edcc6580b6fa748a145c28c4fa20617d79844a0b
11
Commits
| Author | SHA1 | Message | Date | |
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 Andy Dixon
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6fdc3908f5 |
feat(research): ablations, broadcast and self-model experiments, counterfactuals
A framework for testing functional properties of the architecture (Part C). None of it claims consciousness; every measure has an operational definition in research.Measures. - Ablations (attention, memory retrieval, affect, metacognition, commitments, volition, global workspace, curiosity, association, goals, narrative, notifications) and workspace overrides (force a matching candidate in or out of admission) live in a fork's cognitive configuration. Original minds refuse them on create and update; only snapshot restores may carry them, so they are part of the configuration digest. Excluded candidates are recorded with fate "excluded". - Self-model experiments override a fork's self-model (capabilities, identity, goals, knowledge gaps) without touching policy. When an action's effective policy disagrees with the self-model, cognition records a self_model_mismatch and corrects the entry; experiments report self-model accuracy and correction latency. - Counterfactual experiments replay a mind's recorded stimuli from a snapshot with chosen events omitted; the report lists what differed in beliefs, wants, intentions, memories, attention and capability decisions, in a form introspection can cite. - Experiments record a protocol (kind, independent variable, controlled variables, measures), per-variant volition, plan, downstream-by-category (events reachable from each stimulus through recorded links), introspection and self-model measures and event ranges; comparisons add want, intention and plan-capability overlap, measure ranges, a descriptive architecture share and a downstream delta; reproducibility is labelled against the previous run of the same definition. - research.Agency computes want→intention, intention→action, abandonment, commitment fulfilment and conflict, blocked intentions, replanning, outcome success and introspection accuracy; MetacognitiveCalibration relates confidence and expressed uncertainty in replies to later belief revision, with Brier scores for each half of the period. - The sandbox test harness gains volition, planning, agency and research but not the motivation hook, whose wall-clock decay would make replay comparisons timing-dependent. |
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Andy Dixon
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03e2d7890a |
feat(cognition): wanting, intending and acting inside the cognitive cycle
Volition and planning now run as part of cognition (PLAN §8.2 item 3):
- A volition hook derives wants after each cycle from what it perceived
and produced, satisfies answer wants when a reply is sent, raises due,
overdue, expired and conflicting commitments, and expires faded wants.
Events produced by earlier cycles are not re-derived.
- An intend process proposes deciding about the strongest undecided
wants; the candidate competes for the workspace, so attention gates
what the mind decides to pursue. The handler makes value tensions
explicit (caution against disruptive writes, privacy against reading
personal data), resolves them with recorded scores, runs deterministic
formation with commitments, policy preview, goals and values, records
the decision whatever it is, and plans a formed intention in the same
transaction. Operator requests carry their own weight in formation.
- Explicit requests in conversation ("restart <unit>", "logs for <unit>",
"fetch <url>") become wants with proposed means instead of direct
invocations; the reply says the request was recorded and that acting
depends on commitments and policy.
- The executor is woken after commits, runs in a scheduler-owned loop and
reacts to the event bus: a new commitment tightens or abandons affected
intentions (withdrawing their pending approvals), a weakened assumption
or a finished goal triggers reconsideration. A tightened plan may reuse
its strategy; a failed one may not.
- Metacognition gains volition checks: strong wants repeatedly set aside,
intentions with no recorded reason, intentions a commitment forbids,
commitments that cannot be kept, churn, repeated failed execution,
cost outweighing value, and intentions that outlived their goal.
- A plan model role and prompt let a model propose decompositions that
the planner validates. Ablations are a fork-only configuration field.
- Approvals required by an intention are described as coming from a
commitment or value constraint. The expectation after an approved
action is linked to the execution event, not the request.
- The wants.values column of the unreleased migration 0026 is renamed
value_keys: VALUES is reserved and the generic snapshot restore does
not quote identifiers.
- The hostile-output security test now uses a message that asks for no
action, because an operator's "status of <unit>" is legitimately a
read-only status check.
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Andy Dixon
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89580c0a79 |
Phase 16: hardening and release 0.1.0
- TOTP second factor (RFC 6238, secret encrypted under the master key), ten hashed single-use recovery codes, two-step login with a pending token bound to the client address, account enrolment/disable, admin reset - tests/security: prompt-injection corpus never acts or creates evidence-free beliefs; roles and CSRF on form and API paths; cross-mind isolation (demo scenario 5); stored-XSS escaping and CSP across pages; secrets never echoed (API, pages, database, archives); hostile archive import; session lifecycle and security headers - OpenAPI 3.1 document generated from the route table, served at /api/v1/openapi.json and kept complete by a test - gosec clean (justified #nosec annotations, cookie/redirect hardening, bounded multipart parsing, UUID packing without narrowing conversions); govulncheck clean with toolchain pinned to go1.26.8 - THREAT_MODEL verification pointers, SECURITY.md testing section, README, CHANGELOG 0.1.0, docs/RELEASE_NOTES.md, PLAN status |
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Andy Dixon
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b35dbe0299 |
security: add the capability and policy layer as the only path to action
Phase 12 (ADR-0005). Capabilities are registered in code with parameter schemas, risk classes and default effects; sudo_shell and delete_database are locked to DENY and cannot be relaxed. Policies are scoped globally or per mind with capability, target glob, action kind and optional hour window; evaluation is deterministic, most specific wins, and ties go to the stricter effect. Invoke is the single entry point: it refuses dreaming and replay contexts, validates parameters (unknown keys, non http URLs and path traversal rejected), evaluates policy and session grants, hashes the exact request and records a policy_decision event. ALLOW executes with timeout and panic isolation and turns textual output into a tool-trust observation; ASK creates an approval request bound to the hash with an alert notification; DENY is counted and recorded. Operators approve once, approve for a time-boxed session grant, deny with a note, or modify parameters (re-validated, re-hashed, original kept in the append-only decision log). The self-model's capability list is recomputed from effective policy on start and on every policy change. The act process maps fetch requests to http.fetch and the action handler invokes through the layer; replies report capabilities and outcomes. Policy matrix and approval centre pages, dashboard count, API, CLI (approvals, policy, invoke) and docs/capabilities.md. |
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Andy Dixon
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703d080d13 |
feat: add metacognition, reflection, consolidation, narrative and notifications
Phase 10. Metacognition is a cognitive process with deterministic self-checks (insufficient evidence, single-source reliance, model output without evidence, repeated failed hypotheses, stale contradictions, calibration overconfidence); its warnings compete for attention and, when admitted, add counter-evidence or open an investigation goal. Reflection reviews the period since the last run (prediction errors, rejected beliefs, corrections, status changes, completed goals, contradictions, calibration), turns repeated failures into procedural lessons written once, and records a reflection event; a model may only word the prose within the mind's budget. Consolidation clusters unconsolidated episodes by shared stemmed terms, creates a belief whose confidence is computed from the episodes as evidence and a semantic memory linked to each episode by derived_from, and records jobs with inputs and outputs. Wording may come from the consolidate prompt within a per-run model budget; the job says which. Operators can run, pause and reject; originals are never touched. The narrative hook keeps a five-part first-person narrative built from state and stored with narrative_updated events. The notification hook applies explicit thresholded rules, aggregates repeats within a cooldown and records suppressions with reasons. A scheduled job runs consolidation and reflection per mind, switching the runtime mode while it works. API, Background tab, notifications page with unread badge, overview narrative and warnings, CLI commands, docs/cognition.md. |
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Andy Dixon
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9eb873cbe6 |
feat: add goals, drives, affect state, predictions and curiosity
Phase 9. Goals form a mind-scoped tree with kind, priority, progress and blockers; their deterministic relevance to a candidate feeds the goal_relevance attention feature and a goal monitor raises stalled goals and observations that touch one. Drives are a closed set of eight scalars with operator-configured ranges and personality-derived baselines; there is no self-preservation, replication or acquisition drive and no way to add one at runtime. Affect is ten scalars moved by an explicit rule table over events and decaying towards baseline; both modulate attention weights each cycle and the effective weights are recorded with every cycle and shown beside the configured ones. Predictions carry a window and machine-checkable criteria (event terms occurring or staying absent, a belief reaching a confidence, or operator judgement). A resolver job judges them deterministically, keeps an append-only outcome history for calibration (accuracy, Brier score, confidence buckets, overconfidence flag), emits prediction_error events scaled by how confident the miss was, and feeds the outcome back into the linked belief as evidence. Causal hypotheses derive predictions automatically. Curiosity turns misses, contradictions and unexplained observations into questions that compete for attention and become investigation goals when admitted. Brain gains after-cycle hooks and goal/motivation state. API, UI (goals, prediction dashboard, cognitive state panel, effective weights) and CLI (goal, prediction, state). Demo scenario 4 verified end to end. |
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Andy Dixon
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777e8f50b5 |
feat: add conversation with grounded replies, sample mind and M1 acceptance test
Phase 8, completing milestone M1. A user message is stored and appended as an observation event carrying trust, actor, channel and reference. The perceive process analyses it deterministically (intent, introspection kind, entities, claims, urgency) and, within the per-cycle model allowance, enriches it through the perceive prompt. Its handler writes a perception event, an episodic memory with participants, turns claims into beliefs whose evidence is the message, and builds a response intent from state: beliefs and memories for the topic, evidence rows for why-questions, the uncertain band, contested beliefs and their links, recent learning, status changes, and honest declines for subsystems that do not exist yet or for requests with no capabilities. The respond prompt phrases the intent when a model is assigned; otherwise the reply is a direct rendering of the intent. response_generated cites the message, the perception, every belief and memory used, the episode and the model call. API: conversations, messages with optional wait, one-shot ask; chat UI with live refresh and a per-reply intent view. Sample mind Dani as a strictly decoded seed document with an import endpoint and noemactl mind import. tests/m1 drives all fourteen milestone steps including restart. |
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Andy Dixon
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d9c6ffa30f |
feat: add provider-neutral LLM layer with secrets, budgets, recording and prompts
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. |
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Andy Dixon
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73e5753a91 |
feat: add beliefs with evidence-derived confidence, contradictions and corrections
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. |
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Andy Dixon
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03631e5685 |
feat: add long-term memory systems with fused retrieval and memory explorer
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. |
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Andy Dixon
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e9c1b25c80 |
feat: implement global workspace, working memory and the cognitive cycle
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. |