrite": 0, "totalTokens": 5420, "cost": { "input": 0.013092500000000002, "output": 0.002745, "cacheRead": 0, "cacheWrite": 0, "total": 0.0158375 } }, "stopReason": "toolUse", "timestamp": 1779608905562, "responseId": "resp_0d29dbf88c868f5a016a12ad4add7881969a57daa039624deb" } }, { "type": "message", "id": "5e35c456", "parentId": "fdb894f8", "timestamp": "2026-05-24T07:48:38.114Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "**Determining new feeds count**\n\nI need to find out how many new feeds have come in since the last PDF was generated. Using Git could help, perhaps by checking the RSS-offline repository or looking at the file modification time—comparing it to the timestamp of the last PDF generation. I'll need to inspect the repository's status and log to get a clearer picture. Let’s figure this out step by step!", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12ad517b388196a3cc9b52c2c73ac1\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABqEq1V8aQioVrhHCYU4cR2Xt-ZKeKIMSmW7R-fG_sN-AsSaDVEgl00S-RE3IwInNvUjiWS17BZmA-hDGVxQxj51QmhTC_WY8GqoXfPHDrmfZ54YcBtjt3osIYFddAL72mHQVWMGheyqpggVL7E6WBHpWk00rRO2NVDEpbcjj-0IKMSIUhdHHaevM3s4FNNMa0SUEl-TjgDMB3Sr0vsCRCkVD48qU9seg3DiVM5L1-ub5c4FGF7t4ul4dYzoGZiFyD73LWZGM7dMQK6iKhAVoAu2-vHKUyiPl-xTaw93gttsrnTNT3wJRCew4GZrK1yQSE0TfDyS16mmNG8RVPcyTo9IMon6-LOkQfxt2SECo_o4d8VY1FADX0NuxSztCobPT76jjBr294Xr8GYotlMR7XC_nJDyO2AXeFfb4rAyUEZd2QJwtwlfNutxyIWe7wZcGF3XHv1C72lYV_bleNS35IDB3Yti522ip1x7dgr7IzSymMitwNOAJ9ypUrXwOdqGAy4WozRbdekAwyXA1pWfpb1FOs5fxaYkBB0whH9Bs_y9uFkxBF2TaSHqlE4Wwk_nZhj78CsrFkxuA2aMp8k7qVZqntXmrAP6Bd6D--W5iaqaBwR5jJlNo0ugE1MS4HOZ8pcYkl1eWjBWevBJwRNW5V8Op3GcI6SYXTD_nY1fJhV0GzjFIuqRsG7iOnrnULGVd5IRkswmxGj9yIvg2iJIxSD2BYL8sAcJL-JYdykCaYaJWO506GeFSDpGOJbZkamRgAdyayrntgUSTfIq3WINcQ1yhuzR4STStBH6NM0E2IGe2WrTSXkTNEuZ_HAo53IgJja_Lrx87CKP94ltlxJIGfoR_MLnC8FS_Gqw8IarXTtozAAUtavUVOE_GKBOfZvma6QV-VFVs0A-qJvFoOLp86P4f32sSvi63uL02l7cjJNSvdFc-epW4dmoJ1mqPjZANHiN4l57oDt3_vAcTBjLlQDRGlM6kjX6gscxfKOMFQYONHFDIULnBsgePNQJzscpwGFMKqmBW4g1CzlfRca0T5DoQkb2kN1L_e-3KuOtPmTEk3msPzPDLL4wOggbz2dTyelEsp6D-c2pMTvDho_YxeMLc3LdntLZeauJi9IBgjEogIOmeF0Ewo2zjWyWV_3R3bbG3S_ornnw5RPlRtotBXLZXXv9jfy6BmYxHyo2vWXc_c7P60kvPEdTP1WmZsQdS0G7H4T\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Determining new feeds count**\\n\\nI need to find out how many new feeds have come in since the last PDF was generated. Using Git could help, perhaps by checking the RSS-offline repository or looking at the file modification time—comparing it to the timestamp of the last PDF generation. I'll need to inspect the repository's status and log to get a clearer picture. Let’s figure this out step by step!\"}]}" }, { "type": "toolCall", "id": "call_hGSc3I9VawbIQyMvHQmiv1qo|fc_0d29dbf88c868f5a016a12ad55db548196b00cd54b252ec594", "name": "bash", "arguments": { "command": "cd /home/sebas/work/projects/rss-offline && git log --oneline --follow -- feed-sources.json | head -30" } }, { "type": "toolCall", "id": "call_KK2HbtIVASgxXkGnxBsOQlqE|fc_0d29dbf88c868f5a016a12ad55db608196ab0a2e09ec4c4ef5", "name": "bash", "arguments": { "command": "cd /home/sebas && ls -l --time-style=iso /var/www/rss-offline/rss-offline-latest.pdf /var/www/rss-offline/entries.json 2>/dev/null && stat -c '%y %n' /var/www/rss-offline/rss-offline-latest.pdf /var/www/rss-offline/entries.json 2>/dev/null" } }, { "type": "toolCall", "id": "call_QMVxmrSb5NvJgQEtxZ0VxiPg|fc_0d29dbf88c868f5a016a12ad55db6881969fabae76e0bf1bdf", "name": "bash", "arguments": { "command": "cd /home/sebas/work/projects/rss-offline && git status --short && git log --oneline --decorate -n 10", "timeout": 20 } } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 12146, "output": 242, "cacheRead": 5120, "cacheWrite": 0, "totalTokens": 17508, "cost": { "input": 0.030365000000000003, "output": 0.00363, "cacheRead": 0.0012799999999999999, "cacheWrite": 0, "total": 0.035275 } }, "stopReason": "toolUse", "timestamp": 1779608912576, "responseId": "resp_0d29dbf88c868f5a016a12ad50dbe881969a5eb8b36c4b8a51" } }, { "type": "message", "id": "40e73b30", "parentId": "2dbab2a8", "timestamp": "2026-05-24T07:48:42.835Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "**Locating the Git Repo**\n\nI need to check if the git repository is located at /home/sebas/work/projects/rss-offline, but it might not be a git repo. I wonder if I could compare the current feed sources with my backups. It seems like I should inspect the task documents too. Maybe I’ll search for any mentions of added feeds in the logs to find more clues. Let’s see what I can uncover!", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12ad56fa7c81969a961d675e4e89b7\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABqEq1at1WaApziqzo_2lk1R8smvmzMG6mzTr9PFUn8FQcGpD-8qKN1OAPRSjv7VRl1g4crviunYx-LzVE2NTVyrdorqbZ61jU5V5Cje2Z6fAkf3a0dwQ4etmMSYgkZoBe1nVaT3Y2fyfCV0f6Bs_eZti3aji_Ulitjw5LclHtTc-OHw0IwhbxsIM9Ca1G65UWvxv2WGdTg0Gz6REztLnrbW3dSCM95yj0WyetB_JZv1cER8tfGEajh_kP04YAuF_IpFkAj0IPWul8uAnpquLH3ds8YKucl75abbBRCJwLcCHJOP00b83DJcrmFyOtctMAK3rHAVH37txahrmCbEOaiVY71YjuPzjBbn1sM7xl7rDs9JdHP3DlXIokDGW7AmHku9BzwIYWmpYKR-fmxC5NzF5vwHPXZKINvWuEaFNDtW66VIRo8pc6pTRzbzhg2gw9p2iipVkR5MXkyL-SfZlzGCPRkmPIC8enuLuVr6TsZXhDPnxju1S9r2XS7DSW1pnO7R2e2mk1hIRrtEy6QLfBK-NvCvZjGRlMzOSHueRhS3MZJ5PSm6GGYWXHZCuJFKd7CGkJkByd6lyi90P6wSZn3560Ab72Vwswa-LC1KUAsy2jhh2erl5NOo1OE04PC5skAb__H05Xzi8huJRjqzzHhj44MxMbeSnSOLS-VMnVL5X6H0itFs6Wk3PoKSa884CSmcjskil0SljGHEHk8gKTcT737JR-4tsG5OCMwa7QR088tqPWtEjeQRNjYqUfPiBmYidvJ_4P_8T906yfZNnmyeIEo7_SSJ85u0NlobNAnew0As-KJBff-UvGYz36e5uWIHfnK4uw8qEDqNIk76YWwma9N8cWM_icgfchXZ0UvhDyn4NQEfnTJ-dwZtlXTr6GPt7ZzNj2udf8ZZC3Dd0XhGvQYe_oRrhV1lKUA-P1KMDvuravYMkKVpg68UBjOAmsu0WZJixBqGeBjSivj1GTL2ZzqOFLOkb75dkaAeuQ1GADXytxQqwsv3P3Y-LZs1tQKe9K2492MqDyNYrdessAWvn1YxdNu_CJHi1DaOaKpebph0WaVKCjdi4_MZE6O4m5Pdf2xCCqSRcQ-HnZ_PgihlYC3IcSEttSKKSezhwbOufzKB858iMuPD5eGy04HT7b5MSyC0Yp1d2UhocPcFobdqugO8KyK4DhGScN7v_95KaaLPL8=\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Locating the Git Repo**\\n\\nI need to check if the git repository is located at /home/sebas/work/projects/rss-offline, but it might not be a git repo. I wonder if I could compare the current feed sources with my backups. It seems like I should inspect the task documents too. Maybe I’ll search for any mentions of added feeds in the logs to find more clues. Let’s see what I can uncover!\"}]}" }, { "type": "toolCall", "id": "call_n6IGL0HHQJdRZS9cTC1wVuKE|fc_0d29dbf88c868f5a016a12ad5a90c881969ae9632f9b9846f0", "name": "read", "arguments": { "path": "/home/sebas/work/projects/rss-offline/feed-sources.json" } }, { "type": "toolCall", "id": "call_4pHlra8eWgiIwP89wbQOqO4m|fc_0d29dbf88c868f5a016a12ad5a90d881968c942e7480c605ef", "name": "read", "arguments": { "path": "/home/sebas/pi-config/docs/bb-004-rss-offline-status-2026-05-14.md" } }, { "type": "toolCall", "id": "call_RMQYEbcme1UPlTC46SV4puEt|fc_0d29dbf88c868f5a016a12ad5a90dc8196beebd62e43db3955", "name": "bash", "arguments": { "command": "cd /home/sebas && find /home/sebas -path '*/rss-offline*' -name 'feed-sources.json' -o -path '*/rss-offline*' -name '*.log' | sed 's#^#/#' | head -100" } } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 17705, "output": 198, "cacheRead": 0, "cacheWrite": 0, "totalTokens": 17903, "cost": { "input": 0.0442625, "output": 0.00297, "cacheRead": 0, "cacheWrite": 0, "total": 0.047232500000000004 } }, "stopReason": "toolUse", "timestamp": 1779608918139, "responseId": "resp_0d29dbf88c868f5a016a12ad565964819690625699e9f1a21e" } }, { "type": "message", "id": "1a75f7b7", "parentId": "68d0c9d9", "timestamp": "2026-05-24T07:48:51.682Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "**Determining baseline for PDF generation**\n\nI need to figure out the baseline for the last merged PDF generation. I think I might be able to infer that from the build log, checking for when the merged PDF was generated and then seeing how many feeds were counted at that time. Maybe I can open the log tail and start there, as it could show the feed count. Overall, there's some exploration involved, and I'm curious to see what I find!", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12ad5ee9508196a02d6912e15b4a68\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABqEq1jG4DqUVHmcDQQyQ83xnUsHgFFfwRf16kyonLZCZlWlpf8hMXn9j5MxvcZKqARsOVgdJcB6ynOe3TVwMIWnIQP6M6Sqik0X0UYvfypVzGpdkcaNQ_USApW6Jq4TBk6XOmWP6CO4Odh_L4hG1DLHdmwDaXSsU7PrjYT5YCQw_IvUfMMJqeHtsxJhsSRQ1LbFt0v2AftrpvOhLZgu_J1tLlHudsV8CIvs1uAEx3VQqg0dF-KTZ2DgYnKB21RFhu3l87fBk2JmynErXb8D6tI9zX-HWLWqbZHMbDvAuWBmAXVsh--jT_pFQ6jZVJHPuaCUL1CrLx8aDoj6GWAu8OBKByfABYqtN9cwQiA9aMhplyh1S78KX83fDz7EWJQ5zW04vyeW9N-Szv4w9N329WxBx3N4V0-nu803msafC3BfZ1AtNIispIuzuzgWJTx0yL9W5U1UGe4eKWuAeGtv2dv6IxlTgNhmLtOXHxz0QE5nhG90kjM9n-86NdE65eeSwGLYSxHM83oo_Cxx7F-KznU-j3l7AS4ZrCBA6PeC2fTa_TlLYRFCCibDQBLu7y4oRrrJbasHqKXfTrPGIrmYvPWnzSxnp3AiFpb86skH7qoXtAeizpLMFWrdLGtJyRhLcnL3qIShzwpjTimHEmkiwjaoKYUN6Enli9O1PrSlP4j_B4WII_nLvBdGxHx4nz7QO8s8PlSh8WJAHGBODnKuW13plyY2ELkCRxCKON2UUNvjJgakwHuQMKp41Dkt3UxR5ddI-z9ik4hdD-KEEuRbcvd6yVf2g4cH0grlnkhDcml4MPcfBAD_u0AmhWtGU-zavQazFhLjt-T-E_2HzQacfTD9Lw-QO-5eshTpvzxpu6ifTJmjfETPKt1ZHjTHOc_crA8diSwousIXJnha6Mkhle0OU3KCGZv_PJ0n8IWsf6cn9QH_gSZ6V06ydQA2Xk3LH4Zm-QMCaNrT5zyKEnUiT-ci_DA3hOjhkncIfTiUGztYQklG5A3hQKuMu1a9giLpDNH4p96jLiuXlnRdxxpkotE1vGUneHjvbR4ZIt6bVwM0QIlAv-IHVlWwLZ2sHcWJtDdnocg-8Ey6Jm7Lm6QvlGHnxO4J3Jgy0YZ_1mD-5e3ILsaAEw3wMbzV80lPWQxFk3zDjuEo82U-obsfJMsapaFJFjM2A==\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Determining baseline for PDF generation**\\n\\nI need to figure out the baseline for the last merged PDF generation. I think I might be able to infer that from the build log, checking for when the merged PDF was generated and then seeing how many feeds were counted at that time. Maybe I can open the log tail and start there, as it could show the feed count. Overall, there's some exploration involved, and I'm curious to see what I find!\"}]}" }, { "type": "toolCall", "id": "call_m4fuE7urW5UbgwnoaglHZk9D|fc_0d29dbf88c868f5a016a12ad636d5c8196a8f1475f1a0d134a", "name": "bash", "arguments": { "command": "python3 - <<'PY'\nimport json\nfrom pathlib import Path\np=Path('/home/sebas/work/projects/rss-offline/feed-sources.json')\nfeeds=json.loads(p.read_text())\nprint('current_feeds', len(feeds))\nfor i,f in enumerate(feeds,1):\n print(i, f['name'])\nPY" } }, { "type": "toolCall", "id": "call_K9njh401SLq42WYpj76HG4WY|fc_0d29dbf88c868f5a016a12ad636d688196ba1e454d4c246dc7", "name": "read", "arguments": { "path": "/home/sebas/runtime/rss-offline-build.log", "offset": 1, "limit": 250 } }, { "type": "toolCall", "id": "call_ZoNa70gtrD9NltLF9qyXOjZl|fc_0d29dbf88c868f5a016a12ad636d708196ac1e33ebbaa45744", "name": "bash", "arguments": { "command": "cd /home/sebas && rg -n \"feed-sources.json|rss-offline-latest.pdf|PDF_MERGED_FILENAME|merged\" /home/sebas/runtime /home/sebas/work 2>/dev/null | head -200", "timeout": 20 } } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 1901, "output": 250, "cacheRead": 17408, "cacheWrite": 0, "totalTokens": 19559, "cost": { "input": 0.004752500000000001, "output": 0.0037500000000000003, "cacheRead": 0.004352, "cacheWrite": 0, "total": 0.012854500000000001 } }, "stopReason": "toolUse", "timestamp": 1779608926164, "responseId": "resp_0d29dbf88c868f5a016a12ad5e50c88196b8130ac7c30b57e8" } }, { "type": "message", "id": "d15e1374", "parentId": "c00834da", "timestamp": "2026-05-24T07:49:00.648Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "**Exploring PDF generation tracking**\n\nI need to check file timestamps to determine if any new feeds were added since the last merged PDF generation. The question implies I'm looking at changes made from the last generation to now. I'll compare the modification time of the current feed-sources.json against the PDF's modification time to see if there have been recent modifications. Alternatively, I might look into bash history for any feed name additions. I could also dive into the agents database or documentation to search for feed counts at the time the PDF feature was added.", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12ad6564c48196978704df56d4b160\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABqEq1slNhRtb-tlfwRmGnwADQlI5tPsm2Z44j1z6WUgkYjVcAo-5NvCW1dMg3ZxcNaObFpkmcf4kY6jn1f3vKM_9srWQhxt0sPTK1k3gSfwsyS042-4Eb0bt825XFwnq7TPvyIrTQHHbxklxm_tnWbSSwOaLLCkY-iqjrH7L1esti2ZQf95QHPXJ0qGq2a5j4GMTG0eTgi0AUohCboib36hY1e-IhnqYcm1qjFQEGbBtQ4lu5ad7QTDNckuhC_k5-0_4qL2HmsH_hlDcmsEGcT4v5lRqav4JP57g65fEZHhMSrNNtBWCmmodU88Oipbk93qNKX4T3QnGWKPBgkkUgWPyUgI6MD7uSVqgMc4_ir1xFwyFKEQPJkwt9ZwIxG_MF7ThLL6kohtAU0ZYK2tWUX4U4-PLRlfceNrskM0jW7VD0IYm2OTl8UkdvsqUrBupp070KLpDWgRbr6dhmU0EyfyM3Cr9wwewJC3I41NDK5RIRdsbBh_rCNGlrdKoC-8JG4NcRuCdBApzoAUAHqaptDP-P6slB5fQohqeFaI2SmZWE5U8Vz3dC6ui5SQkqqQ_nr63O1zMzbbHwPlRJ1bDWmQx0ELcJOkZTx4OnopeM6an3vln3mqB0pBScZ3MvrMlHDXDLqHcXUIqzd2k55T8pZ-fL0spnmH3MoVIFhVp-HVDLhlhJbWA2JL0Mdne9nw_LjR8L3fKI872dHCt7H9rg87n_YD_ZLAJ4EI46NjSRX12W0w_5MNcFAOoz-dK71NOYgIbtAmhlDLM9_fVgC4dltlxp47Nq_WQW6arIzJvDb6Ipr4cslMpdcmI4tK5gHAjwufc07DOc7skG6IV-mfltxy2OlghFJW5UuYYtFEhapdpLRtFoFvdSMUXAzmbfVN2e64VkNudsSgSk8w74eZrXGwCU5wfhNQQy47WDqRQs4FRUY_mh0eXvGY_AI3NAbg6FOSVux2l64w8vWoYFVu942RUd3-eDNWbVj0mKHa7s9F5mscQTzoF-Ji5AoUTFMyeCPi8ILV7YBd1FXGZIKd7_45cRq2Zm2sRNib018TtBCRaHtjY413G7kGztASj7s_zlcqhRPSptXlSdNvzvOrocMYNPdZuL7cxLeheT3IsyWmECuXlUmpKeqpd3GMfEImqRgbBPmtRWzUrqKHgbiJqriZdihN9bimmfff3igS7AO_dyJldazKepmkVgWPxc36RhqlFk_UEuApU1n06cJ0amVEha0Vgh-Z4Jc4YiyR6HNB5ZyV4LBTpt6qtzIzzQg3e5j3pPeyph6kqwGd5AGL35tgdc5q0nlvUmU34i5TGi96xZtrONq5P7w4WQzQKbH32jGlRJBGxYWxXNsOjvOqS9Z44xDnBguVNx7v_PU1b1NRJ6hMl_FlABT0a3Az6d6lV4R1whX_uOP-ASevN62BjJyUhq-EkbIdH15M_MgkrMEqx4t0co__oW-NOipl4uDn4syFoMq1ZNw3CxVD4kf9w3OXAOpDRB3kFLFzfjMt1TtiRePyCBVAOsc2dWWYcHHl7qykV7nniiG9dogDCm7xjRoyYddBCTBKELy1S0oSPV1eiZGrb5nP-FALunaBmXfvnGkRYisZOSESeuv7ustNxf1k_dYFO9QS7_-netdK8FDEhsdRx-ymNbwxRHYo_lspFcQ1939EHP6-z5_UP-63nZUNtMukoHmVcmqaGU12Qmwx2or1IA=\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Exploring PDF generation tracking**\\n\\nI need to check file timestamps to determine if any new feeds were added since the last merged PDF generation. The question implies I'm looking at changes made from the last generation to now. I'll compare the modification time of the current feed-sources.json against the PDF's modification time to see if there have been recent modifications. Alternatively, I might look into bash history for any feed name additions. I could also dive into the agents database or documentation to search for feed counts at the time the PDF feature was added.\"}]}" }, { "type": "toolCall", "id": "call_d38WVEovTLkdQRgifg9wROlQ|fc_0d29dbf88c868f5a016a12ad6c654081969ce7b8442363c042", "name": "bash", "arguments": { "command": "python3 - <<'PY'\nimport requests, json\nfor q in ['rss-offline feeds', 'rss-offline pdf', 'feed-sources.json', '17 feeds rss-offline']:\n try:\n r=requests.get('http://100.116.176.16:8091/api/search', params={'q':q}, timeout=10)\n print('\\nQUERY:', q)\n print(r.status_code)\n data=r.json()\n for item in data[:5] if isinstance(data, list) else data.get('items',[])[:5]:\n print(json.dumps(item, ensure_ascii=False)[:500])\n except Exception as e:\n print('ERR', q, e)\nPY", "timeout": 20 } }, { "type": "toolCall", "id": "call_3zAjgYOrLkO6LFh5DLyRheJj|fc_0d29dbf88c868f5a016a12ad6c655c8196bc51fcb7b5c0e27c", "name": "bash", "arguments": { "command": "find /home/sebas -path '*/.git' -prune -o -name 'feed-sources.json*' -o -name '*rss-offline*pdf*' -o -name '*rss-offline*' | head -200", "timeout": 20 } } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 15304, "output": 387, "cacheRead": 18944, "cacheWrite": 0, "totalTokens": 34635, "cost": { "input": 0.03826, "output": 0.005805, "cacheRead": 0.004736, "cacheWrite": 0, "total": 0.048801 } }, "stopReason": "toolUse", "timestamp": 1779608932500, "responseId": "resp_0d29dbf88c868f5a016a12ad64bd5c8196b585270c2bb51bfd" } }, { "type": "message", "id": "8363ebae", "parentId": "bc493efa", "timestamp": "2026-05-24T07:49:06.668Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12ad6f5c4c81968925e3cbeb6f6e2c\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABqEq1y8vOTspDFlz9lByqWzVjaNakxJrNR48V-toQHl9Rwn08p_LGXA_2DCn1Gij6vlcaD2qRqIXDuPB8Y6nn-QCpAl0MPTKppQJmOauaph_lLL9dZmr1XbkX6IbGuxI3Mc49FFKezOOkSrCRy99LnyYpUWKFJFiCKgW4yVvSm_zic0-gY_DNWEk1ZsisbEnSTKQFeFlfMrNm7WGAHN_VwYVntrTEnp_yTPnenZi6mevCT27qdt2HjAXfBitu9an1jBEQts4vOfdcSD6wl7cZZMORf-0D1L30160ka5WPoILSsSfhnhroyEBvBfy11ZWeeVdJqxKAyBEPerf6sTaLkPjNcdiTbIyqdaYJ1iyDGYk39PHI3-MhPaiJq7JeMqV1R8XE9WU9J0R241sgOgWdk0URu-Nb9N_ZoSuUuGC6f-w7fUHJl52KMyf423EaBvqPbfO_b_AVVq7JjCTTvfnKY_4v2K1CBFgmGMyo-ywE6thV2AkspQO_aUKcw6eO7XvRI5y4KT7wZH6FEeEz2-dYgtQxCt-k0kKQtCs59l99hwp6azuSfxFr_uVLfLKuUdk8R-yFPVrnTC1uW5KWSOQVGz-BSXHIea-x_eq313pt8XH38Im5s2HFe1AUmE_SQiwARDdmNHWtXwlEAv2YqONi8nWx4xH1caBkVEqXJFIVFZXPnofkeh7vaD9GjPQgnd1abbWQ8gsFoWAl9P00J7oRMnDZHOgz-H2S33jGjcSJ69nu-lmsA7ZIiLKARQr_cAM8O4trjZm53NuvzcMoJrKNufI_1O-EIbWFgnJCij_rD01mTyWDbWqkBdJXs4qYJ-CA7sbBDMIc1V-KNJecopyYPOIjt7bopWBHfOtTGg0W9QvtWrAjV3_uzVJg9n_bttnVuZUU7wucf-u5WBe62xEMFIDp40TzI6IfRxFOAY-CTe2tuJSjnuvxKIMrzRX3TWp3R071V6Vty7tEQvn3f72KJ4DpAOlry0sHqfkOvU3Ed-IbLDp8RX2L9Wqz397rk69lr2LLV\",\"summary\":[]}" }, { "type": "toolCall", "id": "call_s0d7eo91pDwFCuJK7wcbrRWq|fc_0d29dbf88c868f5a016a12ad728b9081969f2cbf2c91a1d3a2", "name": "bash", "arguments": { "command": "python3 - <<'PY'\nimport requests, json\nr=requests.get('http://100.116.176.16:8091/api/search', params={'q':'rss-offline'}, timeout=10)\nprint(r.text[:4000])\nPY", "timeout": 20 } }, { "type": "toolCall", "id": "call_uX1F2ylzsKYJgAaIIvihbYxr|fc_0d29dbf88c868f5a016a12ad728b9c8196b91c7fde948d94c4", "name": "bash", "arguments": { "command": "stat -c '%y %n' /home/sebas/work/projects/rss-offline/feed-sources.json /home/sebas/work/projects/rss-offline/build.py /home/sebas/runtime/rss-offline-build.log" } } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 1069, "output": 167, "cacheRead": 33792, "cacheWrite": 0, "totalTokens": 35028, "cost": { "input": 0.0026725000000000004, "output": 0.002505, "cacheRead": 0.008447999999999999, "cacheWrite": 0, "total": 0.013625499999999999 } }, "stopReason": "toolUse", "timestamp": 1779608942617, "responseId": "resp_0d29dbf88c868f5a016a12ad6ec1bc81969c8431c5a67e4bbf" } }, { "type": "message", "id": "cdb6ad47", "parentId": "42390b65", "timestamp": "2026-05-24T07:49:15.523Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "**Evaluating feed sources**\n\nOkay, I've noted that the feed sources haven't changed since the last PDF stabilization on May 20, and the list hasn’t been updated since May 15. Since then, there haven’t been any new RSS feeds generated. When asking how many new RSS feeds are available, it seems clear that there have been zero since the last PDF build. If the user means articles, I can mention that articles might be easier to find based on memory and standard locations.", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12ad74fdf4819697d36dfc70bc1f6d\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABqEq15eeh7s5m8kYDNcINSN-zOcwPJQouImJrU38t_XPI376bTwLUoPTmgtxGjEMoT9juXI0NlUBmZEirPF3IlslXSFnT4UiFMGDrod0xf4kHuUTmY0veDno_77LpeXebX76bULsD0mIPhCG-DLZFnHVtS9vljGoSIrWfAq1ltiri65Nu4s5RyIqGlGhCXWRS2RyUFmC6Z3dFu-wlxfPF7kQZcjIdwoVnyBGza73MMcLxEA4HIgE1b5ZM8XFKg8WbaMZCorfCN5tGF2STrRiIp0RsHBK6ZZ64Jebjo7vMv_L9V4Se_ddQ7RFn3PXIcard2zDTwl0wBgy9hPKv7tstKt_EoBPa8_0Qu6iYFckfqoOZBp_JTxhD8G9eDOCpIvhvLOHvwzJVJ4E15-r6flG7VyoRIOXzcKqu2EP0Zaa5ob6ddq7p9rnd_exE_6wldljv3QKTldDRyAbeffx17A7FZXoIaFsOzlpPm9jRARIqJBkOV8UiqN1g_kzXcuOKWJobZoR9VdFmHZ2YnYK4u8EWSQCBIGjkU62ZZWcEqLoJVHoz2QkXE3eXagXTA2or-vK5MY7L2cjZ84aTTpR2Xhfro1UP2Y4EKQNUr4gKlgqRspAN8mUsOEta74HohERENpetNnTLLrg9RLWj_c88m9yjpE27zTAc21CDl6i57REQbM_hQa2kxDQfuyPyx4MOo5-5U82wMN03MLYrjb0RzVt5fxKdWAHpxTIIeh7EPniALcUMeM9nguyuUfwvQ5xpTCQ9sY0ea5_oGfJhdg2R8tnpfTzKqr-TVQGeinqC-bu10Bg841dDfuzOo-y_7n3mjxN0j8Tpc-LdyoemcVdrFca9n1AuJgIF0QVP0mZxcqB1D8mTdpqvraltwh3cTEMOXDQX34jbWLTPRbbqdmNcfzvFUyHN10zhvR8SFOsQA2F_nOsCv4HAuSu3sWhCe0tHzPE_XP_8OGj3fTU5--ktlZ2NeWtJUrsZJh211Ryq4zPzhFDpObbmQWjrHjSUgTE7X13hKL302PifFForE4s2u0j80E6BKcMIv0QdeOtcPSdTJhdTr5pm4QJF-P_-AN9rDbUqZtpqCjzADowkj5axOlX6MpDYPURX9mCX45NdZwzQ59m7-N3OvLRvbL6Q9rpzLFI6gVpPauOqfEfR1opyTxd8ibSmL_fLmfg0dJOsjR7BB3jGID1FJNwSsGA36mLlNKSEApUW9uMiukT47Jws_0z3RgszoorSsCeIggNCvmoLfkW--_89X__LYTJxY--4eyy6znJUprb-h8WaQ57nhkXMuF5n7lIk5p6CHXM9bOx_1DC6jRqzx4OWaRYRToqNBwDZEAHmB9cBLskE-xyQ81s3CxUiT7jDJ7gqSM8wCBvQP-huKXF589DBbsLhqM4L_yF1piF86Ese3zKGWRQMa2MMv1VgwFlU_Itmt-K9nTIBxI-KTqerMRoWYGYyY1BITuO1L90EaS55SrrbuXW95OOPm8xFj2GxmcbeBLJYvK0hCjbrRt_JHkReAKaUwjFR1b3pcqTZ6sztoDD6SMeFp829WECIZTNzQYi1sHR8yklmR5EJqRC4y9u3G6upf2dh65BPT4fz3sf8Lw2Q7qXrdfs1KFSwuNXo9HxJ4TGzXzDwv-DuAO0ixWUL2wFXZub3oRCZ7PwULHqvh_IHMwCFoD1WCGGZvnPLZ5Xy37E-md4eOi7-bV7tNO1X_nTrt62slsdebp9AjXgZgnsn6ZjbwhkcDAo1MIk2gXmOfR69ql4O5llRyVdRVH6PmkfXJPeT9echgJNT6jgnvhXMlCAFbrBfSGdCO0hptULky49YWTtOQO3IBIjqzm8dqFaLPMPDRCFfnriGplZJCszwuOd_ESf4AgK9gKg==\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Evaluating feed sources**\\n\\nOkay, I've noted that the feed sources haven't changed since the last PDF stabilization on May 20, and the list hasn’t been updated since May 15. Since then, there haven’t been any new RSS feeds generated. When asking how many new RSS feeds are available, it seems clear that there have been zero since the last PDF build. If the user means articles, I can mention that articles might be easier to find based on memory and standard locations.\"}]}" }, { "type": "text", "text": "0 new feeds.\n\nWhy:\n- current feed list: 17 feeds\n- `feed-sources.json` last changed:\n 2026-05-15\n- PDF path/stable merged PDF setup was after that\n and latest merged PDF was generated\n 2026-05-24 04:34\n\nSo no feed sources were added after the\nlast merged PDF generation.\n\nSecond question:\neasy to find.\nI found it fast.\n\nMain clues:\n- durable memory already had the exact\n `rss-offline-latest.pdf` path\n- standard output path:\n `/var/www/rss-offline/rss-offline-latest.pdf`\n\nSo: low friction, not a long hunt.", "textSignature": "{\"v\":1,\"id\":\"msg_0d29dbf88c868f5a016a12ad79fa0481968361242945f4ea54\",\"phase\":\"final_answer\"}" } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 2113, "output": 318, "cacheRead": 34304, "cacheWrite": 0, "totalTokens": 36735, "cost": { "input": 0.005282500000000001, "output": 0.00477, "cacheRead": 0.008576, "cacheWrite": 0, "total": 0.0186285 } }, "stopReason": "stop", "timestamp": 1779608946926, "responseId": "resp_0d29dbf88c868f5a016a12ad7311a48196b26d44b8407a9275" } }, { "type": "message", "id": "aa551030", "parentId": "cdb6ad47", "timestamp": "2026-05-24T07:50:56.321Z", "message": { "role": "user", "content": [ { "type": "text", "text": "[telegram] ok. and btw how is the memory system going last month? brief me on activity" } ], "timestamp": 1779609056314 } }, { "type": "message", "id": "1f874bd6", "parentId": "aa551030", "timestamp": "2026-05-24T07:51:01.839Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "**Investigating recent activity**\n\nI think I should query the agents database for last month's activity to gather relevant insights. It seems like loading the skill memory-read could be useful too. I want to keep it concise, so using something like bash with curl might just do the trick. I’ll also need to inspect the API to search for any recent memories that could provide further context. Let’s see how that all comes together!", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12ade14e8081968cecedf5e9a00fe8\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABqEq3lk6shT5So0D7Z_DhKVJAYCakibq1Lb93eHR3-hXiuCwLYqfhgUPcFzdgrmXuBIYnGsxs1-yM6j-lfrwVRJBtZufsmoYuFQEz1bHKmpKjRTSaBpL51fCaki4lPTTsHHZ3ciCZp2iiG71Rl5B82E3Vyufx_lmLrd60OwyMGtWK-oj0rk5NQFY7qeQDaCvuAXQOffrc95wqCb0MY3PxtIX33u6EaUeMFc7VMsAGJ8vo0GOJB0QVnbqomx1dtx632P6CuGJlaTw0ggo_w4KgFUyCY2Nilzp9h4kqfGAtwImEIsUMoVeeFDvDrSkwcMC-zpN66-0tJJJeBR5F_s7jVtlLhNuvEnCZrYXyvuz7ixvrvL8V7gWtlfWKe1SR4HGggr3b6c7WaJZjw8FWVSIk7GuxKz84haZEfcsGFw_alYZYcIjPz2pPj9fGKctBXJBO1vG2WUITsFROWnHaDGHiMGMMmHmfkVSiDDqyu5CT5i2QqDiEom70iMx_IJmBXS5vuHXqoUzIShkTxfZ2v6VjASfhed1-H6CpgrXIMrv33NOrZWE2yghkSxYrrooTTi8_EiU18AdzskRfzQZLUMzJS3zs31NPXZ36OZwERNNfSxuRysIkZBekEZ5DJvg34TR3ymKRDPFCAVjXIyeO_QhbLv1BzE0R4nZR9m2_6v6v_OG0Uvapht49tROnYkPLF4WLAbJhdWCKT9XNPwN6TX-FEGG_SXBLrhz3nxaEdUOb3U0tMwYqH8XGfhj--2-yGRGewi_syXCLLMwsP1UDOOMf1ldRYf_bYkwZIv-Ri3umkhQHrWqtGrQdK4LL6HGSH2EkS_o9ag_cM4S3nSHSHDAFs7CvwemKELvhQ_xBZc1ofSyDSzpXaLaent-HhMYU3YoLmKn_qDAL2kNpFddl5dD7BuJ-bfE9E8TIeGhefj42y_T5VmpVbcOEIbnfIXvXOKXPhTKzIShDdsLX6R1M0lp35-be-AjK6vEu1AAuISYp4RjGEEfFbbM3ZgPZW-iJOpxzG_YmvX6JvriJ-AgqFw2azSBNHxnU8Vnz_xxl73g35-Xff1L7efsjEoI0A0bE1BFqDpm0Yp9DM6U8eghfyKIFraRhyRn0-3ZB_E2k1Z2-7BSAaU58f6nfvIqrId1nBs9tHbLtEhRE0MngteOMgrfOTctp54Q==\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Investigating recent activity**\\n\\nI think I should query the agents database for last month's activity to gather relevant insights. It seems like loading the skill memory-read could be useful too. I want to keep it concise, so using something like bash with curl might just do the trick. I’ll also need to inspect the API to search for any recent memories that could provide further context. Let’s see how that all comes together!\"}]}" }, { "type": "toolCall", "id": "call_8wgk8WyaIItAsmtZu05tQD3G|fc_0d29dbf88c868f5a016a12ade5962881968e7ffb8b85f677f7", "name": "read", "arguments": { "path": "/home/sebas/.agents/skills/memory-read/SKILL.md" } }, { "type": "toolCall", "id": "call_aGNqfTKF0PFqx0nD68eQGvpU|fc_0d29dbf88c868f5a016a12ade596348196b9f229cc6d4a18a9", "name": "bash", "arguments": { "command": "python3 - <<'PY'\nimport requests, json\nfor ep in ['status','search?q=*','search?q=memory','context?id=mem_2547c456e8d845ffad407ad5b606e24a']:\n url='http://100.116.176.16:8091/api/'+ep\n try:\n r=requests.get(url, timeout=10)\n print('\\nURL',url,'STATUS',r.status_code)\n print(r.text[:1500])\n except Exception as e:\n print('ERR',url,e)\nPY", "timeout": 20 } } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 36275, "output": 236, "cacheRead": 0, "cacheWrite": 0, "totalTokens": 36511, "cost": { "input": 0.0906875, "output": 0.00354, "cacheRead": 0, "cacheWrite": 0, "total": 0.0942275 } }, "stopReason": "toolUse", "timestamp": 1779609056315, "responseId": "resp_0d29dbf88c868f5a016a12ade075d4819690174ea21680cc99" } }, { "type": "message", "id": "164fbabe", "parentId": "4de96f60", "timestamp": "2026-05-24T07:51:08.299Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "**Exploring activity metrics**\n\nI need to assess the activity from last month and consider counting memories by date and type. I’m thinking querying the SQLite database directly might be easier for this task. I should use the status database path and run a query to get counts from the last 30 days, focusing on top projects and types. This way, I'll get a clearer picture of what’s been going on!", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12ade6f6708196a655f9de091437a6\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABqEq3sJDRaZyf3FKaK2c4vht4vQmcSO4VGg1mfMh_E4Vke_J7Vx2QzGh9DOIMUxXgcbd4oUgRiA8HL30yDQ4zA-fMpvaFrKvAaOD4fzGfGF43wqooHxdF3eo2LNZyjYwTWTOdlJy3e3OcTl_kaEauA0e4Zg5FF4OCAkWFHGOGEjrfQcA0OegEe6a_yK2ih16qfOSWweIX2LFDbqGZ__BNOsUfJD8NX2ovsm7D2Xn_QhDLRn5Hnc7Su9ICZyp6jE6wlHSh1CQA3NqYSJ0LriYiqu-ATiQdtQUNSuqm2qg_GEsf8J6NH9Cn3nOxnJfmhwgGen0gmDZ3S0XVR3HyJk_QSwgekkifax-YeYj9TjQTaNwC5mL78mLfFy3f_BLTvZoOkjtZCa-nF2WFeqNAyvmjGXTLa1BpGBwi9455vltDPqWaFQfj-sBE4UOQpiPH9_jnBWlcAwfhDScU8dCfIAZVtuaBGNXRYKb4BVsgoAOzyTTSH4uCXGaSVs6agCANZYyzSHF5zOn9xN74SLHpPIY3yfIGLA3FDPIX6-u9KhY69Xv5NaSIQ8X27n3S8o1Xywsky0I7rAllCRBnFQ2j9IJHoTeIQAvBHEBz19hJaKpONOlyIGOKjmyD803CSRevx_cUq2VtfrAiWWecj57wGwQC6YNrNoOChDlDrNoV4geLajx7UuLch_ZycECbeV69o5IDYKIvk1bVVnHZII2O5wt81D6gRBIL3mUR7JejqyQBhLXbbXaxjoKX32LMNkWnctNM-i9OyybpER8nAlJajBfuHLbcH0MZ6x3ZMzUu7pEDpb22DdmGt4i8WK27rBSXzJvZm9ZvmPD9owyYKGduEWFHieAZ-qzNOVBsHPoJu3hx47frmB7WcTsHIsW0ISQqi0uNTAI611wmbkZ3UQN9ozETrcsKd4e9YCTe6XQ16lgGmnU67IqnFSis-LEHb_BdebMfdixKWqDfzvNtnFeJshhoCpt_9zTyVP3N0I4HcdaTmgWZdLK0vyzVJJYWM2CL4HTiydANhutpp9XmhRqNr1pHbCMqL1iovidWgregamRoQKfKXwQ3qgjTMu1BQSu87ZpwZq54VIFK5W8IpgM1OIZUuGBQJbYq-qaNTR8RFgA9iuLn3ZmNxhfYAGVsia-ItdzuvkxsUYiXmuUZes7KkGIQzCZ92gQ==\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Exploring activity metrics**\\n\\nI need to assess the activity from last month and consider counting memories by date and type. I’m thinking querying the SQLite database directly might be easier for this task. I should use the status database path and run a query to get counts from the last 30 days, focusing on top projects and types. This way, I'll get a clearer picture of what’s been going on!\"}]}" }, { "type": "toolCall", "id": "call_UdNja0C4zHUngCCLKBEUKiTE|fc_0d29dbf88c868f5a016a12adec0a4c8196ba50326b69225242", "name": "bash", "arguments": { "command": "sqlite3 /home/sebas/agents-database/data/shared-agent-memory.sqlite3 \"select date(created_at), count(*) from memories where datetime(created_at) >= datetime('now','-30 days') group by date(created_at) order by date(created_at);\"", "timeout": 20 } }, { "type": "toolCall", "id": "call_SUnKewFNoXq1j8kcwHJu6yfy|fc_0d29dbf88c868f5a016a12adec0a5c819697ab487b237a1534", "name": "bash", "arguments": { "command": "sqlite3 /home/sebas/agents-database/data/shared-agent-memory.sqlite3 \"select type, count(*) from memories where datetime(created_at) >= datetime('now','-30 days') group by type order by count(*) desc;\"", "timeout": 20 } }, { "type": "toolCall", "id": "call_Xf5F2d2VtA36KWBluTe10iN9|fc_0d29dbf88c868f5a016a12adec0a688196939b37c505e39ac8", "name": "bash", "arguments": { "command": "sqlite3 /home/sebas/agents-database/data/shared-agent-memory.sqlite3 \"select coalesce(project_id,'(none)'), count(*) from memories where datetime(created_at) >= datetime('now','-30 days') group by coalesce(project_id,'(none)') order by count(*) desc limit 15;\"", "timeout": 20 } } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 2769, "output": 280, "cacheRead": 35840, "cacheWrite": 0, "totalTokens": 38889, "cost": { "input": 0.006922500000000001, "output": 0.0042, "cacheRead": 0.00896, "cacheWrite": 0, "total": 0.0200825 } }, "stopReason": "toolUse", "timestamp": 1779609062133, "responseId": "resp_0d29dbf88c868f5a016a12ade646888196be171608cb723fcc" } }, { "type": "message", "id": "8f95f3a4", "parentId": "04e7a5f0", "timestamp": "2026-05-24T07:51:16.288Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12aded299881969e42a877e24e00e8\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABqEq30P-OouQk6m0htxHhzv9DOwn8Oc-xmuWRYL8NvTBj-IwbXzSuzsQnjS4WIaiOUvq3eeai-KhW49rg77CxEwgO7Zw9viQsH3WCT7sSz-KIw23hDmOGThhEirtfAsacGEM3O9KiLCsoU_e3iDNZyqSkcGTz8plEqN_bAfmXrqiRzJKKKkYuEbtuKh6Xx3sCK6DaQczNhg3SZmEp6TDYGcHFR8yVADi0kcaoEKvndzbuBfRnD1tYGVpuShMTmUg8rzyYWo63OdXCpr82woGWAqhULWYymBG3o358O6gzemGIkWReBvm20E6nOYAwWyNR26KrD5CBbkArpqrto5NZO1BjrMkjCp0p8sFXESpg4RVy0LzxSMRBbByGd2ZQ4O-vb7jar3VoO4_e0RXxKXwXGj4-iPbdvWnxPMUhNCcwMYOBf4Cx4NIyOXm5FrYHualoE_kLUiZ0-Uzxp9ZXHUm8qMDRwlgGER8AAj2hm7tEj5UdJdm1YIu_CoymoCokA6CKP9d_BqwbkhtPkickILAjeVXEcqU8eBOdSswTMGoFXJIuokZd_j2Mkh4yVn3HX6xnNOyCNT_qiVHof4VYe-nvAOEOscoY507L3oisbyBA1I6r3iVB9VdIldPKhf1mSfYzC8bZSJwhdcjRhn6lRondv7JTNI-YF9reDTp22XqlocFrQ-TPRvP6e2lCcfffo5D7eaUR5ix2EHDWnLs0X1veXRnwI6DNLd26tMVka-dd3JK43le3t5IhQQ53h5J0mlsKHlnpN6HY4xjjQpIbRTnc88iAQsTiv08E_ZOAZTEdZmMvOk1M3ozEE_sJadpODDYIGRB4E-Ys3NmNk32pJGzEZfeZyzD9aS3gcSbF0Urc49YiO2qPCzCWw1ZUIUukXiXeXUc4m732GdNgxhdIQWs4VUIoaJ92kNJn0zsfHRTNjKAlI3W32yM6bUQsT--uVkeQskxcg\",\"summary\":[]}" }, { "type": "toolCall", "id": "call_OQTt8Di1VNDKO1SCIvJmzZ5Q|fc_0d29dbf88c868f5a016a12adf406b88196987abd50ddc5cbee", "name": "bash", "arguments": { "command": "python3 - <<'PY'\nimport sqlite3\ncon=sqlite3.connect('/home/sebas/agents-database/data/shared-agent-memory.sqlite3')\ncur=con.cursor()\nfor row in cur.execute(\"select substr(created_at,1,10) as d, count(*) from memories where datetime(created_at) >= datetime('now','-30 days') group by d order by d\"):\n print(*row, sep='\\t')\nPY", "timeout": 20 } }, { "type": "toolCall", "id": "call_1V93z2DXR6gQhEY2NItJ1R1K|fc_0d29dbf88c868f5a016a12adf406c88196963c33e46727f5ef", "name": "bash", "arguments": { "command": "python3 - <<'PY'\nimport sqlite3\ncon=sqlite3.connect('/home/sebas/agents-database/data/shared-agent-memory.sqlite3')\ncur=con.cursor()\nfor row in cur.execute(\"select type, count(*) from memories where datetime(created_at) >= datetime('now','-30 days') group by type order by count(*) desc\"):\n print(*row, sep='\\t')\nPY", "timeout": 20 } }, { "type": "toolCall", "id": "call_ciKRbmRM0jd9hj79Tk9JFARi|fc_0d29dbf88c868f5a016a12adf406d08196917b63010d3b1c50", "name": "bash", "arguments": { "command": "python3 - <<'PY'\nimport sqlite3\ncon=sqlite3.connect('/home/sebas/agents-database/data/shared-agent-memory.sqlite3')\ncur=con.cursor()\nfor row in cur.execute(\"select coalesce(project_id,'(none)'), count(*) from memories where datetime(created_at) >= datetime('now','-30 days') group by coalesce(project_id,'(none)') order by count(*) desc limit 15\"):\n print(*row, sep='\\t')\nPY", "timeout": 20 } } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 578, "output": 379, "cacheRead": 38400, "cacheWrite": 0, "totalTokens": 39357, "cost": { "input": 0.001445, "output": 0.005685, "cacheRead": 0.0096, "cacheWrite": 0, "total": 0.01673 } }, "stopReason": "toolUse", "timestamp": 1779609068321, "responseId": "resp_0d29dbf88c868f5a016a12adec762c8196901ef0c8242ebf40" } }, { "type": "message", "id": "bf9a15aa", "parentId": "58c9c354", "timestamp": "2026-05-24T07:51:24.748Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "**Gathering activity data**\n\nI think I need to find a total count of activities and compare them to see what's healthy. I should also consider counts of active tasks and look into recent tasks in the database. It might be useful to gather all memories, possibly sorting by origin or agent, along with the top titles and recent activities. That way, I can create a brief overview of activity.", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12adf549bc819685ca40de5b53fa1c\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABqEq38EJbr5f57H3oSQVyquJNMwkezqcoTlZC534iH5fiB6lntd1_0_x4FMoTSXRm9uHK1EmzuAzjJMtcOXprQEzIxUe2Z13z42r3-dI0uRwX_KwJ_6rAKAHqwkeX065Z8VfeU2_1PNdbHk_7OCjOvPEl5Az6flKc52NNk7xwHws-YFDea1DJxPTAyf7uygOX7uUZQewy0CdVN6bLb_ZX1RDi0HAkhbpAdC0TJgbEnhid_o_3s8RokmbcFvPovJtKUYmIqlMPVhTaNnFtdTvidVkzevW9fsyxvLQ8OBEUCPlCs82oKS-HHfSmki7eJHmW6a3RNwFb-ZyekTacDRbAgl2Wxj_qIxbtfVeqqbE3ayEwo1Z3gCzTSnwSLkHwbwXswEYl-UcV61Jrf_sFJTtw_Ejsm-ziIWeldt8AH5NdsnsEE9qCB_e-ZnTCXrCP4yNV_CHMsEuN2tAV5JRRy9PHNeL8Bowc_Z-w1LRH_sxMRilfJb-k66RU7nU8V8lbCIVxSmx9vCo93zFDNmJXeDRdA-3k4AbF8GN2pxg8LIhdepoDb_YQQrDWQt0suw0HWewdDAKzMgyQle0g3QaPOK9Z8xpCjNwu43bKF2Dv7ukFdpn8xT2O6eCoP7cLUntzDrAmNTa93atpVH4EsLdiKl-TWHTbOOllh8ETyJ99D3JPj8TVpEqMPNt5m70yhUoHUscP7J46QXgMNYH6CZpmqMoo44-RScNKpmeQc__OuVBbXXuO_CRIESrrLMQiw9L5vgeLNVLSu0b47slDkXUlD0wXwYGG6PUmxt0we9AXK-9cAC08wpceL_UStMxvG38ETSagZ0CaEbtLPB-1Hsh3_UM3o_FtBMdK5HotJ2S2NBphIaeqaXPh7sbu4Whzgy_T4S9UPysBdDH5GlkwJL29SgY8luuto4Jhi5Dgg5aHuwweRytMPrAGfmACsLsdtpq5hCBwDtazmNfZwhMe2itfZzyH_lbHGQVbO0my-4WYTnJpPe04WWsPt9_As1XZiYEejdaHs47oynQxpIBrnLTOHbJdcxo0RcofknA_kXkvVinaR7GwjkZXVHpJmyByPkofhHU62GOnVuHxMuMYktUjSgXIHqIImB4W02GFjQtF0ZeMIG4eQjNFE-wnvg-IGFvKPLizkWwpwrcs0vVnddnxVZloKjsrzGunljbv-7Ajv2S5ofwlQGVo=\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Gathering activity data**\\n\\nI think I need to find a total count of activities and compare them to see what's healthy. I should also consider counts of active tasks and look into recent tasks in the database. It might be useful to gather all memories, possibly sorting by origin or agent, along with the top titles and recent activities. That way, I can create a brief overview of activity.\"}]}" }, { "type": "toolCall", "id": "call_MRlWTRNf4pgec7EWUZKSRYm9|fc_0d29dbf88c868f5a016a12adfc7e60819686fb1f43ba1440cd", "name": "bash", "arguments": { "command": "python3 - <<'PY'\nimport sqlite3\ncon=sqlite3.connect('/home/sebas/agents-database/data/shared-agent-memory.sqlite3')\ncur=con.cursor()\nrow=cur.execute(\"select count(*) from memories where datetime(created_at) >= datetime('now','-30 days')\").fetchone()\nprint(row[0])\nPY", "timeout": 20 } }, { "type": "toolCall", "id": "call_Q823Y0IW31Brwsw2gwKr6yah|fc_0d29dbf88c868f5a016a12adfc7e7881968af02d03fe074365", "name": "bash", "arguments": { "command": "python3 - <<'PY'\nimport sqlite3\ncon=sqlite3.connect('/home/sebas/agents-database/data/shared-agent-memory.sqlite3')\ncur=con.cursor()\nfor row in cur.execute(\"select coalesce(origin_agent,'(none)'), count(*) from memories where datetime(created_at) >= datetime('now','-30 days') group by coalesce(origin_agent,'(none)') order by count(*) desc\"):\n print(*row, sep='\\t')\nPY", "timeout": 20 } }, { "type": "toolCall", "id": "call_H7qpBxgaEeyH1iFG8xGHrPK3|fc_0d29dbf88c868f5a016a12adfc7e808196a28c7f0c106c8a82", "name": "bash", "arguments": { "command": "python3 - <<'PY'\nimport sqlite3\ncon=sqlite3.connect('/home/sebas/agents-database/data/shared-agent-memory.sqlite3')\ncur=con.cursor()\nfor row in cur.execute(\"select substr(created_at,1,10), type, title from memories where datetime(created_at) >= datetime('now','-30 days') order by datetime(created_at) desc limit 12\"):\n print(' | '.join(row))\nPY", "timeout": 20 } } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 1102, "output": 398, "cacheRead": 38400, "cacheWrite": 0, "totalTokens": 39900, "cost": { "input": 0.002755, "output": 0.0059700000000000005, "cacheRead": 0.0096, "cacheWrite": 0, "total": 0.018325 } }, "stopReason": "toolUse", "timestamp": 1779609076366, "responseId": "resp_0d29dbf88c868f5a016a12adf481a08196bb6ea0fa11560b51" } }, { "type": "message", "id": "e076e2f6", "parentId": "8c8f6580", "timestamp": "2026-05-24T07:51:32.651Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "**Considering memory tasks**\n\nI think I need to check if the user is looking for activities from the last month. It’s worth mentioning that memory writes are durable, with around 32 entries clustered by date that track mostly decisions and projects. I could also mention that the infrastructure seems active and that the search and status from the API are healthy. Including notable themes might provide more context for the user. Let’s piece together this information!", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12adfda4388196a5b06e694faee747\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABqEq4Ailqr91pvJY_K9h7sMDyTisxCpvvuL8MlILIguO7yxuDTxBFIlBn78b3qbj-fCBnySw5GmAqd1UyJ3iQd4oO1r-Mf31z41_0NBXC-u-6FiW8nYiaTwtUcTfdT_5wYSeQkDR_JSBzijHXrcmzYOMjG7_8QkwrmPlwkHBpbj36XyMUTCQWbyBXABGDp52YlL3KyaiU0-gJjxqrSyg2RTRRiXIF22zO32ocQ5gQ6P3rTKJnuU2fQuZP-vrWr-NnE6eAjSQTyc1nJ9W6N5ue2aVIuAJRCpD5nxv6lWIcDcZVWcjzagHnWZIoCmNhPTeOKLudYeAEJ9p66VsilH24seMW0PzeP9Q02OzzjJp624z5DLeMXlWejcpqMn-zIR3rhRo0mmxbNNqLZcTQAsODxaumZRrP77R0AXYBzsMG01SVXWwUutDmz0Tro_V_BUA9cwFDzp6eyEmO3TAQXtMdNU8wowfhTQSoaQLBQFrUH_tplm0CDOCAd9_mTj4CP1s3Xe0uSu2XHueLzQItrEvPzXI11Q9DTqqTGgkz9nBMcGUR0MxX7hvW45EK_OjasYPTPimj0hftZatGqf2mZpkkg_5IuQW42zk0Hf5LvLORZf0XTHetZ7zyPtycl72ZWpnn5nIS2FztmSm_MG0xoDZhxIdm0VGMnoVxhKrPdftJbhPL_6d2z8SZ180e_zKQOkdS-I6r2odzVK2a_Zor22WOveyZBF7RTOJbQ-iFHGl5kq_g-srUgB9mBKskjtA0gySMxzNdXbgXkGG4y3_iWTL_vz1VOWkJegWk474ojnw93CpeHtBThWkLPS9trzfcC0EhfhRPCaOUL64KtVv5GJBnaq6VypcT0Rlq1w5R7xoH0hbZvMB5ZoN7t1t1yNLf9xxUfgoDJ1qd-G2AA_rKBt2fdbrqykve65u_ugdOcCh7NGiwx77PQvav0RtPE7OoUQxxFlqhzngYXSEDhImhCVtI8pJu0PK3Rbbof-2yO4wRPdIXsF_piPNE3NrhddXDymctpTsiTs-0gqSyqdTzKYglCN3ZPQFdrjAU3sk68QK4UgJULG04rQ3uKNDW60GMA0WEwP76QU3xpZeJlh1o3xHhYSq7yt_oJiOEcDJ-e_Mkp0CdVHRSEBChc9E-B3MZrtF3jBGhPk4JY4JEZmKZFNkxNJ2fKnOevPQNNutJDeXMwOjb_WbdiM9uNw1K_KQ35XO_TEpjF5bmLr7jRvQ36jyl-YCFng5lQZB-1DcBhVgyjXMMqZY45gqzVJBl6_ugRMvskEtZX\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Considering memory tasks**\\n\\nI think I need to check if the user is looking for activities from the last month. It’s worth mentioning that memory writes are durable, with around 32 entries clustered by date that track mostly decisions and projects. I could also mention that the infrastructure seems active and that the search and status from the API are healthy. Including notable themes might provide more context for the user. Let’s piece together this information!\"}]}" }, { "type": "text", "text": "Last 30 days: active enough.\n\nQuick read:\n- 32 new memories\n- writers:\n - personal-agent: 23\n - session analyzer: 8\n- types:\n - decision: 10\n - project: 10\n - artifact: 5\n - profile: 4\n - episode: 3\n\nActivity spikes:\n- May 5: 9 writes\n- Apr 29–May 1: 14 writes\n- May 20–21: small burst\n\nWhat got stored most:\n- infra/layout decisions on `ballbox-first`\n- tmux/native workflow shift\n- memory-layer RFC approval\n- rss-offline PDF/EPUB decisions\n- a few durable user prefs\n\nRecent examples:\n- `rss-offline PDF pack stabilized`\n- `Vending web v1 scope and test notification`\n- `User wants minimal repetition`\n- `ballbox-first uses home-first agent layout`\n\nMy read:\n- system is being used, not abandoned\n- bias is good: more decisions/project facts than noisy session junk\n- still light volume, but signal quality looks decent\n\nOperationally:\n- API is up\n- search works\n- status endpoint works\n\nWeak spot:\n- most memories have no `project_id`\n (`32/32` in last month were `(none)`)\n- so retrieval works, but project scoping is underused\n\nIf you want, I can also give:\n1. trend vs previous month\n2. top themes by project/repo\n3. quality audit of the last 30 days", "textSignature": "{\"v\":1,\"id\":\"msg_0d29dbf88c868f5a016a12ae00a65481968e98b285cd9d1e3c\",\"phase\":\"final_answer\"}" } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 769, "output": 382, "cacheRead": 39424, "cacheWrite": 0, "totalTokens": 40575, "cost": { "input": 0.0019225000000000002, "output": 0.00573, "cacheRead": 0.009856, "cacheWrite": 0, "total": 0.0175085 } }, "stopReason": "stop", "timestamp": 1779609084851, "responseId": "resp_0d29dbf88c868f5a016a12adfcfd788196ace36d5051537568" } }, { "type": "message", "id": "26531e92", "parentId": "e076e2f6", "timestamp": "2026-05-24T07:53:42.844Z", "message": { "role": "user", "content": [ { "type": "text", "text": "[telegram] and memory upgrades? like for stronger signal?\nand conflicts?\nall those automatic processes" } ], "timestamp": 1779609222838 } }, { "type": "message", "id": "0e7f2d48", "parentId": "26531e92", "timestamp": "2026-05-24T07:53:51.980Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "**Figuring out memory handling**\n\nI need to provide a concise answer. I could look into memories related to memory layer RFC and possibly conflict handling. I should mention any automatic processes involved. It seems like using the database or search might be sufficient for what I'm trying to accomplish. I want to ensure I cover all necessary angles without getting too complicated! Keeping it straightforward will make it easier for others to understand.", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12ae8971108196922179f102ad9a37\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABqEq6Pyj0W53K5IVOfy-lF5mtiyv50xx99_fOV0v4-hit6W1b3Doi4mfya3d1gN9pEBt69F2Wbytt4Um3KdLq3iZcalth9dhwYIw_t9KGJoufShKLPOrYf5HgC8FHaAYxe78cIydD-Prxjm3-zlfXe5gnSYaNii2esTE4F45Q917cjBYPbHaaReBI_nOUxeuFLLpvqz93qu1DDzVEZpvpjRGvyHYKJtIDIY5d_NofHVcnVpj1lsAdUOrTl550taOoFF_NoFOP7qJBVUDELqjalzkX7Td_-VR_CFo0AWYaO8gG-wi4AnJId23Qebnf6Q5b4EKKtIHkB1h0KJH_v_2dayKW00FA_sqzqAZiKWaDbcvgsxaH2HZ56JGz4VVESjzWJ9pdnNHZTAF80wV5B9z19bpXYxcMVlkM4lqZyHSovDV2N0z9SbNqiCTx6j7MqFXVizjSjVpsfXet1uF3n5c-2Q-ggG_82yCzNIlnTj-vFur4y2OX5m3HQVVzRm6WTBF38c1jiQvMsLzxmxPhXCD8NrmWbQtp1pgIDerlrRn2HrTqBBPGkdKLqd_Yet5aQsEETVWjTU1yAz7jXXBpmeDH_8up64NPBOnJozXHaQACH4ELKvInX4HtiuyXOqX1uUzhOUZJK3iPRXQMD_WmPuqjmyaP2KsENPtyqyM7mHcP9ExuZmjDfAYZ9EU46kH1k6a5BfOaPaitmVg8okJnJvHGlbNc26v4HrKVD0GAXVQJKtAEI_PhgUhgP0-SPGToeSilKxoKxxgN-rbehVnYdAtSH_uBB-zhAPBUhZ_f-dPjOICk4Y47lmZcXTxBodQT4aYXY2z37In2024x789nbWhXDEEcSRd5lUkEIkCuoSDhzAxac0mhHNMR7uxmYMGENz8zrFgM9dKdIRM0JSi9OO3zEZZHvHow0BRCjH6anUdj6KFOxhZFT7Akqrbg9URm4281OGo1gwRkd0g9OpNNax7qqbrs4bnbZYbX_E3PjH864gHWWV1CQQaeXRtFVtG_b_3hBu_Ee4u4T6gC2Oua-6wnAHdAIdihqiHVL6nhSvXvIrfQhfIWhZMZuKW8yCl7vbT-5gh4RVsyvB07d2kQm7iKBmIh3xtn8Ux3oN_cI328iNEDbym4=\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Figuring out memory handling**\\n\\nI need to provide a concise answer. I could look into memories related to memory layer RFC and possibly conflict handling. I should mention any automatic processes involved. It seems like using the database or search might be sufficient for what I'm trying to accomplish. I want to ensure I cover all necessary angles without getting too complicated! Keeping it straightforward will make it easier for others to understand.\"}]}" }, { "type": "toolCall", "id": "call_bR0NCMLFOd2iqjnZAb4CU4ir|fc_0d29dbf88c868f5a016a12ae8fba188196928fe11ad477f9f9", "name": "bash", "arguments": { "command": "python3 - <<'PY'\nimport requests, json\nfor q in [\n 'Memory layer RFC approved hierarchical promotion',\n 'conflict memory',\n 'automatic memory analyzer',\n 'session analyzer memory',\n 'shared-agent-memory-v2'\n]:\n r=requests.get('http://100.116.176.16:8091/api/search', params={'q':q,'limit':5}, timeout=10)\n print('\\nQUERY',q)\n data=r.json().get('results',[])\n for item in data[:3]:\n m=item['memory']\n print(m['type'], '|', m['title'], '|', m.get('source_ref'))\n print(m['content'][:350].replace('\\n',' '))\nPY", "timeout": 20 } }, { "type": "toolCall", "id": "call_Bk6E5karLuuEwtmokW9E81Zt|fc_0d29dbf88c868f5a016a12ae8fba248196b29b1db687c087c0", "name": "bash", "arguments": { "command": "python3 - <<'PY'\nimport sqlite3\ncon=sqlite3.connect('/home/sebas/agents-database/data/shared-agent-memory.sqlite3')\ncur=con.cursor()\nfor row in cur.execute(\"select type, title, origin_agent, source_ref from memories order by datetime(created_at) desc limit 20\"):\n print(' | '.join([x or '(none)' for x in row]))\nPY", "timeout": 20 } } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 40405, "output": 349, "cacheRead": 0, "cacheWrite": 0, "totalTokens": 40754, "cost": { "input": 0.1010125, "output": 0.005235, "cacheRead": 0, "cacheWrite": 0, "total": 0.10624750000000001 } }, "stopReason": "toolUse", "timestamp": 1779609222839, "responseId": "resp_0d29dbf88c868f5a016a12ae86ff888196a5f56c8c821ab06e" } }, { "type": "message", "id": "1daa4f25", "parentId": "b6ec23de", "timestamp": "2026-05-24T07:54:02.389Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "**Considering upgrade processes**\n\nI need to explore topics like upgrades, conflicts, and automatic processes. I might mention hierarchical promotion, deduplication or fusion, and evidence-backed promotion. It could also be worth discussing the session-end analyzer. I’m thinking about the conflict handling aspect—there might not be a strong or explicit system in place yet for that. It's important to clarify how these systems interact!", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12ae91a8b88196bb23af5c09b59d1a\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABqEq6TUtK6fUcky5a0JMHSq1VDjswEuDIILVf9t_D82sH4hez8bDzQhRsyS3yFE6yK8SVjsK_PXr-9HJIUALgAe3Vyt7QyfUNc5ol1_Sriooj_sAUcsw0g1yDFJnB3ATIRieAnZYHOrGEILB4HrVrt01jp5Te4j5bER_soirZfo5aWUBX_EoI6gaD4WKweJ3_yEm8o8qyBT42WhE1rHiI6R4xyEypc0FeMftxW2HziDsqovi7pFD8WkNnrxfW28HtoaLrOzvHMA9YfjV5rsHNyE3a_R2kOXoBLALPPOPvUx9hU-Y8gfn3uhNc6fOzosn0YZ5aJw_dzflo8coNgLMbRqwA-TJ_Qvi92dVNy_LF1YOVgp0baqcEU22mAxMgl6MaJaYnI56j_EOcRtXUkI7FAvySgimf0WOYPRPf3AtNnx0JemSiUmOEBOOlU6zDiiwYIEVjG7yRVp7XyUm55uBDPio0gD3kLoP7_hdgV-9-MlC37kgN6_6e8I5H0Oai5GA-yEJs5jUnWqLXGn7AnMIil0TjLjvY2IGVkEx58UfpgSb1tMGOLBeqqkFUYYscf2AMDXycKJYEmh3GY7TyUwcD8RBZUuPrrwkjNt5hHFHLgLgaZRWYK98irQaPK-SMgfFpHMfVGbnPR3H1xh-Xh21Y4qMhqMzc2-sTAtchYqz-83D4iDntMd8Dg9NIVssUr8TDmArv1dGyuY6GF9zNYgK4TYBcA-NHHzFkPI2C0IxKAyM1RRaC3w_uD2FvimdEX56t6MBFw0sMDStZMXofGh4uKSCwrcbY92vf1EK7eX4NCmBV6xBVbsf5XGEDviIgRMwupXbl5qG5LZelU5fDYpyPEOSHfJ3qpW5e1M-uWaJ2N9LHDqVTJojQCW_xP1X0vn5O4n9hloaxO8Anpa16gT3UMrnO7jBUqYbFalO5ng-UhEUKC94XhaF6ydH4Qr-FAHFMU38I7gWeCpMk2GE6LFrB0kvNvYVhQ9ZY3g_7ugCDrE6hpa7To7irssB3J_jX2BJL5LA8UXuW1dyer9OF-XSQ9fLe17FNbFhL1LDxztW61jThclG8fDC3_1Ay89SqR_GBbEjFJIFrrtxgGMezMEXNze4wi6WOOD5pWmdBJPLjM92mTYBtleL5xXmudBArSVHqDsPeaMFWZyKW84wAqAg-RA1HUfU-dUzoaQUkTOeh3z_jVyLo8IbKzByU-kJXNkCbu5fLL\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Considering upgrade processes**\\n\\nI need to explore topics like upgrades, conflicts, and automatic processes. I might mention hierarchical promotion, deduplication or fusion, and evidence-backed promotion. It could also be worth discussing the session-end analyzer. I’m thinking about the conflict handling aspect—there might not be a strong or explicit system in place yet for that. It's important to clarify how these systems interact!\"}]}" }, { "type": "text", "text": "Yes. Upgrades direction is clear.\n\nStronger signal:\n- best upgrade on record:\n hierarchical memory, not flat dump\n- shape:\n - short-term / TTL\n - summaries + pruning\n - episodic → semantic promotion\n - dedup / fusion\n - hybrid retrieval\n - promotion only with evidence\n- also a policy shift:\n prefer session-end writes\n over mid-chat writes\n- result:\n less noise, better durable facts\n\nAutomatic processes:\n- `pi-session-memory-analyzer`\n is active and writing some memories\n- last month:\n 8 auto writes\n 23 manual writes\n- so auto is assistive, not dominant\n- there was one automation break\n in maintenance wrapper\n fixed on Apr 30\n\nConflicts:\n- no sign of major conflict storm\n- also no strong conflict-resolution\n layer visible yet\n- current practical guardrails:\n - fewer writes\n - session-end filtering\n - explicit promotion\n - dedup/fusion as target design\n- weak spot:\n project scoping is poor\n many memories still lack\n `project_id`\n- that hurts disambiguation more than\n direct write collisions right now\n\nMy blunt read:\n- trajectory good\n- signal quality improving\n- automation not out of control\n- biggest next upgrades:\n 1. enforce `project_id` / `repo_id`\n 2. add real dedup+conflict checks\n 3. require evidence on promoted facts\n 4. downrank or quarantine uncertain\n auto-extracted memories\n\nIf you want, I can do a sharp audit:\n- concrete upgrade plan\n- conflict policy\n- auto-write policy\nall in one short memo.", "textSignature": "{\"v\":1,\"id\":\"msg_0d29dbf88c868f5a016a12ae936b0081968e51f1703ba813bf\",\"phase\":\"final_answer\"}" } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 2793, "output": 413, "cacheRead": 39936, "cacheWrite": 0, "totalTokens": 43142, "cost": { "input": 0.006982500000000001, "output": 0.006195, "cacheRead": 0.009984, "cacheWrite": 0, "total": 0.0231615 } }, "stopReason": "stop", "timestamp": 1779609232332, "responseId": "resp_0d29dbf88c868f5a016a12ae907ac481969c6aaf4235f60de4" } }, { "type": "message", "id": "847136fe", "parentId": "1daa4f25", "timestamp": "2026-05-24T07:55:25.964Z", "message": { "role": "user", "content": [ { "type": "text", "text": "[telegram] id rather see if last two weeks memories were created. specially at session end" } ], "timestamp": 1779609325954 } }, { "type": "message", "id": "b87a9b77", "parentId": "847136fe", "timestamp": "2026-05-24T07:55:37.460Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "**Inspecting session data**\n\nI need to provide an answer based on checking actual data. My first step is to look at the recent 14 days of activity. I suspect that the origin or session end is linked to a source reference identified in the session analyzer, potentially with the creation date influencing the output. I might need to classify the data gathered to draw meaningful conclusions and utilize appropriate tools in the process. Let's get to it!", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12aef03cb4819686bad81d1fa5ee30\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABqEq750Hvn-7mTSeRHe45nWnZklaJMQ44rSLhxaHaF9xD08o_Y3hlgZpao9SvG6TuxDDi_ypZCbqwW4FHGCAi7Hk0CqBCdiy6WMc25LWc0lUWpImBedlLvCsJCmWp1OFR2mx0QFbIsFoQvL9vixEV5IaxQ12HX5IkYLk3uNJOnt3M5DZOVjB4SK-Vov-IC0hUYALyNiuIKKMmfNQKaKECqTOOywQZ4SncClu6yYWCXxuOAmTpoLxJ0risSfIja2ihoXvCsKpmcDrIeHatrzE0vI4GtpkuvVINfy0HncnyuMdQObf-rungbozP1RMNrQVf4h44F_i0m82gx61fjtQShYsALr4Po6Zb4tJ3u1e2WqzZ9Y6M72fpiYBFsuXEiEoC53DeiOGsCgIBaklaCO3fLt2VGlR8NRgqDCIZMv3oIoh14YTQhIqzwNg5qhhBFDuCaFfTtjC-TGLFwjKqIMsj-45f4yM0HVnve2eVzUV2dyA0tIovusweifDrkNOicsmBCtOz9Gt77T_pGdhFDODPRfRcjG66dsWl90YL12_iNcOgRmXYW8pej_APfyPvK8Nsy6BjHdvL6VJNTV-MQ7S33zYU6Dz5OcYOwXwQtaI-KwhT4hL_VP9cUmomqAXhjPLdk4gHfV3Dm3syB5EdUsX7oDD3bJLMc0XiwWZz9alk1PM6854nut5snZYpyhe6buvmxX7kjI-0IsoV9Avohhi4n3NWch3a7HjjSoxasB2h6N63W-54zVd_F3WcQ2KyfeySfgWZWsBUtp4EqkgBWUL6v3r26OBYUHBJNC4uaLwXQz1JavEFNAlMbHVMtgf6qlHYP1-iYH8_v2VeAY5iz6JPXB9j7bjoBGp2e64YIZ7g7NlxAnW1FqIPFiXMMIa2g14eKExnyfJj8kWmSnPFMz8JNaiI3xuLBYgy4c1x7Hn18-kDlWv6y919p8U4I_QiKXkuHLrkYKt7Hddr2XPW039C2QSm2y9h6tIg5jA3TCWcann7DOp5QNwknl6Rl5lLLZ802-d_Sz5RNzWRBwqfAQbCEafRHA7jZ0XC1EBGLBqvsAJrdctVYEw5naN62tVkTc2ewhmHtkm9nIcR5Il64lVoBNZSd89JNj-tS-RPc31GcPPWFQmk9duVsL9VAFjPKrPxKDLcf\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Inspecting session data**\\n\\nI need to provide an answer based on checking actual data. My first step is to look at the recent 14 days of activity. I suspect that the origin or session end is linked to a source reference identified in the session analyzer, potentially with the creation date influencing the output. I might need to classify the data gathered to draw meaningful conclusions and utilize appropriate tools in the process. Let's get to it!\"}]}" }, { "type": "toolCall", "id": "call_geQGM1TVH2yxP6mvYEcp3HW9|fc_0d29dbf88c868f5a016a12aef92f6481968f6f0ac47d0c3a78", "name": "bash", "arguments": { "command": "python3 - <<'PY'\nimport sqlite3\nfrom datetime import datetime, timedelta, timezone\ncon=sqlite3.connect('/home/sebas/agents-database/data/shared-agent-memory.sqlite3')\ncon.row_factory=sqlite3.Row\ncur=con.cursor()\nrows=cur.execute(\"\"\"\nselect created_at,type,title,origin_agent,source_ref\nfrom memories\nwhere datetime(created_at) >= datetime('now','-14 days')\norder by datetime(created_at) desc\n\"\"\").fetchall()\nprint('count', len(rows))\nfor r in rows:\n print('\\t'.join((r['created_at'], r['type'], r['origin_agent'] or '(none)', r['source_ref'] or '(none)', r['title'])))\nPY", "timeout": 20 } }, { "type": "toolCall", "id": "call_PVXckl6hNr2dEmnQcJwZDAvL|fc_0d29dbf88c868f5a016a12aef92f7881968efbbc17f823e74f", "name": "bash", "arguments": { "command": "python3 - <<'PY'\nimport sqlite3\ncon=sqlite3.connect('/home/sebas/agents-database/data/shared-agent-memory.sqlite3')\ncur=con.cursor()\nfor row in cur.execute(\"select coalesce(origin_agent,'(none)'), count(*) from memories where datetime(created_at) >= datetime('now','-14 days') group by coalesce(origin_agent,'(none)') order by count(*) desc\"):\n print(*row, sep='\\t')\nPY", "timeout": 20 } }, { "type": "toolCall", "id": "call_dknrYXWtAs5S14fdEmuQDEIS|fc_0d29dbf88c868f5a016a12aef92f808196800c268eb7c8c5c0", "name": "bash", "arguments": { "command": "python3 - <<'PY'\nimport sqlite3\ncon=sqlite3.connect('/home/sebas/agents-database/data/shared-agent-memory.sqlite3')\ncur=con.cursor()\nfor row in cur.execute(\"select substr(created_at,1,10), count(*) from memories where datetime(created_at) >= datetime('now','-14 days') group by substr(created_at,1,10) order by substr(created_at,1,10) desc\"):\n print(*row, sep='\\t')\nPY", "timeout": 20 } } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 43089, "output": 493, "cacheRead": 0, "cacheWrite": 0, "totalTokens": 43582, "cost": { "input": 0.10772250000000001, "output": 0.0073950000000000005, "cacheRead": 0, "cacheWrite": 0, "total": 0.11511750000000001 } }, "stopReason": "toolUse", "timestamp": 1779609325956, "responseId": "resp_0d29dbf88c868f5a016a12aeef2964819696a272bb4c775a42" } }, { "type": "message", "id": "02005772", "parentId": "44a0d72c", "timestamp": "2026-05-24T07:55:42.061Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12aefa6d3081969642c0a7bb5668ce\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABqEq76D0XxqPwSbKJmIDPqjDkucgy2dTvN_yMG-QrJe_i3GNiJAaKNKFRZfcU-HcKrQ4JOXbKbktAcHCSz2lSVSCwLGfPcR8Pzz0-HfCZ0mY65fHXrOGuyVpBG6xTjx-i74dUdz18IpQ2vjWQpLSNscwjcyqhGQQ-NTy7jPLjzqrxha5uLAGRESc3_SDXyH1V_UMjHDPlXlHcVbx967d4X74cQbyyu8OJ1CitrH91rGANpSi-ss6sv3WJt6tTL98JUrocBX8AaBBse-k77AK5V0ihWaJX76bGIvPKCDPxmeADzAbSnFXzTd2RE8am-SrhmD03oWEjEonkJ0_PGxPCxfLwhQBS7vDBTY-HUwfZXzZiu2zhh0mujK_kSwhyzaNL8lJ53Po3eMtPnoggeRkT7IE0FrdgKP8b2XYms6D0ghIOV8OyoTPbFJeAwSwQhZHoHQTi4mLkPXjJDn3w4ZdnLlj9QPW76QD-lzx74a3r-fpCNNBQl3CI1JpkcmQ1ULCYdP9C2zA7O7ABwtrLaXLF-QnJlz446OpcxBtzmQUUHh-GHUqJBV1Z78qk3k2ZwdyKu7jz-H45QwN39MjrnSQSbPea4RPsIKpPUsrUH9R_svZ1UC5P8cthLzKDsDk7PJ9JXny9an6Q70vvSVcIWyzW8__nfVz0bb92Awn25AcAlxRvOOd9UrZtQpmh8dzmc9Pu0BaOyfJY3Es79Tx9nBwnK6g4aHlriVK7QiOC6LyWqUH2sYGyLuZe_D2ItTzZpu0rfwCvtpqcqqpAd_eqB6cG4ZQ9wJiY1uMi2aUjsXDVND-E4lxhje5m4IKWdmknv7Rzosece201KUFs9k6xIVlClkqV4-wKD8nMyGTpD3-t2RIS8t6_o3tm1s_45tLAJ4-IvUdIUr6qF86lMCLthBaLPhv04CEib5nj_ykg6b8fqAU-EvqHM2avHcdP8BHdbpC5CIxvf\",\"summary\":[]}" }, { "type": "text", "text": "Yes, but very few.\n\nLast 2 weeks:\n- 3 memories total\n- all 3 by `personal-agent`\n- 0 by `pi-session-memory-analyzer`\n- 0 obvious session-end auto writes\n\nDates:\n- 2026-05-21\n - `Vending web v1 scope and test notification`\n- 2026-05-20\n - `rss-offline PDF pack stabilized for iPhone test`\n - `BB-004 EPUB-first offline pack`\n\nSo:\n- memory creation did happen\n- but not much\n- and not especially from session-end automation\n\nBlunt read:\nsession-end memory writing looks quiet\nor not firing in the last 14 days.\n\nIf you want, I can check why:\n- analyzer not running\n- analyzer running but filtering too hard\n- sessions not being ingested\n- writes failing silently", "textSignature": "{\"v\":1,\"id\":\"msg_0d29dbf88c868f5a016a12aefaf6648196a20c9187b133b5b1\",\"phase\":\"final_answer\"}" } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 770, "output": 194, "cacheRead": 43008, "cacheWrite": 0, "totalTokens": 43972, "cost": { "input": 0.001925, "output": 0.0029100000000000003, "cacheRead": 0.010752, "cacheWrite": 0, "total": 0.015587 } }, "stopReason": "stop", "timestamp": 1779609337534, "responseId": "resp_0d29dbf88c868f5a016a12aef9b13881969fcacac20aaca227" } }, { "type": "message", "id": "0bd9cc4e", "parentId": "02005772", "timestamp": "2026-05-24T07:59:02.988Z", "message": { "role": "user", "content": [ { "type": "text", "text": "[telegram] right. and how many sessions/how expensive would it be to manually run session end process on them?" } ], "timestamp": 1779609542978 } }, { "type": "message", "id": "7d1e087e", "parentId": "0bd9cc4e", "timestamp": "2026-05-24T07:59:07.444Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "**Evaluating session details**\n\nI need to inspect the sessions from the last 14 days to gather concise information. It's important to keep things clear and not overly complicated, so I'll focus on summarizing the necessary skills as well. This will help in understanding any patterns or changes in those sessions. I'm curious if there's anything specific that stands out or needs more attention during this review! Let's see what I can find here.", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12afc80ee88196904bfc5e399640d7\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABqEq_L1jBVN6sUq3KZZR8RdMcFwkGTIqegOZDVus2XoiNPkrK5WCYbuAir0MPD730sMz98H1x9FnbhhGWouQY-CAUBkP7vVEXTGRXnbgdERZNx-Ct_EEngCBV6UzpayTh4NBPiQ1ZD-AuomXCg2zNAUKDr_ZxShBQaE-uwFMKGra330hkGdZoAr9ZK-uamZf1K2gJBbjua-5wFDyixJHUvbisx54LBrQbaLjVlPdRuoRLQR69wpGKsQw1wOyUpiovuyTJovwHtyKaQdoHYqJbRi3MHJbPhDbV_q6mNEII-LZchoZS5rpAjHpzWKGvBhnZFJNauuSq7yKAN93l213kamZcgfS428J6IVVQYUoj3lq0FltSwYW4wrhtRvwQM2HfZCNr8VnmKPGQmC2nsYMbXXe3KU6yCEEQyaDrsHplzjMs-iu_e9hN1z0-6s8z4FE60n7D1fDXueTBewCxwI3AhhagNq7SCFGUqlNHf2d0sF7wKHeTX9nTsa7VDOq9k7Clt4FTXmOckA_unvBgyjwPEwDTdzMT3WjuC0v5eXBRMTQ8IMFzQ4VlLF_z5t0aBsnl2q4NqgXjMTmsPkZtAAg7qSK9xvsiTLHCXcGZEDUZUh8dTgyO9vsnKqeEfF7wJ016PB6gIkzG1Oe0Lh83v2lI0UVrvhQ8kY5NaXN_O_-7HKidBhBL_qImie5w_3Pol6n-YcR96uU48FE5bw8raHfgDEjuBM2FfJ6vsRTUy4afbON751oA_Gtl4y92fdIlY_bB77_b7vAOVc9xBpCZl8Ai0T9NnkC7W1UgG3z8EzmrFoM6LjlyUFFiEddp6fMVkOhumbQ0tdMtnHUTByMsEGjb5n04b6tF6Lcbxy05pCNxwikf5K1gif1Xf6r68HBkdTo0x1XAvq5bTAvV-7tXxVee7CfmApPvAPiL60n-2XY3R0YSSyXVn2I3rfw_3D2D5fQyEm38oua8wRLnPKqOFYS1kyTlDYC1__LLDkaV19lAZ1oh_2-zx2mm1gNmfyEcgx9y2c8At\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Evaluating session details**\\n\\nI need to inspect the sessions from the last 14 days to gather concise information. It's important to keep things clear and not overly complicated, so I'll focus on summarizing the necessary skills as well. This will help in understanding any patterns or changes in those sessions. I'm curious if there's anything specific that stands out or needs more attention during this review! Let's see what I can find here.\"}]}" }, { "type": "toolCall", "id": "call_sgOS6BocTBbnH6ax7mWz413B|fc_0d29dbf88c868f5a016a12afcb1dec8196a38b802fa899273e", "name": "bash", "arguments": { "command": "find /home/sebas -type f -path '*/sessions/*.jsonl' -mtime -14 | sort | sed 's#^/home/sebas/##' | head -500", "timeout": 20 } }, { "type": "toolCall", "id": "call_U6mTVJIvJrnAAHGE519fYy0A|fc_0d29dbf88c868f5a016a12afcb1dfc8196a729af082fa18fc2", "name": "read", "arguments": { "path": "/home/sebas/.agents/skills/memory-write/SKILL.md" } }, { "type": "toolCall", "id": "call_mI2yEakRpMzd6Vr9RtGlVkq4|fc_0d29dbf88c868f5a016a12afcb1e048196b9979a365d28a99f", "name": "bash", "arguments": { "command": "find /home/sebas -type f -path '*/sessions/*.jsonl' -mtime -14 | wc -l", "timeout": 20 } } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 944, "output": 166, "cacheRead": 43008, "cacheWrite": 0, "totalTokens": 44118, "cost": { "input": 0.00236, "output": 0.00249, "cacheRead": 0.010752, "cacheWrite": 0, "total": 0.015602 } }, "stopReason": "toolUse", "timestamp": 1779609542980, "responseId": "resp_0d29dbf88c868f5a016a12afc7234c819690b94a5ce2a12690" } }, { "type": "message", "id": "62272b20", "parentId": "6fc25329", "timestamp": "2026-05-24T07:59:20.649Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "**Estimating sessions and costs**\n\nI need to determine the session count and estimate the associated costs. It seems like I should also look into the size of the lines to help estimate the amount of manual time required. This combined info could give a clearer picture of both the workload and the potential expenses involved. I want to ensure I'm thorough in these calculations to get accurate estimates for the user!", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12afcd6a748196a20db3511ea7bf17\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABqEq_YZO-vnLDFJVROX28clA_nS6gEZhfg0_0JGHqPHkhNHHC9rVO23LJ7YEXTRBqgoAKRIvaQXtEpBu0v89wg6KD8TmY8hv3O1jlZrTtBhfer1LkD-jmQ2wH2Sogui2vA62QIQu4prZkyADjxbkR0d1aa6M2bIe3vzG_PJXP6Bu7mu1QpbnCBMDNdWhNj1QG2zWFYoW_CuW-m6aGIvZaXn6yZ03WZNgdjZEO_J15c-S7zid-TJmTJ6astBNNp0puH8oBdbxa4O2WtDJZ7FLStjnDVVaUseVla5i0mM0W49dYoriQviu1UOWk36OwgLo8CE9_cngDWIPBx4JtFMww4UECfiUuc9jExhfump_fdDkMZ7QbkrDxPltCv4gD0OH4ZuKQP5TIgu-TTldiPuuXtCCDflPLhhLQcedJLFyPwdqFyQFLuJQCY0dTyK-4MVyUeKQjMNAHdIKZLnlKxrb_pCyEiHgiUjV-BCwmGhcdkjcF8_Z3cOTyvgbki9ssIRY_a5w-urRdkUTNeLXNnIKXoWUNEPBuZCl_0NU4gMnDpNv1hhXP_HbnFcRX3lV-5IhDO2SDXO7nR0hhE_voPCvtjsCuAd1RAQMYXxfd-Jvi-50q8UZSIr8rAU4y4PLAfhgmolAUr0fjt8klBeDw0RTti-XgsW_34AqEebJswXNCm2tX1qsuOEuWR1I0b0q7UadmI2isUNlF9nxX6KVAU20HyXxuRAPCtM5wBswK75zylVyJikF3RrjmmEalHG0JzJysopZeUVayY2Sxr399f5Kr7EykAihcv5pwMzESuNKFk5pOW3k-bGt3l-DnYpKuTefk_SO-_bN3_ot3MG_cBq_BO0eY_Ls0phZ-YRi_HcMYWOoNJk1wtyMQU9vVQsJsPG3ch0CpGuy-aEkirCMOI_IiJqoZ0UhSiUwNQ2Nig6AyY-q1xCyMXc5XgMqT2yXk0wLJHyHIQsQ_dHAXFfsrE3n4zIxeQsUrudKged7GAS6OjlU8ZXw2pm59AVPIfZ6xScS3HQNImIKcWg_rS49Qh0r4mLMx9IQ==\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Estimating sessions and costs**\\n\\nI need to determine the session count and estimate the associated costs. It seems like I should also look into the size of the lines to help estimate the amount of manual time required. This combined info could give a clearer picture of both the workload and the potential expenses involved. I want to ensure I'm thorough in these calculations to get accurate estimates for the user!\"}]}" }, { "type": "toolCall", "id": "call_c7KZukc1tEzQHL2QIjIe5pVx|fc_0d29dbf88c868f5a016a12afd860e881968e365d46dde71442", "name": "bash", "arguments": { "command": "python3 - <<'PY'\nfrom pathlib import Path\nimport os, json\npaths=sorted(Path('/home/sebas/pi-config/sessions').rglob('*.jsonl'))\npaths=[p for p in paths if p.stat().st_mtime >= __import__('time').time()-14*24*3600]\nprint('sessions', len(paths))\nbydir={}\nfor p in paths:\n d=p.parent.name\n bydir[d]=bydir.get(d,0)+1\nfor k,v in sorted(bydir.items(), key=lambda kv:(-kv[1],kv[0])):\n print(v, k)\nprint('---sizes---')\nrows=[]\nfor p in paths:\n try:\n lines=sum(1 for _ in p.open('r', errors='ignore'))\n except Exception:\n lines=-1\n rows.append((lines,p.stat().st_size,p))\nfor lines,size,p in sorted(rows, reverse=True)[:12]:\n print(lines, size, p)\nprint('total_lines', sum(max(0,r[0]) for r in rows))\nprint('total_bytes', sum(r[1] for r in rows))\nPY", "timeout": 20 } }, { "type": "toolCall", "id": "call_rJTYFS4wZC9XbJUJlYEb1qbC|fc_0d29dbf88c868f5a016a12afd860f8819682fe9e9ec02a8137", "name": "bash", "arguments": { "command": "python3 - <<'PY'\nfrom pathlib import Path\nimport time\ncut=time.time()-14*24*3600\npaths=[p for p in Path('/home/sebas/pi-config/sessions').rglob('*.jsonl') if p.stat().st_mtime>=cut]\n# rough buckets by line count\nbuckets={'<=50':0,'51-200':0,'201-500':0,'501+':0}\nfor p in paths:\n n=sum(1 for _ in p.open('r', errors='ignore'))\n if n<=50: buckets['<=50']+=1\n elif n<=200: buckets['51-200']+=1\n elif n<=500: buckets['201-500']+=1\n else: buckets['501+']+=1\nfor k,v in buckets.items(): print(k,v)\nPY", "timeout": 20 } } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 3220, "output": 533, "cacheRead": 43520, "cacheWrite": 0, "totalTokens": 47273, "cost": { "input": 0.00805, "output": 0.007995, "cacheRead": 0.010879999999999999, "cacheWrite": 0, "total": 0.026924999999999998 } }, "stopReason": "toolUse", "timestamp": 1779609548594, "responseId": "resp_0d29dbf88c868f5a016a12afccc1248196a3801a4ddee013ca" } }, { "type": "message", "id": "77a60994", "parentId": "254325fc", "timestamp": "2026-05-24T07:59:27.176Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "**Estimating and suggesting triage**\n\nI’m thinking that I need to provide an estimate for what the user is asking. It might be useful to also suggest some kind of triage process, depending on their particular situation. I'm curious about how to present this clearly and effectively. Making sure the user understands the estimate and triage suggestions will be key. I just want to help them out in the best way possible!", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12afd9b65881969f59947f8142a6ce\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABqEq_bpvQBErCs5sPKAgXSS44JfHtOg7HUszZTZxPbxYzb-ION1RheQLTTB2Ly-oE6KFZvOGHlHzN6q3XF8HA5am8waPwA799rZ1B7Jvv-Y59jOoFelob5OG2CUD1ZOGW1v9QO-2OWZQa4mIhMjktXzLBqe0mbY3oTF8tNupuEIIw3owiUtuht_vFj0xQq7kVHXgkAkiwmnaMd4FG0qxWsGfQJBHt6VSexRpFe9YHbHEgAbe1JBNPatbIpY0M-8J1-elue6jcMMPLsUunJIPlU9mG1wXulMkSKmWnaZ9t09s9itl_uqia_ftV1J72bkAYDiz-6Aj8TLqFvuqT_9CbfYCJ8E06xk0IPwqLJcJz2sRXLv7dYvNShWOoGYy8IClHArjxnDH9YRIIH4F-KqgZRj4HA6Gpi11ocuUn9veoTzKMiaD65R63vP-wdDQr7zYG2JRO_MEdYj1Y4tqWWltAx-Uhzksqn5bopGLruw-c3Fdg3E_49mcaGA74lgWUJ-3FdcyBdTPc-QnojP22JFaaSuyb30Vi_upLkcqffVIm6Kw16EZW-D_R0vxo4Sn5-NXB_S_WpX8H0gem8fVVNN42wc5dT_2swvOMhP1KCL4hgRSvcB0CVEgZnGPmgujrs6maqJyr7ncmi8Rsa0t8QbNBv2TfI8Mo1WmOaZro4v6OVbX1zEqIB9_b2WkGFNpLh4oW5AWSEGd5NHJENMFd5DW702GGsPKYTQH4q51Pqdd1hw0MAKyDTP9jg6DRzxEWM1f_fsoEkEeftqR0eRGw7Ixgum5Xqq3lGu9yFGtf_5pb416nwaj4uGqjrZsWSWche8VN--fRXZ_S-OT2sZHeFbgIU4vKWDqPDJL365u0XZB4Za9NpU4Ez-VdR55KSDD9u2Ye-7xZKpShuM43jtAjyiflh2gDJzkk-AUZ69Vw1Qf0zBti8E6-_5eh5hupJf3quIfyHBbBoGZrqeNAAvKPZ56rtOpMoxVcqN6XPOGzqDl4O-HheqzU=\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Estimating and suggesting triage**\\n\\nI’m thinking that I need to provide an estimate for what the user is asking. It might be useful to also suggest some kind of triage process, depending on their particular situation. I'm curious about how to present this clearly and effectively. Making sure the user understands the estimate and triage suggestions will be key. I just want to help them out in the best way possible!\"}]}" }, { "type": "text", "text": "Last 2 weeks: 36 session files.\n\nBreakdown:\n- 16 `ballbox`\n- 14 `home-sebas`\n- 6 `vending-status-pages`\n\nRough size:\n- total ~4,132 lines\n- total ~23.2 MB\n\nComplexity:\n- 19 tiny (`<=50` lines)\n- 10 small (`51–200`)\n- 6 medium (`201–500`)\n- 1 large (`551`)\n\nManual session-end pass cost:\n- full careful review of all 36:\n about 1.5 to 3 hours\n- fast triage + only write high-signal memories:\n about 45 to 90 min\n- highest ROI subset only\n (`home-sebas` + medium/large files):\n about 30 to 60 min\n\nBlunt read:\nnot expensive if done as triage.\nExpensive if done as perfect\nsession-by-session archaeology.\n\nBest plan:\n1. hit the 7 big sessions first\n2. skip tiny sessions unless they\n contain a decision/project fact\n3. merge nearby same-topic sessions\n into one memory when possible\n\nIf you want, I can do that pass now:\n- cheap mode: triage all 36\n- focused mode: only the likely\n high-signal 7–10 sessions", "textSignature": "{\"v\":1,\"id\":\"msg_0d29dbf88c868f5a016a12afdb3e188196afcd47c6c6713aab\",\"phase\":\"final_answer\"}" } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 1502, "output": 295, "cacheRead": 46592, "cacheWrite": 0, "totalTokens": 48389, "cost": { "input": 0.003755, "output": 0.004425, "cacheRead": 0.011647999999999999, "cacheWrite": 0, "total": 0.019828 } }, "stopReason": "stop", "timestamp": 1779609560891, "responseId": "resp_0d29dbf88c868f5a016a12afd90b5081969601e4c0731f77e6" } }, { "type": "message", "id": "679abbb2", "parentId": "77a60994", "timestamp": "2026-05-24T08:00:20.789Z", "message": { "role": "user", "content": [ { "type": "text", "text": "[telegram] cheap" } ], "timestamp": 1779609620782 } }, { "type": "message", "id": "96af64d6", "parentId": "679abbb2", "timestamp": "2026-05-24T08:00:26.708Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "**Considering task management**\n\nI'm thinking about whether I should start a to-do list for follow-up tasks. It might not be necessary, but it's important to keep track of what needs attention. Should I inspect current sessions and possibly use a subagent? I could also do a quick triage of tasks. It seems like creating a to-do list could help me stay organized, especially for active tasks. So, let's go ahead and create those tasks!", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12b015f83c81968b85f372b8ea8bcb\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABqErAa27W7t5eb2rQNesm9sYDTxDrlMVugQwe3bs-9ffg45S9k64alzSGFZw-n4G1janWLH-ll_oHrGRMpe882Wfl57EspitGnbWJuHeMGUH9N9pGdAIvdOy4APcEmJP8lW0E3jIah4-nwmeSkzY0StYiwU98LdujLG7AAJRNLh9Khc6Pe4qabhalbo4ONURm4At2lkGYIjFc9E01hfsk4QHz3VtwLOl_UVIXhTLfGzhwyaXSHmConvqvmDrnKgjQb0JlPaNUKIRU8ZMf-bRpNtlh2TSXWP7jEW_mKNX3kNTh2uf4-_rjYe36l16wny2df1415yktn3gs3VVAM2fRLI-igX7pv2vD3UoxldPGJNvD_BPRzLiukaV5gFk26qVJT9a7Tz5w2yjIL6aueBGQNE5LMKLk8t-2VPonqXC6QMirWzWRni8ATFHvo6aM-3WIEaWESOpc7VJ71U0Y0jFbmauePVVAIBVgUAIVKNTNoI_4y51-97ghCoHkeQVpL6J8daUB78P5ci8EN3GycKsh9jqwk_ShWanesnP7B00gkS3jWsptczB0G5Z0F-1WIAbEVki-1zKOJAoYuTMFmgS8EilaaliBOqQ_jtsdo7-jVk6Bb7SwuC_PCSAKipN0UeqX5HWm3JVU36Fd73EpuBvzecyILWiHobf9bWcVsfNLycxsShqAq8GibetI8ifw8g8Sfk3Snz1al24cjgtYFilMeK7yf-9Fz9WtFG1wPtGBTwkalSiMVb5KkzlWGTdu2nAzcmp1Nt4TSIKm758dXwSSgIesRe4Xzn7OzIKThHvQb8hHVSg-EM2VjPuZJjaU3qxhkXdOkW6DvZ0312PgtkfiMA4TWCvjTQ5OeU7GCb2ZTsYex1UXEPvrJMJeRjgiNhg18-cdtub3TH5LbGsNtNOpuO5seXhUb7f3trwLjKILBesAkotVHPU4JOcVUFmv5PC3faXegj97C3f9EkxcBnq7iulKbD0r83-BDaCQU9Lhh8D8zxP5lH4I8Cxf7wAzcG7Nw-G7sRgldOCQa6vollghIRDBPiaeVauACPEIZOGDn2EgWCCDLFtgOu1NRy8vdB2etHp1ETtFkpS3bW5AL9kzkuL0oWznSTHIHeRvXiIbm2SYmW2GFbtfRVtRsp4hocqsw3tk9AsO4S-H-0WNrG7iEzCGgHRUXtZCTRWviDTh_fF_pF4JXgv6zxeBC2R0LCp4VkKASWIPLtwHD9z_rao1YfoUN5A==\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Considering task management**\\n\\nI'm thinking about whether I should start a to-do list for follow-up tasks. It might not be necessary, but it's important to keep track of what needs attention. Should I inspect current sessions and possibly use a subagent? I could also do a quick triage of tasks. It seems like creating a to-do list could help me stay organized, especially for active tasks. So, let's go ahead and create those tasks!\"}]}" }, { "type": "toolCall", "id": "call_foEFZ5bGJJfUGGXdbi4R3Pii|fc_0d29dbf88c868f5a016a12b01a39188196bbb99293a9bd1b67", "name": "todo", "arguments": { "action": "create", "subject": "Cheap triage of last 2 weeks session-end memories", "description": "Review recent session files from last 14 days, identify high-signal durable facts/decisions/preferences/artifacts that should have been saved at session end, and report count plus cheap estimate before any writes.", "activeForm": "triaging recent session files", "status": "in_progress" } } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 48340, "output": 145, "cacheRead": 0, "cacheWrite": 0, "totalTokens": 48485, "cost": { "input": 0.12085000000000001, "output": 0.002175, "cacheRead": 0, "cacheWrite": 0, "total": 0.12302500000000001 } }, "stopReason": "toolUse", "timestamp": 1779609620784, "responseId": "resp_0d29dbf88c868f5a016a12b014f30c819684685770f5f3a663" } }, { "type": "message", "id": "fcb93b56", "parentId": "2c460da0", "timestamp": "2026-05-24T08:00:28.594Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12b01bba988196b681fd438cea1eed\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABqErAc_1IHS5vMk4PUsYKf4RCtHcWqp3t_uo3m3wsL9H5Mh6Get5Gmnh-Y_5tnWqZtK9UYdwjBwQYHodJ3un2IvS3KbNWrQJxmiqliLcwUjd5oyP3apZD9Th14rWdC43q_lT08HB7Far9bv5D2SJ2CN4nSXTpb1nqG7u3jxmA2pJRT7CbqsS139kSBpEnz_y-aMqCBBfVGdwxbiDX6WAqjLFbcLb5dtIYmdk5MSz0RhixS9XPT1cMmQt7JQKYPLLUK3yTzUWgMAV6fH9UoSdR-sMteMkN6qehG0dEyvRzgfmsknMUDduVzZOtY6VhvAfvc-wcvtqd0Kbq6tkJEDJgCqf4G8ZrdFTm_DvliMI4cut_GrL9T6vWeKL0bvaxlJw-qdQuOCZxodmxrUT0q6PuiThzKPWW9zIqHC4KCbW1-yyPlJYblP_mu-eJYLUWmjQqGFMGS6ODyqDr6c-dZRIbLA_Jq2qakc2eJ98LTVfjdQk9RwoNZ5_LNhc-qXwf9xOyXWg5oXL5h219tdJhaqwMCgk_4ObtraWWTbLrVTIFVfvWQYa6NMB383BSMEXYNKG78iv_AToeM8oepcx4ZQI88u9dg1P4TONh3UydbCPi4ooSU6VZJcNEbWNMxM-lIwSfV7D1hxLfl2_RgYB1qjBPNEIb2G0G0wi5fFzy5erbwhWhO-wc9-T4RTgAE9ucks3mNZoW8XCnOSwHQH3QViNpIQCp4_9bOYQPxpIMSnf5ddW-sgMWtcP8tqdIaY5K82KrpCkhXNGVaxyyJlZjVNGQULYwsEUh0tjp6vogioIb7zSqFRiKL9OI6-tncaUCb7kdgPIeL90Pn6yIBvQv5w1Ylw0K0k76l85pGL0gDCOB3IZS9zUVbDHt1s37lfIavggUxcKFDQkAr4WqhTjw3N3T9gNbcnoYFAHIBVIkT9eWkPkDqlxxaEe6biU35jd8kkZKU02Iy\",\"summary\":[]}" }, { "type": "toolCall", "id": "call_nRK9X7Mu4QNV7mUy1n3DkjLA|fc_0d29dbf88c868f5a016a12b01c2b4881968c76e672351dca4a", "name": "todo", "arguments": { "action": "update", "id": 1, "status": "in_progress" } } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 385, "output": 38, "cacheRead": 48128, "cacheWrite": 0, "totalTokens": 48551, "cost": { "input": 0.0009625, "output": 0.00057, "cacheRead": 0.012032, "cacheWrite": 0, "total": 0.0135645 } }, "stopReason": "toolUse", "timestamp": 1779609626722, "responseId": "resp_0d29dbf88c868f5a016a12b01af0d08196b59186b5aca225b4" } }, { "type": "message", "id": "e9ea37ab", "parentId": "ab9df996", "timestamp": "2026-05-24T08:00:35.822Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "**Inspecting session files**\n\nI need to check the sample of the top sessions, possibly looking into the session files for \"assistant_end.\" I’m curious about the format they use, so I'll try reading one small session and one larger one to see any differences. Understanding these formats is key for what I'm trying to achieve. Let's get into it and see what I can find!", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12b01deea48196881a94a47d74ec73\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABqErAjyxvpbLPjo-v5wq9yBvoYEdTxk8y9SEsFIC3IJZj4eSm2tFbQ_62x1siu-jlBAr-uEIFiPpulO-vjEv57RK2SwtyKYFc9Xlqwcj5aSPcBXYdU8_CRNRS-sVK8uMEB2570pMhfvbQdXuGqqw1D7FpojGA5dep1xHcKNdX1juYE0AH1SHEsPxeZGn6vTbRQhbxwHAr2NnmzKBCGqjKfw1kNPkBBkaMBo7zF4qSANSGRAZTFlYeKhi_QpcBBCX7V2JIRiFFf-t8bwl2KgnMaT5NYKLHLL8QdfsZzhsMz6yBD5wKPJ_N3l1-4X_wNJZxVDaagcjT1PPG0wdreS-0PQ8lHObFRu0rOCj1MD1ErAgnceVZt1T_1BetAhIPxhtIEO6OLyTGKKHBJgoll_qpMDeInsyCP3vMbsGkV-4syRSxQI9C6NHLNmsXOqRqhbwDu4oRp6WmAGBD8XMw_7NcQTHqLt9dvb3h6dPJMY0nIg5dEYI3fzfZkugb2PNHtFsAgFljA-2B_6I7oHsV35i34HCYs49ezI1vJwSo3ukZUzL6RJVUBphwXM1q7698BrT6D4cF9Zm4tz2ihC0IJBX44GRLc7E38WkMgga9C3sArYBSv6NCVr-agZWMh4TX72fVuJdfIfEdc_3WeyddL4nB6qfd3NbfwLpHO36WcGjgt8CIu-SkgTepqsPxj9AVWET7oTmHncmzOSMceUv_-wU78EZA2DpsCR-B0erpnEy1SmZyZDMcECyDT1t7abPWspfkCMDE-BFSSkSJ_WI-HO0eqyX5tZqdZk_7WdxgV_5oJwWVtyX78nip9pqtt58148gONSpHatAfK_ePBuHCIgItK3DD0NvshWhXZ6CHcr4LfaprVgY1BpLZ13hggtZTKYDjFaoOgVslcu6txcXw_mpNbTlBVtbuyEfl9O6D3fn-njUI6TywjZuVK_Jj4PPxGyIW5EubPun15J3fGVTZwKzU3eC6cJJYE2sQobSoTnTpeRDB-aKz1gzQbpAKKQWNxIs2hl-BHH_41XoP5d4xh-DOj0TfAYgab7CIxa0Cz1Tw0zc9fjh1DTrGQ_DvvSW7NO4syFalEkiAMymzrF5qoz-JIXZJtsA==\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Inspecting session files**\\n\\nI need to check the sample of the top sessions, possibly looking into the session files for \\\"assistant_end.\\\" I’m curious about the format they use, so I'll try reading one small session and one larger one to see any differences. Understanding these formats is key for what I'm trying to achieve. Let's get into it and see what I can find!\"}]}" }, { "type": "toolCall", "id": "call_AY6OSvXx7ntu7q8UMyEXQwIX|fc_0d29dbf88c868f5a016a12b02352ec8196a1f7ae9e6d89bed2", "name": "read", "arguments": { "path": "/home/sebas/pi-config/sessions/--home-sebas--/2026-05-21T12-06-23-509Z_019e4a6e-0014-76c5-a9f2-fa668d9f2f44.jsonl", "offset": 1, "limit": 80 } }, { "type": "toolCall", "id": "call_y0HzZq3w1NDpgUCD8PuNIl8o|fc_0d29dbf88c868f5a016a12b023532881969f8472c846e3163d", "name": "read", "arguments": { "path": "/home/sebas/pi-config/sessions/--home-sebas-work-projects-vending-status-pages--/2026-05-22T15-06-13-702Z_019e5039-0145-746b-a4be-37c5c81d82aa.jsonl", "offset": 1, "limit": 80 } }, { "type": "toolCall", "id": "call_uFohNEnxA6ZhrP1Rsula4nRf|fc_0d29dbf88c868f5a016a12b02353308196abe510b9751498bb", "name": "read", "arguments": { "path": "/home/sebas/pi-config/sessions/--home-sebas-work-projects-ballbox--/2026-05-17T16-35-27-825Z_019e36ca-e7d0-70e9-b2d1-ed456cbe4f7d.jsonl", "offset": 1, "limit": 80 } } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 442, "output": 296, "cacheRead": 48128, "cacheWrite": 0, "totalTokens": 48866, "cost": { "input": 0.001105, "output": 0.00444, "cacheRead": 0.012032, "cacheWrite": 0, "total": 0.017577 } }, "stopReason": "toolUse", "timestamp": 1779609628597, "responseId": "resp_0d29dbf88c868f5a016a12b01cbffc8196af5d9e71b0b38bd7" } }, { "type": "message", "id": "de515ee4", "parentId": "f9cbab2f", "timestamp": "2026-05-24T08:00:53.234Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "**Considering memory triage**\n\nI need to find a way to perform a cost-effective triage. I can look into using scripts to help me detect final messages from the assistant. To start, I should identify candidate memories by checking session titles, user messages, and the last replies from the assistant. It might be beneficial to parse these sessions to gather insights on the first user messages and potential themes. Since the user mentioned \"cheap,\" they likely want a focused approach to triage and maybe write new memories. I'll work on summarizing this process.", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12b02557c881969476bd5193fa681e\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABqErA0Qjcb1qGkDawUg3vbd7dIvhYdldXuboWoiusq76eHWTEhvC4oxBLFrCdACuHkL7228s1RclQR389K6-vhxdZY3O_NhLI0HJL_l927705qykONDfng4kNRQIY_Yp3XRAfUNE1pwAFjhND9s1ru-fXMxgWC4_JUC4mu9WdUFkH4EnLWM2uxvuRjDkb8Knv3jQO2mRGHKDe0f7GviPLqAiFquCXnkmzfBgd4MZ_soUKUqJKiOTP-MHLeKrCEuQCWvfCEfbyzIrGpQ-qFvBQyvqqzUlpokEniCqeWIYk8r1OMc8wRXcp4VcoOepimhbbElLQsK_NADgzk8jwTOTAkqC-98Icc3uTl9u5sgOn7tMdCENu8LI3UURSt-WknHP0e1fPhIouxxrx1UBNd634FC9MYF6qinZ2Ee1_AMr7HUwtxpqaZtrAmgzUjDOl2D6AC9bqBxC11cNF79oL-C9KeYVNUQ8r9TTEDR8AsMHP8dtRowutClWDpi3khWFtp8KfIQqq1Hjh6RjU4Fm92WqZakhhJhzWh2eFZr6nq8gD1yt7IA4SuBtuTZLQyIXTjdTzQ3d79mAVpqPLrJPSzSROyNmLaNI6Iw8ffP3rvhoKMv1iReT_kOf8FiWy4qq1W8v72c4nsBZvz7CG1UrOubJ9ME02VZH0nNcHbTosrDtdeyKyR6BoRVuYDN4MFHJtfe6QTs4KbAM5OmNEIa2bgOWJxUh7SAKqquYNVcsAP80tA1mrTYquwHKZkL2x-JU1VLbH4Uhr4VpW8Xsne8GfBWCH9OBOlkYx0UQgtwsjE9Je_MJhZOez9Op3asYXBTyAm2dn6_nQNR1mZ33qv_oPS6VihCyARytXydQXzcURq0wTjwBeXhgYNehRcV1__ny97zDfr8As346thhvqY7qj9lu1Cx1Lvq6MaD8kVeXSIVzAxHNV05SYCvL1J3BUHJBmjtUintLI0gSoD6z7zjOpceniNT9SFBOv2CRbOsQzyQey7wuJ3FRwQA29Btf5iGXB2LdMuR4-GgJsRFRJJ3hfhTvN1-qGaj6WLfF48uW_oxIPP582S6BzPhRATlZTIICbXNTBIffAaoaUFy6oY9-ppVqmbwhSMe5j2rtu_eBZOAWvFBdK0yC2B7kNjVNODr-gTHBKUHszru4lPkn4ObTpNWyjrLmtSEd0wMGp-I718hm6qzHdluFDGFW39Lv0EHMKRGTJw3sPZZsynAsqS8ze9Hv-XNKxjZMRvhhMRJS9cg7ffnL606TvNYu7NCYbqlrvDF4bZvr3o3pGqf_vO8x3M2es5D_cgV8fIZap40iya1p1Kv7UiycwFuZWnUEb0KpNMeCbepW09dFZla0TIW6-agkl7PodTmTvpCfXNWKlfeFTY6gUoRAGQ-v4zQt9GccRlbrnGh9oh3FW2KEIyCb1ZmpDPqfM97GgEs5bziL0VDa_YqYp-_9SOKrNURCSoI0zB3eR1NM65mM79zT1cyyYnCcbefZzI43m3ZqrG4DcN5ZYyMjWKYrFVO8TonHpbR-P9OpIlPpJSFGG7_gCHhGga4IUCzAqbFj7r3y42ClyeVueONY-yQW1vq26hSJHjH3HzLfhwua1LLpX5M6qFX1bSgOn7dTalGS3u0UcTSN6O4BbxbyP1di-9JK3NBFJCK5PdheMWUNfmvJ1t3zjbX6QGLm1xOd54BcmDsCZOJNWpidAwE-r7SIxrdXXBkCXa61-jzK5j2gBAIqhopFB6vn8jG9cBnVf13vCbTE7-uCBSYrnCsa2jXe80KQiIHF6KtOTglvjm4li4whXFcgvCnLnaLfFHriu2H0zw8huy_baMmp4BYLSXDgzaXq-_BWLB___dK1AQD8dtihsQnPER2t-1XsToARC8Yw==\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Considering memory triage**\\n\\nI need to find a way to perform a cost-effective triage. I can look into using scripts to help me detect final messages from the assistant. To start, I should identify candidate memories by checking session titles, user messages, and the last replies from the assistant. It might be beneficial to parse these sessions to gather insights on the first user messages and potential themes. Since the user mentioned \\\"cheap,\\\" they likely want a focused approach to triage and maybe write new memories. I'll work on summarizing this process.\"}]}" }, { "type": "toolCall", "id": "call_3nIpUtGPJQM3t0EeYcewg0No|fc_0d29dbf88c868f5a016a12b034f1d48196a34d6d93c5473c5c", "name": "bash", "arguments": { "command": "python3 - <<'PY'\nimport json, os, re\nfrom pathlib import Path\nfrom collections import Counter\nbase=Path('/home/sebas/pi-config/sessions')\npaths=sorted([p for p in base.rglob('*.jsonl') if p.stat().st_mtime >= __import__('time').time()-14*24*3600])\nfor p in paths:\n first_user=''\n last_assistant=''\n msgs=0\n with p.open(errors='ignore') as f:\n for line in f:\n try:data=json.loads(line)\n except: continue\n if data.get('type')!='message': continue\n msg=data.get('message',{})\n role=msg.get('role')\n if role=='user' and not first_user:\n parts=[]\n for c in msg.get('content',[]):\n if c.get('type')=='text': parts.append(c.get('text',''))\n first_user=' '.join(parts).replace('\\n',' ')[:180]\n if role=='assistant':\n texts=[]\n for c in msg.get('content',[]):\n if c.get('type')=='text': texts.append(c.get('text',''))\n if texts:\n last_assistant=' '.join(texts).replace('\\n',' ')[:180]\n msgs+=1\n print(f'FILE\\t{p.relative_to(base)}\\nUSER\\t{first_user}\\nLAST\\t{last_assistant}\\n')\nPY", "timeout": 20 } }, { "type": "toolCall", "id": "call_ejfC46Fo6AiFg6mz9UhY2ckz|fc_0d29dbf88c868f5a016a12b034f1e081968cf657b8b05c00f4", "name": "bash", "arguments": { "command": "python3 - <<'PY'\nimport json, re\nfrom pathlib import Path\nbase=Path('/home/sebas/pi-config/sessions')\npaths=sorted([p for p in base.rglob('*.jsonl') if p.stat().st_mtime >= __import__('time').time()-14*24*3600])\nkeywords={\n 'memory':['memory','session-end','analyzer'],\n 'rss':['rss','feed','pdf','epub'],\n 'vending':['vending','ourvend'],\n 'ballbox':['ballbox','coaches','clubs'],\n 'tmux':['tmux','session','telegram'],\n 'server':['server','ballbox-first','tailscale','nginx'],\n}\nfrom collections import Counter\nc=Counter()\nfor p in paths:\n txt=''\n with p.open(errors='ignore') as f:\n for i,line in enumerate(f):\n if i>40: break\n try:data=json.loads(line)\n except: continue\n if data.get('type')=='message' and data.get('message',{}).get('role')=='user':\n for part in data['message'].get('content',[]):\n if part.get('type')=='text': txt += ' '+part.get('text','').lower()\n break\n for k,ws in keywords.items():\n if any(w in txt for w in ws): c[k]+=1\nprint(c)\nPY", "timeout": 20 } } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 37675, "output": 859, "cacheRead": 48128, "cacheWrite": 0, "totalTokens": 86662, "cost": { "input": 0.09418750000000001, "output": 0.012885, "cacheRead": 0.012032, "cacheWrite": 0, "total": 0.11910450000000002 } }, "stopReason": "toolUse", "timestamp": 1779609636058, "responseId": "resp_0d29dbf88c868f5a016a12b02456a48196a437fd759593d4a2" } }, { "type": "message", "id": "8a91383e", "parentId": "63ba9c89", "timestamp": "2026-05-24T08:01:00.756Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "**Evaluating memory backlog**\n\nI need to inspect the current backlog to estimate which sessions could generate lasting memories. I think there might be 5-7 candidate memories from sessions that aren't stored yet. Loops usually collapse into 2-3 memories, so I should check the significant docs from certain dates: 5/12 for RSS, 5/15 for expenses in Europe, 5/16 for wifi tracker, and so on. I’ll see if any of these should really lead to a memory.", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12b036f7c4819696b0cff3c14218c5\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABqErA8r6GQcyrVcKJ6UlH0iEG0sGTWgrm36drHk_xLJuoWBPxzD2nFznmnsSurKzsySdQ8oCMkoJbWgKWOpnlSZJ62g0H9HZi9dHEBLKVVMGo0Is6DwRua5jfRP3D7FVSjymnPHZEyVR_a2eyGW_Mzluk5z5PVYccZgu_U4c5WzvRihUNOJOHNMyEmmSgdg2DjH5QTRXemojYLRxqz45gAoPxdU-cDjK2nIXAgT-Yg9O6U6pE-_jj3xd6-k8DS7QpD7rkzmIePOUySozCeKnkFTv5lhAalGlBhL3jDudi0YixdUef_ziXJ33QspajalooZ1JSHOqcqpvotvd_qnjzffJlA7JR59m7oQO5BP-dV4ZV5PImQwOdhyev3tN3rKlwdELq5apWc7CdxqtqTSJu3E8t-MNN6xRscDWu6cSB7sjCSr9M0Wiqr1ORsT3ylbC-FwjE6OcgHsKPyP8VMB7Ic87xgHZjFSgJJDjn_qRCMF0IcbbD5Kx2gsEtunz21c38eHcZY0IdRVSuH7OAsPrgQjjlfCbxX_xjXgcnfqhI9g8ws45vtQaQaXbDgF5ZkaAfJh7rn5YbpX0si7rZPkoFjmft6b8one8aIIJMfI2RSuH_8c8HmEOG1_lO2uP-T0t_k7EKaEgfrgaQF1X8BxMQyCu2ZSN-ltmuK4j_aCB0vuZDEFLXfAf6tgrrCXb9p6Mewvcdz8Z-xwoMyvnarbJBulYnU40iiE4pEKv-FjE5vJYj0FJCVHwKAYzm6bgyQ6MDWFaib_i7ZhakmcIWEQB4pp6v2HiQu9XFxOb7qheVcIRt_rUADXGx-UMzPTtQ5163qXuFIepJb4ocUq_EIYB6XtHfMPRCPsfIlN22KpjY-57DQ2MG2uJNaiXWB4d5dYJQJwG7f6B-yDhWEMXERuILlSOrYm50qRIcf_gFL7879hFU3Quwx9_GTqrcu929fgvZKxD2T6tppOY3QyL5eSBKd3WGwoa3MUSKGZSjOOvd_YE3bJ5dVndUSQ-aG9wsE12_eM2-555L58rzZvZDSjYrUuA7ORkAJcU4wJHSXBo6j5hxg5nT4V86o0Yvg7o02t311rt2DfEOZW2Z5o3fDfWx8GIcrirM3qHWbE67B1GvRaikdcH36QuLYDMIXnwKbKjFCZlRuimpylFu92sxJcGSRmc_mriiEjhEtjtNR5MfZrndBucqktnGt4QeZEu9yim0b3bwnZQhFYHtI03Q_LQKlnX-eVglRpsee9_VAwEketJMesvvXgCIp8kAllMXYOXdhzHpCcaUrhCeARjD1IPadzEyYS98xZeVHhK3nGL2ohDHs1zvk8QNhAVATvruFRQ2swrbEdr6VxfgJU1Rw25YINFLFmh0WhRIE8xvXOjp4AJvS6eaI6b5dB4AqWR87H94yw495hZAXJj22gx6pdzAx1uGlP4ZMYAz2QKqi4FsZ28b8_cus9385kkgyHfxo6LkZ4P7uPiakJJ_XZtSseEDDewUhzAzy3Id9-ZENNbU2NuoJfF7sH0czNmFAjHX6U3oNyCcnzvdZd4NlexWU_NqpXKU6Ga7X9foyKXaFfkiX8D-xIsBsUhJYrzlHvAnsB9KVgF65CSNsToEtVflt2L7DxC7Aafaqk0kCe57Va3ZEDIcrODlWMQtDiPIEHI8uAGbmDjVjpdA0t67k5YnAAV-880QGHcAdb_RFA4EXLL0bbTafvzZWBxXCoSnsuTmOxkaDXJ_7zdfzb801o6tLw-1I7c7kSwTdcv4AWxPvPXN3YehWva4WIjFN_tqJN6uPgEvgjN28\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Evaluating memory backlog**\\n\\nI need to inspect the current backlog to estimate which sessions could generate lasting memories. I think there might be 5-7 candidate memories from sessions that aren't stored yet. Loops usually collapse into 2-3 memories, so I should check the significant docs from certain dates: 5/12 for RSS, 5/15 for expenses in Europe, 5/16 for wifi tracker, and so on. I’ll see if any of these should really lead to a memory.\"}]}" }, { "type": "toolCall", "id": "call_sS2wjo3yBy9Tn4LK97KeTGWQ|fc_0d29dbf88c868f5a016a12b03c585c8196a595b7e9d2d76fd3", "name": "todo", "arguments": { "action": "update", "id": 1, "status": "completed", "metadata": { "sessions_reviewed": 36, "candidate_memory_sessions": 6, "notes": "Cheap triage via first-user/last-assistant scan across all recent session files. High-signal candidates cluster into a few topics, not one memory per session." } } } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 5587, "output": 224, "cacheRead": 85504, "cacheWrite": 0, "totalTokens": 91315, "cost": { "input": 0.0139675, "output": 0.00336, "cacheRead": 0.021376, "cacheWrite": 0, "total": 0.0387035 } }, "stopReason": "toolUse", "timestamp": 1779609653676, "responseId": "resp_0d29dbf88c868f5a016a12b035d6688196a7a4887d3df436ab" } }, { "type": "message", "id": "6060e74f", "parentId": "90369c28", "timestamp": "2026-05-24T08:01:11.258Z", "message": { "role": "assistant", "content": [ { "type": "text", "text": "Cheap triage done.\n\nAnswer:\n- 36 session files scanned\n- manual session-end processing is still\n cheap if we do it by topic, not\n one-memory-per-session\n\nBest estimate:\n- raw sessions: 36\n- real candidate sessions: ~6\n- likely durable memories to write:\n ~4 to 7\n\nWhy low:\n- many are loop iterations\n- many are tiny/ephemeral\n- several sessions collapse into one\n durable fact or decision\n\nMain buckets:\n\n1. `vending-status-pages`\n- 6 sessions\n- really 1 topic\n- likely 1 strong memory missing:\n vendor-backed migration completed,\n ads still blocked/hidden\n\n2. `ballbox` Ralph loops\n- 16 sessions\n- mostly loop mechanics\n- likely 1–2 memories max, if any:\n accessibility loop outcome / method\n\n3. `rss-offline`\n- a few sessions\n- some already captured\n- maybe 0–1 missing, depending on\n whether the “save full page locally”\n pivot is already fully represented\n\n4. misc home-sebas sessions\n- one good candidate:\n `gastos europa` raw archive +\n visualization setup\n- most others look ephemeral\n\nCost if I run it manually now:\n- cheap triage write pass:\n ~20 to 45 min\n- output:\n probably 4–7 good memories\n- not worth doing 36 separate\n session-end analyses\n\nBlunt read:\nthe backlog is not “36 missed memories”.\nIt is more like “a handful of missing\ntopic-level durable memories”.\n\nIf you want, next step:\nI can do the actual cheap write pass now\nand ingest only the 4–7 strongest ones.", "textSignature": "{\"v\":1,\"id\":\"msg_0d29dbf88c868f5a016a12b03f476c8196bf0eaa19b3214110\",\"phase\":\"final_answer\"}" } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 710, "output": 366, "cacheRead": 90624, "cacheWrite": 0, "totalTokens": 91700, "cost": { "input": 0.001775, "output": 0.00549, "cacheRead": 0.022656, "cacheWrite": 0, "total": 0.029921 } }, "stopReason": "stop", "timestamp": 1779609660758, "responseId": "resp_0d29dbf88c868f5a016a12b03e5144819694641bbfcb25927f" } }, { "type": "message", "id": "c8a14827", "parentId": "6060e74f", "timestamp": "2026-05-24T08:03:57.237Z", "message": { "role": "user", "content": [ { "type": "text", "text": "[telegram] yes" } ], "timestamp": 1779609837217 } }, { "type": "message", "id": "fa824b74", "parentId": "c8a14827", "timestamp": "2026-05-24T08:04:03.805Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "**Planning memory tasks**\n\nI’m thinking about writing down some memories, but I should really search to avoid duplicates first. Using the memory-write skill seems likely, but maybe just using a simple curl helper could be easier. I might need to look into some sessions related to gastos Europa and Ballbox accessibility. Plus, there’s possibly something with vending migration. Should I create a to-do list? I think I should follow up with instructions inside the active task first.", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12b0efe44481968305cafff4334a42\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABqErDyQwL20HM1lEghrM_lub8JJqiEPkDRrtuIwovKtoY6fhjuVlQzBYx93Bj8d8X9URAoibJ3eFRsZL_78vHcq7vLcAVJfbLdeUu3NTH8n-9PxEstdV3jXC74BTa7jgKSFHChdceFV8MrBjc5NhGbsVOlORCfD_3I0LDHSzm-VWODEaNSBtPuI5zeEfivNh2n6vsbVFsN3p8GjCtFrqIilEeNZCbupc8-e6tv8u19wYrXH--lVQuYnvHfPmj6vFOdmCj7z3IhhMFI0OE5DPKOuP8_t8FWJwm36RgA1jHmWBk7jN65IXv_LGzWA9gcIg5wNhC_Jb9VY1L5567S_-sshU67aLPHYCH-c6mJML93KKW6fJ3MPid7WNRL-6BO4DcwnqibGwnGwJ-UDrCDV9WdCNCpNcLlgv0f7I7uMw6WgLUoeaQEJTl9VlkEPlQUVqWRDgFHGE89jGQJUp1UUfU_luY-T1gWDShcEjRE21ZIsbof3NBAxSKUGefUqwFBSi5W0bCwgBrTfFNobFQnrBFM-iZ_-V4hTu84_TrYHd9-1daosorX-kH--Bl0pzI0wpf_i5Kx9hL4D_amfI5hKeLBHhC4P_M9Amq5nt-4XEr0KrINBXPD6Zd7k4JhL2NikZQIBgoPoWr0rkYWDNwEk7nF3qcmY12kUw0hZDAFz_LhqXzRteNVln6nVR9-v7ew9DwsvE0sJkxuTVkUJZ25CuI-MbR_HJbOEzwaaZYmabl2KWE54wUwN-Fyj1Mpdr2ih4Ipodo3DyfIa46c-w6W9_Yc6DJkL9g0xVp9BbH-s_iELNUZ-D79cZQZFJ4F1QM0UrC4eDjpajlcAMMNrJR7HibKRBL0QWLfnqy09RFsnYChb0vUi_FjNyvzrjAXMO9lPJdwhCG-h8wyU5X9OhRYI60iEHD2meP9w-SMZeUEZiaFfRIjyKk7NflV-GA15u0fOqCwfXcwXFHxJ6NE8blqj9xUiJTiWj7pUlDd3eq8-5UY-f_yUBiU-ZWMhAc4Lmo9WB0pgpeNyGgtQQpgHiROJhFJB4ntm4ieBVKmt1920CoZOlDk9bTsaVnFLVwst7xoSgUBtXheTUDEZQSinlmYkqkv8xmAl3-OEsd-r-vLHj9X9Nn1yk3CnQp7gj4T7X_mfNhsekYHfF0vOjIokwE1p15n7jOEaj46O_wYyA1EQYb4ns4Z9JJOSMduKp0FJ7ftXd75WZ06SUKDz5KqpJN1BeRWwiuRMV67rI_jsO4uoEZPwWA6GJu3GbMDcWLkmX9TK7Neq36zQkHPr_EhdzD-CUaWExi9H55krh67D04ExR2MF54FS4mYwnEPykl045e4H2XFYG4KWwgOjKriLY3dn-rQRdoXbn-aM__ZkNSxPnpgUzsxXwcO-lTi2eUrDQTyvwn1XDMm\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Planning memory tasks**\\n\\nI’m thinking about writing down some memories, but I should really search to avoid duplicates first. Using the memory-write skill seems likely, but maybe just using a simple curl helper could be easier. I might need to look into some sessions related to gastos Europa and Ballbox accessibility. Plus, there’s possibly something with vending migration. Should I create a to-do list? I think I should follow up with instructions inside the active task first.\"}]}" }, { "type": "toolCall", "id": "call_0eoajNk7luZSlnP5KDESyids|fc_0d29dbf88c868f5a016a12b0f2d66c8196befcaa4840c74fe6", "name": "todo", "arguments": { "action": "create", "subject": "Write cheap-pass durable memories from last 2 weeks sessions", "description": "Use recent session triage to save only the strongest missing durable memories into agents-database, deduping against existing memories first.", "activeForm": "writing durable memories", "status": "in_progress" } } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 51385, "output": 146, "cacheRead": 39936, "cacheWrite": 0, "totalTokens": 91467, "cost": { "input": 0.1284625, "output": 0.00219, "cacheRead": 0.009984, "cacheWrite": 0, "total": 0.1406365 } }, "stopReason": "toolUse", "timestamp": 1779609837223, "responseId": "resp_0d29dbf88c868f5a016a12b0ee6a5081969d180613912c11de" } }, { "type": "message", "id": "ee347a3e", "parentId": "d8d48387", "timestamp": "2026-05-24T08:04:07.372Z", "message": { "role": "assistant", "content": [ { "type": "toolCall", "id": "call_106tqvDp9kH04LW3bYO2JcU6|fc_0d29dbf88c868f5a016a12b0f648a081968f3713a0b1414d32", "name": "todo", "arguments": { "action": "update", "id": 2, "status": "in_progress" } } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 359, "output": 26, "cacheRead": 91136, "cacheWrite": 0, "totalTokens": 91521, "cost": { "input": 0.0008975000000000001, "output": 0.00039, "cacheRead": 0.022784, "cacheWrite": 0, "total": 0.0240715 } }, "stopReason": "toolUse", "timestamp": 1779609843808, "responseId": "resp_0d29dbf88c868f5a016a12b0f4b9f48196b06038248db3723d" } }, { "type": "message", "id": "95d629ea", "parentId": "36fe6f46", "timestamp": "2026-05-24T08:04:17.070Z", "message": { "role": "assistant", "content": [ { "type": "toolCall", "id": "call_19g804xfgFeyPyipGpEqrU58|fc_0d29dbf88c868f5a016a12b10080748196b9ded6bad370b190", "name": "bash", "arguments": { "command": "python3 - <<'PY'\nimport requests, json\nqueries=[\n 'OurVend real-backed migration ads blocked hidden vendor-backed',\n 'Ballbox accessibility html-first loop',\n 'gastos europa raw archive visualization',\n 'save full page locally rss-offline full html copy'\n]\nfor q in queries:\n r=requests.get('http://100.116.176.16:8091/api/search', params={'q':q,'limit':5}, timeout=10)\n print('\\nQUERY:',q)\n for item in r.json().get('results',[])[:5]:\n m=item['memory']\n print(m['type'],'|',m['title'],'|',m.get('created_at'))\n print(m['content'][:220].replace('\\n',' '))\nPY", "timeout": 20 } }, { "type": "toolCall", "id": "call_PpME9ZVisxgiI2kqf0foXaMO|fc_0d29dbf88c868f5a016a12b10080848196ac59bc70a2ad7f39", "name": "read", "arguments": { "path": "/home/sebas/pi-config/sessions/--home-sebas--/2026-05-15T11-21-13-095Z_019e2b5e-7c86-743e-a727-efe867ba7d5f.jsonl", "offset": 1, "limit": 120 } }, { "type": "toolCall", "id": "call_JSFanP9QH7xOVomfMKucju34|fc_0d29dbf88c868f5a016a12b100809081969c81d22db38e82bf", "name": "read", "arguments": { "path": "/home/sebas/pi-config/sessions/--home-sebas--/2026-05-17T07-48-17-216Z_019e34e8-42bf-7188-b802-c22ee31bc60c.jsonl", "offset": 1, "limit": 120 } } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 404, "output": 368, "cacheRead": 91136, "cacheWrite": 0, "totalTokens": 91908, "cost": { "input": 0.00101, "output": 0.00552, "cacheRead": 0.022784, "cacheWrite": 0, "total": 0.029314 } }, "stopReason": "toolUse", "timestamp": 1779609847374, "responseId": "resp_0d29dbf88c868f5a016a12b0f872b48196be486e413182bf39" } }, { "type": "message", "id": "3bea6d18", "parentId": "1fffeb23", "timestamp": "2026-05-24T08:04:31.100Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12b104bf988196bd122dfc218890ff\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABqErEOkz-BNS1R9YWOJ_4L46-CRu6bVEFSosW57MBPWQLdJ8aL4qwZvq-7yvK4nuKPZ5Js9Tqqw0R2eE6JgqljhGVvHXd-JCwpklz8tJht3wT9S4w40UPvMDfFhABpxa8_xDlU7lDLnkl9o7vj3nDdXsyYPVSv41cVVXrNa27r5DKAlRPsZW9Lh3hhx89jFCxEbssCL3iqX0e27lMg10rM02LYlWrb-J-vXpU2M6DjSu9twZCBuViRjezWn_hNscgkg32KebPeWAuCf9RbcBwoBduKdm82MGKigsSzQaHjR9ROGKHnTaJXK0_53f0ookPdW9p7hvS7Qb-KBQ_A_rYIqZEl12iTu9kNxtkPjsvN-VuNJTYIDxZbRbpUU0ZIvFRTAQFopNj_rjXU7VeFUkfGSJ8aYF45M2oIn0hjd9IXqiJEGT9M9v4xqkNL4S1mQ5OqC62zXULwJixiYrYH4FCtiPu3jWoUiY_JKhG4icT0Sqza7QIyiqos9nNue5yoyBSCm_X2zKy-7H32Gj-63Y4GXHOkua9B0LYMv5A-CmYrkHWUyXjxodEPmIKZsXiLBMPhQLfuGGZDAu51-72mayWiPdbUTUkoWtMJpYPawTCgsSMT07vliSblSZzJfVvCSuVHuL1JGVqxaaGg1rPCLw7_LTMHuIvrc4WrxukRrBrDbf62WnQ3OSC52Zw94wbNkrU7yILeLsvgwgP7iA8I9ex07MJvR7E-jw6JILkMoSb5dUOEeCdvYQ52Zzi0jvl1DvJ7T7qnrziivrsoatA7X9np7WeoCY5AXzN45QaEaoraWp8YFl8a14ZoTS1wLXSuKVgiw4zvyEYQslsgS2hwm_q5EnpOvnX6ExmhiWjIaaUgbdlPjhVXTtEUSdFC3uCVGSEyZHwhOq4XG7TpxCSb8JK4zo7-WMTxO0Ag0SQSIk4vd4U4OwAH14JiehQ4hZJ7DbIywOucteoJWAbbNfw-tjLV6uAYgiPDSh89A79HRqmvVPOUoKOz_rWYMsWg3o3ubFcgCMwNV0YUqWJD0RcSFhd9s8Yds0hAWQ0mzqKSs49OxasX3ybbiicUd-AaaksqU9FoXmfYhNRl4iDbPFkRQ9mOvbTX6hxYf2UKMbrp-YCDqWgBeNHf4LN4Ih32LSlXWlimrfExlbmu6EGwa3rFBpb8waxbnk9LFGzk_67Dbzi4VJIGPCtAVH3E0Nq7NUq0WgRq_nTK9qj6O6bzOsW-3RzkwFm0VINV1x-iwB6kvA3E7Mht2sQ6hkWJDCkU3QATpsy7274tmfgWGBc5sPO22OtT7e5xsCdet_6iyUow_ABhOyiNy6GJmYUtPbrnNYQA-7K7YbuFjz2InSObOMS9fTCJFBqmCTlyyoJOZNBa2vO1SfSxo3PR03XrASSSrUujvNqzTaJkCBUPd33DJzjuwlymxVVZciBcBeg-O3gJWjBRaYjhzH8LzS1PVa1zdT8QAXkT-SaIDJKxIAo9zO6WaIiVqi_It12qqIl142RMo7vYW0uMv1LLUy7rAoLLcO9Gv5SjjwxQFU1xM2fmWxJTJoPtYh0C94dAEkzMMI9Dvv9jnA-uOcA=\",\"summary\":[]}" }, { "type": "toolCall", "id": "call_2XqWN7bGdJYrjyj4V7qloF0p|fc_0d29dbf88c868f5a016a12b10e4da88196b75fe9ad84d91ca3", "name": "bash", "arguments": { "command": "rg -n \"gastos-europa|Europa|visualizacion categorizada|raw\" /home/sebas/pi-config/sessions/--home-sebas--/2026-05-15T11-21-13-095Z_019e2b5e-7c86-743e-a727-efe867ba7d5f.jsonl /home/sebas/work/gastos-europa /home/sebas/pi-config/docs/gastos-europa.md /home/sebas/work/gastos-europa/README.md 2>/dev/null | head -200", "timeout": 20 } }, { "type": "toolCall", "id": "call_wgsZr6vAsgK6U1taIVlyS7df|fc_0d29dbf88c868f5a016a12b10e4dbc81968fc3a73159aed2dc", "name": "bash", "arguments": { "command": "rg -n \"full local HTML copy|stores a full local HTML copy|save.*full.*page|rss-offline\" /home/sebas/pi-config/docs /home/sebas/work/projects/rss-offline /home/sebas/pi-config/sessions/--home-sebas--/2026-05-15T13-21-22-432Z_019e2bcc-7dff-77dc-a119-d1702176bbb8.jsonl 2>/dev/null | head -200", "timeout": 20 } }, { "type": "toolCall", "id": "call_7pB422a7rFX8WvgMj8qntoyR|fc_0d29dbf88c868f5a016a12b10e4dcc81968f483abbfa9ee4d0", "name": "bash", "arguments": { "command": "python3 - <<'PY'\nimport requests, json\nfor q in ['gastos europa', 'OurVend ads blocked hidden', 'html-first accessibility Ballbox Martin Alderson', 'local HTML copy rss-offline']:\n r=requests.get('http://100.116.176.16:8091/api/search', params={'q':q,'limit':10}, timeout=10)\n print('\\nQUERY',q)\n for item in r.json().get('results',[])[:5]:\n m=item['memory']\n print(m['type'],'|',m['title'])\nPY", "timeout": 20 } } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 18677, "output": 527, "cacheRead": 91136, "cacheWrite": 0, "totalTokens": 110340, "cost": { "input": 0.046692500000000005, "output": 0.007905, "cacheRead": 0.022784, "cacheWrite": 0, "total": 0.0773815 } }, "stopReason": "toolUse", "timestamp": 1779609857415, "responseId": "resp_0d29dbf88c868f5a016a12b1029e8881969b9691a5e558711d" } }, { "type": "message", "id": "5d353087", "parentId": "80c377ee", "timestamp": "2026-05-24T08:04:48.084Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "**Writing memory entries**\n\nI'm thinking I need to write about four memories: the gastos-europa project, the rss-offline full page local copy, the vending real-backed complete, and possibly the ballbox html-first decision. I need to ensure there are no duplicates. It might be useful to include project IDs if I know them, but if not, I wonder if using repo IDs is necessary. I can use the memory-write helper to take care of these four entries.", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12b111fa8081969bf0be4765e8f451\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABqErEfdEUqTtv5sKpOt7UktojXGnptbmuRxIckNUdAoi--BiPdbmmi6tK1MRjhrLbXA_Z4_L24I-Mz-hYcH9lUXlYv2B0Cp2DcF39w9ybgdsFobqUNDVb8SWsfKmvh2jmfUNM4g_def_K6k1ojNgXuywxll0I9rvGNZVhyU-lzB2QQTbh8-2B2h7kHM7uOkyANveI3_2xpGTk-z974yj-Jhh-QUt2TTZgD51_oM0XGvVgnb0EZPS6UepXWeof6CXPfi65FLbL2fUqS0iG0x4eQnfqda2Lyc0lQmvbjqvR22tT0NHTgrnFUqzRgHqMACTAzUwYp1OefqLS0bm5_qx1hB0FPjRgk2hdTvDO2vJUHu0pASSNEsQ-TKfxWFJR1E0xql8ez7-bv9G2DIInWnNAMEsFZAF-kkBS7KFiEXnMZQbBhtttzOHMvw9L1MWYNqsaux4BA-ps3QYDvexAMhUcwvk9eZYTlAeFJsSRULqii6hvOnjawovu8ZNijmp2FWwy0P4R-WvxASqoPUEZQQHH0hBouqEUmc7u2oMFdA05KZ-9rK4RNfwyoGiDaoUEXYlEqDiEwJ4zFNxtu0SXmHGIwK7-rB_W0PCyLmfJGrEAL5zUWQLUgDTTMt6nG-ywWPszN33x5XVGcgf7au15HzQAgINjhfXxy6zg-KRUP60vGE5fbcAijgxeAs_eh4HiYguaAcmJorVlHX5_MpK26TMzrPJ6Io7FSch_ydWx7W4Dp6VleZTrbWZt0CgIRrCsXbBKHsDk3LEFdrpWTWUpbY-VTomwDHee5SEJvgPAIuu9sspi0c-cZcCzZB_qDgzo9Opqe84R_0rv6sA3jXNCkHK8mFURy0FfT6NrML9XctpZJW0IeUYtLxH2PyrbvOaHQqnhaFjgA9DFE7PwLmp7-8aQ390GoSDTn6llracCAjHAn5RL84FXgXoKZsA5zD8eej4ZDRhcCCRVX1R0WDJrLauqae0KRm5S--fU-d9f23fjRNiOV9RWHZ_mY1Fa9q7wOxf4P8hdYzdwVjeAaiKOPPb8P_oDQvjVyPOe4og3PSjKwVY6xbTgG5jIR34JWYNgB-ywSaM7jjjEJCAKnAvf0kJg_YV5opgzjXZU4Zo6sk9n0Db7fmIiIAXmfcz3BzIyWkIS2UB-2yIMkBTJz6KZsCKG3nCEfe5Wts7I4DdmwZn3fWhRzVUHYbb7fOe-UC4Qpz_hTukrAfSpxgkyHPlBI5g0qrqczI82EocelOCVkYAyjoMd_nHS4CkTubho4gNMk9FHyM50HddldePNXcFcGYFXsoHm7UbSvzlLrvTOkj3av_VLndaHas9r8jwZieYx0DSMOIQZ6JmEIB-qTNNdY42bkOyD2zg==\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Writing memory entries**\\n\\nI'm thinking I need to write about four memories: the gastos-europa project, the rss-offline full page local copy, the vending real-backed complete, and possibly the ballbox html-first decision. I need to ensure there are no duplicates. It might be useful to include project IDs if I know them, but if not, I wonder if using repo IDs is necessary. I can use the memory-write helper to take care of these four entries.\"}]}" }, { "type": "toolCall", "id": "call_e7FA526Ta80vTlGQuoYxzwjj|fc_0d29dbf88c868f5a016a12b11f2184819690d0186fe5aa71a9", "name": "bash", "arguments": { "command": "~/.agents/skills/memory-write/memory-write --type project --scope project --title \"gastos-europa stores raw receipts and published allocator app\" --content \"The gastos-europa project keeps original receipt/card screenshots plus extracted text under /home/sebas/work/gastos-europa/raw, builds a derived transactions dataset, and publishes a phone-friendly allocation UI with persistence and URL filters for Sebas/Vicky shared-expense classification. On 2026-05-15 it also absorbed additional Deel/Airbnb screenshots and the dataset parser was hardened to tolerate notes like insufficient-funds or reversed transactions.\" --source-ref \"session:019e2b5e-7c86-743e-a727-efe867ba7d5f\" --origin-agent personal-agent", "timeout": 20 } }, { "type": "toolCall", "id": "call_dBll69Oa2pNrtTiAxILwjP2O|fc_0d29dbf88c868f5a016a12b11f2194819698649aa091c66726", "name": "bash", "arguments": { "command": "~/.agents/skills/memory-write/memory-write --type project --scope project --title \"rss-offline saves full local blog pages with mirrored assets\" --content \"On 2026-05-15, rss-offline pivoted away from text-only article capture. The builder now saves full local HTML copies of blog pages, mirrors same-origin assets locally, supports rendered Chromium snapshots with a bounded rendered-entry cap and simple fallback, and shows the used capture mode in the UI for better offline fidelity.\" --source-ref \"session:019e2bcc-7dff-77dc-a119-d1702176bbb8\" --origin-agent personal-agent", "timeout": 20 } }, { "type": "toolCall", "id": "call_Hf3JnLiEJkXEaLIifTrd0Jxj|fc_0d29dbf88c868f5a016a12b11f21a08196937865cd06370b0f", "name": "bash", "arguments": { "command": "~/.agents/skills/memory-write/memory-write --type project --scope project --title \"OurVend real-ui migration finished with ads blocked hidden\" --content \"By 2026-05-22, vending-status-pages completed its current real-backend migration: visible routes like /, /products, /products/new, /ads, /machines, and /api/machines/2601070188/feed were revalidated as vendor-backed, fake local business truth was removed, and unsupported ad CRUD remained blocked/hidden until a confirmed OurVend endpoint exists.\" --source-ref \"session:019e5039-0145-746b-a4be-37c5c81d82aa\" --origin-agent personal-agent", "timeout": 20 } }, { "type": "toolCall", "id": "call_1qg9Acfd84BCxFz3FMYKDmmC|fc_0d29dbf88c868f5a016a12b11f21a881969b2b3305afb7168c", "name": "bash", "arguments": { "command": "~/.agents/skills/memory-write/memory-write --type decision --scope project --title \"Ballbox accessibility should follow html-first in Next\" --content \"For Ballbox, Next.js is not the obstacle to html-first accessibility. The durable rule is to start each screen as valid semantic HTML with native links/forms/buttons/labels first, use JS only as enhancement, and avoid custom div-based widgets unless native semantics are insufficient.\" --source-ref \"session:019e34e8-42bf-7188-b802-c22ee31bc60c\" --origin-agent personal-agent", "timeout": 20 } } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 24757, "output": 721, "cacheRead": 109568, "cacheWrite": 0, "totalTokens": 135046, "cost": { "input": 0.0618925, "output": 0.010815, "cacheRead": 0.027392, "cacheWrite": 0, "total": 0.10009950000000001 } }, "stopReason": "toolUse", "timestamp": 1779609871739, "responseId": "resp_0d29dbf88c868f5a016a12b110d06481968c1007e0b260ef0f" } }, { "type": "message", "id": "dc9de554", "parentId": "9e56f023", "timestamp": "2026-05-24T08:04:53.804Z", "message": { "role": "assistant", "content": [ { "type": "toolCall", "id": "call_PTIkTIdHkn4sN5JlXnEfnfcR|fc_0d29dbf88c868f5a016a12b12348bc8196afbe7f0ef0205488", "name": "todo", "arguments": { "action": "update", "id": 2, "status": "completed", "metadata": { "memories_written": 4, "memory_ids": [ "mem_58309c3e69e444d7b15c377d18b6b960", "mem_8008ca82485848cd9f5492c09c236fa4", "mem_8c5c0ef5a6e3412289c6fbe2210108b1", "mem_caa17fc9013941b08d40188047b0958d" ] } } } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 2512, "output": 124, "cacheRead": 134144, "cacheWrite": 0, "totalTokens": 136780, "cost": { "input": 0.006280000000000001, "output": 0.00186, "cacheRead": 0.033535999999999996, "cacheWrite": 0, "total": 0.041676 } }, "stopReason": "toolUse", "timestamp": 1779609888330, "responseId": "resp_0d29dbf88c868f5a016a12b121d6a4819695227f3627002b53" } }, { "type": "message", "id": "68e0435e", "parentId": "a2ebd697", "timestamp": "2026-05-24T08:04:59.085Z", "message": { "role": "assistant", "content": [ { "type": "text", "text": "Done.\nWrote 4 durable memories:\n\n- gastos-europa raw + published app\n- rss-offline full local page capture\n- OurVend real-ui migration complete\n- Ballbox html-first accessibility rule\n\nIDs:\n- `mem_58309c3e69e444d7b15c377d18b6b960`\n- `mem_8008ca82485848cd9f5492c09c236fa4`\n- `mem_8c5c0ef5a6e3412289c6fbe2210108b1`\n- `mem_caa17fc9013941b08d40188047b0958d`\n\nSo yes:\ncheap pass was worth it.\nSmall number of strong writes.", "textSignature": "{\"v\":1,\"id\":\"msg_0d29dbf88c868f5a016a12b127cf4c81968c0571cf4025f2ce\",\"phase\":\"final_answer\"}" } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 607, "output": 159, "cacheRead": 136192, "cacheWrite": 0, "totalTokens": 136958, "cost": { "input": 0.0015175000000000002, "output": 0.002385, "cacheRead": 0.034048, "cacheWrite": 0, "total": 0.037950500000000005 } }, "stopReason": "stop", "timestamp": 1779609893808, "responseId": "resp_0d29dbf88c868f5a016a12b126e7b48196a26e2eabae2d53cb" } }, { "type": "message", "id": "67b29e41", "parentId": "68e0435e", "timestamp": "2026-05-24T08:52:33.610Z", "message": { "role": "user", "content": [ { "type": "text", "text": "[telegram] curious of how you use it. suppose i talk about something without the exact words it was saved as. how do you approach it?" } ], "timestamp": 1779612753590 } }, { "type": "message", "id": "b0584b72", "parentId": "67b29e41", "timestamp": "2026-05-24T08:52:46.884Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12bc557db48196974409a953e653ca\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABqErxVE0gw_KmR7JFg3jziBxVKRZILimo-KpT3n4EwaTzunG1x2dKWIDJBufQVnba92FbEcF2qWBxHX8mlHKESZV_v3ogc6OT-BQRdhSxuP3H0vOBVcLzIXrbzFaTk271VeQl6VjIdrnzksLcMprDDnpJVs8QsaojMuW9NelOjNEdOkMqebBX52gYfP3FEYQRJG1xK5Ia824wVoklnxDe8saINsV-nMyAxW1VJIWTEubQ-xWclTUiVxiuXLifNvFA0kpJnzcwYKoJLzaPE-VNueeeCwx4c_-Y9vAkiIuj6H8aSDLW_G0XhQq3cnGSWNUd5-_VixmQ6C40hXyl_fTFC_wnfost6B5HSW0rL2k1Pop18QXciG1OkibWmdh-uN1xmoq9LJcKonA8J2Ib6_AnuJeewKy0R1Is6oRiiot5zOqAuy57khJjA75zlfDUt7RykL87I8zaCiMXrJ9U5Y2ZdrF82WwjGvELIIIwVqbCitrsKWjo3wGj25od0M-FQn-vdh1ViEkINDj1B1oqHYRRd3xg_npzFDBDK2vGl-8wqmANYz1m2_F5aVqpWJ-hGcgNtghrNiPODjCL5GCMG-_Eg24d449N3-cEH-Kc7iE0xxLWOWurFy1VjlS1dADeDokAm6K9oXghO9dJzzltl3BK1lU4xNEKZSjVNqyRqsurnqnYttcQoLxR8UdWsbyXywS5wgMTpx3K10TVY59HSH9pHt4dSiRb2xFWbmWpCavOd5kVD-B5K0kexaCJ52a4R6r5_hTTRpp9TlZF_SSVuB2TWWjZZH9OTxn1LJwPPXlSUNV0FU94SzYUhiPKZXYtOd6iirVRSC-E9tN2Qjn1mvtLdc4optObFpIrqGqW0Tl7f2b7wQFfuWN_mN71Fd_4bDEoaCRx8P1DjyQRVtd2R_kiaB-j_rvHw_-yHjYFzmDYDaAvcz7XTHRq8Gtz2N2VW-b_-DY8x\",\"summary\":[]}" }, { "type": "text", "text": "Short version:\nI don’t rely on exact wording.\n\nI use it more like:\n- semantic recall\n- keyword recall\n- context stitching\n- then human judgment\n\nPractical flow:\n\n1. I infer the concept\n- not just your words\n- example:\n you say “that vending dashboard thing”\n I may search:\n - vending\n - OurVend\n - dashboard\n - status pages\n - machine status\n\n2. I search broad first\n- usually a few overlapping queries\n- names\n- purpose\n- outcome\n- nearby terms\n- possible old names / aliases\n\n3. I inspect candidates\n- titles\n- summaries\n- source refs\n- timestamps\n- memory type\n- whether it feels like same project,\n same decision, same episode\n\n4. I use context around a hit\n- if one memory smells right,\n I use its surrounding context\n- related memories often reveal the\n exact thing even if first hit was fuzzy\n\n5. I cross-check with files/runtime\n- memory is not blind truth\n- I often verify against repo/files/logs\n- especially if action depends on it\n\nWhat makes fuzzy recall work:\n- searchable titles\n- compact factual content\n- source refs\n- recurring domain terms\n- durable aliases/rules\n- having fewer, stronger memories\n\nWhat breaks it:\n- vague/noisy memory text\n- missing project/repo ids\n- too many near-duplicate memories\n- very local nickname with no alias saved\n\nExample:\nif you say\n“the thing where we stopped faking the\nbackend and hid unsupported stuff”\n\nI might search:\n- fake backend\n- hidden unsupported\n- vendor backed\n- real ui\n- OurVend\n\nEven if the saved title is:\n`OurVend real-ui migration finished with ads blocked hidden`\n\nSo:\nI search by meaning first,\nword match second,\nverification third.\n\nIf you want, I can also show:\n- a real example query chain I’d use\n- or how I’d improve memory format\n for better fuzzy recall.", "textSignature": "{\"v\":1,\"id\":\"msg_0d29dbf88c868f5a016a12bc55f4e08196be59d5f4c306b50d\",\"phase\":\"final_answer\"}" } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 136736, "output": 437, "cacheRead": 0, "cacheWrite": 0, "totalTokens": 137173, "cost": { "input": 0.34184000000000003, "output": 0.006555, "cacheRead": 0, "cacheWrite": 0, "total": 0.348395 } }, "stopReason": "stop", "timestamp": 1779612753596, "responseId": "resp_0d29dbf88c868f5a016a12bc53517c8196942bbf276b462549" } }, { "type": "message", "id": "ea1b1965", "parentId": "b0584b72", "timestamp": "2026-05-24T08:56:12.179Z", "message": { "role": "user", "content": [ { "type": "text", "text": "[telegram] and what about memories that should be attached but are semantically far? like perhaps a specific work behavior rule.\ndoes surrounding context hit it?" } ], "timestamp": 1779612972148 } }, { "type": "message", "id": "e7b6ddcd", "parentId": "ea1b1965", "timestamp": "2026-05-24T08:56:20.567Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12bd2d79708196844c211c9eb349a2\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABqEr0tUEJpzYtT9Pb7JMUgzKPythM8NzbGzzPIBUYrgyIB04kKh_1vH9ZW6KZf11nhhzgKiY6_dubHElnL6fItXhCsSwFg_eRTvO8H0P5ufGsMw2UMPTECxYbxgVmdn9wwiMUacTcl0KBeEi78tBYCMnC7CmJVdAooHsCVTvn0WD2nMwigUgNDC21gNAcEdNKp6GozLwyy-V-pk4JxTIKwGweT1H7SkD-sUYTa_iOetFwVle9cdUf8rbT2zNPo4YxPUoaKyT-0hcCDMJLlgzFVDe-IrRUTGejIn42NRK4-YgiaUT_CKP-oSTGskDFZukB9XqBqwybKcD8_BEdG61ryZntLEc0_9VRxFfrTb4olTqOrPBjqZWbSXm2PH8_4RJORfoTxDl9IDsHsGW2prCaO402CITDrvmXRwWOrYuvWtZVb1-JV64Izoje6DldoMQ9h9w--kbY3JsFf1tlXeY2vCgCz7tWKKY9PBcXpfSiSsX2W7lnHSG62wr4UHSMV6WElIjlbSIOxSI81FG1Ut4JIE8JuuAG4q8D9DUCujxw1hW4hl4N5GiOADyqx1vV8brRUAnFIj67H_FWTIulifriyh1ZaVTFwtuT2ceQpjumKDZWqkYj39HuBVIUSojHqQjNZ7mDD1m4V90ItyooIPBPKz3A2FOYwMoubjuKNbu0GlJR5LQHfizzNXRsxaa8vbfw8PcjZXa9vIA_PBR6wd2ZFljWy3PqidtubGruJqlE_Y0xMtvPG7dlb7-FE5a1l4qObbQXpeQUhbq9kgzPcqYR5HXshpszwy7u48_nSv4vZPc77X2UN_g5MqojHYxaaIzdSU9xaal_qlMSpBLwxR1exoi1VIpUSV6w5QsXIIzRuW888nVzhKAWJuO8hvQ6fCOWWg5AP4xNY79IWxC2ztXvL9EWanXPBxPxCSPprSMPsCHyFZAIpXPzfeEPzf9g3qDs8sCux\",\"summary\":[]}" }, { "type": "text", "text": "Yes, sometimes.\nBut that is weaker.\n\nThere are 3 ways it can still hit:\n\n1. direct profile/decision retrieval\n- if the rule is strong and durable\n- example:\n “follow-up instructions go to todo first”\n may surface from:\n - follow-up\n - task flow\n - active task\n - derailing\n\n2. context bundle around a hit\n- one matched memory can pull nearby\n profile/decision facts\n- so I hit project memory A,\n and context also shows a work rule B\n\n3. agent-side prior habit\n- some rules are loaded from\n instructions/AGENTS, not memory\n- so even if memory search misses,\n behavior can still be correct\n\nBut bluntly:\nsemantically far memories are the weak case.\n\nExample weak case:\nyou ask about RSS PDFs,\nand the relevant extra memory is\n“Sebas hates repetition.”\nThat will not reliably surface from the\nRSS query itself unless:\n- context bundle includes it\n- or I already know it from profile\n- or system instructions carry it\n\nSo surrounding context helps, but\nnot guaranteed.\n\nBest fix:\nimportant work-behavior rules should live in\none of these places:\n- AGENTS/instructions\n- profile memories with very clear wording\n- linked project decisions when specific\n\nBest memory design for this:\n- explicit titles\n- explicit scope\n- maybe repeated anchor terms\n- project/repo ids\n- not too abstract\n\nRule of thumb:\n- project facts can be fuzzy-recalled\n from project talk\n- behavior rules should be stored as\n behavior rules, not buried inside an\n episode summary\n\nSo:\nyes, context can rescue semantically far\nmemories.\nBut I would not trust it alone for\nimportant operating rules.", "textSignature": "{\"v\":1,\"id\":\"msg_0d29dbf88c868f5a016a12bd2dd45c81968c68e74560ae21ae\",\"phase\":\"final_answer\"}" } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 1008, "output": 383, "cacheRead": 136192, "cacheWrite": 0, "totalTokens": 137583, "cost": { "input": 0.00252, "output": 0.005745, "cacheRead": 0.034048, "cacheWrite": 0, "total": 0.042313 } }, "stopReason": "stop", "timestamp": 1779612972156, "responseId": "resp_0d29dbf88c868f5a016a12bd2c51008196b982c438b4b42f28" } }, { "type": "message", "id": "76cd6e8a", "parentId": "e7b6ddcd", "timestamp": "2026-05-24T08:58:42.560Z", "message": { "role": "user", "content": [ { "type": "text", "text": "[telegram] that’s an ok compromise. and if a memory is deemed as needed/helpful on every conversation, shouldn’t the highest place for it to go is AGENTS?" } ], "timestamp": 1779613122538 } }, { "type": "message", "id": "88e229f2", "parentId": "76cd6e8a", "timestamp": "2026-05-24T08:58:48.821Z", "message": { "role": "assistant", "content": [ { "type": "text", "text": "Yes.\n\nIf it matters in basically every convo,\nbest home is `AGENTS`, not memory.\n\nWhy:\n- always loaded\n- no retrieval dependency\n- no semantic miss risk\n- behavior becomes default, not recalled\n\nGood for `AGENTS`:\n- stable communication style\n- universal work rules\n- irreversible-action policy\n- default operating heuristics\n- machine/environment facts\n- always-on preferences\n\nGood for memory instead:\n- project facts\n- chosen decisions\n- reusable artifacts\n- profile prefs that matter often but\n not literally every turn\n- handoff/episode context\n\nBest hierarchy:\n1. `AGENTS`\n for near-universal rules\n2. memory\n for durable but situational facts\n3. live context\n for current-task specifics\n\nBluntly:\nif a memory must be remembered every\ntime, it is probably misfiled.\n\nMemory is better as\n“retrieve when relevant,”\nnot\n“bootstrap my core personality/rules.”\n\nSo yes —\nhighest-priority always-needed stuff\nshould graduate into `AGENTS`.", "textSignature": "{\"v\":1,\"id\":\"msg_0d29dbf88c868f5a016a12bdc4014c8196996582a1600a70ab\",\"phase\":\"final_answer\"}" } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 911, "output": 223, "cacheRead": 136704, "cacheWrite": 0, "totalTokens": 137838, "cost": { "input": 0.0022775, "output": 0.003345, "cacheRead": 0.034176, "cacheWrite": 0, "total": 0.0397985 } }, "stopReason": "stop", "timestamp": 1779613122541, "responseId": "resp_0d29dbf88c868f5a016a12bdc2b204819699c3fbf905b26996" } }, { "type": "message", "id": "c2ea1c26", "parentId": "88e229f2", "timestamp": "2026-05-24T09:05:55.030Z", "message": { "role": "user", "content": [ { "type": "text", "text": "[telegram] cool, can we add to the automatic process a check on highest signal memories? if they match this criteria send me a telegram message offering that. if i deem correct, ill ask you to move it" } ], "timestamp": 1779613555012 } }, { "type": "message", "id": "27b4fc27", "parentId": "c2ea1c26", "timestamp": "2026-05-24T09:06:08.798Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12bf75c9308196b4b8e8d094ab6e16\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABqEr94FeFx4adacCRXPRmfz6JUBydLNquecWrEMIF2bfEW74E55PORrQvVPmucg-4mQsmHCjyClklienNwSMwyAWC_zm5spRjFXG1ZuKlXwc5Ocqg2tlRY05l4XiG7_M5AXeu_Gwq1pY4m92lp1pEwRoU-V_j2lDPAlDoRR9OtTenvkgllOFqgQrpJZ9cjr6fauhsUh2URxBXRmCd9wKiFtSoSxzl3nbf28qHMH_I70IVITo2_c9u70X_nunAdFVoDPGCWIQQZNwGZ6eJN1CotN_Uzb4ELFg5GdBWiGeaxLk6nCfbOYTqLKSAd-COxjkAmGIpDx8l64j-VhdMVKli_3sQ0YmUCDpzhXT5lG3wojbzn25pXAEGVhtKKhMvTbcv7omyPsNawOoMC_DfaF2sPj6hDtEnvg41F7zARRAPboojYmNdYkLfBng_23aWp7-iamAbnL9wDOmw-qqLZArDWIcVwvJPMGycuwKRDb5Zma7HhI3Mz5Yf3MjCv5Z-CELKZEGxnQ4jx88ZqA4IOUqAf0vNXGf_ObcjoV4bzxJQtvPXgudGHhe8Zu0M7ehRIF8syZ6EG4xU1E1cKkTeQ-_EpREWr3fiMF6PZd1RgZKQsrFHqaLfwj2J3GC-3heEvREQ94DGDV4n2UxPQw1_DLlzsVnpB-rmJJ8BihUI5sg3nBiZzhipsf-a72WW5w0vKv37dmiv2f4n3idnbWkFuSLsfkn6gOnSs3GDQ1DakyQnFhoMd0CHQllf402FbqOV_8ek5V0ajBTpqzGYMxy38ORBAxAHcyLoYZ2Z1-pGdtIG0SYMvOe9i1VKGfzu4munDlbtxvAuAmW0xQkhbonielu2YTDBvhU-dOq3rTXg6Z4kqQocmamUK_8LBeRB4xkY0ua8WZ1_rUdyfU5VG15e4CgnVnhe2ipkXFB7FtpbMPoXezkV8D-9uRg0MTiJyeoY9VOv_n_vfk9GAv9gAuaskXqoAyyCeAoMqgfAF7ma8w09z8kl4nRhLpPU44lh7WRALmZCMiMKiVtQxaJPzq3yZBq5oX6e9Q32ix5-4w8_ab3neTwTKvjXGlvlsho346L2bzT3Nppe_lb4yvleLOp1BYejVPVTodHstuCtjIQT9SHukwgZWVutHy-QX2cO0qsYKv74K6s3f8dTE1FO7Gxh0TXsYo3nweSbNxEmwAGiSotCTfvvqxSOSbvbbZ22F5nfvHfWd4kO87uLKtgW779inoxupTNSObv_Bl2QgkGVmdjfKX9PiIqbd1o2twBinWLfYGOhhRGeOITRXBt5j3bwmzAIkkpYb1EMTSroindfzklqhsZJreqZLSfqhKan04-HJuJ51JtWWkPKHgxNwmzVJ8tzY_jmo-4Tj_B66GHnZ19sLJ2nw4JMUMYzldt0xYU6xEKCnBj8wGaoVFNGjpl19cAhtMOJSl-gui9HnY9-lGSloqEQhJO3kMK9Z-fJw89JHUJtrm04o68Ks6ffG1Za4reQsGx8Z-fREe3nKggVsFMOI9egsMEsGA70zUGiaT71LXf8DsfYEXZ2FQ-UixvOS8jMSe-mJZJhFINg6w-9tGQYatRkSmLE=\",\"summary\":[]}" }, { "type": "text", "text": "Yes.\n\nGood idea.\nClean pattern:\n\nFlow\n1. session-end analyzer scores new memories\n2. if memory looks:\n - high-signal\n - durable\n - cross-conversation\n - behaviorally universal\n3. send Telegram nudge:\n - “This may belong in AGENTS:\n ``”\n4. you reply yes/no\n5. if yes, I convert it into an\n AGENTS patch proposal\n6. only then apply it\n\nWhy this is good\n- keeps AGENTS clean\n- adds human approval\n- avoids silent rule creep\n- uses memory as staging area for\n possible promotion\n\nBest heuristic for “AGENTS candidate”\n- type is `profile` or `decision`\n- scope is broad/global\n- wording implies default behavior\n- likely useful in most sessions\n- not project-specific\n- not ephemeral\n- not secret\n- not redundant with current AGENTS\n\nTelegram format should be tiny\nExample:\n- `Possible AGENTS promotion:`\n- `User wants minimal repetition`\n- `Reason: global behavior rule`\n- `Reply: promote if yes`\n\nImportant guardrail\nDo not auto-edit AGENTS.\nOnly suggest.\n\nI can implement this.\nBest place:\n- session-end memory analyzer /\n maintenance automation\n- plus a small dedup check against\n existing AGENTS content so it\n doesn’t spam obvious duplicates\n\nIf you want, I’ll wire it now.", "textSignature": "{\"v\":1,\"id\":\"msg_0d29dbf88c868f5a016a12bf783dc081968877747dc0fe8176\",\"phase\":\"final_answer\"}" } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 671, "output": 402, "cacheRead": 137216, "cacheWrite": 0, "totalTokens": 138289, "cost": { "input": 0.0016775000000000002, "output": 0.00603, "cacheRead": 0.034304, "cacheWrite": 0, "total": 0.0420115 } }, "stopReason": "stop", "timestamp": 1779613555015, "responseId": "resp_0d29dbf88c868f5a016a12bf748228819680a21e062701a96e" } }, { "type": "message", "id": "d8e88681", "parentId": "27b4fc27", "timestamp": "2026-05-24T09:07:50.154Z", "message": { "role": "user", "content": [ { "type": "text", "text": "[telegram] session end process can sometimes not be hit for a while (like now that i used only telegram for the last two weeks)\nis there not another periodic process set up?" } ], "timestamp": 1779613670130 } }, { "type": "message", "id": "87288290", "parentId": "d8e88681", "timestamp": "2026-05-24T09:08:00.136Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "**Inspecting service status**\n\nI need to provide an answer based on the known information available. I’m thinking I should check the current service status for clarity. It’s important that my response is concise and easy to understand, so I’ll look at the details closely. There’s a lot to consider, but staying focused on the essential information will help ensure the user gets the answer they need quickly.", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12bfe96f148196b22eb4051014a1ed\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABqEr_v5fp0xPN9F0jybXbpZA9ReRC6LP_wHf-oFEBgZ2eha4WUMn0kkLCrtHTvpk2KFewUN1G6NpuN1RT3IdzzOmqI3acVxfujGT1T9tpQLp9uc25ZyQLbNHeBAEkmZiiWeVNkAHL1UEwYH23UMLqt8UYnIb8N2nLzXpF-XXq6G99BOzo3AIDRB4mYeY7vRxVNYNSqPLpDWDA2UWFjdCspNJd2up1d8AmCTybDNvtaZfd84l45s_y_BJMKG5xCzT-F0vO_qM0x7cYlrRDt0ZOpByeEdDA6CEdb1oB--BLqbTzIIfn-oScQBIZFTHN2z8YRokgwkgoSRLYnzZON74N4WrFIpPNUBFAwi5vvbRYQ6IXyJJVCi6fDbrM3GPtQTJi26PGSbHsvbhky0_9E0zAt5v2EdxLAWrhMZcKC8gMxCQ85RU_B4Czx42XMP0zyymqD5mEZTGONK3gtR6imHs53Rw6R5GsjI_P_8eAg1Y85jbCMnp3AHxOchztAuikzW5ljJ38_Fc8VqCOAN_dTYV9d5RIDep14tXv44AuParp-wOge5IQD-eCSjD0wSpatCULtAYaqvu691uaFABMYifD3KupPrliO6jwnzG-VdCn6DM-1tARcBYhqD7jaf23OlHONxX0ThmyI_SitWMNpC8wVnyTUrl5TLFY_Kwh5FVy-YnAs9qJLVruMDaz7uOEA1Zv4xKdfqvOgvboLiDXqQePdlSVX9zWOSRx_-MuVfMIxJJgP4w9FzRYgOe4p8JY0oZ0MqR6OMoiIzR_ctjelolDQEkwERDQgAJXvCrJlOq8Jm5evqLmLvpNWnwBSJ7eW43m8wL1nUPjhDURxaYWRcK0W4G8cuuhJxvQa25_mLRO_a8g4l-hd0qdACYnxIvKGVOGAQZP4pWCV0zAGOrB0d4Esn1_YWq_OnwHa-T4ewAMwVTy5wTrRbp7I2KhkG8oVWkbYRyU9taVptKBe17ATXbDO4LUaaMd_VtOBzR7R8hQ4kxNyOX9j78uPsZTTqA7k8l8HXvi1\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Inspecting service status**\\n\\nI need to provide an answer based on the known information available. I’m thinking I should check the current service status for clarity. It’s important that my response is concise and easy to understand, so I’ll look at the details closely. There’s a lot to consider, but staying focused on the essential information will help ensure the user gets the answer they need quickly.\"}]}" }, { "type": "toolCall", "id": "call_5PHZfwVD58XkBMmywltKiRkQ|fc_0d29dbf88c868f5a016a12bfefda18819690192859efdbb121", "name": "bash", "arguments": { "command": "systemctl --user list-timers --all | rg -i 'memory|agent|maint|session|analy' || true", "timeout": 20 } }, { "type": "toolCall", "id": "call_OsKbzg9bjZLD0qlQe0zRNkZM|fc_0d29dbf88c868f5a016a12bfefda448196978f3aa5dd04f596", "name": "bash", "arguments": { "command": "systemctl --user list-units --all | rg -i 'memory|agent|maint|session|analy' || true", "timeout": 20 } }, { "type": "toolCall", "id": "call_DS4gWBsvS5YvDBvh71664Lka|fc_0d29dbf88c868f5a016a12bfefda508196887177fd51bd12a6", "name": "bash", "arguments": { "command": "python3 - <<'PY'\nimport requests\nfor path in ['/api/status']:\n r=requests.get('http://100.116.176.16:8091'+path, timeout=10)\n print(r.text)\nPY", "timeout": 20 } } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 503, "output": 198, "cacheRead": 137728, "cacheWrite": 0, "totalTokens": 138429, "cost": { "input": 0.0012575000000000002, "output": 0.00297, "cacheRead": 0.034432, "cacheWrite": 0, "total": 0.0386595 } }, "stopReason": "toolUse", "timestamp": 1779613670134, "responseId": "resp_0d29dbf88c868f5a016a12bfe6658c8196b9ee31183f660485" } }, { "type": "message", "id": "3e5ab99d", "parentId": "bc389aae", "timestamp": "2026-05-24T09:08:08.110Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "**Evaluating service processes**\n\nI’m considering whether there’s a periodic maintenance process, like a daemon or session dispatcher. However, it doesn’t seem to be yielding any results. It’s odd because I don’t see any visible timer, but the services appear to be active. I wonder if there’s something else I need to check or if it’s a misunderstanding of how these components are supposed to function. Let’s see if I can find more clarity on this!", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12bff211388196a6592b3b41cdb1cf\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABqEr_22TRvLtTRD48XePdEHplcVEiArLYkd619SSpxqpAXwJscTejIMpd6-0PfKyto4HtdAkb_ByBZUWdU8HaFD7OJN7tkZFcji3yU-Jiu6n8gJDWHZ8Az5-PW41pyMIuFlLQC0ff9akUsx0p4z3BjKjfeEoWcNb98VFEozFA-1mzn05Ft4M0-UKnR0UGQMXpQUtIT8Ukhb90tCDHOoncgfztBCrC05tL5hO2pp-r7qpqZxUIkGPyFsSd1RF56bUpdwI4t58_BCGFhIZykPxxji4xcqdCPpOHGpOffGc9maoytM8QBjXxuRehRp_kQcISq_OwfWQWbShqs6DYObuQs2pCCTvrByOvzCJ-OZ44fXMljVsoZJWtKFvHaX6nNLpj2R3GkSSQ6I9XKFpCCfW2SfzjoBGrMLzN0aUQpKMlYEiQWYDz4vJABH0r2yAgef-0HjONc2wknaHolNiXuFeLDBelCMq6NxUz7maC6d7fXXwNPJ85aEClOSN6jnYOp7TkOMxQdDaUla1AsI66AArn8VFQio6rBAeaZnZdzNrqPr279aOgDC7sSVbTsxSAIMwG8Edik0UPNOp0EBkQCUX0XQ8ecbyztLpB6gavb1MYBZ9ZCMNzwrd5X9E5IeSq1sTr8vDShOh5YdQjxgQEgjN2l8HzqKjGZdrXIY4l-dXyMu3fE3jPp53BLr1rTxzRzggY6JcbbHqKBTTPfTk1Ivvm-uv9s7x_m5u7wtGlmfRpscIFW-65k7s6i1D_ADfLlMD7nZ6QUFlGo4L0AzFIHxZ85gEMgjMTtyeJc8Pgm5SwKNMIJxHZz6Jq9d3W1NXa5UTiHO4Sh5nTWDwGk7-aAhTWiMTfGr4LXyt-q8M6l0OxQFFAGuXaBwqL48XgrlA0kB8t1hYqXjRplIOw6t5VxRbrZqb4ReW8QZaLxawppws2YhmapBVboJ0ETAyt7yleQHrob5UULpS_ltYsE4vccTUzEt-XoxVF_LuTpjQCQVzj1-oQlzyx_7itTRFpk9LZ3211E8AMkX5s27T8RydMRbgrmvjC6YQb_6x6pNqcRWlV3F9svMDHEay5wPkXKB8uSFQuFgsTTuaG39mgGCaoxV3DiYQriewyFQL0E54aGQWpPtdc_R8A=\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Evaluating service processes**\\n\\nI’m considering whether there’s a periodic maintenance process, like a daemon or session dispatcher. However, it doesn’t seem to be yielding any results. It’s odd because I don’t see any visible timer, but the services appear to be active. I wonder if there’s something else I need to check or if it’s a misunderstanding of how these components are supposed to function. Let’s see if I can find more clarity on this!\"}]}" }, { "type": "text", "text": "Yes.\nThere is other automation.\n\nWhat I see active:\n- `install-session-memory-dispatcher.service`\n- `agents-database-maintenance.service`\n\nSo it’s not only “on session end”.\n\nBut:\n- I do **not** see a user timer listed for it\n- and in practice, last 14 days showed\n no analyzer-written memories\n\nSo likely one of these is true:\n1. dispatcher is event-driven, not periodic\n2. periodic path exists inside daemon logic,\n not as a systemd timer\n3. it’s running, but not picking up Telegram\n sessions\n4. it’s running, but filtering/writing nothing\n\nBlunt read:\nthere is automation alive,\nbut not a reliable periodic\n“sweep recent sessions and write\nmemories” flow for your Telegram-only\nusage pattern.\n\nThat gap is real.\n\nBest fix:\nadd a true periodic sweeper:\n- every X hours\n- scan recent session files\n- detect unanalyzed sessions\n- run cheap memory extraction\n- optionally send AGENTS-promotion\n suggestions by Telegram\n\nThat would cover:\n- long Telegram-only stretches\n- missed session-end hooks\n- delayed memory promotion\n\nIf you want, I can inspect the two active\nservices and tell you exactly:\n- what each one does\n- whether they already scan periodically\n- where the break is.", "textSignature": "{\"v\":1,\"id\":\"msg_0d29dbf88c868f5a016a12bff6177081968d00ccd1d40c80de\",\"phase\":\"final_answer\"}" } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 9460, "output": 317, "cacheRead": 137728, "cacheWrite": 0, "totalTokens": 147505, "cost": { "input": 0.02365, "output": 0.0047550000000000005, "cacheRead": 0.034432, "cacheWrite": 0, "total": 0.062837 } }, "stopReason": "stop", "timestamp": 1779613680434, "responseId": "resp_0d29dbf88c868f5a016a12bff0950081969e705cbb1f68b858" } }, { "type": "message", "id": "4780de6b", "parentId": "3e5ab99d", "timestamp": "2026-05-24T09:09:11.786Z", "message": { "role": "user", "content": [ { "type": "text", "text": "[telegram] then how were memories upgraded lately? or they werent?" } ], "timestamp": 1779613751762 } }, { "type": "message", "id": "a356f822", "parentId": "4780de6b", "timestamp": "2026-05-24T09:09:17.000Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12c0392ca481968cd7e2c857f4193a\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABqEsA5PenWtHYY7YIik3MvHSTCozyakbMi26A2vNv9CfjzBOQXUU9QiZoZu50rNxcns2yPdWxnAwhcOoTsEpI8sSzCVr7u1OrBPVNp32smdzoRvtQeqXdN1H6D4EPEYgCT8Q7DAerdU6Ij8RytRyDLk3pjJJD-zwXCXJ7e5rjQXcBgMODRDZqa7VhdDlb9ysA8v1GSFwKiJ7aTOWWgWkiX9xxEP9uyW3CFmVVEwNe_uiRwLetgo6b9O5W5s-bE2cSJk6yqkKS3jOsZXXlgKJrzqDVrYQcpwHX1GwoXNWY8bTSsOq35T8kVpQN_0f-IzN6_O5btqDOTUMO9a3-Ps7SBiE18iD_BsgsQYvPc66cG4nimwKQpHBd7J6Z93lXoOUEgKI9xE5OFNOJUYoIdLLb6c6Dn2Kqi0C6ZppnjHG6nj_bvsDGDxOtiy1eYAW0o6E4qrlsH-IXdecUIZe2efpMQ9m3uzaiotw0-sDJwbq8f-iMC5cT7G6M9WTSYmbvALi1e-L2Woyf5EEYDIT-1jw1uuGt51OsDpp3kC0fZ6wgrUCf3Ju7OWeNfeQQpSikX-IhenGAzN8KTWnZXPsT711PpMs956Tw4GEjANmqABG2QTWBodFLDAMOFy29L7CnV-c0zVvCG0K4A9ADe_8CFLCRO7wt0TrsLChH1OngcmPkunGHJKPhR0pEJjLSBf0mCmMi4GmIQVZpTg2XeiYeE1B1l3Gajxiftfr4NlMv8vGOgLmoxYujVFOoKWL3Ec6Hqp-Yy6Uc8inYSuu2j9ZDMDjI8UeiccxK_pdlVd_nzyQKfcCHgALpVLpT_CK_l1ILi_wtKq7Dw_wln1ZMomOeLEU0KydD5M6zbicqlkuc33PCBwETfvZ3w-kmMWavv8_bjih-82tuW4UsSSTL3P9LpEY6EEy2nl5LIgXrVW9fubXyjFZhbDzDaVXD3Z8E49vSRfWtW-E2h\",\"summary\":[]}" }, { "type": "text", "text": "Mostly they weren’t.\n\nLast 2 weeks:\n- only 3 memories got created\n- all 3 were manual writes by\n `personal-agent`\n- 0 were from the session analyzer\n- 0 obvious auto-upgrades/promotions\n\nSo recent “upgrades” happened only because:\n- I manually checked memory\n- then manually wrote/promoted a few\n\nNot because the automatic pipeline was\nquietly doing it well.\n\nBroader last month:\n- some auto writes did happen earlier\n- mainly from `pi-session-memory-analyzer`\n- but not in this Telegram-heavy stretch\n\nSo blunt answer:\n- lately, automatic upgrading mostly did\n **not** happen\n- recent improvement came from manual\n intervention, not healthy automation\n\nThat’s why your periodic-sweeper idea is\nuseful.", "textSignature": "{\"v\":1,\"id\":\"msg_0d29dbf88c868f5a016a12c0398f8c81969377a3757c43b7fc\",\"phase\":\"final_answer\"}" } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 9742, "output": 183, "cacheRead": 137728, "cacheWrite": 0, "totalTokens": 147653, "cost": { "input": 0.024355, "output": 0.002745, "cacheRead": 0.034432, "cacheWrite": 0, "total": 0.061532 } }, "stopReason": "stop", "timestamp": 1779613751765, "responseId": "resp_0d29dbf88c868f5a016a12c037f0ac819686610e02567974c1" } }, { "type": "message", "id": "59cb0f3c", "parentId": "a356f822", "timestamp": "2026-05-24T09:10:58.316Z", "message": { "role": "user", "content": [ { "type": "text", "text": "[telegram] dont care how but simplify and automate this process. seems like it has many ways to work and some deprecated even\n\nadd later the AGENT promotion suggestion we discussed" } ], "timestamp": 1779613858293 } }, { "type": "message", "id": "04701821", "parentId": "59cb0f3c", "timestamp": "2026-05-24T09:11:04.195Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "**Evaluating repo actions**\n\nI need to act on the pi-config/agents-database repository. First, I'll inspect the documents and services associated with it. I think I should create a to-do for follow-up instructions since there are active tasks to tackle. Modifying the config and scripts is likely necessary, so I’ll take a closer look at the relevant services. I’ll also consider memory aspects, but I'll focus primarily on what's essential for the task at hand.", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12c0a4204c81969290fcdcd21aba37\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABqEsCnRl2Zg5tOtacmZyDvDeLi1oGxfZnf-4Te6uceoBaTgCKac6noeILbtYx9voDX5oEKIHXkvB2W-2EuxOBADxOipOEPVHveUxh7uwmZBDPgZttQLf1lR6OFqk0F4kYxCmBHN19rT9CfqYv5bgvQ3cDpd2cbFPwY3AJvptg_BStdRb3Dzlef9AqZgxLxRzzFEjE7wQpCeA2O9gauoPi_92vLaXR9aaHb0HYN-YPQcO5wEKHE9bd3bFgmKMGWNqxktfJuOR1CGk0fsV-Pcf3ntd5e66bv7_CnuhujVEYPDoDNQ2eDgQScHwqYzdT2ZrQ6V3JxuYx06YRltPJEqE8A_hWDPerjXHxIMRW7SU-rKuTWNfy0hWnfSUZD9yJi8UBVYDyPnwDCPjrv6IMC5d7Numa8XZa3LbTYVUh38xxHjcIfXL0OWuPUxZNhhAjZ3GizrAUoZJyS9PzU6vfE2F4-dgQ7CcjTRj0nB7rr0WMKO3LDUP2FX8BF-LYHbQ4BCe_RvyqTFDkwQSfHWWQd2gM_xV4bLU_Vq2gRjXDRaJe8sAgRiCRdgYfxcLE5A7vvuDjK5U7dtOrOSnITl_7luRd9hxGq7U2dcH7AMO68ICmuYG7Sg9Vs09MzCMcgL1in9RLps5i-8YQMtR9YrdQhGt4YgEfCXljUIiBJZ8uFOVog-pPMW6Tl3lYw8MYNWhOqND4MGpmJPUkKGtRIak_AqOtdql3X7Zvq5tuqR9BHmM79EpcifvSj8z-PIr_Mq9FJBGoKC4pmpKlG2P0tZF_1TR0LmAImsmRc4C4OlxmHLxgpZzqqHPCL7WIz7kZCIG9iqfK8ukZgdaWgwMT3KfD-gG47FE5PR7ZFQS9J84P9e-XyE1BlOB53Nm2iBN-W2HtCTNI2Q9rt6PiJBJttAqIW_VmZxAz1Bh_eyBl2KOaAIDZZxErfg8tp1XmyYAe8rZGKb2kGoqSGT9PrYrV3JkIN3_JEFPCcp-aXvigXwdAZ3FgmoFuBnrK8-8tf9mvFYlgg6DrP-3F3lzhH5hNydGspIFGjYLri3_MsD3jsn2JYdS8FH54DX0PP3Ed2XFjp8k0SH-l_14NHfxRxexRvAj8Vu9DaJ-Hfz1US3-dOMkFnDqJpVXYy6SloobG2-X_iBkO2ihQO8o0y75syM_RzNk8O-BxiqelByOWFhMGwN_eT5FKQKVJmw7qeLOf3WkkHPnx_sa6Dh3rp6uLMczUWDlP8UvVAJ9jx28FpDBL604MM3w0CUdoP188N30Ejn3KeeveQBEA2M2Fd\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Evaluating repo actions**\\n\\nI need to act on the pi-config/agents-database repository. First, I'll inspect the documents and services associated with it. I think I should create a to-do for follow-up instructions since there are active tasks to tackle. Modifying the config and scripts is likely necessary, so I’ll take a closer look at the relevant services. I’ll also consider memory aspects, but I'll focus primarily on what's essential for the task at hand.\"}]}" }, { "type": "toolCall", "id": "call_WiJoudd7sHg4V8BHBOrofO8f|fc_0d29dbf88c868f5a016a12c0a7ad28819687e7f6f57bb3e78f", "name": "todo", "arguments": { "action": "create", "subject": "Simplify and automate memory ingestion pipeline", "description": "Audit current memory/session-end automation paths, remove or bypass deprecated/duplicated flows, implement one reliable automated path that covers Telegram-heavy usage, and leave AGENTS-promotion suggestion as a later follow-up.", "activeForm": "simplifying memory automation", "status": "in_progress" } } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 738, "output": 141, "cacheRead": 146944, "cacheWrite": 0, "totalTokens": 147823, "cost": { "input": 0.001845, "output": 0.002115, "cacheRead": 0.036736, "cacheWrite": 0, "total": 0.040695999999999996 } }, "stopReason": "toolUse", 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{ "role": "assistant", "content": [ { "type": "toolCall", "id": "call_ypa1WaDjny8KYImlzoC6zUAU|fc_0d29dbf88c868f5a016a12c0b1a9148196bbbd23bd4a81bad4", "name": "bash", "arguments": { "command": "cd /home/sebas && find .config/systemd/user -maxdepth 1 -type f | sort && echo '---' && rg -n \"session-memory|memory|dispatcher|maintenance|analy\" /home/sebas/.config/systemd/user /home/sebas/pi-config /home/sebas/agents-database -S --glob '!**/node_modules/**' --glob '!**/.git/**' | head -300", "timeout": 30 } }, { "type": "toolCall", "id": "call_UyxQEvcaJBBwO5b3pt2ZT181|fc_0d29dbf88c868f5a016a12c0b1a9288196b8b08cb9a326fd64", "name": "bash", "arguments": { "command": "systemctl --user cat install-session-memory-dispatcher.service agents-database-maintenance.service 2>/dev/null", "timeout": 20 } }, { "type": "toolCall", "id": "call_NxixTPAPxPO6QRcj7JIsxYSL|fc_0d29dbf88c868f5a016a12c0b1a9348196872adad121ce4909", "name": "bash", "arguments": { "command": "ls -R /home/sebas/pi-config/bin /home/sebas/pi-config/scripts 2>/dev/null | rg 'memory|session|dispatcher|analy|maint'", "timeout": 20 } } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 436, "output": 220, "cacheRead": 147456, "cacheWrite": 0, "totalTokens": 148112, "cost": { "input": 0.00109, "output": 0.0033, "cacheRead": 0.036864, "cacheWrite": 0, "total": 0.041254 } }, "stopReason": "toolUse", "timestamp": 1779613868142, "responseId": "resp_0d29dbf88c868f5a016a12c0ac4ab08196b92a07f7484434d3" } }, { "type": "message", "id": "a085278c", "parentId": "a69d03dc", "timestamp": "2026-05-24T09:11:18.115Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12c0b36dec8196b6892fcc43ab32fa\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABqEsC14L9ix8crbZG9Rx7U_r01wsmQnpTFmojVQkXE1AqIMb9DmNC6awqNFJjz-CN77VE6uurjTIzr_WXxxQjyKEm3FHSxV45cRSZSlpVHsECY22_dBoBDx012z_WaVP4Yx7t-YqqlHvVdFHG1ASNf2GepItUXEB_GMTdUBYwpRLLWaoGdutB2_oQ8P67x_aQOh_mlg06RvqeELDcrjXLdDDN9FwXRnhD6rVg_tZ-Vp_UgkC9dPja-Pn-LGFESJpgJ3OlPEVSakVWQTv2WCqmsKsyAyetNiDg9JnbGsRddPOx4X7hX64HLs6AVlnvuHC4tLFvfNTAZD6Q2mgrD2cym3E-SOnvMs0sv6pnohrrMOfmloVVPE04ksbgBGQtBDtb1hK5RJr2cF8mXZNqWnWAAUIs6NnO65PhpqLnAInkwvOrOVWdtnmA_T4wo3EdJQntZJCRStnu013pPNEOVleOZqEeEdQXkOpqh4zoKVLP9376xykl1FH-_2GohgM_3GbLXajNtMT1iLjcfFQtaCSc1DLPrZxl45lHdO04rWEqdHam5IKNqhmRXMWCaSYhbsWsoSBzxDB2veRLHM5ksKO9oVqYugtQOFLY_CSdbH83D_oJXLhbVyx9Z2Sf3oFkxAc2E1gKsRAW5lRZxyJXhzLP2Hf9UKxZ0mg8p5NsOTVXSDXwcUcMUISUp6rlttggvv78QEqqAFKDDdK6X2KX015Ua9-_WBYmsJqyviI2QZynf9oyRMxq4fe-X53ytx9vwMnrz8eVVv7tcKywfsPhAASBl_RzpSwps9aC9ni1_JW9B3f5X2Gf4jiO6RA9UpI1WR1NlLURL1oMdOWGlIbFJzxT5QfDDkc7Ctjmwp3zL8RdP00PCLPFDo-aP91emjI5vySqlbHuolI4YwFWBTir6SYyE9TufFANYdl0EjlNJdPUdS-vGQTWvIIdqHJnM36yTI5dkrhwH\",\"summary\":[]}" }, { "type": "toolCall", "id": "call_ZmVhn9AV05hgfEiWwHHGp8Ri|fc_0d29dbf88c868f5a016a12c0b5cec0819699e51732eed2f44c", "name": "read", "arguments": { "path": "/home/sebas/pi-config/scripts/session-memory-dispatcher.py", "offset": 1, "limit": 260 } }, { "type": "toolCall", "id": "call_igBqD2t6HLenm2fQJyQUSvGZ|fc_0d29dbf88c868f5a016a12c0b5d2f481968105c71766215409", "name": "read", "arguments": { "path": "/home/sebas/pi-config/scripts/session-memory-analyzer.py", "offset": 1, "limit": 320 } }, { "type": "toolCall", "id": "call_PEGs67LdULdWeJcySsb9XGkc|fc_0d29dbf88c868f5a016a12c0b5d3008196a5d2503453ec27ca", "name": "read", "arguments": { "path": "/home/sebas/pi-config/extensions/session-memory-dispatcher.ts", "offset": 1, "limit": 260 } } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 10298, "output": 128, "cacheRead": 147456, "cacheWrite": 0, "totalTokens": 157882, "cost": { "input": 0.025745, "output": 0.00192, "cacheRead": 0.036864, "cacheWrite": 0, "total": 0.064529 } }, "stopReason": "toolUse", "timestamp": 1779613874174, "responseId": "resp_0d29dbf88c868f5a016a12c0b256bc81968462b2a51e8ea182" } }, { "type": "message", "id": "0a143394", "parentId": "dcec37b8", "timestamp": "2026-05-24T09:11:26.013Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "**Simplifying design possibilities**\n\nI need to simplify the design. Maybe I could create a periodic sweeper script to replace the prompt and dispatcher functions. I should inspect the job directory for this. A periodic scan using a cron job or service with a state file could analyze recent sessions directly. I could leave the dispatcher for manual hooks while unifying the analyzer logic to be reusable by the sweeper. It might also help to build metadata from the session file and queue unanalyzed recent sessions.", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12c0b74044819681f306ce18b5dc44\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABqEsC9L7MX2koDtD6U53i8yMlg_YRNsdO5xm7xQ2N8ouqVqvny7-GkiDf4nsnW-nuAWekaoW7N6r7ImIEK-RA93xOpw46lXbCxhipA0ydm8h7koJvn17FvmAYyJV_cTj1ipo57oRCelCOMhGpqhRsmpSXDMR_V5CIyDsGZvZePPe3sydpaxz74I_fbgZXNEitb0_Q9J69l0rvHf6c8otNahth8KWEbC5RQa71pmktGU6woG1YBdDwNSVK04Rf4HQsYKwZIs4zEYGtvzbrVp5SXGyHuTAPUFf5QWRbXjE1HZHmecVQxJRQHTKZDuM9XOjAXza9pD1a8Sx-cwMvlTmIECbhiZtD-5V8SliN0uS1ND0ZNCGLl-aogf6L_LAghArKUJS1JoZ3gzDxEmh9pEjTwZc-udCgNltakzaVREuyl2H_j6qrUikarJLGgPBWakhfOEOGD6-tnUwg7auCmn_is7TGSmL9BtW1I21lAo0AZI4Uum-vwnXCj7udenywX3AwNWFzgdDy-2qonofPx31B57KH3wwxovVDw7OK2HYxEPnm1XqWmrwOH8WAcLRl_e6BPV0_uMksoPwmMQernFtQNZP-rnuYk-k1s2i9_Z5pPnJfeMsAaJKd2N9Vvuee0a9h1EnCmtJc6BdVQwgx9-5uwRVAkkJRyLWk79ZhvjERCgMXLnKGN8_g0H2o5tVtPLWM2U1KMB1k1xhzrDWSx3BcwcYf-I5b1_2nonI6J8sbTr8wpAZ90ggGL0479dlgjFk2aLZHGdjWeAeQU0Buzk1AplzuTgCjAy78WfAWhkHeGTUZCDWqdpjoRLfnNB1u_x4iJ5fGcTMAvyTdsTh3BBu2px3dabcr983PWBMqHeOQBKcHnz489xN-VEGVvCnudt0kgXTdh8SL0tKTfBnOndG4niOYDvLu7gpcc97sUF3e1_xR1O8wc74S8OPqJhCEu11ANSVh9Nd8-2XYkdtFlt_mwH__IqrpXgCQkhgp2tAK5Q3_sR3fz4I9vuh9arIAV0yeFb2wAiLNYFSq7XufQrRrOigF6Q_jWWc-VXMThACc-9YYiV8Z59hFAPPkFvpnlnrIRQrWRv6-RP8titKwbYw4JDvnOAHO4ZzWpqtacPPTEUvWQidbCyF5Cgeiavdikq8Fe81GUgHChggda5yzpIQ4-acLKX2v0sVnvsiWAaWMf0x2tuwSKDveKH2wPBUzU_3K_2JMFH4bvAQ3Pfe150pV86Ur-qagDCSk0mX00N5_IOWQttBtEeDWMdm87U3QslPbpdiOIFjzR1bDIMEVHgPvB6DAMCVAVY9h-2Y9syl77eqz8Ut2QvCU8EYBzglFbAWDWmCUn9LXbV0I-B5t6MFt4R0SRy6N3jNKAtaZhwm2Qq4XevDCPddiUN3tPMxR_WLftx7Mj1g2Zxa2PV2yaQ-Ud72A6axrpAAOGCSzazce6vaWfUisvVgtGaEo5QoaJLMEva3ocJykQr5N-0CiLS7WuRSc0YATydHSjTsRCX0hqJpM4_7Av_SGoUYTVVLBF8WNNLW5C9gEHocqObAJXnzOVuxmuvAsuj33JksUGEWQ3xLmlE2I=\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Simplifying design possibilities**\\n\\nI need to simplify the design. Maybe I could create a periodic sweeper script to replace the prompt and dispatcher functions. I should inspect the job directory for this. A periodic scan using a cron job or service with a state file could analyze recent sessions directly. I could leave the dispatcher for manual hooks while unifying the analyzer logic to be reusable by the sweeper. It might also help to build metadata from the session file and queue unanalyzed recent sessions.\"}]}" }, { "type": "toolCall", "id": "call_eZJjps6JAFcwd6SCO1Go3yXr|fc_0d29dbf88c868f5a016a12c0bdbbe08196a6b9cd14f5cc796a", "name": "bash", "arguments": { "command": "cd /home/sebas/pi-config && rg -n \"session_file|last_user_text|branch\" scripts extensions -S | head -200", "timeout": 20 } }, { "type": "toolCall", "id": "call_kCxqEz6cZlnaMtKMYWjekRRr|fc_0d29dbf88c868f5a016a12c0bdbbf08196a6bf6af5f002417d", "name": "bash", "arguments": { "command": "cd /home/sebas/pi-config && find sessions -type f -name '*.jsonl' | tail -5 && echo 'jobs:' && ls sessions/session-memory-jobs 2>/dev/null | tail -10", "timeout": 20 } }, { "type": "toolCall", "id": "call_NX0Q6zNN0R5fZ7K3YE3mxhjr|fc_0d29dbf88c868f5a016a12c0bdbbfc81969c731559299792c4", "name": "bash", "arguments": { "command": "python3 - <<'PY'\nimport json, pathlib\njobs=sorted(pathlib.Path('/home/sebas/pi-config/sessions/session-memory-jobs').glob('*.json'))\nprint('jobs', len(jobs))\nfor p in jobs[-5:]:\n d=json.loads(p.read_text())\n print(p.name, d.get('status'), d.get('payload',{}).get('session_file'), d.get('analysis',{}).get('status'), d.get('analysis',{}).get('saved_count'))\nPY", "timeout": 20 } } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 5361, "output": 349, "cacheRead": 157184, "cacheWrite": 0, "totalTokens": 162894, "cost": { "input": 0.013402500000000001, "output": 0.005235, "cacheRead": 0.039296, "cacheWrite": 0, "total": 0.0579335 } }, "stopReason": "toolUse", "timestamp": 1779613878214, "responseId": "resp_0d29dbf88c868f5a016a12c0b65c4c8196ab050f315d6cd5fa" } }, { "type": "message", "id": "fa3edd29", "parentId": "a4dedc1e", "timestamp": "2026-05-24T09:11:30.386Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "**Inspecting job failures**\n\nI’m thinking about the failed jobs and I believe I need to check the logs to understand what went wrong. Maybe there's an issue with the PI binary? I'll start by reviewing the recent failed logs to gather more information. I want to make sure I understand the errors so I can find a solution. Let's take a closer look and see what specifics pop up—it could lead me to the root cause!", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12c0bf3e8c8196b6d1ba22b25b664c\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABqEsDC2P3lYR_XOR2BU9eDQCoerTLbcZuB9t8w6zKfUI-rEpSi7TqYtrRdw-c5Mh-LJ1cQDG8LPAASmyq_h8jFvVx6H7Aak73Qn0WieQtTvYntBSqQNqqMKX5OBD1tOsERsNHoX8jP72PcWwrsPvNLyziyoMP8PdnlSi43hFDSkC1p9CtvEyv6ZuXmtwnCwiP2u-Zf1KaJi-PpNgxcHZaaRJDCd7jQg-Ve7gtCnYI5XAEqAmrXNEuGxjfNckZYnyxi1k-FHnNAu7eNzv3JPP2c3VKhArUpVGKEYAKw8Gr8AXLNjXI3IkOmxlhR53Lc1ibD667XxRKWQ035E1lgWDCjonwc7UacF-lJgEmN0h4zHbOfPVEE1dKYVvWagTav17yw5FT01Qr7IfJlZx8fgATW_rb_h8j8nK-CEm5pW8LaKpcddrEh_kIypBeAkIByLI0EEdgIC9HOtCykRzInpAddOuguenb-tnrd1N5feDtt4Kgrn2xg88A6FkSR-Bha0Y-9VmBI-5dUXVPkPC--dUDzmOM9zJKZsDxBJgpjc31fjd6Ilm8BztOALHf7cO6NdQd4iiC3pM_ka4mEeUMUuwRxEkIzbPWqj5X2_wIkGmH8srA_6nUr6855DcliJKLESIMQbXd_jlvuCJ2SLxPdTiTpBf5dk-cJkNDdMUHSjMK_CCCXu7gU-gL-bG6m-ClfLoOYwfL8BhLJc6b7mgdC3llExDFKfp-MTHLnfBHo23_N71rWBVhwNoHyaoTN_xAY-KRV1XByfyKGLfmPOXz5f9Yh7r78gqdUpc8lDhRABOJ9KOz_nqfXjzkEgwL0bGbK548q6lUg3Wo6-avMnY613MeX_0uE3Hue5j3WEmTgux2L_4dxSW6z9h4DllN16SWuhmWdv9AQLF9_Gp3cr4PchWGAVWtVvbvTC4eXFLfWi5d_rivObzal_TVmRXjELUD2lKgxsKfYY3AXQImaOgzpVnSHVDABAfZaHdkjnDGwETP-o5GDKseREOWKhNSqJgT8EwhFTM_V4igCxrGxVZ926FmY_Oq41A==\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Inspecting job failures**\\n\\nI’m thinking about the failed jobs and I believe I need to check the logs to understand what went wrong. Maybe there's an issue with the PI binary? I'll start by reviewing the recent failed logs to gather more information. I want to make sure I understand the errors so I can find a solution. Let's take a closer look and see what specifics pop up—it could lead me to the root cause!\"}]}" }, { "type": "toolCall", "id": "call_FL5M9jZ7eYSETEnFe2zNZS3v|fc_0d29dbf88c868f5a016a12c0c21c64819696bf39e66bf78147", "name": "read", "arguments": { "path": "/home/sebas/pi-config/sessions/session-memory-jobs/20260507T202641961301Z.json" } }, { "type": "toolCall", "id": "call_nha3eOG3WJQVpnE25uN1aCQN|fc_0d29dbf88c868f5a016a12c0c21c748196a909327778980d64", "name": "read", "arguments": { "path": "/home/sebas/pi-config/sessions/session-memory-jobs/20260507T202641961301Z.log" } }, { "type": "toolCall", "id": "call_swA7VJGeBgmkOwaIPbSpR6Sb|fc_0d29dbf88c868f5a016a12c0c21c7c8196b9722deffb3de5c9", "name": "read", "arguments": { "path": "/home/sebas/pi-config/sessions/session-memory-jobs/20260507T210856564296Z.log" } } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 1505, "output": 149, "cacheRead": 162304, "cacheWrite": 0, "totalTokens": 163958, "cost": { "input": 0.0037625000000000002, "output": 0.002235, "cacheRead": 0.040576, "cacheWrite": 0, "total": 0.046573500000000004 } }, "stopReason": "toolUse", "timestamp": 1779613886114, "responseId": "resp_0d29dbf88c868f5a016a12c0be411c8196a64aff41998a646b" } }, { "type": "message", "id": "026de8f2", "parentId": "93e3bbe4", "timestamp": "2026-05-24T09:11:49.872Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "**Evaluating architecture changes**\n\nI'm considering the simplest architecture, where the extension can queue jobs immediately, although it's optional. I think a new timer service could run every 6 hours to scan sessions modified since a specific watermark and queue any that haven't been analyzed yet. It might be a good idea to ensure the analyzer doesn't depend solely on the PI by default, using a better fallback heuristic to avoid silent failures. I'll need to check if systemd timers are okay.", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12c0c3caa8819681b792af91cff62a\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABqEsDUoqkDvzTgZoh5yi3zEqAKgCkyQVZm9CDKVm2WdH_9YucF0A1mDwND-dg4sbv-fmGWkV8u4e5_xLlNZlsJOwNAUlNQHy-Uc8PTUWZecXwUwlkFpC5jnig8d_Pr3Ao8Q5_WLAFXgMQrZGHsyDzgbie2FbIbLxbB3juXAaK7_rW2w5OaXPpTcVdsPwEIhVnJO9HMPYUuj4t5ayJjlvv2-2wyHz-1BQSvPOz7ylAmiRU-C6FOnNndogoFo9i8py1xfet_dKJ8saMbIWgTdAJg1QYRmrDoFyWdIEmEDioHCIXgEPYLWl-jk3x01dbzPxAP5SZTlpmFW_tx50PfLrlflorYPPjuig4fLuTbgMhrm_Jm5r5GNCUl77v_A5u4w405_DsQvEAn6aKpfx9INt7YvIJvoAgv74zP0u2J1aAaSWUd80VbVbiT3MkFVTQh1NEk7Ucno63EZj1FgtsLWqF5o81ToGCnvg8SMcfbEPIm-Ed7uFIEDLFdjuCD4_Q8tYdRtq5PtRsRBTtDASIHwtq56Q09SWkZpxRfXEDHxZTZOITWJS9j05Ssh0V5lKB5HlKyasrQfHJM0mUXibVt4ZXB-uZptpgoZGRcrc1zrnSn2VVS-0YVOOfsBe4lqUaUTvW0XBI4S7QQaSdpAq2hjeHPWUM7WB4HraEjAeRSi-zYEt8_yFRxSZsvuecHqkLhGL1OrcA0nAqd-Vblp-NWrh3WMxEte31NpGyw19zRdjXHMvkXdoffRXsdjZw9MNwc-eKwEtOtE3iBNjLIUeAb-T7eRsvpkuq0bQvGKV9whGolTx3I_Q9-7xq2NyKSTdotNPIpiNC_UOcjnMtBDSntIscjFOjf63WzcNHFfDrj6KJM7M5ao6PeHBBrzODE3E2-SkJBebp3MOH1kd3R_HokxBHbE3-xziUWDYuo7TJWZtoawwobW1sbZCB6pl_rcnESdx-CHILS4ZuAyUxaolujO-IL0WwGqiOYH1XI7bnRiUpLOaBKgclS578tmr_vmlHJrhyQFLPGpb26V9huvAF-yaIOTjFSRdkhuQicyMLrjmzih08aD667I-1sgWdJFNt_SvIadq94cpG3i8BqUIgXeAciQyDDru8v8A2kbpvd34XcZfxGyzPtuvk_jgYoiHpERtQWC55HmoXOsUqfk_CkFniT0xC8vA_wiQgpoA9J5iyVcpCXD1lMTYBvFOIaIPAzj8VP2m_Jzr20FCjdXIKHD3mFo_-tImfSblyyalmy2nUSSgY4x6dvY1vrdNTuz80jBSEbK71iA9JiM46uT88Dri6MPD_aJUR-bwEmhhxapCEdXUc9ohOKw5ll8PQheXGSQom-bbjxky6LkFs76xS6spD25WQZTIfnIeC3aeoXfmeOsTFqETZ-lBwFG_0Jp9DGD64rw9Y2TFwpsFbnzkI5iwwSk-7cFt1inn_xTG-r174Nx7p7ezfZBL8MgLyLPghFOu4_1Vpyd9mel6GclfipIo6BKVnNmq7JGS7YcLoPdly27L8ptRqnk1UIHDu106y9kltRElImGzjp3feJptddNR3DVakksBxnawnMCA3R_rBRFbI7FEbsqxClzu6jrGd3bf7dsgFeM4vJQVfIUA0dEl5GTYkazy3LHwyEf1ZsbuJRSqlXnKmdX_rJi02pOAe1coq3-iPW-FxpXLdJe9HPxjEVhNyBjLTwcGrIN-rGuJDnKnFjKNMm-sF1EOHrLe_OceyyJ7SACmiypWFEOi8dUjRcvjxj8jXvw4Lab6Mo4wL5FRLklJwx00hDFTcM6VRGEw1IT3hp_5_loYd2SyJELizYT1bSW_fQb8BBwO0ntBJrgvcpE4lDOIvhxPx4RHo0P-IZApLDpwXAvC9bVf7ph6-E4DEkjfXy4cgzGQYnVu7XzBewDY5wAUObd2BSQCwbZoWesE31pYksRBm1Ib5WWtN3uy6Y4lNswUt4YyF2xyD3ehjnMCGuSPkDyJ6XWqOc7jBBQ3zk5cRJVQnqHX6xZ3bQZxyEpCUFJ-nnvCA0aXPWC6QjHAkm7kcK1H-zKVferOoTCUtD2H1VxqmFxf3UNzmHBhwxXn4nTuRZ-D9byyv3Gx3OrmcJOFqJwvUBNwKJXPflIuVVqbu3EvCCix5d-RG1-kI_4k2DIAvHwWWH22ze93OkAIFPTpG0Mxfc603W1_4jZskLmQC1aCz9p7ubn3SCAVvMI4EC9ZYjyODkJDO-ex6-3APzIeVW-fRlCpCEJgERT3lg5tEqikqbokhB9reH63orfYk4jUlEm6XHrJ_u32QCl5H-4vWORg6UvV2dXyl1bWBX8VWUwYUedBi6htEZr4bWH8TlDPaaKTjpcGqMZCVCP1LEoDONXpSROJa56KQAdICienKmiWSpo7ews_UG1oJUgXfUzuVrParkS7DbzxE2aLBwHm6cOZcv1dWkkzKRbiFjD0qk-DMqa5EwN7nrGbmRxWhVrZUO0EAEFo7dqLbY7BpzZyj-7u9eEe3zwX2pl6Nq6uaEhDHUfWTmJIJXdlqLjWObPxaZ-6CWEURdWFVDNjuAmSlbX4DgEE2ItpJ1qCYAY6eFEwyPeEolYKEoCEsozLU2F0UV6kOGH53H3vtRX-74snWo6_kF9T43cDHtgVKRiWARLP0ZWjqqnHZN_UdBQd7EvNJ81nM5xGDr_U3LVxcZIN34ga5jykl8yW4DwJ9rPBsFjH1D54DceZkMUWmdPBqbDsb6wZLnC95voszHHmHMvShpIVUo9VGt2v9ut56EeDWDyGbjTkzkVq1tMQmLqcWjwq4kn7OiABjh3cdnsBqXbxJVx92MpBJEsSDRuB1RKWd5ynnGx6UxpPMiMPo3C0Id46_u1uFeQp1ihNMHVgOAZXCjnFiEMN-LX_alpj188WS2XAeoYywHLGnqnfK5qYOHl5K-BRP-CeJXUDFUnTHrUZxVZViZ7p1vhOjTTmt_LZfmwSpw2IpwMBJs_rW6WmHr7-EiHHteKP_c71JsXOHeiu5j1ijG2linsinDJqHXxS68z3JnuYQPARbGPJgFHYOVi9gk6F2K5FjEzqZu2ZrH-ChwrjWaZyuB2coEuW6iyt8FiqH9AcMYBDVt-s75OZcbo0N2uay6WtAcA57Ypp33n1wvvvCxlhax7fIuF9EHjsh_iFp397ej7M0HTYNJo_4Kg8LMH4LYzykLzzntAjBxOu6HHz8752CZAb2g6d8QegVJGZBVHJocb69TjJFsJQsz8uGNYyETrQThVVOKu1kBsJEbBDI2uV5HMqWPAJWCoiHqyh60kOZbLCV-kguioRUY7GfWjBCradyDuw1-rRvj7S1CG_wp4ZswVvEK7CFpA4HUN3s9oQGpObynN1zcmXWuDwK--rDHIGxQTOIhfZylSKl52D3JYR9A6BxpzIjbsYULQt7mKyQjl1gHiJ3kP6mirkTchfZWE8dtpfQnoWNplNuYnOzsi_6Lbertt6dcSr6l4yaBGboqB0W4VY3ccFC3lexl3kwOCrwcXyMGzxMSCTLy0JzgAiw4vry_IOr-OD5eH48XV6Yvif0pR781D9n3vpMGhnHcuRFuxyRbyIvAihmhW10n9CRzOlBIRQpWmTgCgnXMB7hpMPHLfGnQgIrLbIZ6mjxUxcPt7XCK7QsMOXoB2qFc4fe4Fi407VgDNf-uLdCPdgt_02YBlKbDLawDP1yNQndhaOuupgCDQKXr2WkDWk6Dknog7gAvMzXvpqzrsfOvcBV-PyVOucWJqfwF4zQR3507zZ_VrD4rXEUOJ7Z1slMPvHY21FoPnHzssbu-QSkdyZAanWIhJBSx1P7lCWySBy335Wc1ToSK2yIwjYLJcp4vDMwV12Kq5jcWc6_7-GVLJTUM99eME21veONTwRZduP9ONIUvorqW7f9nSy0U19PlhvqqsHRRzRv-iRTJFeqaKM-d9V-rFOUhztIaNWcfZhC7Euh-0moKUHRp-gcKv6onip1W18YcLK4U87_P3tr0u7r0RzIUCIDch_bX9U7Ul74VlEo8Kbog8eVafmhnVe8wqvuyT5yZX788bD8Pj_IlCr1nRDE34w1QAPD7678P9DUwVg9qY4kmnZ_7DFZFVsLfz5FzYMjStbE88my6-DGLwghI-DFsOBMUVIClvcK920Bw_jya1Xg7Q1ihAOgvS62T5QbCha6QXDrnmePFkjElNa7ipHdB7gZslnD5O8FOZ-m8bL2nft2CCestpUctHv3RTQeZm6JrBOON1tEXJhIkXI2B_HG7bs0DKELotrfDowu0Gc4pPHocC5ZP_K2EbfzwtdzNGeoFE5gJ64uudrjiTBW65w_UKbfVItyO6N8ugR7etCjAkaYCwST7JxQ2Gi_9uays76Rca0a7I5UICLwSRdKcqTXJr7SBtRjfsMyEsS2qqnn8v83Qbld0Ls90rh3yO0sNXKZDUqzRcdYxj5WTaRT8AK1-LmKmIXSwbwfODTPeERZ6vQxMWzcBxWSpfT7C1nnBlfRpe6xUdQ9QfIb0zJ_0NJOfZtKQSFLis9Y7NLyuk1AITdG_h4O0QdkbSW8ONI6LTTpHkDJAqBfQGH8DdMvrwry5qq816KcFXodAHG3MHJnXO2eBJwUu0SEHCWRTv3An_FOA_yTdSmfHWiejVAW-HdIHlO9wOPsqy2dmkON06WeR5plDlYlfbKBbyXGWX07aqUBLjZ2E-6s8gbX0S6QBvlkNhRWWwQrvC7J0m6Iv1aR_Hr1GJAJdGOQDAOY5slQZXF1Pfz8_BGHYoZCvEXqRiH25jHlJ0H6biz_82_89XnlieXu5PI8CI_YgSJpnX3RnRLYxxPM3_aUnBR5d-7PpwH25Pcd90zkHu1pFJzpGKM1dNrLd5c7IVJXRgTeCVpaqWbZ_pIj_UFwoAIqdEc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architecture changes**\\n\\nI'm considering the simplest architecture, where the extension can queue jobs immediately, although it's optional. I think a new timer service could run every 6 hours to scan sessions modified since a specific watermark and queue any that haven't been analyzed yet. It might be a good idea to ensure the analyzer doesn't depend solely on the PI by default, using a better fallback heuristic to avoid silent failures. I'll need to check if systemd timers are okay.\"}]}" }, { "type": "toolCall", "id": "call_vGbZwjMHPkMgBDpwKnuCd9yr|fc_0d29dbf88c868f5a016a12c0d4797481968978f40a884bb68a", "name": "bash", "arguments": { "command": "python3 - <<'PY'\nimport os\nfor k in ['OPENAI_API_KEY','ANTHROPIC_API_KEY','GOOGLE_API_KEY','OPENROUTER_API_KEY']:\n print(k, 'set' if os.environ.get(k) else 'unset')\nPY", "timeout": 10 } } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 19070, "output": 784, "cacheRead": 163328, "cacheWrite": 0, "totalTokens": 183182, "cost": { "input": 0.047675, "output": 0.01176, "cacheRead": 0.040832, "cacheWrite": 0, "total": 0.100267 } }, "stopReason": "toolUse", "timestamp": 1779613890470, "responseId": "resp_0d29dbf88c868f5a016a12c0c2a3108196afbda7b1bc5546b7" } }, { "type": "message", "id": "9fdaf10f", "parentId": "e2899010", "timestamp": "2026-05-24T09:12:54.219Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "**Implementing session sweeper**\n\nI need to create a session sweeper script that discovers session files in `pi-config/sessions`. It should maintain a state JSON with processed file paths and modification times. For each recent unprocessed session with user and assistant messages, I’ll create a job payload by reading the session summary. I'm considering calling the analyzer directly without writing job JSON, possibly using a `--payload-file`. I might implement a timer that runs every six hours, so it will be a one-shot service. Additionally, I’ll look at updating the extension.\n\n**Reducing dependencies in analysis**\n\nI'm looking to reduce dependencies. The prompt can still queue, but I want the analyzer fallback to work similarly. If `call_pi` fails, I’ll implement a `fallback_analysis(job)` that generates 0-3 candidates based on deterministic heuristics from the session branch. Instead of detecting work rule patterns from final answers, I could create an `episode` memory inbox summarizing the session if the assistant's final text isn't empty and there are more than N messages. This summary would include a title derived from the current working directory and some user context, which could be helpful for handoff.\n\n**Considering timer implementation**\n\nI’m looking to add a timer, and it seems like I need to implement a session memory sweeper. I think the relevant service files will be in the `.config` directory, specifically under `pi-config/scripts`. It’s a bit tricky since naming conventions matter, and I’ll want to keep things simple. I might need to create new files under `.config/systemd/user` and ensure everything is tracked properly. There’s no need for user input since it’s a machine configuration change. Let's get this implemented!", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12c0d75acc819685191bfcab62990f\",\"type\":\"reasoning\",\"encrypted_content\":\"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\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Implementing session sweeper**\\n\\nI need to create a session sweeper script that discovers session files in `pi-config/sessions`. It should maintain a state JSON with processed file paths and modification times. For each recent unprocessed session with user and assistant messages, I’ll create a job payload by reading the session summary. I'm considering calling the analyzer directly without writing job JSON, possibly using a `--payload-file`. I might implement a timer that runs every six hours, so it will be a one-shot service. Additionally, I’ll look at updating the extension.\"},{\"type\":\"summary_text\",\"text\":\"**Reducing dependencies in analysis**\\n\\nI'm looking to reduce dependencies. The prompt can still queue, but I want the analyzer fallback to work similarly. If `call_pi` fails, I’ll implement a `fallback_analysis(job)` that generates 0-3 candidates based on deterministic heuristics from the session branch. Instead of detecting work rule patterns from final answers, I could create an `episode` memory inbox summarizing the session if the assistant's final text isn't empty and there are more than N messages. This summary would include a title derived from the current working directory and some user context, which could be helpful for handoff.\"},{\"type\":\"summary_text\",\"text\":\"**Considering timer implementation**\\n\\nI’m looking to add a timer, and it seems like I need to implement a session memory sweeper. I think the relevant service files will be in the `.config` directory, specifically under `pi-config/scripts`. It’s a bit tricky since naming conventions matter, and I’ll want to keep things simple. I might need to create new files under `.config/systemd/user` and ensure everything is tracked properly. There’s no need for user input since it’s a machine configuration change. Let's get this implemented!\"}]}" }, { "type": "toolCall", "id": "call_0GUDzaNAiDLwSl0oZHbCWA3x|fc_0d29dbf88c868f5a016a12c0f4ef808196941b6fcf20707309", "name": "write", "arguments": { "path": "/home/sebas/pi-config/scripts/session-memory-sweeper.py", "content": "#!/usr/bin/env python3\nfrom __future__ import annotations\n\nimport argparse\nimport json\nimport os\nimport subprocess\nimport sys\nimport time\nfrom pathlib import Path\nfrom typing import Any\n\nBASE_DIR = Path(__file__).resolve().parent.parent\nSESSIONS_DIR = Path(os.environ.get(\"PI_SESSION_DIR\", BASE_DIR / \"sessions\"))\nJOB_DIR = Path(os.environ.get(\"PI_SESSION_MEMORY_JOB_DIR\", SESSIONS_DIR / \"session-memory-jobs\"))\nSTATE_FILE = Path(os.environ.get(\"PI_SESSION_MEMORY_SWEEP_STATE\", BASE_DIR / \"runtime\" / \"session-memory-sweeper-state.json\"))\nANALYZER = Path(os.environ.get(\"PI_SESSION_MEMORY_ANALYZER\", BASE_DIR / \"scripts\" / \"session-memory-analyzer.py\"))\nLOOKBACK_DAYS = int(os.environ.get(\"PI_SESSION_MEMORY_LOOKBACK_DAYS\", \"21\"))\nMAX_SESSIONS_PER_RUN = int(os.environ.get(\"PI_SESSION_MEMORY_MAX_SESSIONS_PER_RUN\", \"12\"))\nMIN_TOTAL_MESSAGES = int(os.environ.get(\"PI_SESSION_MEMORY_MIN_TOTAL_MESSAGES\", \"6\"))\nMIN_ASSISTANT_TEXT = int(os.environ.get(\"PI_SESSION_MEMORY_MIN_ASSISTANT_TEXT\", \"120\"))\n\nSKIP_PREFIXES = (\n \"you are iteration \",\n \"continue the bounded ralph-loop\",\n)\n\n\ndef load_state() -> dict[str, Any]:\n if not STATE_FILE.exists():\n return {\"processed\": {}, \"last_run_at\": None}\n try:\n return json.loads(STATE_FILE.read_text(encoding=\"utf-8\"))\n except Exception:\n return {\"processed\": {}, \"last_run_at\": None}\n\n\ndef save_state(state: dict[str, Any]) -> None:\n STATE_FILE.parent.mkdir(parents=True, exist_ok=True)\n STATE_FILE.write_text(json.dumps(state, indent=2, ensure_ascii=False) + \"\\n\", encoding=\"utf-8\")\n\n\ndef iter_session_files() -> list[Path]:\n cutoff = time.time() - LOOKBACK_DAYS * 86400\n paths = [p for p in SESSIONS_DIR.rglob(\"*.jsonl\") if p.is_file() and p.stat().st_mtime >= cutoff]\n return sorted(paths, key=lambda p: p.stat().st_mtime)\n\n\ndef parse_session(path: Path) -> dict[str, Any]:\n session_id = None\n cwd = None\n branch: list[dict[str, Any]] = []\n user_messages = 0\n assistant_messages = 0\n last_user_text = \"\"\n last_assistant_text = \"\"\n first_user_text = \"\"\n\n with path.open(\"r\", encoding=\"utf-8\", errors=\"ignore\") as handle:\n for line in handle:\n try:\n entry = json.loads(line)\n except Exception:\n continue\n if entry.get(\"type\") == \"session\":\n session_id = entry.get(\"id\") or session_id\n cwd = entry.get(\"cwd\") or cwd\n continue\n if entry.get(\"type\") != \"message\":\n continue\n message = entry.get(\"message\") or {}\n role = message.get(\"role\")\n if role not in {\"user\", \"assistant\"}:\n continue\n text_parts = []\n for part in message.get(\"content\") or []:\n if part.get(\"type\") == \"text\" and isinstance(part.get(\"text\"), str):\n text_parts.append(part[\"text\"])\n text = \"\\n\".join(text_parts).strip()\n branch.append(entry)\n if role == \"user\":\n user_messages += 1\n if text and not first_user_text:\n first_user_text = text\n if text:\n last_user_text = text\n elif role == \"assistant\":\n assistant_messages += 1\n if text:\n last_assistant_text = text\n\n return {\n \"session_id\": session_id,\n \"session_file\": str(path),\n \"cwd\": cwd or str(Path.home()),\n \"scope\": infer_scope(cwd or str(Path.home())),\n \"reason\": \"periodic_sweep\",\n \"trigger\": \"periodic_sweeper\",\n \"branch\": branch,\n \"user_messages\": user_messages,\n \"assistant_messages\": assistant_messages,\n \"last_user_text\": truncate(last_user_text, 2000),\n \"last_assistant_text\": truncate(last_assistant_text, 2000),\n \"first_user_text\": truncate(first_user_text, 400),\n }\n\n\ndef infer_scope(cwd: str) -> str:\n home = str(Path.home())\n try:\n resolved = str(Path(cwd).resolve())\n except Exception:\n resolved = cwd\n if resolved == home or resolved.startswith(str(Path(home) / \".pi\")):\n return \"global\"\n return \"project\"\n\n\ndef truncate(text: str, max_len: int) -> str:\n text = \" \".join(text.split())\n if len(text) <= max_len:\n return text\n return text[: max_len - 1] + \"…\"\n\n\ndef should_skip(meta: dict[str, Any]) -> tuple[bool, str | None]:\n if meta[\"user_messages\"] <= 0 or meta[\"assistant_messages\"] <= 0:\n return True, \"no_dialogue\"\n first = (meta.get(\"first_user_text\") or \"\").strip().lower()\n if first.startswith(SKIP_PREFIXES):\n return True, \"loop_session\"\n total_messages = meta[\"user_messages\"] + meta[\"assistant_messages\"]\n if total_messages < MIN_TOTAL_MESSAGES and len(meta.get(\"last_assistant_text\") or \"\") < MIN_ASSISTANT_TEXT:\n return True, \"too_small\"\n return False, None\n\n\ndef existing_job_for_session(session_file: str) -> bool:\n for path in JOB_DIR.glob(\"*.json\"):\n try:\n payload = json.loads(path.read_text(encoding=\"utf-8\"))\n except Exception:\n continue\n if payload.get(\"payload\", {}).get(\"session_file\") == session_file:\n return True\n return False\n\n\ndef write_job(payload: dict[str, Any]) -> Path:\n JOB_DIR.mkdir(parents=True, exist_ok=True)\n job_id = time.strftime(\"%Y%m%dT%H%M%S\", time.gmtime()) + f\"{int(time.time_ns()%1_000_000):06d}Z\"\n job_file = JOB_DIR / f\"{job_id}.json\"\n job = {\n \"job_id\": job_id,\n \"queued_at\": time.strftime(\"%Y-%m-%dT%H:%M:%SZ\", time.gmtime()),\n \"status\": \"queued\",\n \"job_type\": \"session_memory_analysis\",\n \"payload\": payload,\n \"analysis\": {\n \"status\": \"queued\",\n \"save\": None,\n \"memory_id\": None,\n },\n }\n job_file.write_text(json.dumps(job, indent=2, ensure_ascii=False) + \"\\n\", encoding=\"utf-8\")\n return job_file\n\n\ndef run_analyzer(job_file: Path) -> int:\n proc = subprocess.run([sys.executable, str(ANALYZER), \"--job-file\", str(job_file)], capture_output=True, text=True)\n log_file = job_file.with_suffix(\".log\")\n log_file.write_text((proc.stdout or \"\") + (proc.stderr or \"\"), encoding=\"utf-8\")\n return proc.returncode\n\n\ndef main() -> int:\n parser = argparse.ArgumentParser()\n parser.add_argument(\"--once\", action=\"store_true\")\n args = parser.parse_args()\n state = load_state()\n processed = state.setdefault(\"processed\", {})\n results = []\n\n for session_file in iter_session_files():\n if len(results) >= MAX_SESSIONS_PER_RUN:\n break\n stat = session_file.stat()\n key = str(session_file)\n marker = f\"{stat.st_mtime_ns}:{stat.st_size}\"\n if processed.get(key) == marker:\n continue\n meta = parse_session(session_file)\n skip, reason = should_skip(meta)\n if existing_job_for_session(key):\n processed[key] = marker\n results.append({\"session_file\": key, \"status\": \"already_queued\"})\n continue\n if skip:\n processed[key] = marker\n results.append({\"session_file\": key, \"status\": \"skipped\", \"reason\": reason})\n continue\n job_file = write_job(meta)\n exit_code = run_analyzer(job_file)\n processed[key] = marker\n results.append({\"session_file\": key, \"status\": \"analyzed\" if exit_code == 0 else \"failed\", \"job_file\": str(job_file)})\n\n state[\"last_run_at\"] = time.strftime(\"%Y-%m-%dT%H:%M:%SZ\", time.gmtime())\n save_state(state)\n print(json.dumps({\"processed_now\": len(results), \"results\": results}, ensure_ascii=False))\n return 0\n\n\nif __name__ == \"__main__\":\n raise SystemExit(main())\n" } } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 949, "output": 3471, "cacheRead": 182272, "cacheWrite": 0, "totalTokens": 186692, "cost": { "input": 0.0023725, "output": 0.052065, "cacheRead": 0.045568, "cacheWrite": 0, "total": 0.1000055 } }, "stopReason": "toolUse", "timestamp": 1779613909898, "responseId": "resp_0d29dbf88c868f5a016a12c0d6150481969dd9929b21700f89" } }, { "type": "message", "id": "deca059f", "parentId": "1bb95bb6", "timestamp": "2026-05-24T09:13:15.762Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "**Considering execution options**\n\nI might not need to make the executable necessary. It could be sensible for me to edit the analyzer as a fallback instead. This could streamline my approach while ensuring that I'm still effective. I want to be cautious and think this through, as I always want to find the best solutions. Are there any other alternatives I should be considering in this situation? Let’s see what options I have!", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12c118445c819697c164c24500ac89\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABqEsEZhsE9FasXhmVtACa4x_aTO2rUoBl8_ROI7cCHxlG4DTNjvnV1cTB_B9Bm_axqhieyrfQOZsEWc1BsmQq7SKHueSyM_tY_Y_8j9vEXjOQ6MoUTOb4u7BoIHFkEB0j-9HJl0E7QfJv50IEWtBjpVUT0HmqWL-rgbSRpx1xBlGuLneLQJpb2YDElW_kvz7nAFrCE-E6aVY8NOMGnqE83aTyMIF1QZ6DDUqZZW6xpCp-yaM6h8AhnaLblCuHHSlEXUKPbdj7HWJisiNjfSPUHU-FYIL3GE8SBxT6vmEC-h4doQI3px4PMjWYfyEmbV_ikPtfBOxOxLVJ8mOqhQ7_18_eMFVZsw_BlMRwRRtVjIrdOok9EvsD2FIzQmCXBj9-qgZj8pYa7X5yp_pl7AP0sRC9Xg-If5j5WYjtg8S5Szjj6EtIJ4rgADyeuUSpOmLGKpkdpE6ltqwqDLHssT9CFEfsE93onwS7xqTS9AF7nT9BE-j1hYNin8_xCS38n6T8q0pPWMqqlpU-fL92vH-cpm5eQyqWp7Tnv-30dKonWEtvum52GFQNlK7hkDNT_OfSCzJCtx1wyTe1Mm2g5TPvMGPjVTwWRaHbFPaYFyum8SAauYZuZj5vnxXEaxaTmPFd8tj9DTzasnc1A7mZwdsuo7pue1AJY2lNVzDxOF-4wrMAJxI-r-S84WBw51hLyJ0C2T1GQKi2vCoo__E871P7DzvoVx55iY3VlsQ-1prk7ceQG9r3FhDyO2t6TP7WqgEH14QjXwkuQLZ6cXOs7OTkepUr9RAgT1k0mUIZmwqNOvMCHfvGlR5e-kWUg9cVW_qtqJLGSEp95zqmVybwRmDbibKv2eB6YHbAT24lNITfpzznickqWSAlnbQZLFsU1zdgYy21a6FQIXSsPaJl6WGXosDyGMYAQugeM0zoo_FHrp-5M9HLW5Uo7WTdRiNaxp1a625Q6LrSbCy5xmL1AaT9t7AUKSv4I1IgN917jhPBO6OxBE5J-qtQky0LVg7A9TjnTazUL\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Considering execution options**\\n\\nI might not need to make the executable necessary. It could be sensible for me to edit the analyzer as a fallback instead. This could streamline my approach while ensuring that I'm still effective. I want to be cautious and think this through, as I always want to find the best solutions. Are there any other alternatives I should be considering in this situation? Let’s see what options I have!\"}]}" }, { "type": "toolCall", "id": "call_J5efYUAXnrM5GGCHEeQjxkJr|fc_0d29dbf88c868f5a016a12c119da3481968c0874fce55ce7af", "name": "edit", "arguments": { "path": "/home/sebas/pi-config/scripts/session-memory-analyzer.py", "edits": [ { "oldText": "from pathlib import Path\nfrom typing import Any\nfrom urllib import request\n", "newText": "from pathlib import Path\nfrom typing import Any\nfrom urllib import request\n\nFALLBACK_TITLE_MAX = 72\n" }, { "oldText": "def call_pi(prompt: str) -> str:\n cmd = [\n resolve_pi_bin(),\n \"-p\",\n \"--provider\",\n \"openai-codex\",\n \"--model\",\n PI_MODEL,\n \"--thinking\",\n PI_THINKING,\n \"--no-tools\",\n \"--no-session\",\n prompt,\n ]\n proc = subprocess.run(cmd, capture_output=True, text=True)\n if proc.returncode != 0:\n raise RuntimeError(proc.stderr.strip() or proc.stdout.strip() or f\"pi failed ({proc.returncode})\")\n return proc.stdout.strip()\n", "newText": "def call_pi(prompt: str) -> str:\n cmd = [\n resolve_pi_bin(),\n \"-p\",\n \"--provider\",\n \"openai-codex\",\n \"--model\",\n PI_MODEL,\n \"--thinking\",\n PI_THINKING,\n \"--no-tools\",\n \"--no-session\",\n prompt,\n ]\n proc = subprocess.run(cmd, capture_output=True, text=True)\n if proc.returncode != 0:\n raise RuntimeError(proc.stderr.strip() or proc.stdout.strip() or f\"pi failed ({proc.returncode})\")\n return proc.stdout.strip()\n+\n+\n+def fallback_analysis(job: dict[str, Any], error: Exception) -> dict[str, Any]:\n+ meta = session_meta(job)\n+ last_user = (meta.get(\"last_user_text\") or \"\").strip()\n+ last_assistant = (meta.get(\"last_assistant_text\") or \"\").strip()\n+ first_user = (meta.get(\"first_user_text\") or last_user or \"\").strip()\n+ if not first_user or not last_assistant:\n+ return {\"memories\": [], \"reason\": f\"fallback-no-summary:{error}\"}\n+ title_base = first_user.splitlines()[0].strip()\n+ if len(title_base) > FALLBACK_TITLE_MAX:\n+ title_base = title_base[: FALLBACK_TITLE_MAX - 1].rstrip() + \"…\"\n+ cwd = meta.get(\"cwd\") or \"\"\n+ cwd_name = Path(cwd).name or \"session\"\n+ return {\n+ \"memories\": [\n+ {\n+ \"type\": \"episode\",\n+ \"subtype\": \"session_summary\",\n+ \"scope\": meta.get(\"scope\") or \"project\",\n+ \"title\": f\"{cwd_name}: {title_base}\",\n+ \"content\": f\"User asked: {first_user}\\nResult: {last_assistant}\",\n+ \"source_ref\": f\"session:{meta.get('session_id') or Path(str(meta.get('session_file') or '')).stem or 'unknown'}\",\n+ \"evidence_ref\": meta.get(\"session_file\"),\n+ \"confidence\": 0.72,\n+ \"freshness\": 0.95,\n+ \"importance\": 0.56,\n+ \"reason\": f\"Deterministic fallback because model analysis was unavailable: {error}\",\n+ }\n+ ],\n+ \"reason\": f\"fallback-analysis:{error}\",\n+ }\n" }, { "oldText": " raw = call_pi(build_prompt(job))\n analysis = extract_json(raw)\n", "newText": " fallback_error = None\n try:\n raw = call_pi(build_prompt(job))\n analysis = extract_json(raw)\n except Exception as exc:\n fallback_error = exc\n analysis = fallback_analysis(job, exc)\n raw = json.dumps(analysis, ensure_ascii=False)\n" }, { "oldText": " job[\"analysis\"][\"raw\"] = raw\n job[\"analysis\"][\"result\"] = analysis\n job[\"analysis\"][\"status\"] = \"completed\"\n", "newText": " job[\"analysis\"][\"raw\"] = raw\n job[\"analysis\"][\"result\"] = analysis\n job[\"analysis\"][\"status\"] = \"completed\"\n if fallback_error is not None:\n job[\"analysis\"][\"fallback_error\"] = str(fallback_error)\n" } ] } } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 3938, "output": 1062, "cacheRead": 182784, "cacheWrite": 0, "totalTokens": 187784, "cost": { "input": 0.009845000000000001, "output": 0.01593, "cacheRead": 0.045696, "cacheWrite": 0, "total": 0.071471 } }, "stopReason": "toolUse", "timestamp": 1779613974254, "responseId": "resp_0d29dbf88c868f5a016a12c11667448196a9f78d02bfbd497b" } }, { "type": "message", "id": "f047bafe", "parentId": "bc65add2", "timestamp": "2026-05-24T09:13:21.788Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12c12d2ca48196853723d8b4880fff\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABqEsEu6PzB29rlOLGFnaVQlZYtBX65D_l9hfqoMVjWmkkfcb2-KOnMEnZQ2zRCr7i8cJaOpOFDgmb006udHKdHI3Ee9_HmG5yx8p7iWdPJ6ut6ivg7PNqMNtpbDYHUrWsesATZIrPyb299LcgQSOSlUl9izCtMit_9qL2B_ey1KGId6IUWmVzFFONeazLa0Lk8rcKVja5eleJugzdQ_lYiw1YlItx1e7cv8HGw1NnFQrqa6Eawdf60SEaR_FXrG2FsEFFqMGgqn49OufUXA5_RZHHbEbykqWSrGul9TABwAH7Bm1aKjF3d85R5ptxp20jycQRr1RfK7vSKWm6lK_vB_Lj9w2hk3lHu7XxiwnPrvjzU0tLbJpLqcrUwYYRSiKrP_WBaRCUpeWkeq6cEKJI1g2GHwrsqtsIrBz_rYaLujjoGgF9kt1PZ1n3N-EDoXQrI5vGHhqLoI9LOByMvYKLdY42yU0K9SBcraDilVIyfRUtgQOR5UK7RX5pNL2EiI7tyYx49dCKQJ-nkKyPKAAlTLyxP8G3c7g1FzQKWsH4_hAJ0aW9CLjg6zN_dfd6N4lVeLgpvZ93TmOo1SKQZKHQGPMnKpCHgj6JSHxWp13tV5LpGHDNpzAapjn_EqWTKMVXP1KS77ucza2q4QG1XcMRluNpOau1lfVV6NwLVLt7sphBdI8iXq-tSKU9GEcWxKtxvITJVe1QF8UQV1uZhQHCk-AzaTEPAGVAClKEhx2V7lBMgo5AJ0eGMuOLe8lLV9CFD-ja_iy7KBs0C8FExwGefKc7GgxrqXSQRSFFkDNPI5tGBDQHMZ3QZhpco-ZFdqUQcn78z1vZdy0ZD9nnGmYm1mlA86y66tbAU1ERqmYKqM_3CzTzvLGrYLae9qPPXwvr26sGb1r_Wxj0wN5gYdsdTu2Nbu2BCNDWfZ7Ruj5PK17q2G-DME4_fxjN6haMB5icuogr0Z5OrnWeAa4HfEahjd73xRHdHTSnZ5Hh0UgWBbRCQbuvnmTeBP179UWQpXKkXSD7WKfpVihOdSwI-b1Ouh8ErJssx03MEtbiG_10UVJqjOLycxV3n1gC862QHJ0t1zH4LD00rKNv6rIDq0b77D_NdH2PN-XmQwWS1Kk6KJH7Veoqbhku1U7Vh6V_jFLnH9JAPMLDWR2qYqAlmqZvisoA2FQWmi_7yyUMyBcJJrVir-l9UBgbuZX5LkWklyaTIw2npQm6Omm3EZkXWU3n4lgJ8sVBA4TpzbGNBqxMlvgV5BybAibS57HstxhvmbnWjKcNjj2YDsxrfSMrU5KNvZ393xcYq68nPIuJEkCUM89f7gK4Q-E2lAWUmtFeOjwEti8pnMcA-H6sKxy2mVgSkuMjTyaN6U49rgfjaWLgfpihau0E=\",\"summary\":[]}" }, { "type": "toolCall", "id": "call_uPYtyF4Sx6wHh4XxTL7CuMld|fc_0d29dbf88c868f5a016a12c12eb9bc819682ac48100b93aca0", "name": "write", "arguments": { "path": "/home/sebas/pi-config/scripts/session-memory-sweeper.service", "content": "[Unit]\nDescription=Pi session memory sweeper\nAfter=network-online.target\nWants=network-online.target\n\n[Service]\nType=oneshot\nWorkingDirectory=/home/sebas/pi-config\nEnvironment=AGENTS_DB_API=http://100.116.176.16:8091\nEnvironment=PI_SESSION_MEMORY_PI_BIN=/home/sebas/.npm-global/bin/pi\nEnvironment=PI_SESSION_MEMORY_LOOKBACK_DAYS=21\nEnvironment=PI_SESSION_MEMORY_MAX_SESSIONS_PER_RUN=12\nExecStart=/usr/bin/env python3 /home/sebas/pi-config/scripts/session-memory-sweeper.py --once\n" } } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 1447, "output": 234, "cacheRead": 186368, "cacheWrite": 0, "totalTokens": 188049, "cost": { "input": 0.0036175000000000005, "output": 0.00351, "cacheRead": 0.046591999999999995, "cacheWrite": 0, "total": 0.053719499999999996 } }, "stopReason": "toolUse", "timestamp": 1779613995812, "responseId": "resp_0d29dbf88c868f5a016a12c12bf96c8196ad80284ee998fbc9" } }, { "type": "message", "id": "159cfbd2", "parentId": "9b2751bf", "timestamp": "2026-05-24T09:13:25.303Z", "message": { "role": "assistant", "content": [ { "type": "toolCall", "id": "call_OzBRIEusJzOcCTchmkl2Mipy|fc_0d29dbf88c868f5a016a12c13358e4819682590fb2d528dce6", "name": "write", "arguments": { "path": "/home/sebas/pi-config/scripts/session-memory-sweeper.timer", "content": "[Unit]\nDescription=Run Pi session memory sweeper periodically\n\n[Timer]\nOnBootSec=10m\nOnUnitActiveSec=6h\nPersistent=true\nUnit=session-memory-sweeper.service\n\n[Install]\nWantedBy=timers.target\n" } } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 686, "output": 89, "cacheRead": 187392, "cacheWrite": 0, "totalTokens": 188167, "cost": { "input": 0.0017150000000000002, "output": 0.001335, "cacheRead": 0.046848, "cacheWrite": 0, "total": 0.049898 } }, "stopReason": "toolUse", "timestamp": 1779614001791, "responseId": "resp_0d29dbf88c868f5a016a12c131fd84819697ae43104246abed" } }, { "type": "message", "id": "ea54dad9", "parentId": "b5a215b1", "timestamp": "2026-05-24T09:13:35.844Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "**Installing systemd timer**\n\nI need to install something into the `/.config/systemd/user` directory. I'll use a bash command to copy the necessary files and then run a daemon reload to enable and start the timer. It could be a good idea to check the permissions as well to ensure everything is set up correctly. I might even need to update the README for clarity afterward. 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I'll use a bash command to copy the necessary files and then run a daemon reload to enable and start the timer. It could be a good idea to check the permissions as well to ensure everything is set up correctly. I might even need to update the README for clarity afterward. Let's make sure everything goes smoothly!\"}]}" }, { "type": "toolCall", "id": "call_nDEnzDIEIs6VJ5jX40piIUnd|fc_0d29dbf88c868f5a016a12c138909c8196aa771f12d4cf4ffe", "name": "edit", "arguments": { "path": "/home/sebas/pi-config/README.md", "edits": [ { "oldText": "- Session close hook now prompts once before switch/fork/exit to encourage saving durable memory into agents-database.\n- Session memory now uses an external local dispatcher on `127.0.0.1:17882`; the hook only captures session identity/context, the dispatcher enqueues metadata, and a background analyzer decides whether anything durable is worth saving.\n- The canonical memory pipeline lives in `agents-database` (`MemoryService` / `MemoryEngine`). Repo-local helpers should only capture session context and hand off to that service.\n- The analyzer uses `pi` in background with a cheap model (`gpt-5.4-mini`) and thinking off when possible.\n- The dispatcher/analyzer are restart-safe because queued jobs live on disk under `sessions/session-memory-jobs/`.\n- Use `./scripts/install-session-memory-dispatcher.service` to keep the dispatcher alive under systemd user service if desired.\n", "newText": "- Session close hook can still queue memory analysis before switch/fork/exit.\n- Session memory also has a periodic sweeper so Telegram-heavy periods do not depend on session-end hooks.\n- The external local dispatcher listens on `127.0.0.1:17882`; it captures session identity/context and enqueues metadata under `sessions/session-memory-jobs/`.\n- `scripts/session-memory-sweeper.py` is the reliable catch-up path: it scans recent session files, skips obvious loop noise, and analyzes anything not yet processed.\n- The analyzer first tries cheap `pi` model analysis; if that is unavailable, it falls back to a deterministic episode-summary candidate instead of failing silently.\n- The canonical memory pipeline lives in `agents-database` (`MemoryService` / `MemoryEngine`). Repo-local helpers should only capture session context and hand off to that service.\n- Use `./scripts/install-session-memory-dispatcher.service` for the dispatcher and `./scripts/session-memory-sweeper.{service,timer}` for periodic catch-up.\n" } ] } } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 292, "output": 482, "cacheRead": 187904, "cacheWrite": 0, "totalTokens": 188678, "cost": { "input": 0.0007300000000000001, "output": 0.00723, "cacheRead": 0.046976, "cacheWrite": 0, "total": 0.054936 } }, "stopReason": "toolUse", "timestamp": 1779614005306, "responseId": "resp_0d29dbf88c868f5a016a12c135900c81968234aad5e92cf5aa" } }, { "type": "message", "id": "ff42f1e2", "parentId": "251eb149", "timestamp": "2026-05-24T09:13:41.566Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12c143a1d48196b786500b675135ad\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABqEsFEPD_9Q_ZaCBurBAbiykbScVu3qpjBebMbpixrNEIWEUmG6B-z3vGAUKn-UHsbfIjslWt_l6kMMG0EsymjjykUcgWuSXydENAdK1-ZogHWagPUF4KroJrgreDSG7EOF7-n30yOoglzPcFiU6DzWVFTOV1cXVENu4WD9-RTszJjdfQCBshVq4lNVjQAskFQRpUNWmVxkUjapAtmUahy91vrGCi-481JAPK5ueB3PhE_hiXirT_KmAqoEsLCgexDyIbJ760gGCgcd5cIssZm1MCcgeOlggAewybQ-irNmXjtQ89nRsh_yl6UEhKTU-WT5i-dmElvE1TMUktMGNWKhyFqVxlQ7Cx5gABRsBc8DSxRvkrdDlZeTkp_NJ5bdCLr_zTCe06zwMJc-PotutZ7DAynESOrqlOXglbA85_Ii7uXCNw5mzLYnNkUAiVunDmnpuVkcPDahyDsHBgsanFBrMae4f0YJiq2soxJjcMYiX-vMonKDTByyr-c93grGm6EDHZcoqLf5EHM9piHXj6g6cht8_yDmRcVFkpPdaMY_Bfxtg082gooy3j9sJsLITFMjxS2dg25PCCejTN0swa9UVcvAzYpF9xg34R6ebU88ll87RhAgNXkh_dggSPzU7KVfPD9J0Gkdj2R-PU7l1RYy7PpFkwgZHCljcLn7lkASy7ceCyNtTcoDt3a22fl5XNG5ezgmbz1VilCuYm_G-FTJD9HJ3_Reen55CyzlxNIifz9ffZw1IW6RpdEne568MxOydTSUxBchGcj3YRlpM5eba9DgZlA_bGXhOnpPwHq5QFmRugdE0lmzsDHpHLbCJNhK7BZvjt4-ygwzxXmSP0qYiItfkom8BbmIhJTxzeMWTps4EC50zldwe6uUQPWNrCKXfh3ve2gDLShxq8XbYaP1xjC6VoCA2CiRQPS-NjCuXh_dzZ5M1dD2s_QavAuLH8C_rd7\",\"summary\":[]}" }, { "type": "toolCall", "id": "call_6OqntkU3QqtryqtRFWJ6TxuZ|fc_0d29dbf88c868f5a016a12c144298c81969e69a1a86d1aee18", "name": "bash", "arguments": { "command": "rg -n \"Session close hook|Session memory now|dispatcher\" /home/sebas/pi-config/README.md -n -C 2", "timeout": 10 } } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 814, "output": 60, "cacheRead": 187904, "cacheWrite": 0, "totalTokens": 188778, "cost": { "input": 0.0020350000000000004, "output": 0.0009, "cacheRead": 0.046976, "cacheWrite": 0, "total": 0.049911 } }, "stopReason": "toolUse", "timestamp": 1779614015849, "responseId": "resp_0d29dbf88c868f5a016a12c14009a48196a7935622c8b6fd43" } }, { "type": "message", "id": "f6fe5f5c", "parentId": "33723470", "timestamp": "2026-05-24T09:14:03.050Z", "message": { "role": "assistant", "content": [ { "type": "toolCall", "id": "call_GoFsu8VIK3HvUlCWLSkPD2QH|fc_0d29dbf88c868f5a016a12c151cd248196b2aadb1d9a214944", "name": "edit", "arguments": { "path": "/home/sebas/pi-config/README.md", "edits": [ { "oldText": "- Session close hook now prompts once before switch/fork/exit to encourage saving durable memory into agents-database.\n- Session memory now uses an external local dispatcher on `127.0.0.1:17882`; the hook only captures session identity/context, the dispatcher enqueues metadata, and a background analyzer decides whether anything durable is worth saving.\n- The canonical memory pipeline lives in `agents-database` (`MemoryService` / `MemoryEngine`). Repo-local helpers should only capture session context and hand off to that service.\n- The analyzer uses `pi` in background with a cheap model (`gpt-5.4-mini`) and thinking off when possible.\n- For unattended `pi` scripts and jobs, prefer explicit provider/model selection. Current safe default on this machine: `--provider openai-codex --model gpt-5.4-mini`.\n- Use `./scripts/install-session-memory-dispatcher.service` to keep the dispatcher alive under systemd user service if desired.\n", "newText": "- Session close hook can still queue memory analysis before switch/fork/exit.\n- Session memory uses an external local dispatcher on `127.0.0.1:17882`; the hook captures session identity/context and enqueues metadata under `sessions/session-memory-jobs/`.\n- `scripts/session-memory-sweeper.py` is the reliable catch-up path for Telegram-heavy periods: it scans recent session files, skips obvious loop noise, and analyzes anything not yet processed.\n- The analyzer first tries cheap `pi` model analysis (`gpt-5.4-mini`, thinking off); if that path is unavailable, it falls back to a deterministic episode-summary candidate instead of failing silently.\n- The canonical memory pipeline lives in `agents-database` (`MemoryService` / `MemoryEngine`). Repo-local helpers should only capture session context and hand off to that service.\n- For unattended `pi` scripts and jobs, prefer explicit provider/model selection. Current safe default on this machine: `--provider openai-codex --model gpt-5.4-mini`.\n- Use `./scripts/install-session-memory-dispatcher.service` for the dispatcher and `./scripts/session-memory-sweeper.{service,timer}` for periodic catch-up.\n" } ] } } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 731, "output": 506, "cacheRead": 188416, "cacheWrite": 0, "totalTokens": 189653, "cost": { "input": 0.0018275000000000001, "output": 0.00759, "cacheRead": 0.047104, "cacheWrite": 0, "total": 0.0565215 } }, "stopReason": "toolUse", "timestamp": 1779614021589, "responseId": "resp_0d29dbf88c868f5a016a12c145cdb48196a815b1c0865513fb" } }, { "type": "message", "id": "a63c6c59", "parentId": "ed50d48f", "timestamp": "2026-05-24T09:14:10.454Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "**Considering documentation update**\n\nIt seems I need to update some documentation, just to make sure everything's clear. I might also need to install certain files and run some tests to confirm everything works well. First, I’ll check the syntax. Then, I’ll copy the service and timer configurations to the .config directory. After that, I should perform a daemon-reload and enable the timer before starting the service. It's a process, but I'm on it!", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12c15cd68c8196b33497a203b30f1c\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABqEsFi8evbvFxZjbV6UX6z1WknU56TBdzb8Ow-MkCsQEpL1PEjjIvK-Ks_gidgz-JAy8meL3InOpLvFlTfspEdu2XQ471X9yjEGVVhA6MeYJuIm-MqFW9KSDrUUDodoAYQ60CWWCqM9EQM_4AIboBNZzpQQTVg1TjgmMi74AuxwWd_EAuCWVZRmKbxECM0-Kf8K4WVmEunz9lAG4lI4eIu6xNCIXhA4GeuWZ_1hR5jYeog3jYHStl7t5mWsm4DpVTwFpXSm6bGZw7rFMTrs2boCywFL21JVhZMhS2J5_ecm5BPGAWFxpN3d6ri0-2KNp6u185nOzemGUYlm50UAZNDJafh2inoKBzXpMmC2UAB6L9slc7HY8YATU3AjFKS29eqllJxwnn5VTr7m53D6PjTVM3yOT7mL6TYLqgG5aqNPbGYz6LqcHjXUDfHod2i2GYqtcyX837CnjRiitucGwXkGfON1GDbN9KEryAYWmQGDoA7PBtPtCy_HYxuEAq_Kp90xW78RQ5Sbo5CDcuPWBR-g5ZcbSc6VM6ccqQl_4dKpx8zzGlsN6jT2SAm7D0x1egvf2wibo9SXqaOCuGFxozHekph-AcG9qGEJWsu1RM8Ehih1AS414Cmp9SKLaNft9oDwagD0BOCcATKq_9yHVcueP5-cCbNTckfBoFIdvxkV4JQdxVoDfKEKqVPeQzmt0BAHpHHGrjX_HsyTBQPr1o1TPzkV9qljvrf6MPlj0Wpk3-AnIhEr-rr9ufcAeg8BAOlEkl_zfJT9SX2830gFX-VvyeMgP1CVSqhwOKbeyizM_0DVY_yL5UjftBedo35tbEsTHRNnhQuZd5XCLSTtjSl4eF_vup61Dp5HNamq6Pf5JXQFotkDs0xPF5EhKdVmY-2KWFy6T6mwdV9dG7PTI5Xlgt6WlDfrNScAafJh-lbjlp1QF_aEjdFnX5SaJDUSgTULtvaba1iNiG1xljwz-Ux_GPtREagxUL9Q22YbOiIFYOYJI7PNNSCUDO4j92ZEhEuhBpzqvzPcx5wtzxzG0Mkjbjlwm8QWkj3il1RGfY6NaZ8lArqnb71EOGZyx68_p1FNyfWLYGh7J-T_-PsINIIlC8cIM2t3_1EavgVPuqu61PCPsr-vmGlg_1thqd2hHtddJgHVaIl2erhci0Ure2yUwDKNu5DA48huhbm1apAbwjhoxY=\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Considering documentation update**\\n\\nIt seems I need to update some documentation, just to make sure everything's clear. 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It's a process, but I'm on it!\"}]}" }, { "type": "toolCall", "id": "call_sjLkhDq6R1ySejQlFz8etWjX|fc_0d29dbf88c868f5a016a12c1622f64819699c4f582f882511f", "name": "bash", "arguments": { "command": "python3 -m py_compile /home/sebas/pi-config/scripts/session-memory-analyzer.py /home/sebas/pi-config/scripts/session-memory-sweeper.py", "timeout": 20 } }, { "type": "toolCall", "id": "call_CIWG5HrbYBEyu7DA7coQsfY4|fc_0d29dbf88c868f5a016a12c1622f7c819695f65e4c93adf849", "name": "bash", "arguments": { "command": "cp /home/sebas/pi-config/scripts/session-memory-sweeper.service /home/sebas/.config/systemd/user/session-memory-sweeper.service && cp /home/sebas/pi-config/scripts/session-memory-sweeper.timer /home/sebas/.config/systemd/user/session-memory-sweeper.timer && systemctl --user daemon-reload && systemctl --user enable --now session-memory-sweeper.timer && systemctl --user start session-memory-sweeper.service && systemctl --user status session-memory-sweeper.timer session-memory-sweeper.service --no-pager", "timeout": 40 } }, { "type": "toolCall", "id": "call_bHFhrTu6TJiS54HKB9V28gRx|fc_0d29dbf88c868f5a016a12c1622f8881968522e817c4f104fa", "name": "bash", "arguments": { "command": "python3 /home/sebas/pi-config/scripts/session-memory-sweeper.py --once", "timeout": 60 } } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 753, "output": 284, "cacheRead": 188928, "cacheWrite": 0, "totalTokens": 189965, "cost": { "input": 0.0018825, "output": 0.00426, "cacheRead": 0.047231999999999996, "cacheWrite": 0, "total": 0.0533745 } }, "stopReason": "toolUse", "timestamp": 1779614043061, "responseId": "resp_0d29dbf88c868f5a016a12c15b40088196af2cb4b69db0436b" } }, { "type": "message", "id": "53bc0e0c", "parentId": "b4dbbb15", "timestamp": "2026-05-24T09:14:19.590Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "**Fixing syntax issues**\n\nI need to address a syntax problem related to plus signs that are leftover in a file from an edit. I should read through the lines around 60 to 80 to identify where these issues are coming from. It's important to ensure that everything is cleaned up properly since those kinds of errors can create bigger problems down the line. Let's get to it and make sure everything is functioning as it should!", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12c167c78c819680ec20119298ee5d\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABqEsFrXyBOlnH78u6ARz3EIU5XKR5KXf-K9Keno9kg3BX_M46uQ-d8KHLEAoMEi7dyO_8Wi4SRTAcZUiFexcb4QZSi8VhNlJBlnYK6PJn2zA8ndKqXKDhIIzGhZWUoeBnYu_uZBi4fAgjrGKE8VDwXkXW2b5qak8l2fDMM-9Jc66eyXBwOEAPCbOQW23Xod__dnad7YpdfCk_jM5lgxFRoh_yZWo5FfGlEJj1_0UlBCUGoVi8tjAugq_3-e9Ohm6gQkLyuXQcdlH7ibHjQiF-IbmAivmMVB_cTu-6TQX1UkLWwB4PQ7jeoPNwuceREaGykf3mh7N1y7B5UZjtEArj_vCFahvQrj3pJ8Huj3Ib9pgSWoifID74ahOhbGwJIxOkx3-OQxnA82tdaudGiZjtc19szZ677aFiOV6nOX4iGPtyCYbqge2RHqHdk3XXdYwCg2C3ERiyehi6ZKKoTYEi5RWDjUSCB_bHYlno_uvqSqiPVcKzoRoPgAujFctDjyVaWvwAp9SY5oh0_1ZyRq8e1nAzRqLwFbGlBP2nEhH83Vfl-Rp-PavWfA2mBQ-LsPYQAgMy6lzIDBWOffxL-TJaYRtZ5c2zqyNUksNLYa5kLhQsfBea00oHjbaakJWsOX4e6yQ1rovBCaNLX7-DuJVouLivhgTWlVR7f1k4vFV577IOtiTgG7cKO_fVJJKxbJzhX2Q3dYNlJRpkf1vP6iRry3msOjZisd60KXeyZX8hBQZ3Z5zcjEIrMf8QggLDJZnSTAkh_Sokhf9j3iapp-BvXbHxGpLC_b3ZX89jxdHDLZ4Zyq26vMDlBgB8MDuuBy44lU29-s_81l40LMYezIqxNwyob4bnqYuXnur_GY2Fkdb4AulcfEyufxYtEdS8esVP14yeYMWGL2hFDt7z_83LByNx-h1WGCmaZUPNv7bLQvG9abh_AtX_B1zS5xUMzzvmQt_WLHLG2gj8LMuJFB_2OBGoVQJgJ9sj6tagLNTg34f-pGmertbrq1k1z6rlZAViiNeQMgjD0XOz2v5cuTdqFUaAYPA==\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Fixing syntax issues**\\n\\nI need to address a syntax problem related to plus signs that are leftover in a file from an edit. I should read through the lines around 60 to 80 to identify where these issues are coming from. It's important to ensure that everything is cleaned up properly since those kinds of errors can create bigger problems down the line. Let's get to it and make sure everything is functioning as it should!\"}]}" }, { "type": "toolCall", "id": "call_U0E4G3qZSZ7rBq1zB7o6L6XQ|fc_0d29dbf88c868f5a016a12c16b22988196a65b2a15ffef167e", "name": "read", "arguments": { "path": "/home/sebas/pi-config/scripts/session-memory-analyzer.py", "offset": 55, "limit": 70 } } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 3099, "output": 62, "cacheRead": 189440, "cacheWrite": 0, "totalTokens": 192601, "cost": { "input": 0.007747500000000001, "output": 0.00093, "cacheRead": 0.04736, "cacheWrite": 0, "total": 0.056037500000000004 } }, "stopReason": "toolUse", "timestamp": 1779614054582, "responseId": "resp_0d29dbf88c868f5a016a12c166bb648196b19a5aace3e2b52c" } }, { "type": "message", "id": "b6362cf1", "parentId": "eb23db1b", "timestamp": "2026-05-24T09:14:41.735Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12c16e69d0819691482eec41212c9c\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABqEsFvuEmdartzPi_oivg5237JCX1yzI7j0dDKC3S8U5-dXFTArN0nfDksMVpB-lLJvuk8S9EZWAbRTAAn-f7x95lEmlB14OB5ZJKfNx3HdkEM4EQ23_ps9rNAdgAORFnwbFINFR5kJVfcfM_Ojb6fuAsxUlt4XIBUsqA6YFEWZ2HeBA6-wqkKbuj3Yv5Wrg216Nhm4KL08mjYX_xntA-LaZsqNRPU5XrQxsJT_YArRG4ez0XO1G01ZZ9XjFGEoGPbG1PVjw7oiBCixHM8Pkr766xHnVmAKp-TLO8tA6WU7WJ_ikOI2ldaJT6mF-YqYcgRja4n5zrji3e6n7o7PWxj9AqDOQQijcS2mu7uuCQz1WZC6N1Dd4tAX3vp0xp1pNgKGCpVZ1_Lp1hlf3UqpJmTp-J87WfGUq7QhPA1mfMXj3dBmiABPeHjOMVHF7P1BY9dNR8xzU8kAFcuzAmbs-enKP-JEME6xld4j0Sekq10Fj8bdyXY_upGTcv42TSye_KesI4z3XhvlItB2wImSA1V6SYiYzEmsY6yk-CTr1u9SdT7D_WS1L2hclN0Pa7-0jETK2YvkfFQLCZ1Z0iNvuxCGHjkLFfLoeHBWZLSFl0UsK3OG2znG63ZxYmFhBj-9UXBDWzzJ85b980SOPdGfr4Co0gDt8vca13GeAHIYTBjwcuPnONlnVT_6ZTTeROZks6HfHqVyPYBikWJyDzMzQPsM56EvDD7Q3qBlhmxSSKOdc0mWjNwd8Dy-NNVmt8FgHxoM64g4sPMN5frw1yy_oC3lCADN1hSfTdqKzas8N7993fwCz6Axl1VUd4x9rXb1TK05FZ4omDJDF1OPl_m89tyaRDntuqYYFdvxAaK5lMTQqzUbDRUptnKM9EY36eDNZ2xWKdQVTuOXrR5CHnnXzLmyzJ9FDkXdCJo1PaAOfQFrLIrvwrMqJoMK-5dk_F5GoRrlzs3\",\"summary\":[]}" }, { "type": "toolCall", "id": "call_dAofO9kYgK4yYwy1nOV7ysl6|fc_0d29dbf88c868f5a016a12c16f0cd48196aefe1f0f8145500c", "name": "edit", "arguments": { "path": "/home/sebas/pi-config/scripts/session-memory-analyzer.py", "edits": [ { "oldText": " if proc.returncode != 0:\n raise RuntimeError(proc.stderr.strip() or proc.stdout.strip() or f\"pi failed ({proc.returncode})\")\n return proc.stdout.strip()\n+\n+\n+def fallback_analysis(job: dict[str, Any], error: Exception) -> dict[str, Any]:\n+ meta = session_meta(job)\n+ last_user = (meta.get(\"last_user_text\") or \"\").strip()\n+ last_assistant = (meta.get(\"last_assistant_text\") or \"\").strip()\n+ first_user = (meta.get(\"first_user_text\") or last_user or \"\").strip()\n+ if not first_user or not last_assistant:\n+ return {\"memories\": [], \"reason\": f\"fallback-no-summary:{error}\"}\n+ title_base = first_user.splitlines()[0].strip()\n+ if len(title_base) > FALLBACK_TITLE_MAX:\n+ title_base = title_base[: FALLBACK_TITLE_MAX - 1].rstrip() + \"…\"\n+ cwd = meta.get(\"cwd\") or \"\"\n+ cwd_name = Path(cwd).name or \"session\"\n+ return {\n+ \"memories\": [\n+ {\n+ \"type\": \"episode\",\n+ \"subtype\": \"session_summary\",\n+ \"scope\": meta.get(\"scope\") or \"project\",\n+ \"title\": f\"{cwd_name}: {title_base}\",\n+ \"content\": f\"User asked: {first_user}\\nResult: {last_assistant}\",\n+ \"source_ref\": f\"session:{meta.get('session_id') or Path(str(meta.get('session_file') or '')).stem or 'unknown'}\",\n+ \"evidence_ref\": meta.get(\"session_file\"),\n+ \"confidence\": 0.72,\n+ \"freshness\": 0.95,\n+ \"importance\": 0.56,\n+ \"reason\": f\"Deterministic fallback because model analysis was unavailable: {error}\",\n+ }\n+ ],\n+ \"reason\": f\"fallback-analysis:{error}\",\n+ }\n", "newText": " if proc.returncode != 0:\n raise RuntimeError(proc.stderr.strip() or proc.stdout.strip() or f\"pi failed ({proc.returncode})\")\n return proc.stdout.strip()\n\n\ndef fallback_analysis(job: dict[str, Any], error: Exception) -> dict[str, Any]:\n meta = session_meta(job)\n last_user = (meta.get(\"last_user_text\") or \"\").strip()\n last_assistant = (meta.get(\"last_assistant_text\") or \"\").strip()\n first_user = (meta.get(\"first_user_text\") or last_user or \"\").strip()\n if not first_user or not last_assistant:\n return {\"memories\": [], \"reason\": f\"fallback-no-summary:{error}\"}\n title_base = first_user.splitlines()[0].strip()\n if len(title_base) > FALLBACK_TITLE_MAX:\n title_base = title_base[: FALLBACK_TITLE_MAX - 1].rstrip() + \"…\"\n cwd = meta.get(\"cwd\") or \"\"\n cwd_name = Path(cwd).name or \"session\"\n return {\n \"memories\": [\n {\n \"type\": \"episode\",\n \"subtype\": \"session_summary\",\n \"scope\": meta.get(\"scope\") or \"project\",\n \"title\": f\"{cwd_name}: {title_base}\",\n \"content\": f\"User asked: {first_user}\\nResult: {last_assistant}\",\n \"source_ref\": f\"session:{meta.get('session_id') or Path(str(meta.get('session_file') or '')).stem or 'unknown'}\",\n \"evidence_ref\": meta.get(\"session_file\"),\n \"confidence\": 0.72,\n \"freshness\": 0.95,\n \"importance\": 0.56,\n \"reason\": f\"Deterministic fallback because model analysis was unavailable: {error}\",\n }\n ],\n \"reason\": f\"fallback-analysis:{error}\",\n }\n" } ] } } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 1299, "output": 1002, "cacheRead": 192000, "cacheWrite": 0, "totalTokens": 194301, "cost": { "input": 0.0032475000000000004, "output": 0.01503, "cacheRead": 0.048, "cacheWrite": 0, "total": 0.0662775 } }, "stopReason": "toolUse", "timestamp": 1779614059599, "responseId": "resp_0d29dbf88c868f5a016a12c16d2b4c8196870ea5a786c19875" } }, { "type": "message", "id": "65602d9e", "parentId": "f290b81c", "timestamp": "2026-05-24T09:14:48.725Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "**Inspecting markers and logs**\n\nI need to use `py_compile` and then try running the sweeper again, since it seems like the markers might already be set for the failed sessions. It's possible that the analyzer writes out the failed jobs but still processes them. To test this, I could run the analyzer on one of the failed jobs first. Maybe I should inspect one of the new logs before proceeding with the compilation.", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12c18382048196b87b438d4afeb5a5\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABqEsGIgH1OvvFpxgQCRpqOUTTZL9yBFz97wdaI6DlE4XQ4WDMxL6fo6UW8yo7Yxfc6oT1jEBQ5AgUOunsPsTdlkOBsC8bpJCBFEiBh1KrDhJs2wAZqs2EHCel7PEhkVqmMRIdJM2-Ugd_cjjsHE52Wr0myItAEYwTsjbBNBbihTo_bAPRwe0iZGoV3QZJFDNeHu5BdoBiIbbz_xraFopX_XqsknPP_4u5H4x2u0v_Tzi6atU5kXaCMSSaIG1wo-_xZHnIEUgBbvzuGInWiNL10AxMNONeMTDyhIe8MkF1hbPbm4k6WYcVl3Ts1zJi9RZo0IU2mIgf0HtuoRLuhqu_nZcnIXKIVmhyFNPBzDX5QbynlZDHpyyeLKu6nXFij85DBYlmWE6E_7RbO84Wlu3UAfIKDKWITVbQfud1jDgTcfLSvDgMO76rpTUYt3RZtyRBvE4HGOY5fo1Y9Dd6QglvAnZF0xN8lThA_ph4SH29of3WLymOVT3qQsWZeuXbRYxUcXRR4QRHF3VTif-9EcK-c0DpVvBKzjeyCA7Svfo70RO-GbaHuSiVznlE428C_D3pRdHfSl02lwUhQ1wOKLAixgvjO6ToW8h00NECmx0ifA8l-c3xuUFtrCNZwm11Z0FKdx2gq1QRFZC5Br_S_siNvqmzh_PdGin_IfBnx4ntMIiBSlqMlG0IjumuuFJ8LoWT9DYBhtdpcNCEeIe9IHIEWbSTHI6-U5cwC5yQ0SLNJzWzwDIo0JoOw56M30OszbmyKmEV8Lv16YLRqsyNZ8KdzA6OInBui9nEXicMhlY7oPG61uOEer6WTOPUSYG72oidEXxcu4LXZSNzKpKHEvJUEH3nNaXZDy_-A0jKExx3Kd32qAcc8gQrjeDMfTB9uSxMGCcAdPrAKZzRO-2Sw5qkynH1zrbvkLnwK8wF5tJbuDezlklPEZtWVJzDylkDoCUdyeIDCBzvABTDxLY8oSmfXMk8uIMQsZhbZDlzOfIpDhjK-It9kGA0fc5JG2nZcLl_ee7yrEny7dxpR4yK0wl0sNJbx-iaSiUgMWM21YolWe3ymrS2EVqykVFn5ob4vS7CR7O6NE9KBJb7oXRFIc0uiXKZYgtWVvsHicBc2J4w3CxT-VVUt9Sy87zQ3RtH0uGxlRLybaZIddC4wBzZNASNvSklBWfmx_wbvuG0-I5wkHu4gjaFsl5koUleBlCSj5IGzJwoEwvgmYRR5eW_ziXUgYOGZZQ==\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Inspecting markers and logs**\\n\\nI need to use `py_compile` and then try running the sweeper again, since it seems like the markers might already be set for the failed sessions. It's possible that the analyzer writes out the failed jobs but still processes them. To test this, I could run the analyzer on one of the failed jobs first. Maybe I should inspect one of the new logs before proceeding with the compilation.\"}]}" }, { "type": "toolCall", "id": "call_7PNbI9erZlbFqOtcSijsIXsY|fc_0d29dbf88c868f5a016a12c18871648196ad535abdafecb7e5", "name": "bash", "arguments": { "command": "python3 -m py_compile /home/sebas/pi-config/scripts/session-memory-analyzer.py /home/sebas/pi-config/scripts/session-memory-sweeper.py", "timeout": 20 } }, { "type": "toolCall", "id": "call_NLHbt00c0izinuX8FYOZTMex|fc_0d29dbf88c868f5a016a12c18871748196979216c3823028c8", "name": "bash", "arguments": { "command": "python3 /home/sebas/pi-config/scripts/session-memory-analyzer.py --job-file /home/sebas/pi-config/sessions/session-memory-jobs/20260524T091411438822Z.json && echo OK || true && cat /home/sebas/pi-config/sessions/session-memory-jobs/20260524T091411438822Z.json", "timeout": 60 } }, { "type": "toolCall", "id": "call_JQ73J4Zm6EaX39pxvJyoz4IY|fc_0d29dbf88c868f5a016a12c188718481969d81fa1236e32407", "name": "bash", "arguments": { "command": "python3 /home/sebas/pi-config/scripts/session-memory-sweeper.py --once", "timeout": 60 } } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 1308, "output": 240, "cacheRead": 193024, "cacheWrite": 0, "totalTokens": 194572, "cost": { "input": 0.0032700000000000003, "output": 0.0036, "cacheRead": 0.048256, "cacheWrite": 0, "total": 0.055126 } }, "stopReason": "toolUse", "timestamp": 1779614081787, "responseId": "resp_0d29dbf88c868f5a016a12c181fed08196895414927e54bf97" } }, { "type": "message", "id": "3f765b80", "parentId": "7388a974", "timestamp": "2026-05-24T09:15:49.238Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12c1bf2cd4819680458b762eaf3cb9\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABqEsHEjr3uAO-T9OUAwxhS5SzIdkW6U9OZ93YIkNmEawBcFoVh4Iea5k3BLPBxEMBE_pHuzC_yRKF2E0DdT7pz0Zy1u9qV0oHQ1ezZ1vAFbhuGT3DUMbwb01rhfvCW77yZE2dnaL9sXDvtJHK9CSb4EHRtIsuQwXC9zc-58NwMgmJcZMre4tRD4S8rj-sXFx55FysvxBcEi8emzk_Tc9IyiOdeHCfvLEq_yySJeEyquHixtMD8BF_nLfScMBGDoXKiKoM08Ta7AkErg10ArJH8Ybww02xYzSOeOovXQvU5ACSE0q_qfD5JTTJ8C3OgLYoGKc8LeQYI_OxqeVrjVW_8n77zbKMNANdTDA6_FwFx7Hedr3hLuwoRn9lV1aJ0sLuAjz0KZoKhgk2eF36wD3tNbbjHtCngMNglrxIT4L3vo98VCuRAveLgk8_yIdKNko-YS8j00_UzpuKm5dsehlkdjty544cGjYqVEzA5OxKJ2JYThxj3QinWzf-619Eb78zeNoXyz2WJWYMh4lMDUqtd7B7UbNClvw9epelQ3W8VAWOE7hSHqBLcZlQcayA7rx7iXrsav2yspQKj5zupwzd4EFpiL2dFDdiGHsZDB3IDQm4LZLbfY_1IzqxyzLnW7tcE6Ke6KyTM7F5pUeTfOU0lVDt8L_UR87S5h1t2mvc5o-pnAXe0ppzcp1_00CMEUBU5H61EyUrOLb8J9mNSHgh3qNrKBn5BHRGsns7pUrKCAkICbSgOnSpG4RuRRJZqyDD0hEUEeDbFN_z4kjUklUZNB2IBYlxcFA4qMhgyhThrATiE_iX0LrMFwmt18BWm3NsgjFKv6HvnK5LM0aRTpLt9CQngYgVPeGZLbSqz6nyLJ_xaAWNpISiga1QmNUkQcitahoZuyBi4HID1GDJyD6AqsqzIPYa39JHC0ZX5YYZtr2jML9CynSuINe9-zTr6j15Ti_6FaWWu806l7A95hjGe3cZSObpwonyLbx4F76-_ADhdgATzF4Qaas7YmHpTYddPhEpaKeFwcVskOBdj2by1iK6SfhjOUCk-jQnrMru0dBuVp8yrCAWC6NfmLHAwnzhqUnLwR0xc9Uc9BdSPGH7bQ5hJjpnYXI-XYqC0fk2Ni0xpxj5bo3cSOKDeMfUmC4vnBD4RkVSI775m4kJ81v1dfbkbRguYxX_CaAHj92H4GqkE1U6bbec6mrtQXAtDIl0PHgp-spT4L-Yw_faZ5ceq14F0ltkSQepEKeQfKGNnrtbpMPwerNEXWlZQjZ8l-_TovNmUgZfN-eWLuZeAumQYvs63ApeAqsEDvAkcpUmxtZGEhCb-bhPJ1R-SRlwyvdDZURsPVd6nhQVK95BRxb2fA88XZKL6jGo7l_m-xyIFgIe3DQeHX7h6s4_BkOJVGkjY2vBIOR7BIHD9aRPpeNNgTvsvHL_x3Z_EDqR720iJ-0PLDxVMocykIeIBNBxf_VX37T0XDaY61Qg2DjfDfpKQv567OkM7hay_joUp2LOBKi2t6ng1lIzJ_ETK1uvgjByu0p3MPG3ZhkkE26c-5UlrT9lSJMegsYaTXCxDPSYppnpyyuQTPRvBpe0xo03uOpRd7m3ePdBQyrHKVewZmtZ8bf9p-4ceST0hxBV78Tk35Q3H28COCR5l5Rv1v_Foxx9NpXN4FRnqOugUv3YMI8rBrXHoHg0Xbdz9q3RAAJrXAQ7tpvYjOubFnb5hbVcF-uxog7ORL3GCRI8g5ujypK510gk2D_orJ2xky6dRcgny2aHJkq0=\",\"summary\":[]}" }, { "type": "toolCall", "id": "call_VgBLKwnQkoszBOzee7EXaFvW|fc_0d29dbf88c868f5a016a12c1c4f74c8196b3841f37dc4c5946", "name": "read", "arguments": { "path": "/home/sebas/pi-config/sessions/session-memory-jobs/20260524T091449627951Z.json", "offset": 1, "limit": 220 } }, { "type": "toolCall", "id": "call_ztmWRPOd25wVMMkIFPRCMM67|fc_0d29dbf88c868f5a016a12c1c4f7a48196bca7808a55afb85d", "name": "bash", "arguments": { "command": "python3 - <<'PY'\nimport json, pathlib\npaths=sorted(pathlib.Path('/home/sebas/pi-config/sessions/session-memory-jobs').glob('20260524T*.json'))\nfor p in paths[-8:]:\n d=json.loads(p.read_text())\n a=d.get('analysis',{})\n print(p.name, a.get('status'), a.get('saved_count'), a.get('fallback_error'))\nPY", "timeout": 20 } } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 20624, "output": 302, "cacheRead": 194048, "cacheWrite": 0, "totalTokens": 214974, "cost": { "input": 0.05156, "output": 0.00453, "cacheRead": 0.048512, "cacheWrite": 0, "total": 0.104602 } }, "stopReason": "toolUse", "timestamp": 1779614141576, "responseId": "resp_0d29dbf88c868f5a016a12c1bdbd188196958fb24dc42b6030" } }, { "type": "message", "id": "dfd900d1", "parentId": "92395b2e", "timestamp": "2026-05-24T09:16:00.548Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "**Considering job status adjustments**\n\nI think I need to adjust the job status at the top level, though maybe it's not that important. I could leave it as is, but I really want to avoid marking old jobs as processed before they've succeeded. It seems like a failure might linger. Maybe setting job status analysis states would help? The top-level \"queued\" status is a bit odd. I wonder if I could set it in the analyzer once it's completed. Okay, let's patch this up quickly!", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12c1c6d2088196850926936dd53bdf\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABqEsHJGArpNsqRMXDT3BMdicW0RCDShH_9B-ANUHIYAdsPs_CUNycSU0JP3Hyy-54EtNQ5wAsnxGPc0wBKp-6ZVcPyIzxLwGY-hTn0V4T7elY_EZKoh21_cy-TZ0e1BWfp16BpbvD5X7F85jANeIDbP4oFMfI6UYCfElsbN2OkcKhiKvUrkZL3B_uVAAAnV00TFt89XDDkVAN6cB-yzOAf5Udt4SWm6qs4_cHYrB7Pk_-LXSWJ68Z_pRDM9MhAjWnthdC-D9ky3Bo5auY0DXms7b5URKJ70PZM84zTs6_s99hiGvzQbmvnxQOVQmMVPIFYgmooWoiws4IvU9owzAsciBL3M4GdSeokl0j6lzfiNjl8cwAAP19pF2Kpgn7hTeJ90q2yzblTtzSmKBDxsXLc4b2fcHUaFGOigjcYrJiteVV0kDP4Gfem5AV1s5u1eNCbLvUQkxOVu3BcYs6_PaxNyRJm1sy1B2KhGb6lNrePbFMipRRwLhslAFPN8nq8tVOxDuXaQ8x8mZkcFzdJJtxyreYrCwwh2G1b4z1gGQ4mrHrW4ZBYO6A9dUdUIJ_En32KdihRuFW8t4eEgaWpBBPnDktpptmS1CeuttaKn5Qz2pPatwxLY9BbgVm3OHoqiqPyapfqiy1JIu5h4hmbIZUwfZ3lEQ_ijpZuFnmqawXCwDpRAQ8jA4IhTb5LOnyJn2KmO7NVjzK2CD9ZPfaVq2C9PzZf4q1q99N-XKeUOj3t-Nt_Q3D4pesHN8aZ8wX9Ubc53-2k3ZeZG9Liz5QvEHo9qjCKf2z5V8Pi23IrH4e7QOvublQtdDTNp20cCmMT8RWrBDvgEtRRIw1S4PKFP7Ck8IJLojWe0wTco_M10ENczVMRsCuCm-XH_4Fxgoq4RyRn8tH8xjHChNDUY2rap2HMJvALUbNu0FRDqgR5gwp840sFPbeVyxQJWIZUgi-EKPaDcA-Aif5SSZw4U4iL3MTpqokcEnKTfsanG568o8303TVVAqUfylfLUgM_nQiISAMVSkqOtnmRsmEZbMZQZF4C6L_tevFdrJB35fHMvj_tpK23-36XOQbKqxHC8PlnpzjAt0SImAACXrjqFgpe2q4Yg03q_50HEOIE6Fl3Zs1LP7cLHxGzlheZshuo25q29DApxS-sY7ylgNPb2N7uA08syilzL7rUpV9S66B_oRGYEFJR3UnfZnWMItVB1swaK_Pijeu6iSeV4S5q5zgVA4ynrwh06b3wnlF_GESF22tCljwwYdhsYs74LZ705e1Ts0tS9B-2CEPjpwyj843I7L7i8vWZuwjgioUhcapFrnGMw5BVcjiCZ3pvnJLtTZb1knzhEBjwyKh7cdDe6NZVy6Pc7LZ0WgkqlJrBOub9tJe4q0dOL5UmcolK9TuLpWWwhBPD0OoOfdMO3axOnIU6V2JyITUCOA==\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Considering job status adjustments**\\n\\nI think I need to adjust the job status at the top level, though maybe it's not that important. I could leave it as is, but I really want to avoid marking old jobs as processed before they've succeeded. It seems like a failure might linger. Maybe setting job status analysis states would help? The top-level \\\"queued\\\" status is a bit odd. I wonder if I could set it in the analyzer once it's completed. Okay, let's patch this up quickly!\"}]}" }, { "type": "toolCall", "id": "call_oDReD0wIWCIbrrWVwa3zygRG|fc_0d29dbf88c868f5a016a12c1c96534819692196d47d0a33674", "name": "edit", "arguments": { "path": "/home/sebas/pi-config/scripts/session-memory-analyzer.py", "edits": [ { "oldText": " job[\"analysis\"] = {\n \"status\": \"running\",\n \"save\": None,\n \"saved\": None,\n \"memory_id\": None,\n \"memory_ids\": [],\n \"saved_count\": 0,\n }\n", "newText": " job[\"status\"] = \"running\"\n job[\"analysis\"] = {\n \"status\": \"running\",\n \"save\": None,\n \"saved\": None,\n \"memory_id\": None,\n \"memory_ids\": [],\n \"saved_count\": 0,\n }\n" }, { "oldText": " job[\"analysis\"][\"raw\"] = raw\n job[\"analysis\"][\"result\"] = analysis\n job[\"analysis\"][\"status\"] = \"completed\"\n if fallback_error is not None:\n job[\"analysis\"][\"fallback_error\"] = str(fallback_error)\n job[\"analysis\"][\"save\"] = bool(saved_items)\n", "newText": " job[\"analysis\"][\"raw\"] = raw\n job[\"analysis\"][\"result\"] = analysis\n job[\"analysis\"][\"status\"] = \"completed\"\n job[\"status\"] = \"completed\"\n if fallback_error is not None:\n job[\"analysis\"][\"fallback_error\"] = str(fallback_error)\n job[\"analysis\"][\"save\"] = bool(saved_items)\n" }, { "oldText": " job[\"analysis\"][\"status\"] = \"failed\"\n job[\"analysis\"][\"error\"] = str(exc)\n", "newText": " job[\"status\"] = \"failed\"\n job[\"analysis\"][\"status\"] = \"failed\"\n job[\"analysis\"][\"error\"] = str(exc)\n" } ] } } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 7069, "output": 517, "cacheRead": 214528, "cacheWrite": 0, "totalTokens": 222114, "cost": { "input": 0.0176725, "output": 0.007755000000000001, "cacheRead": 0.053632, "cacheWrite": 0, "total": 0.0790595 } }, "stopReason": "toolUse", "timestamp": 1779614149380, "responseId": "resp_0d29dbf88c868f5a016a12c1c587f08196b7b722db88459b6c" } }, { "type": "message", "id": "67e95eb6", "parentId": "dcd7c87e", "timestamp": "2026-05-24T09:16:06.850Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12c1d3241c8196a2862076753a63c1\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABqEsHTZPyGghk6mTBlZBGvL_14tBl4i3RwfMM6jmdURP7xmxGNVYGp-aqX7tpuQC5D6gHbQ1ysvIbs8iFTCRW_TrbHAOVRLzIz-2vX8xzANCwfEqCDNbbM40Nte9ZZB5XR1s1SogOjzRt8GLGVHKUztFKfX3zX9wHGlSAyqn9mRv-CsVgBDXzfQIbZV0jNLtfRqNXVMSopWuPaK-C_UPH9bFdkCaa2XX1fInM5fRBtGb1pE1--sI83XZyM7sRVeejMmGo-BYEdrCdStGFacBftLWJllgIqnwDm9FH2JuqWXsgpJH3UenhBfdxV-5rw2h37e6GpEJvXCjfbowMFZg2-lciadPSl6OXu9xGYNuitDhLVC5tdM_tcC8tOSdpImhKzRX_Uo2RssDkWB2irovaVXoIl6uo2Ho-Vrp-t-VWW5i64-1oy0jjffKlwCMt_n8di2mjKsAXSjFWiDusUhSG4N6RARq_UPNMr6qnX_ZtdjcfBPomiotJASlK9fB-TiwpEMSJMIkZVbOaRN1ebmHGSvlS8--49RIceDSzhczxsmgPsuOEZMRRZfDkJWqaPKVDju0R2Tu46GUvqB9nRbXSnqVdNfb7mgO6POKK98B_GSOOauC8pcsTM7FTCTw29Lkjn4KTrjK3X7EQHtHIPyed74Co5dS0sRNKGoq1DWJAsg2LFrn4fIHqLoCJXdCxXrFJxKKjXkKiEAw9kKqk_NGs_FB8878eLolxFfD1zEWPBjlKjZslMnefO7RwgfvFwcx2S2-_ZasxX6DRIIkXD0fI_YF9Ax0dsLfs9JNlYQkGwyqv7Y6zJqAiHUMRTVUkkuFRzV2Fwwg8G5wizwinptR4xp1HBKbIEibZokVS8mZvWunryU-utphJqSIMMMqLJgwCUDctFHbBEI2eN39643yOA-05gq9TFwV_1imYkM-1vdS4qDcQwm3I6n99p8haMNlS7vmhH\",\"summary\":[]}" }, { "type": "toolCall", "id": "call_odPvJ2OlRCkFMNqcV14VAdqq|fc_0d29dbf88c868f5a016a12c1d3a8508196bb768a65a822502e", "name": "bash", "arguments": { "command": "python3 -m py_compile /home/sebas/pi-config/scripts/session-memory-analyzer.py /home/sebas/pi-config/scripts/session-memory-sweeper.py && python3 /home/sebas/pi-config/scripts/session-memory-analyzer.py --job-file /home/sebas/pi-config/sessions/session-memory-jobs/20260524T091449627951Z.json >/tmp/sma.out && tail -n 1 /tmp/sma.out && python3 - <<'PY'\nimport json\np='/home/sebas/pi-config/sessions/session-memory-jobs/20260524T091449627951Z.json'\nd=json.load(open(p))\nprint(d['status'], d['analysis']['status'])\nPY", "timeout": 60 } } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 961, "output": 182, "cacheRead": 221184, "cacheWrite": 0, "totalTokens": 222327, "cost": { "input": 0.0024025, "output": 0.0027300000000000002, "cacheRead": 0.055296, "cacheWrite": 0, "total": 0.060428499999999996 } }, "stopReason": "toolUse", "timestamp": 1779614160557, "responseId": "resp_0d29dbf88c868f5a016a12c1d0be2c8196987579e0ccefc2c7" } }, { "type": "message", "id": "9db94f5c", "parentId": "293c492d", "timestamp": "2026-05-24T09:16:37.599Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12c1ec55988196acf14c9d060508e8\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABqEsHv_PD7ZnxeBsDEaoVHBJPsvKlfXI2ZDVQqIPdJ6uqZuDivQWW9_23ypFmOyYq_6GH5NrhLP1_tciewyDQK3FinxaeevA38c2kMPxVtBBcc10BfS7klD4nquZcuE9IoZExSJyHvfOitj75lk-xR5OWfnTFkMRUH1LqBLbT4hUapfeyRD1sHoSnZQCX0enegnvYMuxc9lcUpl3UFd22OYLtheQBrYD6U_p4gv6_gTvE54HrmngVdNfAayPL7X6ZS-yd_bd1HV-1QEIl29Kxho7H7tK78v_MfsVRPxinO04GLaj527_4IxjW5f_BOiQ3VBNjWlw7AxgK_abozhwg72QgIk6mEetWYaNejPn6Dih2HzvH0C0MJR4PK_8fmg0u6RTlbRWhKdd-03ackzPhOohP7-Bs3bHKAU23o8Zn_Yf_eSVaZvIDmXnSIGAODnGUg6-3uBFsQArzRxEswm3lbHqS7uY18elH_BPX1HV2_sPiHwsBtF2vkal1epvqsY6yLHtGlhoqyDl6enrsrok73tK_UQ_iHzgpBdjkc3940fo2h4Lwsquuj2UwKM3hlFRmMXPg-VUQp1K--o7jmCQlUTVGf60Nc-3t81HQ67uN5b4vgTXUJixvnJEzQTFOCIofprdgXExXBZ15xBiT9wXWWfxJAy_UKoQLsQWYUcH4Dk6xsGRjE0NjFotkqQH-7v3xPpDErfuyKD3O3DGpxNJBmLzr5TkVI3ox1frJFgWzHeYAGfA5q4UvjvSkToKktFqVGF0f3z2CeTGMBIKcTumZM74hnJD8vd-k9HPmy_2HEjCvuIGuXYIQqkchI4bwOIIMK3oXlRyDg-6492J3ftnYRC0iJgDOJctZkpNxweID8PBdzdnlwhUwcnvnP8eFDdtCU5JQ3dv8wCs9vEqgB1U4KGCFdHYmmPaTHVe3icat_xCGsQ8sllwXgFTLk-3l8JCF4dXnmonDePl846NoM-e78xr1uWPfaE3S3JYu3PcUw_4n8CKlGwLB7X1O74HyLyd1vQao3PkUfZFVsWj8za4ZwvhDZe2gO3odegEnqpqybY5bzNELCjNi13uaPNhNwFfzepMlzUsk-j-f4K2WOYDvlXlAVUWlN1Ib71AThcI40olxHSVk0U1lrISfKQMNDxgwcVdZrTQMAPZzUdBdXhaW6sQQ0loJAXUmfcJSgfgUTYJBrl4GnmyPcKNtrXFP9zk5YlpApMx1TS99nzQkSpf6l_SIBG3go6JrnbeXuQtcvI3yd3_UMfl1-2f-uR8EW2anKIjc-6Y2iALsMgj5LfLwScSOfPuQG0nFtheMcp1duGnnnaffvON3u4TXCbeoczbLxKyZjFdNC9Othbpz5xl8hqK4rAam5wZg-LPF1gL6vTQR9yM2dF8Ngwq7bYxP1PcuSBK-FWVBJ6K4-rvOZiO6ZbuKFQSe8i0p7kajpxGh26DiKstP_rfU7gtCV63UMkB9Od8z-jO80-0894yZnixADowiWGQa45BbJYZHCUMoQGGSpOQsDHaUa6xBLuBVBSomRBgFVYoh-NjCvIk9t8XcfUvwN3ju08uEwfn-lcC8PiOEgaP9aeQqj_ZvSYZlu5oB2uAcZhTTTBAKzauln6dEnp41HL0OkshMnx6w5WaDQy2vyP0FVI1BMrRb42pMT8nFZPacb52YlKQtMUjR2FFN83i7OyMnTitt7wP4SLoXle5urfvxigJoPCP1UOSVqVoUMO0i6eKqCatu7Ot-Tee2k9vEcGfj44DBztgh4UaAxCpaofAo=\",\"summary\":[]}" }, { "type": "text", "text": "Done.\n\nWhat changed:\n- added one periodic catch-up path:\n `scripts/session-memory-sweeper.py`\n- installed systemd timer:\n `session-memory-sweeper.timer`\n- cadence:\n - boot +10 min\n - then every 6h\n- it scans recent sessions,\n skips obvious loop noise,\n and analyzes anything not yet processed\n\nAlso fixed analyzer behavior:\n- before: if `pi`/provider auth failed,\n job just failed silently for memory purposes\n- now:\n - tries cheap `pi` analysis first\n - if unavailable, falls back to a\n deterministic session-summary candidate\n- so pipeline no longer fully depends on\n working provider auth\n\nDocs:\n- updated `pi-config/README.md`\n to reflect periodic sweeper +\n fallback behavior\n\nWhat stays:\n- session-end dispatcher still exists\n- but periodic sweeper is now the\n reliable catch-up path\n- this covers Telegram-heavy periods\n\nCurrent status:\n- timer active\n- sweeper service installed and ran\n- new jobs are getting analyzed\n- some sessions were skipped as too small\n- some were ingested\n\nNot done yet:\n- AGENTS-promotion suggestion flow\n as requested for later\n\nBluntly:\nthis is now much simpler:\n1. opportunistic session-end queue\n2. periodic sweeper catch-up\n3. analyzer never hard-fails just because\n model auth is broken\n\nIf you want next, I can do one more pass:\nremove/deprecate old confusing paths even\nmore aggressively.", "textSignature": "{\"v\":1,\"id\":\"msg_0d29dbf88c868f5a016a12c1ef0b308196bbaddbb102b24d47\",\"phase\":\"final_answer\"}" } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 2512, "output": 457, "cacheRead": 221696, "cacheWrite": 0, "totalTokens": 224665, "cost": { "input": 0.006280000000000001, "output": 0.006855, "cacheRead": 0.055423999999999994, "cacheWrite": 0, "total": 0.068559 } }, "stopReason": "stop", "timestamp": 1779614181683, "responseId": "resp_0d29dbf88c868f5a016a12c1eb01a48196bee73f4179e7978d" } }, { "type": "message", "id": "dc97c500", "parentId": "9db94f5c", "timestamp": "2026-05-24T09:29:36.149Z", "message": { "role": "user", "content": [ { "type": "text", "text": "[telegram] do agent promotion now and in case of memory upgrades downgrade on the periodic session also notify via telegram" } ], "timestamp": 1779614976121 } }, { "type": "message", "id": "7b2fa7dc", "parentId": "dc97c500", "timestamp": "2026-05-24T09:29:49.176Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "**Looking into maintenance upgrades**\n\nI’m considering whether maintenance can help with upgrading or downgrading something. Maybe I could notify users when the sweeper provides active vs. inbox counts and AGENTS candidates. That seems more straightforward! I should also inspect the telegram-notify skill to see how it can assist with these notifications. I want to ensure everything is clear and direct for the users. Let’s explore what options work best!", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12c50479fc8196a1b4840d01c71a57\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABqEsUM9Lg_ZpNr2N70rS7-A3qeoqX6Dq84ar-qV-HpoTcwjTM-5TwdQrLoOPyJM4SOZWohCIVbMQL5L-KCOaZgschO1nzhBUjjVAMnxKF8hxlZgyMZVM3owL1ho7WcAo9Mw4UqxvICyte_KIKxy_BQdH5Ih_IXIEGa9wAhD30xebH3V-bPTe4AO03WfcUGO7aZ0CEtHLCOUMJS_51lqq_vkxutgRRdtziOEGnYTMCD6hLjSFd1NE_hNeCKygUGLw2O1VeMr9ETjR65CrHx59MaZYfE-sg7KfI7DU8IrUNNjL7C8QhpRlnjHw__cLG1rFK77NeQ86T2h0giktsIZtvajMFxsPwIqF4UEB3aW1qnw3pizT84podfR61bBcqVfAxXMGQyew0KnUKQZYzzHQ4Ni7Gwr5B7_zqSsK5kB4HEpcQ7ehOiUR07UutLMmG5vzuqVdVejc_eE2XxN2uFLDi-VPPCgxVBbiCkhpWWjAgnVh9iBsqkxDCKiApjceuh09gwSe2Eg-a4uDyiKxjv1pNK7k0I589mgZgqUxDv7L-CGko3Q9Eu8DXLnOIDk5HtMcNs0BXZpXSmcP0EnRW3G9rdyajSE5wxA5ixrOY6J6-l6Re4Ep7HygKSjc_EawBCjlMGHb6wyCT0-cdxYGCKLc3uJ-r2zS12Vvs309RaLHJTMQopboC30ITwzv29b_ZjhTk0pza2zf-gm60h7mXXZrGHyPOTBKECpQ-LwtFeQ_AT39dXHHNdcpc0IPQ_aozjp4NIFVb4OV9kPxZ6JQEr0hMW4C849C_iUu1d2QO9Cj6C2t9hXA4FdwIR_Qywy7YrfVy3kYwMttTNL2YnoIPaJDVvTNC3FYha3bDOjP8ouAE83KN34v55JnCWXEWbSbSu9uwEnpTCcZK7lUiQptqLWERj7hXFQxMEbtdDqjwnqI4EtkLuUrcS17G9AdNjfF9Zjq8Qq3QJAw_7JaJHwQ1SNd5L6VWC9T6tE1j6K2XvCefQqu9XvfsDk1XlzwCb5rX28HrYPjHS_mk64KQLBURpKFOBezIykmJu88_W_3RsScmSdR_Z_krOQkNqPwI7CW4IFaUuwEgfv30Lf-Z46PGVOTOeM_72HmCAUuWXqq8Xno4pLpQSYtmqMbzK00ErTNS53OklA9aHXgl1ZPAVlrHnZ7yyiGu7pEDAMZx8VLyBm9rAthzXERsXASXS6SRq8G9O9fvVU3H5ZpUXjwizWPZNz6ZREsXpqX0Cxl2FULA9ifPzupjvkj5Z6u4VinNWNGStp0yR1PIagLR_Xh5aro7unY0ia3HUMA-TNsKxQQVuf6ZFa-9_dTLWZ6zVfIB6AoKhPcie595upVjiTkthfFagXdOVf5gjUIHD6NG2mcVXeiQ9FZbpNbAGdUEoj9yTJIqpHsPd5rib5RFmqZe3IwfBQHGQt1ovOkw8j8KXZIXJzN0bJx8oY4pp43LEA9IKGKL-V1k-TNFHUqQYSpt3avjWGf8yaYsE_MQFcrBNECFMw8ruZcKeKCS1GDwCdRQKPSGNGLYAPhuA0senZ3EF126bDswBrLkahy4dg2KCr-VyHRw_eowb-DRS56GRuSsvyCNquB4Io2_m9mRhoImI8mBK0-hBhOPNc5eJ6X-gFmGAVPZWoxJqtFIo0WMt7lPVzNUF6CRTNQfSemrnuZ7r3oBKh1vMYmhtSzmWUKS-Oclred_M4TFb1uLnI5m4etsdV2TT_3WyH4OQJ2GkUlBaivl8xPoeUW_8C1aaQkowCSlI54vWZWuNANvLks3YfFgljNrmTXmckWYLsm9_b-Lw1vgDkmk55pjvm_IMStnDKUZVH8oImAuoHGZt79pbLy322tL1CxMxP2yDbuiduNfxxn3vb18w_QfuKGHiV4CbI5FEeOY5Gm1uNhmmvP4mEYcuS7EvcsrHrrmLlUQuGOEepx14M89pWVcEqgy8TFAUVyN2nJjBSfpq6Hl5lssx05izQKxpNgoN8ZMYt5pRvnPnHo_ZMgi9Nf4lz31Wh-bS193Vq7zgCAzoR8HwWuSLxW9GPTZca8n6AHc5SIr5XEAjJQVeMpLBG_5DJ4sTfevKFd5MF9_Ip-HHm1LyWsWtVqlTV6Df0NDIa68i5TvRIYByqyTjxA8i90tCl0DcJMbzlf4cSuGM7nIH-hsVZqeB28DOf7Nvq7FNGL9H8FXdCkzNfUcPe696P_4oRJwL6cmrxTZeaaJFNOeUpb-3OMHm2Nni2fjg63-02XOu09VJMgLZdT8XBXfv5F7VQj5hAOhped6apwsYvvRR0FgSrJmmHCTbBLUN2-6ejAeij2DC6brDBCtug-nEM0hLJjAaeQA8Y4k9rp7ELJ7bv0283-zOOi-LcyWyLG4jL7JMfTuPofDnsWHmAOGq_Uh8ruAC8EcjgUO5tc5H993XFBGKA-KYX0felpusGVxKXYHVY-66xJU-pvh3cR0fuDPrqICo41YwR_Ywl5yNY9QufUpEJaFfA4nEFI-InuZ-CN3Kz1-AMFQU4dmUng6sdPTg7jJQf6Ga6IoyNjSk4AryWbbobPQopUh9n0dDZ-qdK-S8ije6mXRYvQuQUoPmghUdPp_tYK6_EimgHVnyU0V9qEc=\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Looking into maintenance upgrades**\\n\\nI’m considering whether maintenance can help with upgrading or downgrading something. Maybe I could notify users when the sweeper provides active vs. inbox counts and AGENTS candidates. That seems more straightforward! I should also inspect the telegram-notify skill to see how it can assist with these notifications. I want to ensure everything is clear and direct for the users. Let’s explore what options work best!\"}]}" }, { "type": "toolCall", "id": "call_4V0f5ikhj428zEWelK3SQZ23|fc_0d29dbf88c868f5a016a12c50ce3a081969e0a2b1af60cb857", "name": "read", "arguments": { "path": "/home/sebas/.agents/skills/telegram-notify/SKILL.md" } }, { "type": "toolCall", "id": "call_A24eAkQvytLazjYWWozJXGIF|fc_0d29dbf88c868f5a016a12c50ce3b08196a7c3b2e8fac5b25d", "name": "bash", "arguments": { "command": "cd /home/sebas/agents-database && rg -n \"consolidate|status == \\\"inbox\\\"|update_maintenance_job|memory_conflicts|promotion\" src/shared_agent_memory -S | head -240", "timeout": 20 } }, { "type": "toolCall", "id": "call_zxqy5rJFULQF6LekDlK02gqI|fc_0d29dbf88c868f5a016a12c50ce3b881968f14a9d783f1e674", "name": "bash", "arguments": { "command": "cd /home/sebas/pi-config && rg -n \"telegram-notify|telegram\" scripts session-memory* extensions -S | head -200", "timeout": 20 } } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 74443, "output": 390, "cacheRead": 147456, "cacheWrite": 0, "totalTokens": 222289, "cost": { "input": 0.1861075, "output": 0.00585, "cacheRead": 0.036864, "cacheWrite": 0, "total": 0.2288215 } }, "stopReason": "toolUse", "timestamp": 1779614976129, "responseId": "resp_0d29dbf88c868f5a016a12c501d61c8196beac231f18fd3dc8" } }, { "type": "message", "id": "84082059", "parentId": "5efb5d42", "timestamp": "2026-05-24T09:29:53.090Z", "message": { "role": "assistant", "content": [ { "type": "toolCall", "id": "call_YBTiOzKK4rOLrCD3QmVA5fyg|fc_0d29dbf88c868f5a016a12c510d13c8196b184fd96e546f9e8", "name": "read", "arguments": { "path": "/home/sebas/agents-database/src/shared_agent_memory/service.py", "offset": 250, "limit": 140 } }, { "type": "toolCall", "id": "call_jOJUm4nmevHPoBNH5W9DqxNP|fc_0d29dbf88c868f5a016a12c510d15881968b3ad47d4582f739", "name": "read", "arguments": { "path": "/home/sebas/agents-database/src/shared_agent_memory/service.py", "offset": 318, "limit": 120 } }, { "type": "toolCall", "id": "call_ugnBNLC2XowaWNmXe2xGr3Xs|fc_0d29dbf88c868f5a016a12c510d1608196bd11f9332f1a7de1", "name": "read", "arguments": { "path": "/home/sebas/agents-database/src/shared_agent_memory/engine.py", "offset": 1, "limit": 140 } } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 1129, "output": 123, "cacheRead": 221696, "cacheWrite": 0, "totalTokens": 222948, "cost": { "input": 0.0028225000000000004, "output": 0.001845, "cacheRead": 0.055423999999999994, "cacheWrite": 0, "total": 0.06009149999999999 } }, "stopReason": "toolUse", "timestamp": 1779614989201, "responseId": "resp_0d29dbf88c868f5a016a12c50d5b84819686829fbac6e18434" } }, { "type": "message", "id": "3bdd3d18", "parentId": "29a96926", "timestamp": "2026-05-24T09:30:12.249Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "**Planning notifications implementation**\n\nI'm considering implementing notifications, maybe after saving in the analyzer. I need to decide if I should send a Telegram message when the periodic sweeper runs or if there are archivable items. The user also mentioned notifying them about memory upgrades or downgrades during periodic sessions. I might inspect maintenance jobs to see if I can promote archived items to active ones. It seems reasonable to notify about promotions or downgrades whenever maintenance occurs, as it aligns with the user’s request.\n\n**Optimizing agents and notifications**\n\nI think it's a good idea to run an agents-database maintenance status check. I might need to locate the maintenance job configuration, but maybe that’s not crucial right now. I want to implement a notification helper in the sweeper after analyzing each job, and I need to prevent spam, perhaps by aggregating notifications. For AGENTS suggestions, I'll evaluate saved items based on type and importance. Modifying the analyzer to derive agent candidates should be feasible, allowing it to read saved memories and send notifications accordingly.\n\n**Summarizing analysis results**\n\nI’m thinking it might be enough to derive the notifications from the analysis results. The sweeper could read the analysis after each job and send a Telegram summary. It could say something like: \"Session memory sweep: saved N memories from <session>, active X / inbox Y.\" If there are any AGENTS candidates, I might add, \"Possible AGENTS promotion: - title1 - title2. Reply if you want a promotion.\" Also, I'll check if the maintenance consolidation results show any promoted or archived items. This seems like a clear plan!\n\n**Considering script execution**\n\nI realize this matches with upgrades and downgrades. I’m thinking of running a sweeper after analyzing the batch maintenance tick, using maybe a Python module or direct bash. But I might need to define an environment and virtual environment for the agents-database path. It seems simpler to use subprocess with a specific script, but I’m also wondering if it’ll accept the “--once” option or if I should set the environment first. Let's inspect the script to clarify!", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12c51320448196a269c5a1af01d5b6\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABqEsUjYeatQOgYlT0N8saUIDup_aH7dQmOoAM_z8r28i1loHeTWDhACsV3DBRedOqHq798brDwkWxWSZAHDK1kLzJwp5wL5OcjdG-dUC-cwpVsca3XTD9ZW3WOP9UvzdzaPJpGunUfSgf3iaLJSFLgI1Ybwt_-rar7wM7c7y7o9k6Z5JBkZ_L3-9Gw_1t3JaN775nr2S9ppeFBiUEdQYLLJQaIetyDGVFBYvxd9o7B2Iyiyyf4toaphh180zy3Wk6PisIMLTiPD0FVFB83TrcEVAx48DCNryBtXdMGmBFCZ9IJ62MOPw4ntR15t9pJIGvdmhRLMAxgpPOjizBm0-9Bqw2EaVePqfvITxW_kZFCmtVS81yKCArO6Ty1SkYRPBTkyx1kZrOSGy7Z_TLLNK_an26SAtMsoaC8D1cdv0HTIuT1tuj6S_Xn40ZjwyeHOroy2JXMtHeeClxxL5xi7H7SyrM6wETcno2l7J4VccTV5fm5l-YRv8G3FNpEYEWHkQVV51O5yeGgE0RwbqC_Fw1gxl7iBKdaXHKsN2uidQEJN3PCmYD_wVm81RAoU7k94ETCaoSTRYPW_jesKAsxdDqw_8dIA9wJLVX50Q5auO1yies6tvsP1lpwxs38_5FRZQCMP-HW1l8t8-c0mGcTto-peSN3P4iIecVyQmJcq98c3zdrtIbTHg3h-vfQgxElpiDO2K349Q_qVgY5SdCUYtCWWvBZPhu-q6NK428PMQuCTPY9yoVBruiKRcZECc1KRiTm0EWkEIKmNyRg4pZkm3ZgwH8d87brqVwfwxU8-8txW3saI9C1MNjQ2sOF4ZnvxzrEsMZCvrV6ltI1GB6Cv_oyJhzcW-UI2DMNoVB5NzjJOEBlH9ydrqXYF4sz_ZPyGw3HdVaTSZ7E2IgMSwIkrSYj2jy30lQ0y362IqeAD2YsY6pdudMtb5ra0l4grYvF1jnAXu_r353QLFyGV_0zI8RSLZYtLI7SmLJqs2KHcapQFD5288NOxchMLGB81oAjzYfWomvPAXF7BXYL7EVjO3LnwKh1cQj32yB8Dzma0bGuAPcHZKLH9jeJkUw3_VV_RXpgkBUjQjlSemx1LzmaT2Gas_DVndUX-YU_g8zdc6lL3iN_grxNMqFDQHqsJ8JI2bgQHLhHvK6tDOB-Ugy9NglPXvuNEr8EPgQMkC5qzZdo04rQ2vsngjX4Pg8uqkbM0Y0wogsJ6PyrLs6AP0uyx4ErhGJVkW_TRpiyPNL9d3VSQSE7t9m-OPCywCYu9iyN2j9S5CHgCS6DysmPld0IiROwOXqnfxXghaH1p5x2tpEvrDcX56IbSiC9sCHt2D2F9JUsgMaS8Wfg0JKIy9nf5Ydr023GypL-atctj5uR_tzKA6ASRutMbeUEtIMtZuDPGLBq9NgtpFevYmgBXexmzetQnJrOLNZZpxKAx8t-BbRdP2n_ImfAuHPGYnw9hYvSUBzYROLDgVCoXh7r1I2btkK5vHjym2a6FFZ6S_cHCAQfA719BGmtoEsXNEpM8hPqABCW9CZBZhTEIegOzpU9mlH8ybOlxrcHqxVqXDUo1ngNk1XN9zVEFq2w62HO8FfsQOHYSu-GWNo3I0u9cV0yqudoG76Ma7u0GzoyBYVoP-EjhBv2bwEDQhhvbz9TRKXYmH9GdkXTlNF71_OJlSUbx8TdQC1TKxO6iZaip8Z_aODhEguDq2CHGRI-O_zy7ArhNLz0F7NP20LJzqI4_xZ4lpytAQu-8nJv7b6nTGcdLvA7J0uOvVN5ifGNAmVGdwojFjWALoDzZEHS2sqhsC3Lba2HiRZfnqI4Q6H0KOy0A3Y87Ex6J7blbXFhLdYbUWfqpMZwL-49H0okwXZG5VWq4uImbdNNN0wesLfSDG5THBCgUStTTqiV9o5gTx0-CygMEr4Vzze55xCC9leKlyzTbPXsCFNN35hnruszX0bDLnoFb1oV-z9ST9KEiSgBfyNWYtuiReKvpk7TBV9g4qOrNZ766x3M57mHPXm7mhDgomtvNXA6oKrdLus9zwsJYzLftBJq4wTKd2szWkmYR-ooKuZyfcQpGzcUXST14xyA8Tvj5aarJcnD8CFwLIhDi0DgvhGip5ZqzR7_Vr0CDDk-PNkUMX3Oh5dXgySgAYOMfdqkM-keo-OxLBIiIZm00pCyRThKT7tvqFikpgsOL0gMTZBzul1o7fIyCKi-eZ-Te2eLQ2azqWIJj3vAJZXBFxCZ0TgicGLuGfH9ojSC8SRVr9EmCd8w9Lrgtq3CkWxSuvJS_hDVZSDzY3rS3Ww0LH_lKJqBAoN2qg9mCosjTL8CfhN4Tw_5WWM0j4b6hdu3nJnYDlukblA-SADdljxSQAtwaAwUxKgI6ujKePrsrL4lITMJqJUk3V4SXq29QWPVAcvoEQsOC_xlHPJrkicpKLpHTv3_xN-jm0Qis3jHsF1zTVe4KSnpKLz9jkR881RfzX8PW5f7vQko6KWSsnWf7T-rS3WnibUVkuWNal-e0XE4wohXjIXtTUGflvySqgweM0RgaXaM9sRoH5Ur9xlndWvVTluEACqQzKQFKjoSvRwYJm0oRPp2DzFeWNSqCYz_YiS-i5M0IyFCz41PGAPZ4NnBG1rZbNMy5oMO899rwOC4jbGJEnxSb054_R6JaleZm-DYbvKgPv_AKhudXfwpnV27odiicwsh1AOdInfB1rSbEDvTEGf4CEnwF5kqNYPLwGGsqHDnXlcYYWBQUXBV5Ma0w7-Y2lo8LewdWsHOrYQGCTkgsQEzUcb1GotOOlFWsEsSipu_6sKaAGOuSEJjjypyDtMRSFVnfj6LPW7O-LhGqux65UHHwdAXP-S-Jg9gbTzCBxN5Vc8SHp948pAMzx-RelVMdTj6PyfsXpEwali7h2QjxY3eu7Nx_ibZD_P110ZPrW0HwoXX73B_iDv4Xg5AKm294ZeG_sDkWH1l8oF7qdKud6pK9ZPYu68lZ9k8ovVIp4zTlGrz76EQP6cnyvOHcSuCpYto7USqzV113tsHoJhBTLr0h4j_YO5-x2QTlP_-CVotC2u0bXAyINkmBgB-7oBHn95qkHgayF61GAIVIknNYJURGvjYPDatBcsVL_mT9CcXlr9IDEHsKIrXntXiX53R_U8gZrE3TwNElbYB5dIY7Z-EkcC9jb5fvvMGKtJesHx2hegn021hJnrdcT71NuHyE07CV2i4V4ShKFmfZUOvq41dvYziVSKGgxSI_g67acFiIHIK0slagBDsR8TqN1a_VVRPZl3m57u2k6hWMpfSSDOu1VPzKa6vr5tdwAi0yGxe__zmrs8YuaUOcuXfM5xGNx3XXf0hO3WeS9UXgr4tPqKea_i4s6UOEU3Ls7jURaHb2794NeJYPthLCcfYYDT6XMDpvDqQOhRLacVrZbomRs61YQ9_k4O00959dKunBxbogGqn5sb0G3P4tpVtzS0-v6u7hZZZ7mTkb3_JRpPyCZNRS2tjKntlbIdldqMG3FgvC7ljbFQBRpSs8UNm1Z7CycMQO9GrSk6r7pRl5I28v-nq9BAO2x5saVCInu7IbVCHYqV1rzntgbRILmfxZx5BYUjQlPtk-sbTjglXpNgIcW6iL7VLvIQCtX8G1LS0DeV35wdekh5tOJq6K8JB29DyPnRr77sMq6RQE1aXaH7bdbC-QE_5_aVDpFhxmY3JkrVUkDpaKpdAh5SKPoL7KnqXybDX-0AaDi86L3kNx4NnG9dMOhRm65yaAVJFkaDTpQHeSPSYXgcbZhDLhzTDgL3s1c_tXSHnFCNapnEci9U4Z2BvL-ZBi-zsiVRpmbMXFEkPOS77y6RmcXGiLtFideJRD7HNk1dC_IeXIKsSyWk7jrOZd_7xcZ_tHx2pSG8Bf6YVdrPbCVG7ooWFnPZToaz2eTQh2CPkotJyvyP7X5vWHfTfndSMpLY4tZjYm_DmmnROk1bq3LmY94VTqKJzILlclN4TDx2ttmI0xKVziIMn1vAuxwqspX2weAmVXVIOh0d2W00Y1x6nYVWnGGjsoKTXypl8B2zOGTKJIQ7r0zdwuAFqInGW-_BsNQxaJ7ui8x48aGjzM9aeJ7w6QaosvQpVA1PkuElm9o2oucc04VV7ogUEDtbRtwiXfJAd5xpJ6eQjp6DSMeS9yGa8nc_L3mGMcUUHJesG_ZDK3KxGqVRgSR71l4sWWOVMzqYdqZSLWfaRfgiLplSLqYl4lg---5Bjg_JiJBTwgEKiOonKhX3oserki_XVdsVn5KG-39Io9XTAB6gIichoal4tkG0wEOEUdmeUCdH6196dNfTPyUB8CZ6j_C35aM8BQqJsctQ7eOjSHOKCraBwAjh-akCaqhsstxjcR6YPnGxmfNtetLDqZee5o0j1_veYJxXDkC7o7d6_B731q2N2gU9a5MrNc2moCxvomPiIFwqFNLzc2R-h9LSPBuBKsA4cUS8Bpd7L96nNiEALp-pM2YQ1OvDKrmV2yMmNrIXesE6ixgLBVsSzOK4STLkvb6lLBXq57xBdnii3JwdafpKe8NR03kvMCTO3p3Wn3ByOJdo5-jRJyJcDVuhCkQC8VtOjo1tz6645ZTtegPMTSJX1iTSCxO9g9Vqx4G1674kWFNdoT4z7s-AJ8ikPhZmY8XSrUfSHByWTFdl8HU07IadGcZo_3t2hBK_sbsfIF_ULJFqkB24RAyAaHhy-Dh5sfcXsJSX9pF8znWVCdDVb9zS6dQHtAtuBel-ZB_UEweN4-NelRosbBA2b-aT-j06woUCtGwRSRS6yexaCtzu-qBmcVVZWL3HHfipIluC0-vrkFHUmY1PHdXXPNFlPa9NYwghXYLWLHfGqsF5Ud-anYjYTIQSJ_S_u4gxYI9yBuDpO_8dqsaG-7didtZRWR_uL__TlI9xkAaIBOcibFDR24W4rBZZHfOogjavftfRaNfm2wLMzqXHc9dUZd0_5sC6X3d-BjARK0Jtjp0v6RticlWNMWB2jkHQ2dmLi6nuyKbNRpq-YuydciO-9qvhflAfdQI46k4Arrcxwkw5SD1kwifnj8oGBDGcGuAKzGGCzIdAHVDaOopgLPp5rAkfKfE4rGvQKb5YYJXXx-13F8DGR8nUcsiyERMJN9XxaGP-bsM_gm7Q844kk2M62CrAPIjPyWfJbkItN__mWAflyTOjw1zLX4aZZ63Fsj2FBlh88SwuloW5M9BTXkQql5ANceeU3Y3bfA4nYXGoF2Cx1HWAlNAE-yIWK4VBkSS-Nn1PEG1f-EfNuB3JUq-ib6bcoTFBId67R1bsCZ7DC2DWmV-alzyNxWO9kuDmTK_bxD4qYy6CUfF7HQVsllE8TMfY52GLUSjlCuzdBkHkuXa1-fV0lFg_yRt6bwS8O5A4Yic2soHYbIylORUU0h2WOqePDYd_IX80hHoJqATMUFbZ8NsQ=\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Planning notifications implementation**\\n\\nI'm considering implementing notifications, maybe after saving in the analyzer. I need to decide if I should send a Telegram message when the periodic sweeper runs or if there are archivable items. The user also mentioned notifying them about memory upgrades or downgrades during periodic sessions. I might inspect maintenance jobs to see if I can promote archived items to active ones. It seems reasonable to notify about promotions or downgrades whenever maintenance occurs, as it aligns with the user’s request.\"},{\"type\":\"summary_text\",\"text\":\"**Optimizing agents and notifications**\\n\\nI think it's a good idea to run an agents-database maintenance status check. I might need to locate the maintenance job configuration, but maybe that’s not crucial right now. I want to implement a notification helper in the sweeper after analyzing each job, and I need to prevent spam, perhaps by aggregating notifications. For AGENTS suggestions, I'll evaluate saved items based on type and importance. Modifying the analyzer to derive agent candidates should be feasible, allowing it to read saved memories and send notifications accordingly.\"},{\"type\":\"summary_text\",\"text\":\"**Summarizing analysis results**\\n\\nI’m thinking it might be enough to derive the notifications from the analysis results. The sweeper could read the analysis after each job and send a Telegram summary. It could say something like: \\\"Session memory sweep: saved N memories from <session>, active X / inbox Y.\\\" If there are any AGENTS candidates, I might add, \\\"Possible AGENTS promotion: - title1 - title2. Reply if you want a promotion.\\\" Also, I'll check if the maintenance consolidation results show any promoted or archived items. This seems like a clear plan!\"},{\"type\":\"summary_text\",\"text\":\"**Considering script execution**\\n\\nI realize this matches with upgrades and downgrades. I’m thinking of running a sweeper after analyzing the batch maintenance tick, using maybe a Python module or direct bash. But I might need to define an environment and virtual environment for the agents-database path. It seems simpler to use subprocess with a specific script, but I’m also wondering if it’ll accept the “--once” option or if I should set the environment first. Let's inspect the script to clarify!\"}]}" }, { "type": "toolCall", "id": "call_kwOlse86cdQVRwiWgZ7Oik8l|fc_0d29dbf88c868f5a016a12c523daac81969fb184b25241094e", "name": "read", "arguments": { "path": "/home/sebas/agents-database/scripts/run-maintenance-daemon.sh", "offset": 1, "limit": 120 } } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 3512, "output": 636, "cacheRead": 222720, "cacheWrite": 0, "totalTokens": 226868, "cost": { "input": 0.008780000000000001, "output": 0.00954, "cacheRead": 0.05568, "cacheWrite": 0, "total": 0.07400000000000001 } }, "stopReason": "toolUse", "timestamp": 1779614993156, "responseId": "resp_0d29dbf88c868f5a016a12c5114f0c819685ac9b12f3712d73" } }, { "type": "message", "id": "44e4b67b", "parentId": "57c6cbea", "timestamp": "2026-05-24T09:30:46.317Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12c525de2c81968011c1ec5856c4df\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABqEsUotbj4LnxUqdNHtkrkA2o8huCsV43fNs50uiWIPzSMeBPykmWI1is1kvh8ksNwVPOFpwq7GRxK7d62cR4aPJ-4ooDD9uDpGu1jIPEDCe9YbprPTfOJfGieMdMHjbjLzj9TpZjSEYFdoyxiuAX5QAPab_eiXUi1uXu_sRFTJVoUVYESZPjXoIlSTP0MzfmW7k3mMbhtOUif8DDATCtmYy5YiJewxnREQPS8i5YtuTTJWXpBwaZoveI7D8BZfqoINpNuwF7PhHIQXY4t883pB-GKsMhbVR0U5BqTtl3VYkclRvDOlZhsmfFZJ6RfnSzoP4zdJ6M3YCKPEX4UkSgBn9xKok9qY22RfnxGC3CqnVhUX72EPv4MDRFca5vMVCpGZSVw1B9uTuYKAO5mkLhvuHGUczYqjjinfbeffEmTUFHyr-TYtB8UdRAC0aNPpy1HDb-Q4qjTsHjUntnUbT5kmsntNPqFcna6rcajxaUzYb9qkL-5P8RB1ahLdRULF-eVFjI8XbbCWkFLPMZEprejNqjC6jGFIFT_EEmn87HITeLtC1IXPhijkpvfByhpCSMM3XLIk0AgB04J5IJsgViCet_Gh7_kkFh_4Nd-3iVQJ_O-hn2fgEbxtckxcrTmWAO4xoOux8Vyemtxsdd8Sszn4clciun6VuqsD4eWW8cQfBnR1D6R_0-Sf7rBITNHKF_vZVZbyxvnwJj-KALfISzyY3PsTRsyo4E6YQf_tW4CqSJlYR5r921WBIPaSxIbB_9jwA5fWk2uIdyPgrP3TPlF4QY5R7JLMlrSx640epq6H0n6chX6Wvdvv8ldombXIts34HTL-vpHlZvedUdt32p_aXoeZ8JhEVmMWrhWOCqzGiVeYnXVsUpjwTj1T-HYVrJGlttw7Cigr72wODtKCbqKB9kkp3nDYnsSr2F8BEmzvV_cvCmyPHN83o7nyIC08To-tIV86kGDdS693MgwC0q9tTl_KNGegbmdkqhTHkES1nQpkLyP_Tu_oCfZ53NxaX5IJ6RDZ9LQzcAIDXuVIa-Ku6jYauBEpHheiESFZ7a1saJt_1s6VjCcNbACecZkPwQkz_bwCqy_excUErwhemwq-uYmkgXAG3MRABdT3Wdn8011mRMecwarO3Pw0AFQfOPXC6iYSmp6fCxQQmFF3LBVIfBhDm_s1UyDd0HRyxm4rv7Dx7HMLjbc_kKuJ_zWfjHfgYZEN5Lti3B7l3waL-EiaVLRzN5T0smIymzcgYwtaXjoK6AWFSdHwsJsytowCkedJy8oTC0Me7P2fxJgUrcpLsRONHLcqKoRZZqd8-DYvg4LYICWvoqBdlwfNDAn-LCsbVpAiKni5bYp64pozbGZJKpJq1UkbZKCqbe4KfgwSrcESubNLVeFW7yFf-ofFD7sCpT_WGjjEVjijhoGcCyC0HqtxDP6is1JYQZsp7KUVwCO-jA3dxb-g4Ph7Ia0cYOU-pYeWwWo88vRYLCQe18NKQ7JwIYOlIo7w73untLu_dk4KAah24fBtf02dlM5yyelu5_UH7dfselCF6q4hCPA6CgkMSmulJG5v_rhc7_5DPS0qGG_5-UNZO2Jtf2dg3QK7hTk\",\"summary\":[]}" }, { "type": "toolCall", "id": "call_LP4N0dpO27k3uN5iGptFdu1k|fc_0d29dbf88c868f5a016a12c5285cb48196bb3ea450138f672e", "name": "edit", "arguments": { "path": "/home/sebas/pi-config/scripts/session-memory-sweeper.py", "edits": [ { "oldText": "import argparse\nimport json\nimport os\nimport subprocess\nimport sys\nimport time\nfrom pathlib import Path\nfrom typing import Any\n", "newText": "import argparse\nimport json\nimport os\nimport shlex\nimport subprocess\nimport sys\nimport time\nfrom pathlib import Path\nfrom typing import Any\n" }, { "oldText": "ANALYZER = Path(os.environ.get(\"PI_SESSION_MEMORY_ANALYZER\", BASE_DIR / \"scripts\" / \"session-memory-analyzer.py\"))\nLOOKBACK_DAYS = int(os.environ.get(\"PI_SESSION_MEMORY_LOOKBACK_DAYS\", \"21\"))\nMAX_SESSIONS_PER_RUN = int(os.environ.get(\"PI_SESSION_MEMORY_MAX_SESSIONS_PER_RUN\", \"12\"))\nMIN_TOTAL_MESSAGES = int(os.environ.get(\"PI_SESSION_MEMORY_MIN_TOTAL_MESSAGES\", \"6\"))\nMIN_ASSISTANT_TEXT = int(os.environ.get(\"PI_SESSION_MEMORY_MIN_ASSISTANT_TEXT\", \"120\"))\n", "newText": "ANALYZER = Path(os.environ.get(\"PI_SESSION_MEMORY_ANALYZER\", BASE_DIR / \"scripts\" / \"session-memory-analyzer.py\"))\nLOOKBACK_DAYS = int(os.environ.get(\"PI_SESSION_MEMORY_LOOKBACK_DAYS\", \"21\"))\nMAX_SESSIONS_PER_RUN = int(os.environ.get(\"PI_SESSION_MEMORY_MAX_SESSIONS_PER_RUN\", \"12\"))\nMIN_TOTAL_MESSAGES = int(os.environ.get(\"PI_SESSION_MEMORY_MIN_TOTAL_MESSAGES\", \"6\"))\nMIN_ASSISTANT_TEXT = int(os.environ.get(\"PI_SESSION_MEMORY_MIN_ASSISTANT_TEXT\", \"120\"))\nTELEGRAM_NOTIFY_BIN = Path(os.environ.get(\"TELEGRAM_NOTIFY_BIN\", str(Path.home() / \".agents\" / \"skills\" / \"telegram-notify\" / \"telegram-notify\")))\nMAINTENANCE_SCRIPT = Path(os.environ.get(\"AGENTS_DB_MAINTENANCE_SCRIPT\", \"/home/sebas/agents-database/scripts/run-maintenance-daemon.sh\"))\nDB_PATH = os.environ.get(\"DB_PATH\", \"/home/sebas/agents-database/data/shared-agent-memory.sqlite3\")\n" }, { "oldText": "def main() -> int:\n", "newText": "def classify_agents_candidates(analysis: dict[str, Any]) -> list[str]:\n items = []\n for memory in (analysis.get(\"result\") or {}).get(\"memories\") or []:\n if not isinstance(memory, dict):\n continue\n if memory.get(\"scope\") != \"global\":\n continue\n if memory.get(\"type\") not in {\"profile\", \"decision\", \"procedural\"}:\n continue\n if float(memory.get(\"confidence\") or 0) < 0.85 or float(memory.get(\"importance\") or 0) < 0.8:\n continue\n text = f\"{memory.get('title','')} {memory.get('content','')}\".lower()\n if any(token in text for token in [\"always\", \"default\", \"prefer\", \"should\", \"avoid\", \"never\", \"every conversation\", \"working rule\"]):\n items.append(memory.get(\"title\") or \"untitled\")\n return items\n\n\ndef maybe_send_telegram(message: str) -> None:\n if not message.strip() or not TELEGRAM_NOTIFY_BIN.exists():\n return\n subprocess.run([str(TELEGRAM_NOTIFY_BIN), message], check=False, stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL)\n\n\ndef run_maintenance_once() -> dict[str, Any] | None:\n if not MAINTENANCE_SCRIPT.exists():\n return None\n env = dict(os.environ)\n env[\"DB_PATH\"] = DB_PATH\n proc = subprocess.run([str(MAINTENANCE_SCRIPT), \"--once\"], capture_output=True, text=True, env=env)\n raw = (proc.stdout or \"\").strip().splitlines()\n if proc.returncode != 0 or not raw:\n return None\n try:\n payload = json.loads(raw[-1])\n except Exception:\n return None\n promoted = 0\n archived = 0\n linked = 0\n conflicts = 0\n for item in payload:\n stats = item.get(\"stats\") or {}\n promoted += int(stats.get(\"promoted\") or 0)\n archived += int(stats.get(\"archived\") or 0)\n linked += int(stats.get(\"linked\") or 0)\n conflicts += int(stats.get(\"conflicts\") or 0)\n return {\"promoted\": promoted, \"archived\": archived, \"linked\": linked, \"conflicts\": conflicts}\n\n\ndef main() -> int:\n" }, { "oldText": " results = []\n\n for session_file in iter_session_files():\n", "newText": " results = []\n notifications: list[str] = []\n\n for session_file in iter_session_files():\n" }, { "oldText": " job_file = write_job(meta)\n exit_code = run_analyzer(job_file)\n processed[key] = marker\n results.append({\"session_file\": key, \"status\": \"analyzed\" if exit_code == 0 else \"failed\", \"job_file\": str(job_file)})\n", "newText": " job_file = write_job(meta)\n exit_code = run_analyzer(job_file)\n processed[key] = marker\n job = json.loads(job_file.read_text(encoding=\"utf-8\"))\n analysis = job.get(\"analysis\") or {}\n status = \"analyzed\" if exit_code == 0 else \"failed\"\n result = {\"session_file\": key, \"status\": status, \"job_file\": str(job_file)}\n if status == \"analyzed\":\n result[\"saved_count\"] = analysis.get(\"saved_count\")\n agents_candidates = classify_agents_candidates(analysis)\n if analysis.get(\"saved_count\"):\n notifications.append(f\"Memory sweep saved {analysis.get('saved_count')} from {Path(key).name}\")\n if agents_candidates:\n notifications.append(\"Possible AGENTS promotion:\\n- \" + \"\\n- \".join(agents_candidates[:4]))\n results.append(result)\n" }, { "oldText": " state[\"last_run_at\"] = time.strftime(\"%Y-%m-%dT%H:%M:%SZ\", time.gmtime())\n save_state(state)\n print(json.dumps({\"processed_now\": len(results), \"results\": results}, ensure_ascii=False))\n return 0\n", "newText": " maintenance = run_maintenance_once()\n if maintenance and any(maintenance.values()):\n notifications.append(\n \"Memory maintenance: \"\n f\"promoted {maintenance['promoted']}, \"\n f\"archived {maintenance['archived']}, \"\n f\"linked {maintenance['linked']}, \"\n f\"conflicts {maintenance['conflicts']}\"\n )\n\n if notifications:\n maybe_send_telegram(\"\\n\\n\".join(notifications[:6]))\n\n state[\"last_run_at\"] = time.strftime(\"%Y-%m-%dT%H:%M:%SZ\", time.gmtime())\n save_state(state)\n print(json.dumps({\"processed_now\": len(results), \"results\": results, \"maintenance\": maintenance, \"notifications\": notifications}, ensure_ascii=False))\n return 0\n" } ] } } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 1321, "output": 1778, "cacheRead": 225792, "cacheWrite": 0, "totalTokens": 228891, "cost": { "input": 0.0033025000000000003, "output": 0.02667, "cacheRead": 0.056448, "cacheWrite": 0, "total": 0.0864205 } }, "stopReason": "toolUse", "timestamp": 1779615012271, "responseId": "resp_0d29dbf88c868f5a016a12c5246edc8196918aaef13d6781bb" } }, { "type": "message", "id": "7be0f6eb", "parentId": "3b7710b8", "timestamp": "2026-05-24T09:30:52.864Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "**Figuring out unused imports**\n\nI'm noticing that the shlex module is imported but not used, which seems unnecessary. I think I should avoid any notification spam from just counting the saved items. Maybe I'll run it once to test this out and see how it goes. It feels like a good idea to clean up unnecessary imports while also making sure everything works smoothly. Let's give it a try and see what happens!", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12c5496960819694eb06eb93a18a7b\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABqEsVMRamZlYJLfyevV88M6okcTJ3UjUpZTkHioWe9h9i3aCoh1luv3-gQCTuQAAAPqZcSqRrfcQWQbEgLgoQ4_WHbJlbLqcGv5dQK_PU3tSMmEJYUG59tk83SP_AcBz4qwj0Yh4XOota7avcRGB-vz0PnXal7zpgUiJ-kpdZzOLyZ1ui6hPWwPa4axlH1ECXz77VL5ccnwjD-vGWC5CCH-M0vaVwS3ghHlZnIzr-NCLTotqZzRwQpr-0EijEv4qAAKe3fIitKJgbHYfrFiHj0kxzU-c2f188Jl0d2ss4Ua9kn01gpP7l-lWs42j9DT4WbklbDdejWRahQpYwn6fEOPtMmAFXZ6SlJWuAGsYH80YavamdkPp_57Jfq7YtnKZfCF1HJ69AsArNDX9eeL5aBIgL9NfeuN-bYePw-FYv-P7ujfk0aJHGPGU1RKU53EDiSVArnbw2UNZurzdx3DOe3ZVGp2LhPaMOngfmVNtoSReNPP29U_oyaZnbq4qhaueVlK-v1HIo5ZXnLspD1U0JKBJsgd9whgBIEzicW94qjgMu4JYrnxRVVIuKEposC0WtbrHvQdX0ZZs72HXREgKdr0E8BpL4GKkG7lWvhDGMesrG_ROU63DQ0EwEmhrLdi6KTnasvoEWgBBSBiTFH-Kc8QyBo9j_ANxHckY7Tx7ngjTeWf8N3Na3LTF4ujVqaSJYE_7Dq9VNEXjC9MkP7gGa934PweqMF6MUFFLbys8Il8BDFUMvcjQX8ivPmrPTf4UusX66aUIBUAqWcmV-BJL9ibwpDQY-npgrraPSa79NOJFrUSNRQ2unUoyOrwBVZPsEE4xicSI5VT9IAqyTMF8TSls5VHF0XymwfQrXCWLD1py_DzAE6GEkI0LUDMCRcVH3JOFC_w2xv_7YmnmgJjEBTC5Xi1Ci9rXAcfPNMTVLp2EuBN12yJEEKM0_XiEqGnSNRtmeH_aAxnOj1j83ukAz4DEupWvxG4R_2s8fDbVUAtTWoAxXmniCBWf4_3zoXImD6hw9AhYKhZsLhmBGlAIRGfJcAAQQCcxC6G1o5hujiw7qtV09iqp3uK3bjywO4gpH9xDHk\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Figuring out unused imports**\\n\\nI'm noticing that the shlex module is imported but not used, which seems unnecessary. I think I should avoid any notification spam from just counting the saved items. Maybe I'll run it once to test this out and see how it goes. It feels like a good idea to clean up unnecessary imports while also making sure everything works smoothly. Let's give it a try and see what happens!\"}]}" }, { "type": "toolCall", "id": "call_C0zBUwWQJhHJE4cyzIQQ8DmT|fc_0d29dbf88c868f5a016a12c54c2e208196a7143687d58ba0e7", "name": "bash", "arguments": { "command": "python3 -m py_compile /home/sebas/pi-config/scripts/session-memory-analyzer.py /home/sebas/pi-config/scripts/session-memory-sweeper.py && python3 /home/sebas/pi-config/scripts/session-memory-sweeper.py --once", "timeout": 120 } } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 2107, "output": 102, "cacheRead": 226816, "cacheWrite": 0, "totalTokens": 229025, "cost": { "input": 0.0052675000000000005, "output": 0.0015300000000000001, "cacheRead": 0.056704, "cacheWrite": 0, "total": 0.0635015 } }, "stopReason": "toolUse", "timestamp": 1779615046421, "responseId": "resp_0d29dbf88c868f5a016a12c5469f6881969d32d107d5437847" } }, { "type": "message", "id": "5fa6aae5", "parentId": "97d29de9", "timestamp": "2026-05-24T09:31:28.897Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12c568f28c8196b8b837143c38c2ac\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABqEsVsghi8R9Phc2dtXcee3zYD4M6NecbivP57xpyjgMafpW7nYetv5uslV8XtT0lDo3A7kOVQCM62QUpaKppb6SZU7ET1gsikUHtDU0a_lvzwD_RwNmExxhEz0zOjJKFEd5puGuGeLXeSaaE4PVKPrTiQ9VrvsxdKFJMRi0sEvGIiJwxmtL_tqHbD7Dpy-maEMM8lAK_0qwZl4GftDQi3ZftaHE_LvXsuSEHBfzapKIjYwVzA3oZO1zhe8o7iojTevlBbaz377vdNWemKrQbED-Pk3dIw_bA7JyHS3UKRF5pzW5GtrVka_izQbde_rnV8IOaarwrk8LS0mhipVHgeiF0gB0RDBQ9Q_9-i8MwngEJa-UuU-nDQEBP5U4O2P74Lgdj1vQ6DkS6ZYQefppubEu3FcH1E_LRWO1LBn2UNvLuhB6lPoU21oolgWGNEtCB-Y6NgDt1TfAWjnZd8pxyXJXrBuZxDdUq5nsIsB4f-mhj5NyxURVhNAQ3TzonEJJs9VhWiNyDQmHyoNnbBGRbx-A4aB5VjGiuJuvREONMf7g4bOfj3erlOAHFCbcvC4SbZuleyHqTI8PNaFs_uk2Pmu3yUgo4uv79KFdSMv5r9o2r2TUjjVLXwiLobiJICacIVQlkKZd6P57fUS9SiR4d7Mvb8Vgfr5fzZk_hBrKcER9MlqM1JE1TYwpIWAtXTXypo3ht8Iq-8XCG7oWfWJ_gyBfmSTEnkooMr1XBJe8l0KrDH3K1ykkJDkV8TrX-eKVSvHsvcjjZt3Q3RZQCmADA4VTqqJFmY5r6ofuvI68Ynori0BhiByBjwwVRFCjUDOyAhoQsPCK10jScTxUapD3PFFPoEZ_1MR23ju16eAPOct-yk-wLoylE6ZXXyrTv3tZU_NZWnp0Jj1u2QADXJ03MNlIoNHTQj3_UiO540WfOw0ffosl5OHhDGMs5imAeniojmmSWRgx6abjz8_dVXKuMwFJ2-Ia0dVw94SKKFoEMZinh3wEh0ALdb01mPjGrM0Ly9EOSb5KVIMTYdXeAjGJctMWfuUmSlhCy81beeKQh_k20BnD7XGnXDgvOLAQKvC1GNJDmLLmVRNJtVK-06LD9DAh6aKDC5IrBBzv3IaD4YrSMGvTnIJSN9zC6GAgTtMM0OFsra1joEeUF6N3tIxNswh1m25A-UjuEl1APFbN4v2ul8F3goiP6ZZwxHVluDWKK9Q7xYICDcU-rqB6t6RKq_rBkY_HNlKLP5WqC_kp2mZ5R3j6NXb4i3R4mrSXfOAaEhNmQ3H_FdWkUG6xNptJDxN4bQrS31oZ11LfiKCEu3D7aDx2QYIE-asqAiwh2FYmrUGyaj1QMp3-fUJNeqTnbAtiL8ncwDKAwUsxp00yXv06XtZNmRw7haoENm3HicUoxERaOxsM-CWcxs4SRwTnxPfxDB13QOUEH15u0htLqgdmlu7mR8IE25Ez5sLtt0mfKWmSmVHTDsrGYclATYEGKMSTZ6iRDCRhzHJoDUXCnqW5o6_gPzas2jm71ED5OPLxfvyiKcxiaRdfLJgpQgAPk9sxU_QAknJTKtwC8p2TE4Sy_1DIWnNbkzt4DflqEkDa2ayhUzZqJL41lZUf3bGMp_oGIpp0ep81Vt_M5W3sNcffN6OQFQ7wcLQmg4Z1HhreJFnd1JODTrtINQpfrlVJAgyPf88ZVj2fefqMeySJBoJtWeuuHbR7JJvmGPVFOFid9DGjeL2iG0xJFb4mQseXXe7fpDEs5yLe2DHFHVhI4xS-NkJ8qm_IUPkH0gHzGyXKK5zbOGJnGqBs7x2Qmdq7cZO3WanfErkRTe54WInsxSbDKFEXss9UrIKsBITxall_R2BW70RAT05eccxN4cwCt3pmw_BT-n0xxtD_JKjwNFz2HTlD-PXpgxdq7-YvnHPx44dkq_UIgLMGU8UYJbVhP4e_i1lAHJLKxgHsVTeLiCYWVDaulN_BCbjbaqPrXzYet1qGIPuIzmWa65z1zP-4VCtFP9rRWJuHLurxGF8bJJL6Jy6ert7Axb1t5lHXfSWAVijMvyo5oLsLmriEXbH_Z9Y0WbtpihhSfVSG8UQA5KYgLqDbX0VDNuNAV6b6mubAaGDJyoGmxukjwzQvermv8h2YITn13wbLSoTdoS3YnuKQ2tcpPSBcEKioE6Z_KBcrWtT7LfmjXaSbUbEsKDqiI0zRJ-JBXpzqejwt2_6Tu1hu8BXAn6z-QA_qlbO_Mw3TaB2VtO4Hg4BCiCClaUXh9te86xERdLDcZMmUwodqSTPvDtgqcZm4nJ1fAjPghTHdqruU8v9ThTQyBmKiJJsyUDQkInuQ==\",\"summary\":[]}" }, { "type": "text", "text": "Done.\n\nNow periodic memory automation does this:\n- sweeps recent sessions every 6h\n- saves memories\n- sends Telegram when it saves some\n- sends Telegram for possible\n `AGENTS` promotions\n- if maintenance/consolidation causes\n promotions/archives/conflicts,\n it will notify that too\n\nWhat I added:\n- AGENTS-candidate detection\n from strong global behavior-rule\n memories\n- Telegram notification from periodic\n sweeps\n- maintenance-change notification hook\n for promote/archive/conflict events\n\nCurrent state:\n- timer already active\n- sweeper runs\n- AGENTS-promotion suggestion logic live\n\nIt already detected one candidate:\n- `Prefers fallback to free AI models\n when quota runs out`\n\nSo pipeline now:\n1. session-end if available\n2. periodic catch-up if not\n3. Telegram nudge for:\n - saved memories\n - AGENTS candidates\n - memory promotion/archive/conflict\n changes when maintenance does them\n\nLater if you want:\nI can tighten the AGENTS-candidate\nheuristic to reduce false positives.", "textSignature": "{\"v\":1,\"id\":\"msg_0d29dbf88c868f5a016a12c56cccd4819699cd045774651c9f\",\"phase\":\"final_answer\"}" } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 1752, "output": 440, "cacheRead": 228352, "cacheWrite": 0, "totalTokens": 230544, "cost": { "input": 0.00438, "output": 0.0066, "cacheRead": 0.057088, "cacheWrite": 0, "total": 0.068068 } }, "stopReason": "stop", "timestamp": 1779615079162, "responseId": "resp_0d29dbf88c868f5a016a12c5674fc881969fb93008c67ef9de" } }, { "type": "message", "id": "e8213b6b", "parentId": "5fa6aae5", "timestamp": "2026-05-24T09:34:18.081Z", "message": { "role": "user", "content": [ { "type": "text", "text": "[telegram] check if google models are still free. Then “Prefers fallback to free AI models when quota runs out” mem should be ypgraded yes, but only using google models (the rest are too prone to timeouts,429,etc)" } ], "timestamp": 1779615258042 } }, { "type": "message", "id": "0ebea7e2", "parentId": "e8213b6b", "timestamp": "2026-05-24T09:34:29.734Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "**Checking Google model pricing**\n\nI need to find out if Google models are still free, which might require some action. It seems like I only have tools like bash curl to work with since there's no direct internet access. I could also consider checking OpenRouter. I should inspect the available model configs, but querying providers might depend on whether I have an API key. I think the best first step is to use curl to check Google's AI pricing.", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12c61bb2a881968c04ac40c7efe89e\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABqEsYl-tok2fWw-RVL-4vIxXgz5DYNnJ-iXR119-q4HiBQFy9FhX6jZ6NaYv3UO_UyOAxNAMzvbQd7hN0v9_TBVupZ8H9mHQrz5uH8phUFH-4Rr6kbtjVup5ROgWe2hUqW5IpCu3d22DXokGTdQ9MTIk-RvrlTMdgNUHTz6dNUanO_0sg3kaMj1FB9iPK8hCvxq98kxl6JNiF6y-Sfx1OdbfEtWHbjHEC8SP6Zns-Z52Ta4HZ2xVy9QgbkPSnofQ2_CbV6YlN1h5jCqA9hRlEGdeWiq9vg9m3VdbcPOZRVsKbKn7BhRAhzpZ7211W7XpHERXW4XRatJjsyumuDmzJv359AEkTvM57-umSL70OmzJSIsIZY_gJl4zLsIbUBTherCNRPhLhvDh7nvi5Xe6sciSz7rLvjYYPiRSbpvAybvoKNJWkGPi2-qeLWngxgRzk3z6LWN25BSHcO6sDHdXMelnKjYYl7Czvj-IM5VWM4AmtHbVUSdvgqmrwtFgmr-XR2JUFQxVYP0CCg_BHiRi-0ozxzZn0Hd3ZYg25qOuXr4kV0-74_bJpdQ7KB83v9jD2K-AsV7DLCTY8iAJBMGROebVFus-lNt8nmN-iRtfVUh9ONzuZaO8s2nVXQW-BsKVtV2YvS9QmBl3mM05dDo7Yo_HsGKX_z0CswlkJF9K-CRH3fgjYAMNWWuizH39NeD0IP-hZXAS7z8G9lKujhKJ58fwSIHYQ0vpesstlEAFp4m5l9Jyyd_HikZD05wLetysvZrgBjChCufOk67xZ6kpuIVTqAiU6LRd-AQX0S4vgU63M9nag670rgT8G-_oPczZsIAsI0nmRQ1TQI1Wp-Y6oiUaaUGTO4Gg4leR9i-hnMSNAcbgk9MCw3ZQOFzMxCtOwlHxcuvz-5mnM3KaSd5Rddj8_CkOK6Yk6CxyHgzZpiFyMeBoZDDsLEoc55oMoHyr8RHh_plFZMQVo2RnYiTcdVeL4tGe9_5p2P39YwfwWm04GGwtHMziCijPunGwOyvkdNP7eShtTbdbA4eP1R8C5Xyg9jccJgS1wkcJy9PedUpwxaLnNMWnWQinYTxdeGPDBr8i9jLONCFb2x3XDc6GW6iFH0YS-YACpT16gjLQirbkGZpnc8tEyPUrs-5Ko8CSOfiu13-7X-0zfG4pWUMdbcP2YxzOTvL9SAdUIv6KykDLJL9aHsJJ9d0KGtsWRnCwC4EWpq8V-cvvym24ftTsPaNi9hSy65WwApegi3qf3NkCE-9YVA89DYb8d6YIoZXjT3OkvOfHPLunWDW5dMVAChKurgrzMJRkT9eeoEg5A7PrKl3Ji9xxnctDTyjTqj9lQr2Snr4aQothRlAIXVDkjod_QtcKRdr1XIDxhUd6P-e9RQ2JAlC5LoJmyFPMZpM8qEHC0MkjEkvFhskVOFxtHPVEFFqQ==\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Checking Google model pricing**\\n\\nI need to find out if Google models are still free, which might require some action. It seems like I only have tools like bash curl to work with since there's no direct internet access. I could also consider checking OpenRouter. I should inspect the available model configs, but querying providers might depend on whether I have an API key. I think the best first step is to use curl to check Google's AI pricing.\"}]}" }, { "type": "toolCall", "id": "call_aGAMrZBwBTNCaf1eDKNaojD8|fc_0d29dbf88c868f5a016a12c6256af48196b5b8e1ac8b031248", "name": "bash", "arguments": { "command": "python3 - <<'PY'\nimport requests\nurls=[\n 'https://ai.google.dev/gemini-api/docs/pricing',\n 'https://ai.google.dev/gemini-api/docs/models',\n 'https://openrouter.ai/api/v1/models'\n]\nfor u in urls:\n try:\n r=requests.get(u,timeout=20,headers={'User-Agent':'Mozilla/5.0'})\n print('\\nURL',u,'STATUS',r.status_code)\n print(r.text[:2000].replace('\\n',' ')[:2000])\n except Exception as e:\n print('ERR',u,e)\nPY", "timeout": 40 } }, { "type": "toolCall", "id": "call_94BHFgdxOIIZzQJ0X3pqv49x|fc_0d29dbf88c868f5a016a12c6256b0c81968f808535de251fa6", "name": "bash", "arguments": { "command": "python3 - <<'PY'\nimport requests,re,json\nu='https://ai.google.dev/gemini-api/docs/pricing'\nr=requests.get(u,timeout=20,headers={'User-Agent':'Mozilla/5.0'})\ntext=r.text\nfor m in re.findall(r'Free tier|free tier|Gemini 2\\.5[^<]{0,120}|Gemini 2\\.0[^<]{0,120}|Gemma[^<]{0,120}', text, re.I)[:50]:\n print(m)\nPY", "timeout": 40 } }, { "type": "toolCall", "id": "call_FnOWFghxCifg1yk8oMY42StN|fc_0d29dbf88c868f5a016a12c6256b148196b23e66e34c490694", "name": "bash", "arguments": { "command": "python3 - <<'PY'\nimport sqlite3\ncon=sqlite3.connect('/home/sebas/agents-database/data/shared-agent-memory.sqlite3')\ncur=con.cursor()\nfor row in cur.execute(\"select id,type,title,content from memories where title like '%free AI models%' or content like '%free AI models%' or content like '%google models%' order by created_at desc limit 10\"):\n print(' | '.join(map(str,row[:3])))\n print(row[3][:400])\nPY", "timeout": 20 } } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 7737, "output": 530, "cacheRead": 221696, "cacheWrite": 0, "totalTokens": 229963, "cost": { "input": 0.019342500000000002, "output": 0.00795, "cacheRead": 0.055423999999999994, "cacheWrite": 0, "total": 0.0827165 } }, "stopReason": "toolUse", "timestamp": 1779615258051, "responseId": "resp_0d29dbf88c868f5a016a12c61a37488196809d16abcb742072" } }, { "type": "message", "id": "bf55fc63", "parentId": "a16b798f", "timestamp": "2026-05-24T09:34:41.266Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12c62886888196bc389351ca44740c\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABqEsYwY6r9NNZiR9VkzCrGUcRnCkdfXxwiIk4m6PNAt6nH-h54_KUhZrnCVMk0eai1ke3-x0dSWwkSMvp13JvR1Ri8rp8_Uk9rerRSt-zKxLZ-pnwTEXhO9QHjyOFWhQQatjFLZLmBcCHh2xYRtzTHtOGsKbq6r1qq6ZzU8COwYNX-P_5PfWSK6tQ5OFFGqBU2sJol8Jr9cEYmcLBfddeMkWR3s_uyqWYcFLlCTDjoMBtb5B2OkntaQB5YML2TZimuiPCgQtrQ8P17YsqEVDylpPfwXUmL4vJiq1gUfttoIxVGmw6XcoS_B9pj7WRIxOJde9y17551Myz3f_B3j-Ld2AILrgozi4cwV_xTfR8giB64w06iLj21qUqiV0wvbFcSNnUyfzx2BkuB7PSZOKL2tnrJYJ9fOnLak5SbrYY8bD8TfLQZMM-B7qvOadRH2QdVZVReBdMMpLNM8ti3_UbgpTK7f9Kz4QAE4ZBemkCMxSHd5tjNPDyQXzdFhgpj4iJeZe6351ElJ3TZD6ceKGVcwm9A5gxVY7SITDhTReHegXKCY5QaV3bbtCzFj-1An3C3nQCjdiiwQm8hmMq7t18D5yJbU9-rXBghEcK2NphWYXi0PCYDit1C95r1YchUIhq0nEzOq_2kkZwM3-MKRHvqOW1OENvobQm-i2hB-z7Q_Pkj9210ELXJovhngqSJgvtGZV_5EL2AMP4DBcAiAkYnVEl2Xdk8iAn05n7qW2k8uSwSA847AACWDkTmKfY1SBAALkqjd06cU7YIvUuDw4N4eqT3KRFNB8DGKAQ-giuSV9g63Afe1z-yDwe_Bp05fbIGVsGZKS-kcNobzkLPHjhD2nK_Kf_I5MUpLOcELoVQnPYSC53_KRAZ-DCRUXpmDTI1yTS-Z1YnXLNM2jYBRsxTrtuopuCPEELwR2ZRBj5XDYlPD0G5P_s99LpWpIyeg_TNFxeERLdMp8SFBzuN7Xx3g8u1P-TZtdvGvYHhOvDTvcqN_NRd1Mj_anLXITCdVcKz3CIXJrczu5IRSuRMGEMlRRxmZaZIXJzLvs-Q4jbNVeteUKon13IJOX_qTFubsozoy0XIf6HDXasEJocPKBG86Y8ucEaMe1ePO6W5J9oxFj16tcFg62la6nfDludbY0DNSPGnK6hFCuclhMSbEA4V36T1oyrno_8edQn3f3SWm4VkIs5rsdPFL3gl_-_pOdbjVrYhhf67SwXCtr_W1WZo-7wZtxUGXV_N6lQQyQ-3Iwb5sq5DwJ8mw93wb0Gct0Y7wjBGSEnzdQKs8hsxzBcQ5j-VwexSvRvWBq9p-mjpRQ9W1UPqLyPOkNEyl8Ge_wX4NFBSpKAk7PrgGjP2wdafpFKvVSeOnNkrWX93b1NXwRA_8VOqoRdgVGRBVGhc7KtE3pe-uM_rv9x75Sx7cwSnOhqP8mtu8KPJ17ROEXfkmXiRLKR8g1CpjNIkq3PjmG0V716XQrwqWqNgIzITc7nuOkqJKspO7rBqL8TUtbXmaJjL-QOWykusMQpxXRhQn8BL8nS90WP1fwroETbWuX7uCMyh9ECaH2TJKJwGPecxi9VYlL0sZ2wDueR6CCkSmMzjT02SdgLCXe8py4hwlCEEmbhZRQWyU1f4JwabqfE1GsA4AvYA8Dy_camNTLwO7D6yubIX3k0X65N8jQRzMmMFevPZgZ0ZyMvwrIXvaQIsCBXjFLHfggNg-lKkD43AyblZ9CmJeeJODV0f3dpLF0-iSPGQj94rMXPyXxP0MW6GKmCGCd-TjQ-4ceDVQe9QtCto-JaOF20Rkz1OjyIGb_WQv8tNLaNZ3su4z5lol4h7scHSl-RUpZWz7IImJRNCHA2H56EL-Jx8pLaAtYNcsV149eqTahzlfwnDKnZ0hB7MIAcf1dfKojMzCebT9X_GZKRtTme99ht7-7rzYqcnchYKFppSE10wL5OP8CTtP7_vDKf0QZhFcGqsaUk_uJBmpd-0CNWUiBsmQbnEwsma8Jzqok1VhWoq8OJ0NmTPwf745Ezne7Hr_xTD7tfYldW6aaZDbmG6QA9kxzytYxyAOV0moCXCheYoDdNCW-iBEgq4ycsVqotoigi6ILWVkAR04LKK4_-kxVopRChY0rHaIJTqX0nho0ybT3vuBjKGFwNupFOCI4rBBMc4mCX3t6ZPqhoeRJ0ZxttoPH0ttVzhwv82QITwWW831DQTCNod0Y1f5N7SpBX-I53B1QDZlAtpc-iNGVy1\",\"summary\":[]}" }, { "type": "toolCall", "id": "call_IjGhGtdhacgRLidOc0E3zj8i|fc_0d29dbf88c868f5a016a12c630fd0c8196b17652393da1dd86", "name": "bash", "arguments": { "command": "rg -n \"free models|fallback|quota|provider/model\" /home/sebas/pi-config/AGENTS.md /home/sebas/pi-config/README.md /home/sebas/AGENTS.md -S", "timeout": 20 } }, { "type": "toolCall", "id": "call_COh8eDvzEcjpIrfLPXFuXGwR|fc_0d29dbf88c868f5a016a12c630fd1c8196abe1393b18cc4cbc", "name": "read", "arguments": { "path": "/home/sebas/pi-config/AGENTS.md", "offset": 1, "limit": 140 } }, { "type": "toolCall", "id": "call_UAGwJwJeIOqW0kjALV9JHqgj|fc_0d29dbf88c868f5a016a12c630fd24819685e5bf790ae4d4b4", "name": "bash", "arguments": { "command": "python3 - <<'PY'\nimport requests,re\nfrom bs4 import BeautifulSoup\nhtml=requests.get('https://ai.google.dev/gemini-api/docs/pricing',timeout=20,headers={'User-Agent':'Mozilla/5.0'}).text\nfor needle in ['Gemini 2.5 Pro','Gemini 2.5 Flash','Gemini 2.5 Flash-Lite']:\n idx=html.find(needle)\n print('\\nMODEL',needle,'idx',idx)\n if idx!=-1:\n print(html[idx:idx+500])\nPY", "timeout": 40 } } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 3192, "output": 455, "cacheRead": 228864, "cacheWrite": 0, "totalTokens": 232511, "cost": { "input": 0.007980000000000001, "output": 0.006825, "cacheRead": 0.057215999999999996, "cacheWrite": 0, "total": 0.072021 } }, "stopReason": "toolUse", "timestamp": 1779615271452, "responseId": "resp_0d29dbf88c868f5a016a12c6279b04819684753af64632a969" } }, { "type": "message", "id": "30d691cb", "parentId": "f7a39ef4", "timestamp": "2026-05-24T09:34:48.144Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "**Updating agent configurations**\n\nI’m considering updating the patch for AGENTS, possibly in the README and memory. It might be useful to create an updated profile by using memory-write. I think I should include a fallback to Google’s free models only in the Rules or Intent sections. The current README mentions using OpenAI Codex for unattended scripts, but that could stay since it relates to scripted memory. I should also ensure to keep everything minimal while implementing these changes.", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12c6338438819683c0c363efe3ab7a\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABqEsY2PJ2iLwcsj7unkTrqJx4f-f5XxYHLKWEM94VuO0ywjsuI9VJu5Kssdw3KuaIFF4CLEagPamn1bMY51KIBrr7ESk8sNrFoD23OwHKU-dgusy7x6H_0Zdp5f3oMEE63ju_DQHj1XT8msSV3ScIJlaxSzJDo2J8HjtvEeg-W9SXd3VIDT0JU536zbIhRtzv0aJ-iIvBGM6i2fk-AHW3oVUxNjp8RKUe6e6VgfWGnxracqr6eJgPjwU78LWkmclNQegKmeodpbiybW_HZPl39tqFQB0SbQftWA3vUay5uELyHagq2YU0JIbUb5Hv1vhkpZiBIu9j7eNPxLjKiulo3nwb9MXbLJlXylrers3pXRZLU0uvQK6u3SU7Fx07nNTAt2z7WrZTvOL-VvEsWsSCgSQmanV9VWwHYanrlKGdarsSFOKoTayL5qPeOjt8p2vACvEuxBgqvE9z0e53ufSyoSPHGYEBrFv5Na9K8Bp0a64p0CDWyTRJrynZWnRsQLlWOC5RDHvjT3jYJnerAjBEJ5mMS4BLL3Io-j7JOb1B3PC6KfeOoP6mbGTzvIfHj8jhea5lRlCOd4GMeW--jBgv0oAjUVCUCVogIWJIi167NSl-sqk5thMJgSPzeI3pCcpGhAQ-_eQcbDT6SKp7K0JjgcdPMbkfuj3FdaRd37B9JhhRXOkPUh3qmy5Vs4PA6T-cviDTvvEyP25I3e44L9JVugSv2uYpv7pynp_hhIGxnnptrWs65FhJlHJmPFVyQUcjnuRYuWtROp_yu-589t9gzNqcLP5OBNUK8R9q0XlUKFa_IMp9TcqfgBgAs6VcEQUEQhWcqiRWwle8CodxKezi5N-42-uVbpQ0pyoTAuA2DTfDcxNFVzD0mUiO2EdEfP5ySPprYqKgBwbhJ1VUqCKkIgC1pbb92jMKQIVPkkwPefC-uBclzNfhP6XzBTKBRX4Fc11pBzb7wfrR3KeHSCcizbGP0_iSUao72QlPn09rVI6E_28hy52xCIzt5C-nnXl7ks220uF-UYKwPdFIPObCd5Oao-fZPedCvbSKs19TV4pE8YxdEgzEdAzi1xbCWIj9irySNoXvSnJq7Po73irwJNRsvydIv-Z16GGSruGBPeiZRXNAoOFEp390d1f0_AVzoxp3fR8UzMN1ascP_m8553e2BLEHGWfTjjPNwtAisC1UQ5ItfSMCyALH8IM0zxPXkglJJ7dyJf2Au0v1oOaqPU70Q_nC7FGoyp963NiQPACCxzugfArt6UAdAmiY6D-XLmwFnx2j7fV01_-F3YcZaQ9W8irrF0NZ62GTKayRrPwGPqU9WpCFDnDPTHPgPTxF7qxryqp6E7Eg2nPVbr4tY3WOnH7S4O5TCJpHYEQ-fQZRXNjeZA_TmjOCksP9jYy__DeMLD6dwwW5nAM_0SqunwIyzjTJuxwmTge3b2d3KTaH4ALgjAKvX1-StZtZFgpXeMKQg1FmfOdrtG9JQgFC9nVOJ30YacAZnOavR9LUAiD0CooG9LhSWDqxSp-wWIG9pXklc\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Updating agent configurations**\\n\\nI’m considering updating the patch for AGENTS, possibly in the README and memory. It might be useful to create an updated profile by using memory-write. I think I should include a fallback to Google’s free models only in the Rules or Intent sections. The current README mentions using OpenAI Codex for unattended scripts, but that could stay since it relates to scripted memory. I should also ensure to keep everything minimal while implementing these changes.\"}]}" }, { "type": "toolCall", "id": "call_LoKE7yb5sm2dFhOQmlwIkMjT|fc_0d29dbf88c868f5a016a12c63687fc819687a11f9b672166d2", "name": "edit", "arguments": { "path": "/home/sebas/pi-config/AGENTS.md", "edits": [ { "oldText": "- Prefer few strong memories over many noisy ones.\n- This Pi config repo is the place to evolve these rules.\n", "newText": "- Prefer few strong memories over many noisy ones.\n- If Codex quota/rate/auth becomes unavailable and a fallback model is needed, prefer Google free-tier Gemini models only. Do not fall back by default to other free providers because they are too prone to timeouts, 429s, or instability.\n- This Pi config repo is the place to evolve these rules.\n" } ] } } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 3107, "output": 237, "cacheRead": 231936, "cacheWrite": 0, "totalTokens": 235280, "cost": { "input": 0.007767500000000001, "output": 0.003555, "cacheRead": 0.057984, "cacheWrite": 0, "total": 0.06930650000000001 } }, "stopReason": "toolUse", "timestamp": 1779615282141, "responseId": "resp_0d29dbf88c868f5a016a12c6324aac819696986ff1f3141bf8" } }, { "type": "message", "id": "008ac66e", "parentId": "678f5d8d", "timestamp": "2026-05-24T09:34:52.189Z", "message": { "role": "assistant", "content": [ { "type": "toolCall", "id": "call_lgymk1z0qpfl0Ox8sgLm67L4|fc_0d29dbf88c868f5a016a12c63993308196b77c26d3636813b6", "name": "bash", "arguments": { "command": "~/.agents/skills/memory-write/memory-write --type profile --subtype working_preference --scope global --title \"Fallback non-Codex model preference is Google free-tier only\" --content \"When Codex quota, auth, or rate limits block work, Sebas prefers fallback only to Google free-tier Gemini models. Avoid other free providers as default fallback because they are too prone to timeouts, 429s, and instability.\" --source-ref \"conversation:2026-05-24-google-fallback\" --origin-agent personal-agent", "timeout": 20 } } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 813, "output": 132, "cacheRead": 234496, "cacheWrite": 0, "totalTokens": 235441, "cost": { "input": 0.0020325, "output": 0.00198, "cacheRead": 0.058623999999999996, "cacheWrite": 0, "total": 0.0626365 } }, "stopReason": "toolUse", "timestamp": 1779615288149, "responseId": "resp_0d29dbf88c868f5a016a12c6384ccc8196a0126a901f1e0db2" } }, { "type": "message", "id": "ec6fc6d7", "parentId": "fda6583e", "timestamp": "2026-05-24T09:34:58.742Z", "message": { "role": "assistant", "content": [ { "type": "text", "text": "Yes.\nGoogle free tier still appears live.\n\nWhat I checked:\n- Google AI pricing page loads\n- it still shows `Free Tier`\n- specifically around:\n - `Gemini 2.5 Pro`\n - `Gemini 2.5 Flash`\n - `Gemini 2.5 Flash-Lite`\n\nSo your rule makes sense.\n\nApplied:\n- upgraded rule into `AGENTS.md`\n- wrote durable memory too\n\nNew memory:\n- `mem_716699746ab8484e9311cbaeb33f516c`\n\nRule now:\n- if Codex fails by quota/auth/rate\n- fallback should be Google free-tier\n Gemini only\n- not other free providers by default\n\nReason locked:\n- others too unstable:\n timeouts, 429s, etc.", "textSignature": "{\"v\":1,\"id\":\"msg_0d29dbf88c868f5a016a12c63f46c88196b0cf88cbbd849031\",\"phase\":\"final_answer\"}" } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 799, "output": 170, "cacheRead": 235008, "cacheWrite": 0, "totalTokens": 235977, "cost": { "input": 0.0019975, "output": 0.00255, "cacheRead": 0.058752, "cacheWrite": 0, "total": 0.0632995 } }, "stopReason": "stop", "timestamp": 1779615292316, "responseId": "resp_0d29dbf88c868f5a016a12c63c76088196aa4b8d0b34751fd8" } }, { "type": "message", "id": "7c62dec4", "parentId": "ec6fc6d7", "timestamp": "2026-05-24T09:36:15.111Z", "message": { "role": "user", "content": [ { "type": "text", "text": "[telegram] do we have google set up? can we smoke test it?" } ], "timestamp": 1779615375075 } }, { "type": "message", "id": "0200c4d2", "parentId": "7c62dec4", "timestamp": "2026-05-24T09:36:21.973Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12c690ca1c81968eb98375f1186e72\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABqEsaVNsKd-wpA99lOsQGlr429Gn4YUMb3cKROkG4fyk2i54L8mOY66dLM-gUCUdHUc6xnEZMm5l7RHV7eLbvXRe-BZX3AOGw1wwJUNzSW0zijnzJ_6HeaDBpPpaKzKFGWsyYjvBpJN4Y-E1OFg_uXxQh72hXg2gKvUyQxnXtB2orau5nNYpdMnFLpa-vPc82CVMx9qIAC062ApllYRv32tHfZVLiIfcB6-fOZIxXLmMMlGQ9AAw1CvMvFGsfUZrajz5KL5d7JbnhYozqEG3kERVoWtykakAvWwJGmDuJfiqXOVeBpjHIq9791x9-h1DRqsgVeho9HijEN5j9hHXO8Zr2fksCT4Sb6nMfZLNdDpTt7BXfpvnL_m4qbe-E2B5ucMbrCq7AslB39VWZB-2YCbz_JUOwcouaRJCOPm_UXJumTyFW7VxuDQZTG8Bfen_WL0_6gcPtdlz0o4yXIIXJNGzLeGlpFvKdNvcCMWkXmBrmDZAc76-Ofk9lzyiQ0XlsmuWDHcPzrg-hhVkLWpN2t9CjG6CgH-JZg0HasnlBlZeQryHcOiEwtogTCZwN8bUFMiZU9-DRLX2Iyxjn6K11jjS9jJTJpOzkObSDREWgREpAE6yz6a62yKAqhEGKHFpJR33r7lvLSInD7X0Kv2nIDSydcbnpffVMd9bYgQKVPbcDQUy-cCKNKr-dM8yqqmV5jpkV8S13ag4q-fRVTOW9Mz0mCIt-pjEDNRvzaXvhW0qvArvp1jbqyYtIyMEgsfV_3e0rBzZQ1PqxQAdm8ycJa5t1f_DpUpEZ5319anEZRuNiFZZjf9OuMOKXEJZEma8mdzkzSjj-d1R45w0yzrreYsO8UBjX7eMcexcdWAH6SXXWZO0XPGYd5eZXTGXuI-_LJOnEnORbE5rqBAyW4gBRSUM_aNAkz1gJ-moEYSce_N-i-HOOyB2B5hgPfg1FmlJvzNe_UZelEjqOKGOxYy_6WrMcWD53YfSXSZx8pb2UZlPqwXSLrNjuxE5vbiXwhdlKIL66i\",\"summary\":[]}" }, { "type": "toolCall", "id": "call_OGAjoAVClT6hc2DBfNIaUvPY|fc_0d29dbf88c868f5a016a12c695b41c819680024529e366fcbe", "name": "bash", "arguments": { "command": "python3 - <<'PY'\nimport os\nfor k in ['GOOGLE_API_KEY','GEMINI_API_KEY']:\n print(k, 'set' if os.environ.get(k) else 'unset')\nPY", "timeout": 10 } }, { "type": "toolCall", "id": "call_XoV9helnebEbnZIRY8SCouB0|fc_0d29dbf88c868f5a016a12c695b42c819698b9c86031bbd239", "name": "bash", "arguments": { "command": "ls -la /home/sebas/.config /home/sebas/.agents/skills/telegram-notify 2>/dev/null | sed -n '1,120p' && echo '---' && rg -n \"GOOGLE_API_KEY|GEMINI_API_KEY|google.*api\" /home/sebas/.config /home/sebas/.agents /home/sebas/.bashrc /home/sebas/.profile -S 2>/dev/null | head -80", "timeout": 20 } }, { "type": "toolCall", "id": "call_7y10X1qhH7pnHA0HFfVy2S2Q|fc_0d29dbf88c868f5a016a12c695b4348196bde10d5d98c6c0bc", "name": "bash", "arguments": { "command": "~/.npm-global/bin/pi --help | sed -n '1,140p'", "timeout": 20 } } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 6757, "output": 253, "cacheRead": 228864, "cacheWrite": 0, "totalTokens": 235874, "cost": { "input": 0.0168925, "output": 0.003795, "cacheRead": 0.057215999999999996, "cacheWrite": 0, "total": 0.0779035 } }, "stopReason": "toolUse", "timestamp": 1779615375079, "responseId": "resp_0d29dbf88c868f5a016a12c68f3ea081969ec730b5219fb7bb" } }, { "type": "message", "id": "a3f76df4", "parentId": "6b6ed18d", "timestamp": "2026-05-24T09:36:34.515Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12c69c057481969e7eed970309f477\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABqEsaftGJSXHu2ls9Ow9Lil-KOl1X02aebBm5SufLiHL_SVemykncOhRiNjsfHuPxBPogOlmzL3d5T-dlRFFNSLYnI3A1DCK8KmMera5CTOM4GWOzYUtL25EuRvUVhcVdgCnwhA1bC1P3G5I5VJ1K83aLceW-6kYJY5YHfkK9hHokvl_h4gYZjp4duY5F4hZh_-98GmHltjqJiC8ZGlyy1VhlONjmi2mQFDHqW_yAkenuMnqEJEGTFSTOYPDrPVhtz7ej__tZahqz1KogLwdmNayiUdCd7BBRlX4Igi48tZzUH53-81Z3IWYhkJMEmfcUEAuNB2Lk8jgi_k4vfLAPzr0QgWLXFnh6fOxeIogTKPp4IvuOPDG_bpsGDXTyjDued84P0dklnhquBNWBHEzp_h1ks7b7EUj9uW7vtWN1itu5gsMTRTtyWL5DvRoXzH8vp_vVtSjw0YUx7oqLiEaETIbBCpD2IPK-hgO2qtSN_qvkMOPbBe-Vd2vSxk5r0zZzxB8MB-M8PWqwOaq2uRmg2XH_o8IaJ8InfIq85o1eTydmq5UQMwX3ADU8G21bSeDnvvaD-J7FD0F-mQTObKNFoHIBhfrnmytmg6fKB-uNO38P08ipJWOUW60QQnZJz5ZTbjNsPt_Ydn0fK0tiGhhuio38fvsR9g7etx29mTlH0erlfTRgInolUFvVqxen0O2iOKmffnfz9Ya4n-z3KZuySLTUYF-WFIWc80Vy7r9UF1iUxz0Jihi5Sc1Y7_o5Se9VzmoSTwRM_EgIXPcQVCkLHnuUkyQzpJrhq5jMD4Uh_yZZaTSxOXcz8JrBnir4IzQta5W2XJAuO45Z75mkFpe_HHKxDdvPbl6YCVkZp-RbmVFO74oOtnFmp89n0hTl7tdQMGSIeevKrKGZFSYm8yYJgL6i0sFck6DyakWrJnZaapyoDzO5yfACIN47n7t_QLJXq2nNS8iXrWAvswJIULdIAnLFXoL14oCif_LAnQzIQa4gSUwINRYBq-rld9v6hGKMGDv5vsp0wXE9PjGko3Zdwu_I39iwo9HLgQwcqRpv3KNcqi1zfsNV4vM10zDgakoEkpxdHd3sIATi6DogMv11vD75_SC4yTDPsfUF9EQWtRst5Ew4F8KuwaGqvSJaZgCg6VQ9VqrZTrTtnbMJGa3qRiF0kDiGOs6_MeGSdaXmQAW93y_c=\",\"summary\":[]}" }, { "type": "text", "text": "Not set up yet.\n\nWhat I found:\n- `GOOGLE_API_KEY`: unset\n- `GEMINI_API_KEY`: unset\n\nSo:\n- fallback rule is now defined\n- but actual Google API use is not ready\n- no real smoke test possible yet\n\nInteresting detail:\n- `pi` default provider is `google`\n- and it supports `GEMINI_API_KEY`\n- so setup path is straightforward\n\nOnce key exists, smoke test is easy:\n```bash\nGEMINI_API_KEY=... \\\n~/.npm-global/bin/pi \\\n --provider google \\\n --model gemini-2.5-flash-lite \\\n --no-tools \\\n --no-session \\\n -p \"Reply with exactly: OK\"\n```\n\nExpected:\n- exact `OK`\n\nRecommended fallback models:\n- `gemini-2.5-flash-lite`\n- `gemini-2.5-flash`\n- maybe `gemini-2.5-pro` last,\n if free tier still allows enough use\n\nBlunt answer:\n- no, Google is not configured\n- no, we cannot truly smoke test yet\n\nIf you want, next step is:\n1. you provide/set Gemini key\n2. I run a real smoke test\n3. I wire the periodic automation to use\n those exact Gemini fallback models only", "textSignature": "{\"v\":1,\"id\":\"msg_0d29dbf88c868f5a016a12c69f7a488196873e265fdb9197f8\",\"phase\":\"final_answer\"}" } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 12231, "output": 327, "cacheRead": 235520, "cacheWrite": 0, "totalTokens": 248078, "cost": { "input": 0.030577500000000004, "output": 0.0049050000000000005, "cacheRead": 0.058879999999999995, "cacheWrite": 0, "total": 0.0943625 } }, "stopReason": "stop", "timestamp": 1779615384648, "responseId": "resp_0d29dbf88c868f5a016a12c698ccd48196850a0ff5236e1c75" } }, { "type": "message", "id": "2883d670", "parentId": "a3f76df4", "timestamp": "2026-05-24T09:40:03.110Z", "message": { "role": "user", "content": [ { "type": "text", "text": "[telegram] AIzaSyAyImiE9lbkcGIikRTqZI-YknFCvowJNnE" } ], "timestamp": 1779615603083 } }, { "type": "message", "id": "91aad5f5", "parentId": "2883d670", "timestamp": "2026-05-24T09:40:14.910Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12c7773e2c819693f5b39dad03f908\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABqEsd-JdUReuTZ3IrKZI1Wrhz4NB7PzkH4R7dZ1x4kVcvA4AcyO2ZEgDM6XCYCkLKkr2gSPz3iAcRyBjCbT45RYbsVbTGnU7c27a1Z4djzBRnt8f4HbBuBs5K01OyXRgd-LmhaAgZpR-_4MWjQvwW6gGIXHDCsBHOJwuaD10OfMX4acEGf9UsUHFEhffOJICgIuInCeR8hg0jQc5cvEhYlZEyxEJgr7eGYKjGzNC4WW-_YWHunbX8Lc0cC_YLBz9YKAjuIvZuP4XUUusyZLoL-U0axGMtmb6FQVktUtCFGhR7ZznbVyXPRHoDreaIv7uIe_k9oP0bKnecpEcMssQi6jDSIGhJsltEP5nwhGuL23NOSXZj5w6ubX2SNaXPgyXJrTDK7FWAm5NE4RqEuYzvyiTXjrulfRyLkvBHHtMFl6rpp56svogL3Ubw40FAmtqDuCr1Ow9VzHz2gThX3nBkcXtf-MeWum2aJtwTkE3lsu3AOf3q6jEQx5I7wZLViTYICvBwWw73sNp09kardNsgFxIUG4lzxwxI-aOSThC4ZWlUtuxjRUr7tXPq3kXQzceHYRYDuNWRQ5FboyVIfcZ1jcrBhNlMTv_ipJi4XTd1m-9iEKMY7xkuVTB_Uw7prTF-xVpusYg249Ox_JxXyYOsNFQkYQbCeSs0cI5KlSlolf36TdftgvmhsZXzrnKe-ub13Qvr8GbBtaTqSyNn-wzFzeC0PMg9TYU5IGVvVRPOn3cTm5CGPyCzTxFXxiAtPNK7ooYLj9fLNDqaK7O5hjzwPljNE0kiYHquwDFm6Yf9EOXh0kkLWUbbmPToj93dmYctPmaTucFuWNZQQn2c2j-4o_FJyrjGLdzQaBQIEh2JrIAVL8jjI7MLgMkDeaw0tBnoSahGnUb1AZS1qS7Hys4X8rYA617SRBRRTtkvdql6akX5xlYdqAnk6NN5g14fOEiPJq13rj52PlXwskVY0BYsbQsK66prK97RX_YkyF-gag9xLAIQFfe4QnAyyKl81KWeEfDvqaIAmcCVIGbEQKAmsqJ95uO50W-smWve4EQ4BZ5OfnBpwt-DfDigNd_XgFZ7Qca2M2vvsO52_38sDcGX9Jj2eKJC41hUaTWQHIccLsYlCd30Gp0FfgZxfC65Mpiiwa_FHkQBlBnkr1Nn7r1aLIIFREaHHYFf-hsez-9TUQ5JGe26sVYb5bL21Fh9RWN_-qy2wRIxcsS-ayaESe_LJAqbSWGZfb0Qaoo3CF2oLXcY7bSOSHS3ygVy--OSQ1u7_YEqjLq-ORA84az1nFHiSKgOGGbKTlc3NJx8SUFBmvTY_8RvkRHLej5HeCWwfmjfXEJjBpeJz4sHIa5mdxEhTcZ-aPgnhId6B9IvFIKieGbTw9vYR-slyraodvgmAxjkSvGoLkoICsdTriPFHX2YI5-PgcTM3p7INb3GlMcHItRUvqIRli6SXE-GZFHtRxRz5H5zzAkN0vulAuSf2-u2JxDbH7ijgnIWgoDxgRzvzY5XqEiqyvj5FnvbTbD4c9m6ClesH0Gyzj5mDUKn7OyQZ7adLscngurUS44_czQiSHk35M-8=\",\"summary\":[]}" }, { "type": "toolCall", "id": "call_kqO0wT9hquqhbl5lv1QYz5wq|fc_0d29dbf88c868f5a016a12c77e9d908196a4f4c239978e1ae6", "name": "bash", "arguments": { "command": "export GEMINI_API_KEY='AIzaSyAyImiE9lbkcGIikRTqZI-YknFCvowJNnE'; ~/.npm-global/bin/pi --provider google --model gemini-2.5-flash-lite --no-tools --no-session -p 'Reply with exactly: OK'", "timeout": 40 } }, { "type": "toolCall", "id": "call_9VCivEvYXMyeUC1Hg2HIaRY5|fc_0d29dbf88c868f5a016a12c77ea04881968273ce8694cc265e", "name": "bash", "arguments": { "command": "python3 - <<'PY'\nimport os, json, urllib.request\nkey='AIzaSyAyImiE9lbkcGIikRTqZI-YknFCvowJNnE'\nurl='https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash-lite:generateContent?key='+key\npayload={\"contents\":[{\"parts\":[{\"text\":\"Reply with exactly: OK\"}]}]}\nreq=urllib.request.Request(url,data=json.dumps(payload).encode(),headers={'Content-Type':'application/json'})\nwith urllib.request.urlopen(req,timeout=30) as r:\n body=json.loads(r.read().decode())\ntext=body['candidates'][0]['content']['parts'][0]['text']\nprint(text)\nPY", "timeout": 40 } } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 12521, "output": 396, "cacheRead": 235520, "cacheWrite": 0, "totalTokens": 248437, "cost": { "input": 0.031302500000000004, "output": 0.00594, "cacheRead": 0.058879999999999995, "cacheWrite": 0, "total": 0.0961225 } }, "stopReason": "toolUse", "timestamp": 1779615603088, "responseId": "resp_0d29dbf88c868f5a016a12c7733ccc81969439002ac19ff867" } }, { "type": "message", "id": "9cd6ecd8", "parentId": "f4e28131", "timestamp": "2026-05-24T09:40:39.180Z", "message": { "role": "assistant", "content": [ { "type": "text", "text": "Smoke test failed.\n\nResult:\n- Google auth works\n- but project is not usable now\n- API returns `429 RESOURCE_EXHAUSTED`\n\nMeaning:\n- not a bad key\n- billing/prepay for that Google AI project\n is depleted\n\nSo current state:\n- configured key: valid enough to hit API\n- practical fallback: not usable yet\n\nBluntly:\nthis does **not** currently solve fallback.\n\nNext options:\n1. recharge/enable billing in AI Studio\n2. use another Google project/key\n3. keep rule as “Google-only fallback”\n but accept it is blocked right now\n\nAlso:\nI did **not** persist the key anywhere.", "textSignature": "{\"v\":1,\"id\":\"msg_0d29dbf88c868f5a016a12c79454848196916504a9d812af41\",\"phase\":\"final_answer\"}" } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 1110, "output": 143, "cacheRead": 247808, "cacheWrite": 0, "totalTokens": 249061, "cost": { "input": 0.002775, "output": 0.002145, "cacheRead": 0.061952, "cacheWrite": 0, "total": 0.066872 } }, "stopReason": "stop", "timestamp": 1779615634676, "responseId": "resp_0d29dbf88c868f5a016a12c792d34c8196b702cb7eab7c0eb8" } }, { "type": "message", "id": "64bdd993", "parentId": "9cd6ecd8", "timestamp": "2026-05-24T12:10:13.760Z", "message": { "role": "user", "content": [ { "type": "text", "text": "[telegram] took old api ley from \n\nhttps://aistudio.google.com/api-keys\n\ni think i should use gemini subscription instead. can you check online?" } ], "timestamp": 1779624613725 } }, { "type": "message", "id": "1c275a0d", "parentId": "64bdd993", "timestamp": "2026-05-24T12:10:29.713Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12eaaaab2c819698fb9fbdd521d9a4\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABqEuq1y4N4eipkAvn48Gq8cPvsjKewcmgEAtS3g4bP7jhWgeQPZ7GReOmVeiPhgbWqnZgi7lhwbD-Ta5fG86woLGmQ_3Fpy8WyZhiC9-7dCJRghR2joK5CpGsbwiCsng0SAhaAftHkynC1fjm-4oUaUrJicz3syK5ZlH8Jq6rV-0hEQliLPYmu8nOPpbdyHsWAiSt5hhnxmh-ZGEreq_Yl-Jh-AhSFabNbzc-7Hp92x8EU8_Meoelvlgd3aaGAJrSLydsWGp3Y_6MPhb_EmZsVLw2px3Ku5bDrIcTU215bJWHqVvZCQtLAvXKG-7m5gMAVIQfHF9DosFvMuwilwQql3Y2ES8m9CbY6m8vleqGWFGfI5Wy8gkutK7VXhnMMKoN84ONGBz3pqU4556LraitmBUA-Ya_DpTdHVKYEoiNoGD4_9VL0KuYTHVsptAHWKEOmlG_vdCr7GRhfe7J1DSY5JtWqhVpUbFXD_LDt_jG_l4CzbKVxpgmyvMEZKGZWYm7SQxJSYO0RiIEGdjm-60v8fAuWt9pknUkxr-SFSvbf7EhV9dbbV8BqW2AhGn6UMe-1GBLyQ0J7F0aq3w1LTzmYTsjnbor8avooJCz_xwLDnqB8z52ElsAi32P1uv3HXoQjTbrHL55KO18MTjhhE_m9GxnqHbMjxN1Xv13vTkEmiO7erL7TXizuH54QGZVWFosdQLlI0RIlzvt23uiLqy1nQHWVc3XelZDNCsiEkcaXddCxpbuQY4k4IVLogfhQILIn77m5AeCVUIq_ZcM2uAkR8S6R6OHFr_yoOHRwkUbaf4L5JuUzN56u6oWRc6CHWeh_vYbqgnYf9oH0lLnEULBtJhC15Setg53H9XfMVr-Rmz5wb8oRWSOhBfe6bVGgI8qIYIzZ2viewSG6K5ARd1LEEZ66nYaVTTmH39fgpZtmidbhndtLK5ryidnIFmPJ8PQBCjb3KGM9a50BYXs_IEBOWpU4F4MPkOUtq3Vx0EGpuaM8IJjZ5oGVRfFv7kwFUZH5olsgsKvueggHu1yqTmcheMV7eg==\",\"summary\":[]}" }, { "type": "toolCall", "id": "call_LQgvaUpmFg5SscmYot0EkCmq|fc_0d29dbf88c868f5a016a12eab56ccc8196b4f1ed229f67d2a1", "name": "bash", "arguments": { "command": "python3 - <<'PY'\nimport requests,re\nurls=[\n 'https://ai.google.dev/gemini-api/docs/billing',\n 'https://support.google.com/gemini/answer/16275805?hl=en',\n 'https://one.google.com/about/google-ai-plans/',\n 'https://gemini.google/subscriptions/'\n]\nfor u in urls:\n try:\n r=requests.get(u,timeout=25,headers={'User-Agent':'Mozilla/5.0'})\n print('\\nURL',u,'STATUS',r.status_code)\n txt=r.text[:5000]\n print(txt[:1800].replace('\\n',' '))\n except Exception as e:\n print('ERR',u,e)\nPY", "timeout": 60 } }, { "type": "toolCall", "id": "call_5gbI1dzenrStAaopdvpEQEWN|fc_0d29dbf88c868f5a016a12eab56d0c81969315e22c90b7970c", "name": "bash", "arguments": { "command": "python3 - <<'PY'\nimport requests,re\nhtml=requests.get('https://ai.google.dev/gemini-api/docs/billing',timeout=25,headers={'User-Agent':'Mozilla/5.0'}).text\nneedles=['prepayment','credits are depleted','billing','AI Studio','subscription','Google AI Pro','Google AI Ultra','Gemini API']\nfor n in needles:\n m=re.search(n, html, re.I)\n print(n, 'yes' if m else 'no')\nPY", "timeout": 40 } }, { "type": "toolCall", "id": "call_ai5LgQr74oOSG4Mzey07yAdS|fc_0d29dbf88c868f5a016a12eab56d1c8196806629adb4304c6d", "name": "bash", "arguments": { "command": "python3 - <<'PY'\nimport requests, re\nfor u in ['https://ai.google.dev/gemini-api/docs/billing','https://one.google.com/about/google-ai-plans/']:\n html=requests.get(u,timeout=25,headers={'User-Agent':'Mozilla/5.0'}).text\n print('\\nSOURCE',u)\n for pat in [r'.{0,120}Google AI Pro.{0,220}', r'.{0,120}Google AI Ultra.{0,220}', r'.{0,120}Gemini API.{0,220}', r'.{0,120}AI Studio.{0,220}', r'.{0,120}billing.{0,220}']:\n for m in re.finditer(pat, html, re.I|re.S):\n s=' '.join(m.group(0).split())\n print(s[:340])\n break\nPY", "timeout": 60 } } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 248993, "output": 581, "cacheRead": 0, "cacheWrite": 0, "totalTokens": 249574, "cost": { "input": 0.6224825, "output": 0.008715, "cacheRead": 0, "cacheWrite": 0, "total": 0.6311975000000001 } }, "stopReason": "toolUse", "timestamp": 1779624613736, "responseId": "resp_0d29dbf88c868f5a016a12eaa7a0608196829c99048e37cb94" } }, { "type": "message", "id": "6c31e0a0", "parentId": "6c004c89", "timestamp": "2026-05-24T12:10:42.758Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "**Clarifying subscription coverage**\n\nI need to provide a concise answer about the Gemini subscription. It likely doesn’t cover API billing, while AI Pro might offer expanded limits for AI Studio, but not necessarily for the general API. I should be cautious because the hints I scraped are not definitive. It's essential to ensure the user has the correct understanding of what each subscription specifically covers.", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12eabb10a48196a358a29a0e62063f\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABqEuq87kBvv-5p7iYAnP58dLUB62Y6mqdt6_5RYRZRz2h9roob7ETx2g6z0jk6-u5tsaQa-Tj_cb0CaJg2LQpkGCXlUEnkRV-BHDczYxtj1YazSry02RokJ8CjDbTJXqxP_c89B9N_fdkLYmbR41AYeX4ZayZ53r6cD-KYgN615GlLkx9u2KyybY_Y9s0wkGf8kKrJ8lOgDeGjbSd1nevFbs-w6bvDsO5uyrQXfeZJVf9pwiBxP-Gy1lmcoWPhdEoWhK6ydBBYw8RMGZE7D00Ao1MdahceckeH5lE7nqpyHfavf9IAVRkoubKeNDNwHm0bfI_GCph1FhFiThWKrObae02uAn67Y8VAezx-hUiuyQraSLerv83Slieqxjd6NBjn3LqIabolcGZ4frqTsAxfm7DKU_qqSJQ_LgzyFJU4aIWO9aTwVutFcGtH_3_cw7yBtPxyMaACnE9wb1ITftSQ1JnzdHDaEOZ7aTDqO59RXUXhG8NC4AyxkWXsaEEsBHyW9X5smnHZEFXevQhZ0Cu_Ie1qRgVcPDcIEo7IsiiBI36cufZ7_JKLLG9vyUJv4sPbVBdfop0q5KyXTj-yHODgUxQ0b4eWm0KFAlIAjpRzxNU3AC3CyNHWdZoZ9W1ur1BEl3UhyjFRN2wtm1oB5ylUAwOhFoZioXyVA6dQCIU422PVLJkEhzocAXpymUfxfg5K4Id7KwWuZOmN28o0m-PHVYHEyYDfrBR5bou0HHiakYPDr-uwnXuFnQB3W-ft8szPNMj1x3bOS6EVWc1PZXcvBpWYHOxp-aETYg428m-AA7pToUXtMI7VzZvXG4GOeMDgPVS6l7zwmFPZ2qpYzhEo7PPhGCH3Q-q4LmQ7373R74g8i-dRiIhoRsCeEZD0I2sevRpN3wW22M8_LLkc-NO_JXpfSqv9g2hKbUFpE9hZPosnvEyPwz4iWgSqO04H2NfSc-hLWLnBcKmUR-SkLub4ZmYE0O69uxPobXuac12MkqauDDFjebqjqIOjoW7pDLzv1mrSPCKPNdffnLh6FoTUyaRIiZtIaUvuJYc9Q-UPP2nsvYgvOg0bVntktTlsFpctokwG5yLdTgx4NgnRRdPjzEi7WKy7sSXwgQAIyGwRjVUJTtG7GebBf01C_bhOPRdfCef6fi5j5PKdIeX3FaetTyACZg==\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Clarifying subscription coverage**\\n\\nI need to provide a concise answer about the Gemini subscription. It likely doesn’t cover API billing, while AI Pro might offer expanded limits for AI Studio, but not necessarily for the general API. I should be cautious because the hints I scraped are not definitive. It's essential to ensure the user has the correct understanding of what each subscription specifically covers.\"}]}" }, { "type": "text", "text": "Likely no:\nGemini subscription is **not** the same\nas fixing Gemini API billing.\n\nWhat I found:\n- your failing key hit the **Gemini API**\n billing path with:\n `prepayment credits are depleted`\n- Google AI subscription pages are about:\n - Gemini app/features\n - AI Pro / Ultra\n - expanded AI Studio limits\n- that is not the same thing as\n “this API key can now call\n `generativelanguage.googleapis.com`\n without API billing issues”\n\nBest read:\n- **Gemini app subscription**:\n helps in Gemini app / maybe AI Studio\n quotas/features\n- **Gemini API usage**:\n still depends on API project billing /\n credits for the API key’s project\n\nSo for your use here:\n- if `pi` or scripts call the Gemini API,\n subscription alone probably won’t fix it\n- what likely fixes it is:\n 1. a different Google Cloud / AI Studio\n project with working API billing\n 2. or replenished credits on that\n project\n\nImportant nuance:\n- the Google One page mentions\n “expanded limits in AI Studio”\n- so subscription may help **inside**\n AI Studio usage\n- but I would **not** assume it unlocks\n API calls for this key\n\nRecommendation:\n- don’t buy the subscription just to fix\n agent fallback yet\n- first create/test a fresh API key on a\n project with active Gemini API billing\n\nBest next test:\n1. make a new key in AI Studio\n2. ensure that project has working billing\n3. run the same exact smoke test\n\nIf you want, once you make a fresh key,\nI’ll test it immediately.", "textSignature": "{\"v\":1,\"id\":\"msg_0d29dbf88c868f5a016a12eabc87848196b0452f893eb3b7af\",\"phase\":\"final_answer\"}" } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 3714, "output": 402, "cacheRead": 248832, "cacheWrite": 0, "totalTokens": 252948, "cost": { "input": 0.009285000000000002, "output": 0.00603, "cacheRead": 0.062208, "cacheWrite": 0, "total": 0.07752300000000001 } }, "stopReason": "stop", "timestamp": 1779624633325, "responseId": "resp_0d29dbf88c868f5a016a12eab97a18819682bd99797879d0d0" } }, { "type": "message", "id": "6b18b413", "parentId": "6c31e0a0", "timestamp": "2026-05-24T12:12:47.675Z", "message": { "role": "user", "content": [ { "type": "text", "text": "[telegram] see how people using pi set it up\n\nor yse new key \n\nAIzaSyD_d9JDP4zJKZU9EALH-cyiQ5BXCHNJTs0" } ], "timestamp": 1779624767638 } }, { "type": "message", "id": "69663249", "parentId": "6b18b413", "timestamp": "2026-05-24T12:13:01.074Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12eb450bd881969d49b3d3640b1697\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABqEutMRq9tm-h2TcXIvCeykcM7Rv592wH2kG--LLAZTCMbJzdxuZ2BVScC2x8ZOThM8CWH-lpZARRja5I86Z4MCFq9ExJzpE2qsQY-HBNAbe6G13HqMeHuE70kM0NL_nMmXGW3N1L9c2ZrkS3KSh3eV0AuaF50SS_nyWK95XEbwAG1A92Deq7AIAtNv6WcWlsMKRkS_6Z0eA3-Xitg-ew36puQO5k7Wu8Mlqvn7QOggHUthKXIRHPLXkjlZap9xod3AJ--0Ghm3642JNQGmTrudW3oVK5b3Z3KY-uRm7IxhghDzRhMF_-CQ4jCBJvY2QCIkchp0uiHMfKow4Hmh13HCixBGfftb1Kp5K9Lwo_JHuj99dmCzf9Urvkzdi77TrKebDiB2q7kMSYu5ah0ueFKPKKd2BEesFy0TC-CJ6_Dw-3oI5F0xVvWQq1_v5pV9OXbgu4v5sh06WNUB5REcPwlWPwUg_e_7r5F9as624Y8pGnw4Gb2rl7IAzXSTl5CThTIxnRdZS_wkHNZXO2IwxYWBI2WXJ6C8bvcCXw-8COcR7GLe-3JDclx2mt8zBbdsYaSdRmrXml2D1dBvjVV5tem0zXIJ9Y-vkvOfHbQWkWa1qhgt-MLhMnW5Zc-waO_rChv3fUVnHdQQgfsNHI7pGBeMzujkkQUYDjNG7ssfcrxTGhSHyFTCa97dfARL-omO8mUfzmAdCAXuZmaDLvtdluHmG_MNYMPnC2dBBNzcWPdB3Orx7t9jYJpPIVXZuxFkifW-iVZT4cf4pYGrJtE91MeobofR_mC6lQXX95zMpoeAB9C3aw0lf1nVKSjd__zRtOCkfw_dKl6l4SMks2dQkBRpqm5aNN0OCnxR3rYELfnSKFEB8UJUuyXj4VbX4Dmpc-rFd5Lza9hV-IrXUgIpVW_tXW00eKXytCfoZQQ1VeGwQTFoCmmq_5QCnEqwSvxSnNY_ZFHp67kV3i2hvL9DQbMtkBlAxK2cn9KybGby-ee5gVrWhpIEPLtsj4Mn3LFnIU5tL8pwk3NeTWlYwlsRpr_4lxg37orY--rj9jBb4FW4W2T1f5lwiyLO-eXdcGoofio-QT3CFdzJUydC5inMeFacbocFWfhbYjbu9jr49SsTUPM1fY=\",\"summary\":[]}" }, { "type": "toolCall", "id": "call_OzUHC17LxxJyRVF89QTiLGdr|fc_0d29dbf88c868f5a016a12eb4ccfc48196a8b36c6a40932bb8", "name": "bash", "arguments": { "command": "export GEMINI_API_KEY='AIzaSyD_d9JDP4zJKZU9EALH-cyiQ5BXCHNJTs0'; ~/.npm-global/bin/pi --provider google --model gemini-2.5-flash-lite --no-tools --no-session -p 'Reply with exactly: OK'", "timeout": 40 } }, { "type": "toolCall", "id": "call_5BCbmsIhuAAxXNOcHkvdDZBc|fc_0d29dbf88c868f5a016a12eb4ccfd88196b964881d0846a65f", "name": "bash", "arguments": { "command": "python3 - <<'PY'\nimport json, urllib.request\nkey='AIzaSyD_d9JDP4zJKZU9EALH-cyiQ5BXCHNJTs0'\nurl='https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash-lite:generateContent?key='+key\npayload={\"contents\":[{\"parts\":[{\"text\":\"Reply with exactly: OK\"}]}]}\nreq=urllib.request.Request(url,data=json.dumps(payload).encode(),headers={'Content-Type':'application/json'})\nwith urllib.request.urlopen(req,timeout=30) as r:\n body=json.loads(r.read().decode())\nprint(body['candidates'][0]['content']['parts'][0]['text'])\nPY", "timeout": 40 } }, { "type": "toolCall", "id": "call_rsG8cGZr9bAvzY3c4x3tmigL|fc_0d29dbf88c868f5a016a12eb4ccfec8196b8a0e7d7412444f2", "name": "bash", "arguments": { "command": "cd /home/sebas && rg -n \"GEMINI_API_KEY|provider google|--provider google|default: google|Google AI Studio|gemini-2\\.5\" ~/.npm-global/lib ~/.npm-global/bin ~/.pi /home/sebas/pi-config /home/sebas/agents-database -S 2>/dev/null | head -120", "timeout": 30 } } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 252936, "output": 413, "cacheRead": 0, "cacheWrite": 0, "totalTokens": 253349, "cost": { "input": 0.63234, "output": 0.006195, "cacheRead": 0, "cacheWrite": 0, "total": 0.638535 } }, "stopReason": "toolUse", "timestamp": 1779624767643, "responseId": "resp_0d29dbf88c868f5a016a12eb3fcef88196b41e4334d7712fc6" } }, { "type": "message", "id": "7fb70171", "parentId": "39a846f7", "timestamp": "2026-05-24T12:13:29.278Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12eb63c39081968924beb80f9225c4\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABqEutkcJ5dFTHRFAXnvEZXgdo3icF9ZtEiuzie9jOzBF1wzm6zuGfiEbqV-ullhrJPocBruU75i5sk74VAzsLx-JTCbyPpkvTnve7YbOgqu9OJUahzC0QQtvIIJ2bk3XuqAFr2xWfCRjN5PWEy2DDiSBlF4s3w-DK3_SK-yPrrHSQaD_UTofZyK_n7KP7ITQL-ils0rQEvv1AAdOlbN4CgnHqQDTLiaXerQ-ip-ICjgbaRwADs-Y7UG8nxd6ptAjGO6dd6363cFvB_6Xn07nnuiCbmFj-uS_53VjbGmt3ToY25hx79WcDAmkzlncLQqJPqjJIVChHrbtBjQrFGq7y8jWI-CCA-B875rirPZneFRcmvf-ZKR-sJzkJ8BDG61FmpTe245LK0WN63iXkER4ohbsjsyBs9C-ZMZgbgSLSE4La55al0XPW1H53xvPEEdi5gXcQ42QdfDYp2RZ-ECWzGhWYeSf11f16yG9UsYVrAKai3u1Hp-0SsVrmnUU1rnRPnLnVPeeXH-zfkdivMRxRICdffZkktHdJPLYJC00WvxQqNBvN4L-gcerQQdYREWdhAkMAt_cGxONP4G9lVV1AHIBCgzSuFr5y421B8n7jFdueztglmDIvnu_RCKQ-Aamy4-aMuTNxWSoSokRgALAR53X9olbvHwK5Z7zXhnP2Fm0Fm_nSrcxqg3eMmV0-lGGgK8jyRhvyIqAKRpp9ON8dzSxQ-rjJ0I8DALNWeju_ssUyuJoUtcTBJBJM5D_oUno46o_ZyOfCmrtZqibAfoBhJJEpAMNgbvvsIbDbi140-hvt_TqrdATuw9TZjrtUdTkltnYO5DpKS4TJR055ROPHUueKlBOyrEZc0bISZX1gsuhbdQSHSwXzzbPIaNjn9_C_0ekuA8hRHNETeBhPPg8QJv8_IjrZJIjNtv2wWQRx6pTwxARkiQ8wHTsNYBGweXLQzn38Y\",\"summary\":[]}" }, { "type": "text", "text": "Checked both.\n\nHow `pi` uses Google:\n- via env var `GEMINI_API_KEY`\n- provider can be set with:\n `--provider google`\n- model examples available locally include:\n - `gemini-2.5-flash-lite`\n - `gemini-2.5-flash`\n - `gemini-2.5-pro`\n\nSo setup pattern is simple:\n```bash\nexport GEMINI_API_KEY=...\npi --provider google --model gemini-2.5-flash-lite ...\n```\n\nNew key smoke test:\n- same result as old one\n- API reached Google fine\n- but got:\n `429 RESOURCE_EXHAUSTED`\n `prepayment credits are depleted`\n\nSo:\n- this is not a bad-key problem\n- it’s a billing/project-credit problem\n- likely both keys belong to projects\n with depleted API credits\n\nBottom line:\n- yes, I see how `pi` expects it set up\n- no, the new key still does not work\n- blocker remains Google API billing,\n not local config\n\nBest next move:\n- create/use a Gemini API key from a\n project with active API billing/credits\n- then I can re-run smoke test fast\n\nIf you want, I can also prep the exact\nshell snippet to keep Gemini available\nonly for fallback use.", "textSignature": "{\"v\":1,\"id\":\"msg_0d29dbf88c868f5a016a12eb641288819680859823bd40103f\",\"phase\":\"final_answer\"}" } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 2533, "output": 294, "cacheRead": 252416, "cacheWrite": 0, "totalTokens": 255243, "cost": { "input": 0.0063325000000000005, "output": 0.00441, "cacheRead": 0.063104, "cacheWrite": 0, "total": 0.0738465 } }, "stopReason": "stop", "timestamp": 1779624802058, "responseId": "resp_0d29dbf88c868f5a016a12eb6234908196812592b200519928" } }, { "type": "message", "id": "d6d76a80", "parentId": "7fb70171", "timestamp": "2026-05-24T12:15:15.761Z", "message": { "role": "user", "content": [ { "type": "text", "text": "[telegram] but it was supposed to be free?" } ], "timestamp": 1779624915732 } }, { "type": "message", "id": "8b5a7fcb", "parentId": "d6d76a80", "timestamp": "2026-05-24T12:15:24.281Z", "message": { "role": "assistant", "content": [ { "type": "text", "text": "Yes, but “free” here is misleading.\n\nWhat seems true:\n- Google still advertises a **Free Tier**\n- but your actual API calls are hitting a\n billing state that says:\n `prepayment credits are depleted`\n\nSo likely model is:\n\n- free tier exists in principle\n- but your key/project is attached to an\n AI Studio / Gemini API billing bucket\n that is exhausted or not eligible\n- therefore API returns 429 anyway\n\nPossible reasons:\n1. free tier has project/account limits\n2. old AI Studio projects moved to\n prepaid billing behavior\n3. region/account/project state affects it\n4. “free tier” does not mean\n “unlimited no-billing API forever”\n\nSo bluntly:\n- yes, it was *marketed* as free tier\n- no, that does not mean your current\n project can still use it for free now\n\nThe error message is the key signal:\n- not “invalid key”\n- not “model unavailable”\n- specifically:\n **credits depleted**\n\nThat points to billing state, not config.\n\nBest interpretation:\nthe free tier is not currently usable\nfor this specific key/project.", "textSignature": "{\"v\":1,\"id\":\"msg_0d29dbf88c868f5a016a12ebd715e88196ae3331d85898e3d6\",\"phase\":\"final_answer\"}" } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 255211, "output": 245, "cacheRead": 0, "cacheWrite": 0, "totalTokens": 255456, "cost": { "input": 0.6380275000000001, "output": 0.003675, "cacheRead": 0, "cacheWrite": 0, "total": 0.6417025000000001 } }, "stopReason": "stop", "timestamp": 1779624915737, "responseId": "resp_0d29dbf88c868f5a016a12ebd3e3888196aaa7a383dfa63a5b" } }, { "type": "message", "id": "550a399d", "parentId": "8b5a7fcb", "timestamp": "2026-05-24T12:20:26.529Z", "message": { "role": "user", "content": [ { "type": "text", "text": "[telegram] check online how pi people do it. pretty sure you still can for free" } ], "timestamp": 1779625226507 } }, { "type": "message", "id": "5231bd80", "parentId": "550a399d", "timestamp": "2026-05-24T12:20:44.226Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12ed10e9648196a48806255297c474\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABqEu0b5nRd69mWgY5gbVb8e6MqqMBSMYLnRK7J6jZIAfAsNfhIEMN4b2CX4lqCd6Z2niYTMlVOTsW2rgaPMAsrkMtGbjAujLGdfFyt-T8s-i6qPcb-O1aZWhgMCuQWQujEv_LLc5TJzxkh3Vt-EfLp52tSTXusv0IU-DG8-Sisx1hXLZfgO6zhTJibFhs_PzY6rsigq4GlKqI5_mglMf6AvL6rTd08OMmsKX9hfQytJygKC6_KAum-yjzI59wEU0Mi3E8bRTbfBqVw_IXsspZUYzKpurRhfPXr1GmkQ-uxOcrDEMa_3h51TK_vAc7Ns6F7Uj9LE4BeFzUpxDSBPknBvHGSPHUWdYuAB5tG9OV5VpPm__XKOoqdmpA_Gc5xzB6gMG3o93KnotV50e7KqJFUDyrk0wWltX2WzLSFhqP0CKsupL84AkDIF5mFNBkcF228llZBDE62u_rcpKwTkJth17fY2QpXD1mpN_NzsO9Vb5K2xnrQPuu91y75Kx0js86D2S2AJa2lCL8kYea8DLbs6sAlL5HLmZolC8T9JvSIW3rrt5fwsiObxPIdzjG58VNPbIr_5sVQoPYorv5qzf7TWKRcQoSE4xLv5UTtLRJYFf3i3b-knvLbiDQyiB7Gq1V3EziTwtMF75HOuvuiBHXO9FerDz2K-NZPMELhviaSnetdIKLRHm-tJi4ejSvbiv9OtLq-yX0YlsGcJ7U3prdmW4yNN9r6crgB8V_q0ynB0HnYMU9lvgjEbZYzKYWWUI6NYIABiLi-Aat8APqsNmVFYFWnRuGX0DvB_SX_-ndSuqBu-StAGj-TN6IDrN1VzmSLmSQPi7a6A08uOr7qG-glj8k9V6OiYEuW730mN2_14DIvXvanaGacs-sBaC3jQ-P9gMH-144mhhUSooKUeiAZ4dZd-ssZl324z9cRM0g3bESaCl7BouWVvqetdOn1Km9K0CZhkFBPNFdGI0dbTN87qKIDIB7-yMIPRQL73Qgy35YBwi395YDds-gCYKrA5x7Evem7Ng5K-AesrWYEHHDIGyRUaYWYm9s3FLCaHsmZ0bzg6kIN5J6AsCPLbJ52HC8TQ2MxH-EHR9SwBV7T9BVrW55TnOi1noQJWx42C8fTzrF2lAs9fdX-I4nauGgRZvVAEGT1laiWKamBjiPyrwaC2nVsR5nU-DWFpPVkZoZwbKH6XMk=\",\"summary\":[]}" }, { "type": "toolCall", "id": "call_2nxK3nqAzpDfknwcRWnQK83c|fc_0d29dbf88c868f5a016a12ed1bf284819690cb87d9d25bdd71", "name": "bash", "arguments": { "command": "python3 - <<'PY'\nimport requests\nurls=[\n 'https://github.com/mariozechner/pi-coding-agent',\n 'https://github.com/mariozechner/pi-coding-agent/blob/main/README.md',\n 'https://github.com/mariozechner/pi-coding-agent/search?q=GEMINI_API_KEY&type=code',\n 'https://mariozechner.at/posts/2025-02-15-how-i-use-pi/'\n]\nfor u in urls:\n try:\n r=requests.get(u,timeout=25,headers={'User-Agent':'Mozilla/5.0'})\n print('\\nURL',u,'STATUS',r.status_code)\n print(r.text[:2000].replace('\\n',' '))\n except Exception as e:\n print('ERR',u,e)\nPY", "timeout": 60 } }, { "type": "toolCall", "id": "call_fY5mPRQODPPxC7usuEHqywD9|fc_0d29dbf88c868f5a016a12ed1bf2988196a3dff9b43dc8f9d9", "name": "bash", "arguments": { "command": "python3 - <<'PY'\nimport requests,re\nreadme=requests.get('https://raw.githubusercontent.com/mariozechner/pi-coding-agent/main/README.md',timeout=25,headers={'User-Agent':'Mozilla/5.0'}).text\nfor pat in ['GEMINI_API_KEY','--provider google','free','AI Studio','provider \\(default: google\\)']:\n m=re.search(pat, readme, re.I)\n print(pat, 'yes' if m else 'no')\nif 'GEMINI_API_KEY' in readme:\n idx=readme.find('GEMINI_API_KEY')\n print(readme[idx-500:idx+900])\nPY", "timeout": 60 } }, { "type": "toolCall", "id": "call_gxur7agUkHTBabrcQRKVUdZ7|fc_0d29dbf88c868f5a016a12ed1bf2a081968d0439a1aa486138", "name": "bash", "arguments": { "command": "python3 - <<'PY'\nimport requests,re\ntext=requests.get('https://raw.githubusercontent.com/mariozechner/pi-coding-agent/main/README.md',timeout=25,headers={'User-Agent':'Mozilla/5.0'}).text\nfor kw in ['google', 'gemini', 'free tier', 'ai studio', 'api key']:\n print('\\nKW',kw)\n for m in re.finditer(kw, text, re.I):\n s=max(0,m.start()-120); e=min(len(text),m.end()+220)\n print(text[s:e].replace('\\n',' '))\n break\nPY", "timeout": 60 } } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 255480, "output": 597, "cacheRead": 0, "cacheWrite": 0, "totalTokens": 256077, "cost": { "input": 0.6387, "output": 0.008955, "cacheRead": 0, "cacheWrite": 0, "total": 0.6476550000000001 } }, "stopReason": "toolUse", "timestamp": 1779625226516, "responseId": "resp_0d29dbf88c868f5a016a12ed0c3ad881969cfdc27d04933980" } }, { "type": "message", "id": "62f3fa03", "parentId": "02395bdc", "timestamp": "2026-05-24T12:20:55.278Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12ed20cedc8196af4de4175182a464\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABqEu0i4oR461iz0Mc5Ez-grhzTh_IPiO0j1JTtq3a9IhGFQjVljnD-DW2O4a-dIBC4qxxa_ihPeGwGp7wE4_rp9PnoMQSZ8AdiF4-PwnuyM_CAv7YXR8VBuYKIsXcjKxd9_TYqKh0_yl44HJ9yp1oBYegbYMFJhKzPk0kj3wL3jFjJlMeoC6yogecfsoGnAL0uEvFFHWiZYTT5ckmh0lYQJzbdKqcEUsgbCyPd5NhVo63IukgDudnnIzMpChsXmouKlbn1QQjJy2fGnPOYgQE9bjBgoQh-WYUWQo2jVXMvarFoHFbOdU1DAyAPK3jhNk4HcBAvuRS7e9rKo067p8Jx5IUBXqwhstXyygKx3PCjP-CN8oApop7ibrPArxNUiBbt7kRZ6agKwNPdRLkBRRskGvl6aFDRo5p6pu0v38-eJhqpHnmhOC_RVZAX_BYd_Px0Jreu3TWIt6SPGruTsUBFUk_mjodUwScGb2lHnkZ1pawIrt9oWjL5o9Wg7Bi2ql9oDAKeWpLmJ-2YplRQY6hBJje2WVaNufNwI71a8XLZi5dnE_FTQ0gUuew2ov6mabJfY1dsLcmo8QAVY5RznBEWjRT4UjDYp1Hj-OH9Jw3ICJ7N5oZewVBV-5aCzwplw-zrvIfZp3ICSK3RzoaDeddoDXnCQRHsaVhb8YfTXB2iIK4sXzX9nlZ4rCinPh4odbHUi1Ocn2vxxyfOTm6vp3_Jc1C0jNcQSebO1vQEH_FyjBa87B33A_pOeLP4GM1VzZc3oTyOxjd-LgmeiPVmC7bMONUB6OuVSNOFJA1e7NFH-EmRR2p-UhVzWyJ8T3FoBe1SWqPryPtF86ManlcHwr11IipJpD0f5nm4tcj3nOayYONBTAVTD-s0mUEGqfrzpRdJDVxwwpKx9pEoGj24Tl_ETQxMZYjiGhiJRbjYmxgQLob60Tusv0tS7zwaQn9PrfpEFmLXRBRfX7ZxzTImw1Y9FJFv4yxczu8PM7RArGRjxBkp_yk9HNmGRaALxohZXGHI9Y5fUlIdOtxi09YrI57v1YXEuNumroa-1t0KsU22NYQoe7M9YoM-qTtlsphi8XsnDDsXhT1UOJywPI5VGr7fD3f3D9yOZesJZiV4snGQPzWjY8dQ5u10zKgFB5sLdIux1PMValKf2Y0ECWcEcmUWYipUmrrkSb1lSQEO60HeOhkPvTk=\",\"summary\":[]}" }, { "type": "text", "text": "I checked what I can.\n\nWhat I found:\n- `pi` itself expects Google via:\n `GEMINI_API_KEY`\n- local help says provider default is\n `google`\n- so the usual setup is just:\n - get Gemini API key\n - export `GEMINI_API_KEY`\n - run `pi --provider google ...`\n\nI did **not** find strong public evidence\nof some special hidden setup that avoids\nbilling/project-credit issues.\n\nAnd your new key confirms that:\n- config path is correct\n- API is reachable\n- but Google still returns:\n `429 RESOURCE_EXHAUSTED`\n `prepayment credits are depleted`\n\nSo this is not:\n- wrong env var\n- wrong provider flag\n- wrong model name\n\nIt is still:\n- the Google project behind the key\n\nBlunt read:\npeople using `pi` with Google for free are\nprobably doing exactly this simple setup,\nbut on a project/account where the Gemini\nAPI free usage is still actually available.\n\nFor you, both tested keys are on projects\nthat are not usable right now.\n\nIf you want the next high-signal move:\n1. create a **brand new** AI Studio key\n2. ideally from a **different project**\n3. then I smoke test immediately\n\nIf that still 429s, then we know this is\naccount/project billing state, not setup.", "textSignature": "{\"v\":1,\"id\":\"msg_0d29dbf88c868f5a016a12ed221fc48196bdf735cac6be594e\",\"phase\":\"final_answer\"}" } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 9074, "output": 338, "cacheRead": 248832, "cacheWrite": 0, "totalTokens": 258244, "cost": { "input": 0.022685, "output": 0.00507, "cacheRead": 0.062208, "cacheWrite": 0, "total": 0.089963 } }, "stopReason": "stop", "timestamp": 1779625247231, "responseId": "resp_0d29dbf88c868f5a016a12ed1f626c8196a4d566b382a0007b" } }, { "type": "message", "id": "dcf6db2b", "parentId": "55640644", "timestamp": "2026-05-24T12:34:41.083Z", "message": { "role": "user", "content": [ { "type": "text", "text": "[telegram] then remove entirely the memory that tries to use free llms. no free llm is usable besides google and that is not available anymore" } ], "timestamp": 1779626081078 } }, { "type": "message", "id": "26821388", "parentId": "dcf6db2b", "timestamp": "2026-05-24T12:34:49.953Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12f06329748196a3bc1148bb5c6550\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABqEvBprNg0AHa70oxH1NP3TW4Gmgc6ROVMZ_KHEBGCSb_-htYmLtHIXq45fUizRRzbxEgFUz7wuDcTIA3MpbYqdSL_zhGQlWaEMnGCmwFvHtB8CZm2VnlNDA77ghyS7H26LhRWFNGB1sq9kOZWRV-Ix4Fmfg8iMsqr9bW_hRRuAUzPaVshXiJz40tDQUIC2OexFamfnnBOHtuFBegvEVodB9BQJW-dr7YWi4H0w4KUUOOl2pYgViNlgo7Fw5DUv2rppLFNOTKCWkihBVRzEzqzLMmIrwmv17snal8bLsOrhtjR2lfhZDNb0leu6kMYqX7KJWOKUF2BsAbY7YY4fySlnQngQViHtjeCVd89osODHNUxrJB_QKPlsEld7r1p8J4GByCPeUgPT6H0QJszZemQGXoea3B2prgTC-SySGoUOt6wIJsanVcB-2qZ_hM_XkVo-Dg153wFSWQaFw752Jn9e2AOD8ZsUxawIqJK36-YJOKgoXFwU8g2Ijrin2xVCtvADPoaVlpmgJY5_ySzkRue-U7dd1UYkID_0SuStX4Wt5aCmJUp2-9vgdWObTztBnDZxH-AXQ-zaV16NsV5pnl8mvanqxjTXXwlHYp_LclcfW4vblUTkAAAGnVmngDOoAjmHWS1U0ae6pkYb3uxGltP1lhRBX8wVlcHqCSJhytedIqFw1l2NENy1pD3cYvDyemvPM-g0gDDn-yKhK_UZniqBP1ojvMb928gO6Rwutta0vVg8uUNAQDk6JEtPfmiF4fIElOUHqbiHiyrTpC_zO3a07x2Qb5VNFAKIWGZS1sE5D7ce4mySJVnLuPC55AVZ14n8c95xREfDKkzZ0d4OCMwzNbkqhxqU-0zGcALxfHDLvtqn81oY_WWKSpNDkuNT9JD_F6hCOR39efAZZCYgXW2WQ7L6zz04zIGF-KytMMnlMMO3JG9U4zXJVBB7ZWPoA2N2mriM5tL2sWtwdZ7aJ-4-nRzJr7r1URC_aZbEeFUo0y6Z2yyYWsIjJ-V49ryXSeJ9KBRpx6yiu5CvzTfZzzvKsHcjvq0TYW8DetqRSrBD3RSwH_ohcn0S1SEFYMunay4CfOSyYw8k1Cr9s83C8dn6J_XeK_6Fu9kPmv5KS3ikI0kx-KJiAQJCw8umkJEDOha5htD5p9zXAQBAhZA0tGZdi3Z4OnjTSW__Bl8kPYh5dEvO80G4MTVTsjCDJ-qt5X28blaB9QbjL7KkJkiume7KusLbgDFZ3yx1_1U9CcLfVDCYv5iB06giPvD26gWcinWVQekPtPWXJEtxPkuEekVcquMghhIJTu-DRHh321RRUd9lfSjZMvSarO9kiTVZiXcAXy4G2OWq9NBZk_lkfZw36VdTjz2-anOIWGQ0NHYsqVRxdWvd9oOY_sj6yKGvHZEIT5B6GUvtS5jB-gkEYxgWuqfcVhyLRy5b16t2qXl4Pvfwt0dPQV4vVQV4Lvc7zhA8fiZAr-_wxdRVB3kZMtGwCIk6BJW-X_tuY_5B1sRZ21Q6DkKlprpWN_5ew4y3OloYKGWhVII7UHu7n919FNYNfTmNAfRa_aMJaXulRarKRhb-S2AfGCYVwVXwM6Z775nehYs7hDYSvPJhcRx8KGAG0QogXvCC1XJJDoMiiVv8yVROqIUrcO3cVYZG8smhw8j5DcDUv5ZLyVLeZNm0UEp3CW_uCpz8H-TC9DBwUqjxOnf14bgijFbnS2swUuRAwEgIgGWRYlqhVQNxG7kbjSu4gYV89uQWXAjIxQ2-k7ITLRb0wQ=\",\"summary\":[]}" }, { "type": "toolCall", "id": "call_VgWfl0JkE8GgoSoSrV6e8BA3|fc_0d29dbf88c868f5a016a12f069b0208196bafe0f990f9bc07a", "name": "bash", "arguments": { "command": "python3 - <<'PY'\nimport requests, json\nq='free llm fallback google quota free-tier Gemini fallback'\nurl='http://100.116.176.16:8091/api/search'\nr=requests.get(url, params={'q': q, 'limit': 10}, timeout=20)\nr.raise_for_status()\nfor m in r.json().get('results', []):\n print(m.get('id'), '|', m.get('title'))\n print(m.get('content','')[:300].replace('\\n',' '))\n print('---')\nPY", "timeout": 30 } }, { "type": "toolCall", "id": "call_MEfsI6Sh7rJJRpPdV2aCEcK6|fc_0d29dbf88c868f5a016a12f069b03081969e0c2ea9c77a1c51", "name": "read", "arguments": { "path": "/home/sebas/.agents/skills/memory-write/SKILL.md" } }, { "type": "toolCall", "id": "call_wgNjbYNfQQ4vvMIkj0qB6TNu|fc_0d29dbf88c868f5a016a12f069b038819687d2e7e3035f1aa0", "name": "read", "arguments": { "path": "/home/sebas/pi-config/AGENTS.md", "offset": 1, "limit": 120 } } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 31559, "output": 358, "cacheRead": 0, "cacheWrite": 0, "totalTokens": 31917, "cost": { "input": 0.07889750000000001, "output": 0.00537, "cacheRead": 0, "cacheWrite": 0, "total": 0.08426750000000001 } }, "stopReason": "toolUse", "timestamp": 1779626081079, "responseId": "resp_0d29dbf88c868f5a016a12f06256608196b4ae720e2e74eef0" } }, { "type": "message", "id": "a6b9be08", "parentId": "9d1e3d07", "timestamp": "2026-05-24T12:34:56.987Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "**Searching for delete API**\n\nI need to find a delete API, which likely means checking to see if the service has a specific endpoint available. It seems like I’ll have to use the right request generation (rg) to communicate with the API effectively. Once I identify the appropriate service endpoint, I can proceed further. It's all about ensuring I have the right tools in place to accomplish what I need.", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12f06b1b308196898310e7df61871c\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABqEvBwkCHXlgr5rHP2Mygi5uYXz2Cv4T71C9NZezdlEa3U_HJrQFXv3q4QpZT1kvqUKEJnBsDMno8CtaD958EzDeSb2bB3KK9QPza5N215yhk2U2a6vYCF5HZaj1Dr9LsQ38G3UqwQBrlyV-dq_EAjMkRLbo-hA552SfK66UyH_p6z1n8j7EU4E5fr6gNhmRMOLJik-HvjBN_ZfXMsJa2PdRjksnrTtyTQPRuQPtyjaSjuMwirA04rWgpc9mH0QkukHWqayj6n2TnnhO4zWhZONV91-GtY-647Of69tTiH1EqWik7FONzFGUcBNntGruS-6U28HeEUtKnDYjsneXaVe21zYEBSqx1sq9I1Fj0dZGeJ1vIGtqVDCzyom8U3aBgsDCTyxc_ivWx-QHwE3COc8hcHbAr-X4kxHwoksqK61FzxLiUd4mJkTfGgdoO0o4xVLEBI4KYQwIq3eO6wb7BEM9WHjgn6ZZTX7Do-SKxEVbX81AJ0MxRiUOzQTXqtVRdNCIz_H94c9m_3nJh9YVHec6MELEqjSZitQ1YHqGxRTzV2Vm9YtHK82SkJtl2WVZDoViXize0iUw789SPUZelKILxisoY-NhQKle_u4xKSvslbLvEyGjN7TA5OeCp3fVeaPYSQ3UFCUfVRQKTHv2Wu85WJFZmYdvx9ypOCc2eU6CDEVrRKOuT77AWIyVb5pr3zCLDz3NRO8C0KIxqoum1_MBJZiF2MeKcdf7o-jbnfyD18lINVF6Ow2qnUOky4xzivqZNPn0xce_are5yeNl8SUCllqeNB2DUeHoQ1HrmMuHtqVs4Q-wMQ0lyoCzziVcbML17rnV58TKwR4XmEz4tBODjWPQt1--Bkixq6RW6xnOSS5FcpBLq80_T-BKX0AAgyJIBMCgPkSgljAhZNvfTo18iLz_rY4EHGKtwyJj4JWEe-xBPTl9FZjoWKS856Zhxj27J2KbF1oL1KeXZUhz8fPwEBoeDTJCa7ja5_LU_agMxpgJo=\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Searching for delete API**\\n\\nI need to find a delete API, which likely means checking to see if the service has a specific endpoint available. It seems like I’ll have to use the right request generation (rg) to communicate with the API effectively. Once I identify the appropriate service endpoint, I can proceed further. It's all about ensuring I have the right tools in place to accomplish what I need.\"}]}" }, { "type": "toolCall", "id": "call_3eQjbhRmkHNu0aqyy6p97hhP|fc_0d29dbf88c868f5a016a12f070b8b081969c9219acf8b0c642", "name": "bash", "arguments": { "command": "rg -n \"@app\\.(delete|post|get)|/api/.+delete|delete_memory|tombstone|status.*deleted|/memories/|DELETE\" /home/sebas/agents-database -S | head -200", "timeout": 30 } }, { "type": "toolCall", "id": "call_aNq8JlDnxofHaqZBzhgKayrz|fc_0d29dbf88c868f5a016a12f070b8c08196a9956125233cd3d5", "name": "bash", "arguments": { "command": "python3 - <<'PY'\nimport requests, json\nfor q in [\n 'Prefers fallback to free AI models when quota runs out',\n 'Fallback non-Codex model preference is Google free-tier only',\n 'Google free-tier Gemini models only',\n 'free providers timeout 429 instability',\n 'fallback only to Google free-tier Gemini models'\n]:\n r=requests.get('http://100.116.176.16:8091/api/search', params={'q':q,'limit':5}, timeout=20)\n print('\\nQUERY',q,'STATUS',r.status_code)\n try:\n data=r.json()\n except Exception:\n print(r.text[:500]); continue\n print(type(data).__name__)\n print(json.dumps(data, indent=2)[:2000])\nPY", "timeout": 40 } } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 3278, "output": 309, "cacheRead": 31232, "cacheWrite": 0, "totalTokens": 34819, "cost": { "input": 0.008195000000000001, "output": 0.004635, "cacheRead": 0.007808, "cacheWrite": 0, "total": 0.020638 } }, "stopReason": "toolUse", "timestamp": 1779626090206, "responseId": "resp_0d29dbf88c868f5a016a12f06a68fc81968651de9b79afdc5f" } }, { "type": "message", "id": "091a7356", "parentId": "4868a0a8", "timestamp": "2026-05-24T12:35:04.424Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12f072e7988196b3a5539524862850\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABqEvB4Qa27luPM9lAcIRnykHlOYT6WOjAGwKyhdxAmjz2x8gmQ1d0xYgFSdTJf0nlVUo1erwtZFqf5SYhKF0FazB5yydO9L3ak-orbcW2zvMFnygVT9QSCv15xgK3S_d13jRx3sHcdb7kwEzQB3t5xQo6wyruSHxTS5583E5fTJpTa0r3aKXpYmuG02Jr4WRYHPb4WNkZekSlTMX2nzAtwifHwn1IP-C4KCElfqbD0U-mMNNhFF282fRShtuUfzxKewNlFZFasTQcmMFQqBKrFPcpWzaoDGAwy-KvcN8lps_v5zdsyPZ197Gtm65Mkmz1wsMav5X68XSAcev1YsTtcpIe-Gi5iwLYf0HP-fuos-wrwpjV6sN-Yv69aEZLKzrLbTrIdUic4qP8xknI6_Vmq-VxIIsFVSN6iKbllnR-FoDne7SVACWDpWYSmkZXBURbcZx3SvFPVpwzMtQiv4CvxdQtvqeXWdQNBI-B9Err8iPvcd9BUddam5qne1246gQqBVMK0AvpHK06HHovKDiIF6SwPeV8gi6y-pEW9TrAOQ2YPTmgtcVUZDA4pFYi8GrMu9EZ1HjeHkJ1XEY1Xs0qGkaH4_FBAAz0spxMGsTOsG1R9r5VYPa9klBE61ErSpxdcA3zZDOvpp-O4wQfumqZQOYVofkvKPzu2sGxiNZ40rbu4f-M4KciQG76eVuNw386ssZ-Dn6--PqkOoHDQaAdaw0s49TKG3KJomKeJ43vP8piUxdXatH2LqBR9y8d2MTvSNYaGuSJxuQFiZhyiZehPBu5kCF2BdVei_tfF0qN2TOEQCpG2aauY6IC07bUk76aC-AktFEd-Lj6r0UUno8ZubKeA4w_7wAFFfez_9PJ4kM3reEd8pHCEbPoCW5QswQYIdlaRJnixBDlhs1iurZG54bXbLFwqF6fA1qdah3I_FsMSB6XYP9gGvOvqpH0uzL59cgMTvaafpVAsMRkO3WNhvcmKJQ==\",\"summary\":[]}" }, { "type": "toolCall", "id": "call_xU1WNy3pRJMhsINuyYN9Lkmk|fc_0d29dbf88c868f5a016a12f07842588196aff2fc730e7c12a2", "name": "read", "arguments": { "path": "/home/sebas/agents-database/docs/http-api.md", "offset": 1, "limit": 160 } }, { "type": "toolCall", "id": "call_Jya5YCAVeUVoQQJZiwJFczGA|fc_0d29dbf88c868f5a016a12f078426c81969ca47ee9ffde465e", "name": "read", "arguments": { "path": "/home/sebas/agents-database/src/shared_agent_memory/http_api.py", "offset": 120, "limit": 140 } } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 3795, "output": 101, "cacheRead": 34304, "cacheWrite": 0, "totalTokens": 38200, "cost": { "input": 0.009487500000000001, "output": 0.001515, "cacheRead": 0.008576, "cacheWrite": 0, "total": 0.019578500000000002 } }, "stopReason": "toolUse", "timestamp": 1779626097330, "responseId": "resp_0d29dbf88c868f5a016a12f0717cf88196a89edfc690a4d815" } }, { "type": "message", "id": "bc025e4f", "parentId": "d60d1c28", "timestamp": "2026-05-24T12:35:08.715Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "**Considering database methods**\n\nI’m contemplating that there might not be a delete endpoint available. Instead, maybe I should look into directly using SQLite or a service script. That could be a more efficient solution. I'll need to search for the \"tombstone method\" in the service as well, to see if that aligns with what I'm looking for or provides the best approach. Let’s see where this takes me!", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12f079b6c481969d1d0eda64988c88\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABqEvB843Rip353kA6lukiJGt1UvrSx-fp7SwsdTjYVLF3nVG742_qgMwGcnVEBd4lanpKI3Lw2mk1oTsa3hWSufkZ-BBIsfOtgygvQpkTko6q2jGdNzZ8ZYVhGTjIteZfsqn4KPXYyJ-sK2y3wOG4CZt6uxz-uBmOJtaMcIYAwtTDSCsx5Q53UVjc7-POSBwV1pdR4f8fAlApxKxUQ75AldUGgKEXUTwJE-qLftwW8quB9OYw2F62t1Ya7CU8Vt6m4fs9cgthXIiWX8lYA_LRhk4XDVI8kS68cY_lHucFNykjm5JlZ47j6olBQ-P_Ofriew0Etppb80O1jqpOiJ1mCVyhnnLdvFDFXdpaQdu9zG2w0LwZfWBNbB5vO_SHk7A7SCvBRUJHP30a7Fx7WHTSK_0yv0bjc_MWfjOLGcUBstB9hXkB_wsIppZAIiufVeXMIzyjquSAgwMhzLdUC993jlJdVfhdNdTf3w-6AXDoZ9HK83xk1NMAdHxRB0lfhtubkQEv6SLPDPd0fqqkNxdPneFKZU7O7OP9wNfgp9y-Rm0iTprRC4abx3R-KfOY7b8TMlkaWA9Ybzs8SQu5NcMExECi20Z8lmDG3RvZ92pwNerz-UJAt4JgoV_iTyvruE7UvhXj5d1jb03-mACxk639bakvpuIH6UzYu_1UuirMibspkg7nljPzmBXdp87EWKBYPwA5ci9HoIturv8-va8_cf3t0hpit7SLbpJF-Bl29xhZCXpYV9CCMj1GR6ixZkjj9fCPQ5mzZ9Qlb8rolexXPt5sPMQFfyaAxdL8EXQ7bosUQUuqSrrOWyYMM4bTMIJI-Co45nSk2H9bikLmgJ4vhYXDLhofQsFtkXyw05u_BB9iNSi8Hju708-gNmbqowpYwkCQjEHfo753OS218k_drqQINC5WETXlxUN91ZD8NyzYZpnifPaDDoIBsjpa-M4FBXAICa_65f72SNWAEOUiCUcH491zCnW9T7muirzOfX0yODTaRDqXVd6E2upEGZzeldB0VqkBcjoQpSmMH94nkm83cHB8YDJbWe4uAYXSXudZflXA=\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Considering database methods**\\n\\nI’m contemplating that there might not be a delete endpoint available. Instead, maybe I should look into directly using SQLite or a service script. That could be a more efficient solution. I'll need to search for the \\\"tombstone method\\\" in the service as well, to see if that aligns with what I'm looking for or provides the best approach. Let’s see where this takes me!\"}]}" }, { "type": "toolCall", "id": "call_0EGMKTiZQ0PUziKQoo5Gev5z|fc_0d29dbf88c868f5a016a12f07c93e48196a0265a7bd7a69dff", "name": "bash", "arguments": { "command": "rg -n \"def .*memory|update_memory|delete_memory|archive_memory|status=.*deleted|deleted'|tombstone|soft delete|mark.*deleted\" /home/sebas/agents-database/src/shared_agent_memory/service.py -S | head -120", "timeout": 30 } }, { "type": "toolCall", "id": "call_9uTR1Bm3jskSB9PlRTewh3vC|fc_0d29dbf88c868f5a016a12f07c93f8819688b8b85bb1d3e40a", "name": "read", "arguments": { "path": "/home/sebas/agents-database/src/shared_agent_memory/service.py", "offset": 1480, "limit": 100 } } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 2005, "output": 153, "cacheRead": 37888, "cacheWrite": 0, "totalTokens": 40046, "cost": { "input": 0.0050125000000000005, "output": 0.002295, "cacheRead": 0.009472, "cacheWrite": 0, "total": 0.0167795 } }, "stopReason": "toolUse", "timestamp": 1779626104448, "responseId": "resp_0d29dbf88c868f5a016a12f078a01881969726ac7d4602a801" } }, { "type": "message", "id": "3c7b64a6", "parentId": "2efd69fc", "timestamp": "2026-05-24T12:35:13.572Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "**Considering sqlite edits**\n\nI'm thinking that a direct SQLite edit might be the easiest approach. I need to check out the schema to understand the different statuses, like active or archived. Maybe I’ll look for a way to search for the memory's status to ensure I’m addressing the right entries. It’s a good idea to be thorough here so I don’t accidentally mess things up. Let's see how I can make this happen!", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12f07db2c881968fdc3ffc618ce86d\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABqEvCBg5K2yVi3q3lFPTJQM5q7RxD3PAs2rYPYfT87hG6TxeUSY9LlNLr03mQya0_pSxegSA5URDdpyjZetg6PtKSWpzKf5beZcUPZjDacm_PLw6mzBkXYESDsOSv1xIw86cYL7VlynbtbG9rTnOfWE0o7eejql7OCUx8BGVl7TP5qx7ZPKBl6g6V1qPk4484WQNXv0xqsfCCG_omb5znF7XVm3YK1dS5uiys3XyBqi2GeEOR-FdSUo_nn2fz3Tjz6jpr33SbouroUQmaN-zd95GkRygLe5Si7OA8Ws3xGNNWW4V7ltXNUWaRgckae1heZpp-TsvH3bu3wMD62BZd60-FGjpq_98lZ3ePBc0KZJO4viMi4B8Y7c0cRaIV6-rgjYyudbxjc6xeL1eAbMEze-iVOXSqpmZs-41FdQjHEVLSalfmkI2jcwLgDIqjuSgobBLCHRL-37i7pv8Kt427QI5HpIitsZhp6SUg7Dr5RlZHKmmLnvEddw8bGQLUXWlnwB6jbr3w4YFxiO7kWczLGRjJHQD6pA75i9PnEQOiMza84clEUgji79JU4mgQahM_4VEM7teELL_g-XbVPoQ9KiTeObFadPqAAMV3gzbJEzGthlkCWLQIn5dexOyEk37Rx7YcIe8wXlP9WgOa0V-mH3txb_nPHim9IQv6MpMHW-kOebEnmfHMBgoDuHSYv4KNq-KHmBmlHmfhJnVSZtMk7cxj7mKrsDrm8q108fyAvvMrvIMibmGR0J45ys_mKpMVgCQgGdv7xVWIYirhnje4s792UfdHb7ixPf-2HpoK0mAhNRYagMaPBpQ79ggKCjkwCi45yAd7fH_XRdndHs6pKYIogv2WUL2Pqgq8Tz2mSDqu6nQnhSL64pL3Y0eTr2utFz6c6vZzX9nR5NPdfGP1g7vtHmm769VQ9evTsakQmQrZVtmDj96lD3UMuFGlUOJo5xwbg33ilvD7J0R9vQCLuc-BHcpwjn9L7N9a9GmHSJkFIUQcJWrVbe_f0tJ1NUk0Xkh7f8PvJ8dMvS_xMEKZ841KM2Hui13zGZZuZxHxNk3WoKsETuYrcvXHLXx7oZLadxeMs\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Considering sqlite edits**\\n\\nI'm thinking that a direct SQLite edit might be the easiest approach. I need to check out the schema to understand the different statuses, like active or archived. Maybe I’ll look for a way to search for the memory's status to ensure I’m addressing the right entries. It’s a good idea to be thorough here so I don’t accidentally mess things up. Let's see how I can make this happen!\"}]}" }, { "type": "toolCall", "id": "call_YUOQyBP2Ae4meFW4QBQuStDX|fc_0d29dbf88c868f5a016a12f08171748196962b9fcda226f44c", "name": "bash", "arguments": { "command": "rg -n \"status.*memory|memory.*status|status in \\(|active|archived|superseded|deleted\" /home/sebas/agents-database/src/shared_agent_memory -S | head -200", "timeout": 30 } }, { "type": "toolCall", "id": "call_pqBSUwKULVQFmyV0sAAiueev|fc_0d29dbf88c868f5a016a12f08171888196aac05f617cc5343f", "name": "bash", "arguments": { "command": "python3 - <<'PY'\nimport sqlite3, glob, os\nfor p in glob.glob('/home/sebas/agents-database/**/*.sqlite3', recursive=True):\n print(p)\nPY", "timeout": 20 } } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 1961, "output": 172, "cacheRead": 39424, "cacheWrite": 0, "totalTokens": 41557, "cost": { "input": 0.004902500000000001, "output": 0.0025800000000000003, "cacheRead": 0.009856, "cacheWrite": 0, "total": 0.0173385 } }, "stopReason": "toolUse", "timestamp": 1779626108750, "responseId": "resp_0d29dbf88c868f5a016a12f07cec288196a10a60c5901a6e46" } }, { "type": "message", "id": "4ddcf149", "parentId": "c03d284a", "timestamp": "2026-05-24T12:35:31.483Z", "message": { "role": "assistant", "content": [ { "type": "thinking", "thinking": "**Planning memory updates**\n\nI see that the user wants to remove certain statuses entirely, not just archive them. I could think about deleting rows directly from sqlite and FTS using sqlite3. Additionally, there's a note about reverting the AGENTS line. Should I create a memory regarding no free LLM fallback? Probably not unless the user asks. Still, it could be useful. However, since the user wants to eliminate that memory, I’ll focus on both deleting memories and editing AGENTS.", "thinkingSignature": "{\"id\":\"rs_0d29dbf88c868f5a016a12f082d5088196b79e0eb22f168f78\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABqEvCTg8pGp4LPvDMoMY6zidsrYEyk_w8Arl4yLLmM8hEZdUHo8xlQrpUbNLAcvBcV6rlSW6DVD4I1RNbg-H2urOH0B-O52WTYIeMLN5CLr8utvX9l3WF74UF9zVyIwFICmEcswIpl7wkCosEL-2_cKOixov4sD2ffhQm-bo_A41Dxha4-UDn5rWCkHJ5kIxFiPkCU039NPCllv3b3LForg3PYErpayP-RttHyJkLct84HXPFZEXqIRoFtIcuKPRJAVXfemrsNZa1iNa0Ug47KR2EM79RA4LQRQU4YwM_fU7cwjvx-ZtfelzX_vc16UHxIpPm4tvfKsneKGOapD-QMhyaeOQKaFI0t5DrML4AjKzr7kap0mDiEROOh003QNrpdF64nk16FgXSQA8oW9aCUzhI27ejqFrLHqN27q6nCo0Wxloj9hxofVkQW_KCHF51bRwLM8iZoXCZtglm-0k_k67xsFhW9wtSOPwaB7bU2jhVRW2ITKdZRJDA0rAla9eYMnhbvxEkHu6SDV7u9H4Mqu2RLTZOBdRJDi3gdXfwW3g3PXCEiLVjk8yCGnpuoqw0G6LlPgg05aSLHTHHuFbkNeJMqrlmxbiiRKT1vhuw9DtRljnYriwvsd1Hkh4r78q3POSCtL6Gy_zAvi1r08WQ03swXaT4v49Lx1oIW3CC7fuWnWjVS-8iIGv1B1XsurFOBtMsmToToCFP7qrzztzjM2Hq5HLmufwBuLru9gu9d1CtXnrYu5H9NbC2umqM-oeKpclXJJGQ1VvOJgJn1tFiNqIZ6MwWwxIct6kN5tE7NrLxhKQb_jFrZxNbmJd-ofkMT2UXC6sPv0yF9e2W4ABwgxfwM4v1aZKH_Qrq1hB7JvES_ZjRq8fVXwr5NKvJuMhTo8E5qOl6xs_nGy_DfOXm5J6SYZL97683LFRfznVN2NEQOjSvIWMM6mhkHRoLJbd9XGeml2nnbwXNDMzrz22p1yHwurAgj2BLuLC3TP9I9JQtJdxjOZPAucgUpI3g2cdHSiD16yx6sdNIWvTSSePalJcrdXphJaged-FvIAKpknLd5OFMX0askj05Y2SKFyWaK9tQB1aAanIDX3iQzZnK-8LpY1aunv5rHrit0rRuWoTQxwvGKY654QWgxvflsMxsmbrCaMq8mIa1wljQ9Mkj-Wg3R-cdq64JAEqEbpKvgvo3cTyPSsa0k3VNYzNXEujvr0-iHqZ7-OTjXVAwFiWIE6pG5ugqb5udOF99svCEKt9o4bMuVw_B-TdbP0_YmW1XIoTDOdDwDs9O0JEtArCuhuiiesO6O7esKG4c7yhYnZA2xbEFVdSXvJHoTHSXoBqxgyoIgpb_9LLOJ0El8H1wcA8UhfxLBipsEPwl8KLUUGzxE-MMYuxCK_ori8rD6t0P4ck5IY9Hd1yVW1lJSOtl9D2DLmKI-boGJR8XQtvaR0dVRFFQ=\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Planning memory updates**\\n\\nI see that the user wants to remove certain statuses entirely, not just archive them. I could think about deleting rows directly from sqlite and FTS using sqlite3. Additionally, there's a note about reverting the AGENTS line. Should I create a memory regarding no free LLM fallback? Probably not unless the user asks. Still, it could be useful. However, since the user wants to eliminate that memory, I’ll focus on both deleting memories and editing AGENTS.\"}]}" }, { "type": "toolCall", "id": "call_66dQJqfrB4Nfjy3GiyyK6pNp|fc_0d29dbf88c868f5a016a12f09338788196985608d09a07a0f2", "name": "edit", "arguments": { "path": "/home/sebas/pi-config/AGENTS.md", "edits": [ { "oldText": "- Prefer few strong memories over many noisy ones.\n- If Codex quota/rate/auth becomes unavailable and a fallback model is needed, prefer Google free-tier Gemini models only. Do not fall back by default to other free providers because they are too prone to timeouts, 429s, or instability.\n- This Pi config repo is the place to evolve these rules.\n", "newText": "- Prefer few strong memories over many noisy ones.\n- This Pi config repo is the place to evolve these rules.\n" } ] } }, { "type": "toolCall", "id": "call_ekZ0x8gqlHo99ntlPTMEZGGa|fc_0d29dbf88c868f5a016a12f09338a48196a6074a27870a5a3f", "name": "bash", "arguments": { "command": "python3 - <<'PY'\nimport sqlite3\nDB='/home/sebas/agents-database/data/shared-agent-memory.sqlite3'\nids=[\n 'mem_def0c389189143f28f37df63cebabe3c',\n 'mem_716699746ab8484e9311cbaeb33f516c',\n]\nconn=sqlite3.connect(DB)\ncur=conn.cursor()\nfor mid in ids:\n cur.execute('DELETE FROM memories_fts WHERE memory_id=?',(mid,))\n cur.execute('DELETE FROM memories WHERE id=?',(mid,))\nconn.commit()\nfor mid in ids:\n row=cur.execute('SELECT id FROM memories WHERE id=?',(mid,)).fetchone()\n print(mid, 'deleted' if row is None else 'still_present')\nconn.close()\nPY", "timeout": 20 } } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 1615, "output": 451, "cacheRead": 40960, "cacheWrite": 0, "totalTokens": 43026, "cost": { "input": 0.0040375, "output": 0.006765, "cacheRead": 0.010239999999999999, "cacheWrite": 0, "total": 0.0210425 } }, "stopReason": "toolUse", "timestamp": 1779626113630, "responseId": "resp_0d29dbf88c868f5a016a12f081c8e0819696e4822059478012" } }, { "type": "message", "id": "9d6a6bdb", "parentId": "39f409c9", "timestamp": "2026-05-24T12:35:34.087Z", "message": { "role": "assistant", "content": [ { "type": "text", "text": "Done.\n\nRemoved:\n- `mem_def0c389189143f28f37df63cebabe3c`\n- `mem_716699746ab8484e9311cbaeb33f516c`\n\nAlso removed the free-Google fallback rule\nfrom `AGENTS.md`.\n\nCurrent state:\n- no memory says to use free LLM fallback\n- no AGENTS rule says to use it either", "textSignature": "{\"v\":1,\"id\":\"msg_0d29dbf88c868f5a016a12f09459b48196808480e9dfe0beb4\",\"phase\":\"final_answer\"}" } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 607, "output": 88, "cacheRead": 42496, "cacheWrite": 0, "totalTokens": 43191, "cost": { "input": 0.0015175000000000002, "output": 0.00132, "cacheRead": 0.010624, "cacheWrite": 0, "total": 0.0134615 } }, "stopReason": "stop", "timestamp": 1779626131553, "responseId": "resp_0d29dbf88c868f5a016a12f093b3f08196a12746a21afa5811" } }, { "type": "message", "id": "4718ab96", "parentId": "9d6a6bdb", "timestamp": "2026-05-24T12:37:54.676Z", "message": { "role": "user", "content": [ { "type": "text", "text": "/new" } ], "timestamp": 1779626274669 } }, { "type": "message", "id": "188ed767", "parentId": "4718ab96", "timestamp": "2026-05-24T12:37:57.682Z", "message": { "role": "assistant", "content": [ { "type": "toolCall", "id": "call_yYqUbp5vN2gMP8SC28uTe7Up|fc_0d29dbf88c868f5a016a12f1250e288196b3d038506c0288b7", "name": "bash", "arguments": { "command": "/home/sebas/pi-config/bin/pi-telegram-new-session", "timeout": 30 } } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 42876, "output": 33, "cacheRead": 0, "cacheWrite": 0, "totalTokens": 42909, "cost": { "input": 0.10719000000000001, "output": 0.000495, "cacheRead": 0, "cacheWrite": 0, "total": 0.107685 } }, "stopReason": "toolUse", "timestamp": 1779626274671, "responseId": "resp_0d29dbf88c868f5a016a12f123db188196bca13480558d0ed4" } }, { "type": "message", "id": "c29408ef", "parentId": "5063d85a", "timestamp": "2026-05-24T12:37:59.406Z", "message": { "role": "assistant", "content": [ { "type": "text", "text": "Rotated Telegram session.", "textSignature": "{\"v\":1,\"id\":\"msg_0d29dbf88c868f5a016a12f127173481968f14685b4698a437\",\"phase\":\"final_answer\"}" } ], "api": "openai-codex-responses", "provider": "openai-codex", "model": "gpt-5.4", "usage": { "input": 434, "output": 9, "cacheRead": 42496, "cacheWrite": 0, "totalTokens": 42939, "cost": { "input": 0.001085, "output": 0.000135, "cacheRead": 0.010624, "cacheWrite": 0, "total": 0.011844 } }, "stopReason": "stop", "timestamp": 1779626277698, "responseId": "resp_0d29dbf88c868f5a016a12f125d8548196a468f35ed29d732c" } } ], "user_messages": 24, "assistant_messages": 92, "last_user_text": "/new", "last_assistant_text": "Rotated Telegram session.", "first_user_text": "[telegram] how many new rss feeds are available since last merged pdf generation? (also is the pdf i talk about easy to find for you or did you take a while?)" }, "analysis": { "status": "completed", "save": true, "saved": true, "memory_id": "mem_c089dddd4e6742e388b77447978d883c", "memory_ids": [ "mem_c089dddd4e6742e388b77447978d883c" ], "saved_count": 1, "raw": "{\"memories\": [{\"type\": \"episode\", \"subtype\": \"session_summary\", \"scope\": \"global\", \"title\": \"sebas: [telegram] how many new rss feeds are available since last merged pdf g…\", \"content\": \"User asked: [telegram] how many new rss feeds are available since last merged pdf generation? (also is the pdf i talk about easy to find for you or did you take a while?)\\nResult: Rotated Telegram session.\", \"source_ref\": \"session:019e53a0-fecd-7338-b0e0-2e0bdf5925de\", \"evidence_ref\": \"/home/sebas/pi-config/sessions/--home-sebas--/2026-05-23T06-58-40-462Z_019e53a0-fecd-7338-b0e0-2e0bdf5925de.jsonl\", \"confidence\": 0.72, \"freshness\": 0.95, \"importance\": 0.56, \"reason\": \"Deterministic fallback because model analysis was unavailable: Warning: No models match pattern \\\"gemini-3-flash-preview:minimal\\\"\\nWarning: No models match pattern \\\"gemini-3-flash-preview:medium\\\"\\nWarning: No models match pattern \\\"claude-3-7-sonnet:low\\\"\\nWarning: No models match pattern \\\"claude-3-7-sonnet:medium\\\"\\nWarning: No models match pattern \\\"claude-3-7-sonnet:high\\\"\\nWarning: No models match pattern \\\"o3-mini:low\\\"\\nWarning: No models match pattern \\\"o3-mini:medium\\\"\\nWarning: No models match pattern \\\"o3-mini:high\\\"\\nWarning: No models match pattern \\\"minimax-m2.5-free:minimal\\\"\\nWarning: No models match pattern \\\"qwen/qwen3-coder:free:minimal\\\"\\nWarning: No models match pattern \\\"google/gemma-3-27b-it:free:minimal\\\"\\nNo API key for provider: openai-codex\"}], \"reason\": \"fallback-analysis:Warning: No models match pattern \\\"gemini-3-flash-preview:minimal\\\"\\nWarning: No models match pattern \\\"gemini-3-flash-preview:medium\\\"\\nWarning: No models match pattern \\\"claude-3-7-sonnet:low\\\"\\nWarning: No models match pattern \\\"claude-3-7-sonnet:medium\\\"\\nWarning: No models match pattern \\\"claude-3-7-sonnet:high\\\"\\nWarning: No models match pattern \\\"o3-mini:low\\\"\\nWarning: No models match pattern \\\"o3-mini:medium\\\"\\nWarning: No models match pattern \\\"o3-mini:high\\\"\\nWarning: No models match pattern \\\"minimax-m2.5-free:minimal\\\"\\nWarning: No models match pattern \\\"qwen/qwen3-coder:free:minimal\\\"\\nWarning: No models match pattern \\\"google/gemma-3-27b-it:free:minimal\\\"\\nNo API key for provider: openai-codex\"}", "result": { "memories": [ { "type": "episode", "subtype": "session_summary", "scope": "global", "title": "sebas: [telegram] how many new rss feeds are available since last merged pdf g…", "content": "User asked: [telegram] how many new rss feeds are available since last merged pdf generation? (also is the pdf i talk about easy to find for you or did you take a while?)\nResult: Rotated Telegram session.", "source_ref": "session:019e53a0-fecd-7338-b0e0-2e0bdf5925de", "evidence_ref": "/home/sebas/pi-config/sessions/--home-sebas--/2026-05-23T06-58-40-462Z_019e53a0-fecd-7338-b0e0-2e0bdf5925de.jsonl", "confidence": 0.72, "freshness": 0.95, "importance": 0.56, "reason": "Deterministic fallback because model analysis was unavailable: Warning: No models match pattern \"gemini-3-flash-preview:minimal\"\nWarning: No models match pattern \"gemini-3-flash-preview:medium\"\nWarning: No models match pattern \"claude-3-7-sonnet:low\"\nWarning: No models match pattern \"claude-3-7-sonnet:medium\"\nWarning: No models match pattern \"claude-3-7-sonnet:high\"\nWarning: No models match pattern \"o3-mini:low\"\nWarning: No models match pattern \"o3-mini:medium\"\nWarning: No models match pattern \"o3-mini:high\"\nWarning: No models match pattern \"minimax-m2.5-free:minimal\"\nWarning: No models match pattern \"qwen/qwen3-coder:free:minimal\"\nWarning: No models match pattern \"google/gemma-3-27b-it:free:minimal\"\nNo API key for provider: openai-codex" } ], "reason": "fallback-analysis:Warning: No models match pattern \"gemini-3-flash-preview:minimal\"\nWarning: No models match pattern \"gemini-3-flash-preview:medium\"\nWarning: No models match pattern \"claude-3-7-sonnet:low\"\nWarning: No models match pattern \"claude-3-7-sonnet:medium\"\nWarning: No models match pattern \"claude-3-7-sonnet:high\"\nWarning: No models match pattern \"o3-mini:low\"\nWarning: No models match pattern \"o3-mini:medium\"\nWarning: No models match pattern \"o3-mini:high\"\nWarning: No models match pattern \"minimax-m2.5-free:minimal\"\nWarning: No models match pattern \"qwen/qwen3-coder:free:minimal\"\nWarning: No models match pattern \"google/gemma-3-27b-it:free:minimal\"\nNo API key for provider: openai-codex" }, "fallback_error": "Warning: No models match pattern \"gemini-3-flash-preview:minimal\"\nWarning: No models match pattern \"gemini-3-flash-preview:medium\"\nWarning: No models match pattern \"claude-3-7-sonnet:low\"\nWarning: No models match pattern \"claude-3-7-sonnet:medium\"\nWarning: No models match pattern \"claude-3-7-sonnet:high\"\nWarning: No models match pattern \"o3-mini:low\"\nWarning: No models match pattern \"o3-mini:medium\"\nWarning: No models match pattern \"o3-mini:high\"\nWarning: No models match pattern \"minimax-m2.5-free:minimal\"\nWarning: No models match pattern \"qwen/qwen3-coder:free:minimal\"\nWarning: No models match pattern \"google/gemma-3-27b-it:free:minimal\"\nNo API key for provider: openai-codex" } }