job f4f0a0bc-7d85-475f-9fbe-7689a53f16be

2026-06-03 06:22:59 UTC · POST /memorize (async)

extracted facts 0 rows

Every ontological statement the LLM produced from the memorized text. Each one becomes a real donto_statement row in the substrate.

{
  "async": null,
  "extract": true,
  "facts": null,
  "holder": "agent:omega-bot",
  "images": [],
  "modality": "descriptive",
  "mode": "opencode",
  "passes": 1,
  "queue_id": null,
  "session_id": "discord:1349727923434815519:1349967527178145852",
  "text": "alluring_piglet_29962 in #resources: Yes. It's still early and I expect the way models are consumed to change and then standardise in some hard to predict ways."
}

{
  "aperture_yields": [],
  "dedup_collisions": 0,
  "elapsed_ms": 126,
  "episodic_record_id": "1254ba0c-c400-458e-b238-3fb414933bee",
  "episodic_record_iri": "ctx:memory/episodic/cfbf1ba3-496d-48cc-a45f-c4ffe81e019b",
  "extract_mode": "opencode",
  "extracted": true,
  "facts": [],
  "facts_extracted": 0,
  "facts_ingested": 0,
  "holder": "agent:omega-bot",
  "model": "upstream:opencode",
  "queue_id": "867258b8-ba31-40ad-8f57-13b0928c99bb",
  "semantic_record_ids": [],
  "session_id": "discord:1349727923434815519:1349967527178145852",
  "usage": null,
  "warnings": [
    "opencode mode: no facts supplied (agent yielded none); episodic stored only"
  ]
}