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Carry the agent's own state and dated excerpts of its own record into every live turn — appended to the message being answered at API time, never the system prompt, so per-conversation prompt caching is untouched. One raw ledger line per turn goes the other way. Works stand-alone; pairs with the biomimetic-brain mind kit, which produces the state file it reads. Disclosure — it appends an agent-state block and retrieved record excerpts to the current user message on every turn, leaving the system prompt untouched; it indexes recent user and assistant messages from $HERMES_HOME/state.db across all sessions and platforms into a local plaintext SQLite index under the configured agent directory, and may surface those excerpts in any later conversation (relevant on multi-user gateways); it appends every turn's inbound and outbound text to <agent_dir>/turn-ledger.jsonl; it loads <agent_dir>/scripts/wander.py from the companion mind kit in-process and may run that script and <agent_dir>/scripts/consolidate-mind.py as background subprocesses with the Hermes environment; no network calls of its own, no credentials, no dependencies beyond the host interpreter (numpy and scikit-learn are optional, with a keyword-search fallback).
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Carry the agent's own state and dated excerpts of its own record into every live turn — appended to the message being answered at API time, never the system prompt, so per-conversation prompt caching is untouched. One raw ledger line per turn goes the other way. Works stand-alone; pairs with the biomimetic-brain mind kit, which produces the state file it reads. Disclosure — it appends an agent-state block and retrieved record excerpts to the current user message on every turn, leaving the system prompt untouched; it indexes recent user and assistant messages from $HERMES_HOME/state.db across all sessions and platforms into a local plaintext SQLite index under the configured agent directory, and may surface those excerpts in any later conversation (relevant on multi-user gateways); it appends every turn's inbound and outbound text to <agent_dir>/turn-ledger.jsonl; it loads <agent_dir>/scripts/wander.py from the companion mind kit in-process and may run that script and <agent_dir>/scripts/consolidate-mind.py as background subprocesses with the Hermes environment; no network calls of its own, no credentials, no dependencies beyond the host interpreter (numpy and scikit-learn are optional, with a keyword-search fallback).
More by ousiaresearch
3 plugins by ousiaresearch in the catalog.
ousiaresearchbiomimetic-brainMeters and a gate for a long-running agent — 25 subsystem state files (energy, fatigue, circadian phase, motivation, novelty, attention, conflict, values, open questions), one folded brain-state.json the rest of the agent reads, four maintenance passes that keep it honest, and a read-only PROCEED / CAUTION / VETO decision gate whose refusals name the numbers behind them. Provides the mind-kit skill, which seeds the files, produces the aggregate, schedules the passes and teaches the gate. Disclosure — portable Agent Plugins v1 package; it registers no hooks, no tools and no middleware, makes no network calls, and reads and writes state files only under the agent directory you choose, where a subsystem that has stopped updating reports stale instead of asserting an old number. No dependencies beyond the Python standard library (two shell scripts for the scheduled passes). Its scripts, when the agent or operator runs them, read and write JSON state under the directory chosen with MIND_AGENT_DIR (default an agent/ folder inside the plugin's own install dir), read HERMES_HOME/cron/executions.db for cron counts, and execute scripts/batch-maintenance.sh or scripts/verify-invariants.py from that agent directory if present; no network egress and no LLM calls.Communitygeneral6ousiaresearchaletheiaEvidence-bound scoped memory for Hermes agents, over the Weft substrate: turns are queued for a local SQLite store under the active profile by default, recall is scoped before it is ranked (deny-by-default, deterministic, never widened by anything read), and every recall returns a receipt naming the scope consulted, the ids selected and the tier. Duplicates are not re-ingested, deletions cascade, corrections preserve lineage. Registers as memory.provider: aletheia and exposes weft_recall, weft_ingest, weft_forget and weft_receipt, with recall on a worker thread so a turn's prefetch is not blocked; the built-in memory store keeps running alongside it. Disclosure — the plugin's code ships in the weft-memory PyPI package (installed as weft-memory>=1.1.1,<2, so it is outside this catalog pin); primary-agent turns are queued for storage in local SQLite under the active profile by default (the path is configurable; writes may be interrupted on process exit); no network calls, telemetry, or credentials on the Hermes path; the required bge-m3 embedder and cross-encoder reranker (~0.7 GB) must already be in the local Hugging Face cache, downloaded from their official Hugging Face repositories, and are not vendored; the Hermes provider exposes text ingest only; the separate Weft substrate supports optional image and audio adapters; macOS on Apple silicon only (mlx); AGPL-3.0, and weft-memory is AGPL-3.0 as well.Communitymemory