Phase 7 (ADR-0004). Cognitive code asks the router for a role; the
router maps roles to configured models with ordered fallbacks, applies
global and per-mind daily token budgets and a concurrency limit, records
every call (request, response, usage, latency, cost, seed, request hash)
and can serve recordings back for exact replay. Providers are raw HTTP
clients for OpenAI-compatible, Anthropic and Ollama endpoints, with
embedding support for the embed role wired into memory retrieval.
Secrets are references only: env:, file:, or enc: values encrypted with
AES-256-GCM under NOEMA_MASTER_KEY; keys are resolved at call time and
never rendered, logged or exported. Outbound HTTP refuses private and
loopback addresses at dial time unless a provider explicitly allows it,
bounds redirects and caps bodies. Provider errors are scrubbed.
Prompts are named, versioned rows with system and user templates and an
optional JSON schema; untrusted text enters only through delimited data
blocks. Six defaults are seeded and never overwritten. The UI adds the
LLM page (providers, models, role matrix, usage, errors, budgets), a
provider page with connectivity test, and a prompt manager with editor,
test runner, history, restore, clone and diff. CLI: provider, prompt.
Phase 6. Beliefs are propositions with a prior set by epistemic kind and a
confidence computed from typed evidence: sigmoid(logit(prior) + slope ×
(support × diversity − opposition)), where support from a single source
is discounted so repetition cannot manufacture certainty, and bounds keep
the mind away from absolute certainty. Every evaluation stores its
breakdown and appends a version row protected by the append-only
trigger; the belief page shows the arithmetic, evidence for and against,
alternatives, contradictions and history.
Contradiction detection is deterministic first (negation plus token
overlap): a hit emits contradiction_detected, links both beliefs and
makes each counter-evidence for the other so both trend to contested.
Operators can assert beliefs (their statement is the evidence), add
evidence, mark a belief wrong (pinned rejected, history kept) and forbid
an inference; do-not-infer corrections block matching hypotheses.
Retracting a memory retracts the evidence that cited it and re-evaluates
the beliefs concerned.
The associate process proposes low-confidence causal hypotheses from
co-occurring notable observations, and the hypothesis handler turns
admitted ones into beliefs with automatic alternatives, closing demo
scenarios 1 and 2 without any model call.
Phase 5 (ADR-0003). pkg/concepts fixes the epistemic vocabulary
(observation, fact, memory, claim, hypothesis, belief, prediction,
assumption, inference, opinion), memory kinds and relation names.
internal/memory stores episodic, semantic, procedural and
autobiographical memories in one mind-scoped table with trust-derived
credibility, importance, salience and decaying activation. Retrieval
fuses full-text rank (any-term by default), optional pgvector similarity,
recency, activation, importance and credibility, and returns the
component scores so every recall can be explained. Decay lowers
activation and never deletes; retraction and supersession keep rows for
provenance. Relationships are constrained to one mind at insert time.
Embeddings live in a conditional pgvector table keyed by model so vector
spaces are never mixed; without an embedder the system degrades to text
and graph retrieval.
Attention gates encoding: the attend handler turns admitted observations
into episodic memories (operator changes become autobiographical ones)
with memory_created events; the retrieve process proposes recalled
memories as candidates and admitted recalls are reinforced with
memory_retrieved events carrying their scoring components.
Memory explorer UI (search with component breakdown, timeline, filters,
operator knowledge entry), memory detail with provenance, relationships,
citing events and an inaccurate-memory correction; API; noemactl memory
commands; decay and embed-missing background jobs.
Phase 4 (ADR-0001). internal/attention scores thought candidates as a
normalised weighted sum over ten named features with a per-term
breakdown, ranked by (score, id) so ordering is total and replayable.
internal/workspace holds the capacity-limited workspace (refresh by
subject, decayed competition, explained admit/reject outcomes) and the
decaying working memory.
internal/brain runs one runtime per active mind: debounced wake-ups from
the event bus (own output never re-triggers), a settle window so
concurrently committing events are not skipped, bounded concurrent
Observe calls with per-process isolation and timeouts, deterministic
scoring, a loop detector that suppresses recurring thoughts and raises a
metacognition warning, executive dispatch by thought kind, and one
transaction per cycle whose events are published only after commit.
Every candidate, selection, attention shift and broadcast is an event
with provenance back to the triggering observation. Operators can run a
cycle, pause, resume, reset transient state and change attention
weights live; the manager reconciles runtimes with mind status.
cognition/attend is the first process: deterministic candidates from
external events using an urgency lexicon, novelty against context and
trust-based operator priority.
Andy Dixon