Configuration Spector Yml

📄 spector.yml Master Reference

The definitive configuration property reference for Spector. Every section, nested key, data type, default value, and valid range supported by spector-config is cataloged here.

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1. Global & Concurrency

Property	Type	Default	Options / Range	Description
spector.mode	String	MEMORY	MEMORY, SEARCH_ONLY	Primary operating mode. MEMORY activates the unified cognitive kernel; SEARCH_ONLY restricts execution to raw vector retrieval.
spector.concurrency.structured	Boolean	true	true, false	Enables Java Project Loom structured concurrency (StructuredTaskScope) across async worker threads.
spector.events.async	Boolean	false	true, false	Asynchronous event bus dispatching for background memory lifecycle notifications.
spector.embedding.sequential	Boolean	false	true, false	Disables parallel vector batching; forces single-threaded deterministic vector embeddings.

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2. Multi-LLM Embedding Provider

Configuration block for embedding model providers under spector.provider.embedding.*:

Property	Type	Default	Options / Range	Description
type	String	ollama	ollama, openai, google, anthropic, mistral, azure, bedrock, onnx	Active embedding provider adapter.
model	String	nomic-embed-text	Any valid model ID	Identifier of the embedding model (e.g., text-embedding-3-small, text-embedding-004).
base-url	String	http://localhost:11434	Valid HTTP/S URI	Base URL of the provider endpoint (required for Ollama, Azure, LocalAI, vLLM).
api-key	String	""	Secret string	API key for authentication. Can also be injected via environment variable or Docker Secret.
dimensions	Integer	768	1–4096	Vector dimensionality. Must strictly match the output vector length of the specified model.
timeout	Duration	30s	Standard ISO duration	HTTP client socket and connection timeout (e.g., 10s, 1m, 2m).
batch-size	Integer	32	1–512	Max vectors per remote embedding API call.
max-retries	Integer	3	0–10	Exponential backoff retry attempts on HTTP 429 / 5xx responses.
max-concurrent	Integer	0	0–128	Maximum concurrent outbound embedding calls (0 = unbounded virtual thread dispatch).
cache.enabled	Boolean	true	true, false	In-memory LRU cache for computed text embeddings to eliminate redundant LLM calls.
cache.max-size	Integer	1000	100–1,000,000	Maximum cached embedding vectors in memory.
cache.ttl	Duration	60m	Standard ISO duration	Time-to-live for cached embeddings before expiration.
cache.stats-log-interval	Duration	5m	Standard ISO duration	Log interval for embedding cache hit/miss telemetry.
model-path	Path	""	File path	Filesystem path to local ONNX model file (only used when type: onnx).
execution-provider	String	CPU	CPU, CUDA, TENSOR_RT	Execution provider hardware accelerator for local ONNX inference.
vocab-path	Path	""	File path	Path to tokenizer vocabulary file for local ONNX tokenization.

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3. Multi-LLM Generation Provider

Configuration block for generative LLMs under spector.provider.generation.*:

Property	Type	Default	Options / Range	Description
type	String	ollama	ollama, openai, google, anthropic, mistral, azure, bedrock	Active text generation provider.
model	String	llama3.2	Model identifier	Model name used for cognitive reflection, AISME dreaming, and entity synthesis.
base-url	String	http://localhost:11434	Valid HTTP/S URI	Provider endpoint base URL.
api-key	String	""	Secret string	Authentication API token for generation provider.
timeout	Duration	60s	Standard ISO duration	Timeout window for generative completion calls.
fallback-model	String	qwen3:0.6b	Model identifier	Low-latency fallback model invoked when primary generation encounters rate limits or errors.
spector.ssl.insecure	Boolean	false	true, false	Disables TLS certificate validation (development and self-signed proxy use only).

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4. Cognitive Memory Core

Core memory engine parameters located under spector.memory.*:

Property	Type	Default	Options / Range	Description
enabled	Boolean	true	true, false	Master toggle for the cognitive memory subsystem.
persistence-mode	String	DISK	DISK, MEMORY	Persistence backend. DISK uses zero-GC memory-mapped files; MEMORY is ephemeral in-RAM only.
persistence-path	Path	.spector/memory	Path string	Base filesystem directory where Panama FFM off-heap memory bundles and WAL logs are persisted.
dimensions	Integer	384	1–4096	Dimensionality of stored cognitive memory vectors. Must match embedding provider dimensions.
capacity	Integer	100000	100–100,000,000	Global upper capacity limit across all memory partitions.
id-strategy	String	TSID	TSID, UUID_V4, UUID_V7	ID generation algorithm for new memories. TSID (Time-Sorted ID) ensures chronological index locality.
nodes-per-partition	Integer	10000	1,000–100,000	Number of memory records per rolling partitioned chunk file (semantic-xxx.mem).
checkpoint-interval-seconds	Integer	30	5–3600	Off-heap dirty page flush interval to persistent storage.
max-namespaces	Integer	100	1–10,000	Maximum tenant namespaces supported concurrently.
namespace-id	String	default	1–63 chars	Default active namespace identifier for memory isolation.
persist-working-memory	Boolean	false	true, false	If true, flushes volatile working memory ring buffers to disk during graceful shutdown.
pin-source-episodes	Boolean	false	true, false	Prevents source episodic memories from being garbage collected when consolidated into semantic abstractions.
edge-importance	String	DEFAULT	DEFAULT, SALIENCE, DECAY_WEIGHTED	Weighting regime used for cognitive graph edge traversal.

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5. Cognitive Tiers & Capacity Quotas

Capacity quotas for Spector's 4 memory tiers under spector.memory.*:

Property	Type	Default	Range	Description
working-capacity	Integer	100	10–1,000	Size of the volatile circular buffer representing immediate short-term context.
episodic-partition-capacity	Integer	1000	100–50,000	Record capacity per chronological episodic memory partition.
semantic-capacity	Integer	10000	1,000–10,000,000	Capacity of general declarative knowledge and consolidated abstractions.
procedural-capacity	Integer	1000	100–100,000	Storage capacity for agent tools, workflows, executable skills, and rules.
entity-graph-capacity	Integer	50000	1,000–1,000,000	Maximum nodes and relational edges held within the entity knowledge graph.
pinned-quota	Integer	10000	0–1,000,000	Reserved memory slots immune to circadian decay, pruning, and tombstones.
provenance-capacity	Integer	8192	512–65,536	Maximum audit trail entries tracking memory lineage, merges, and generative synthesis.
default-ingestion-tier	String	SEMANTIC	WORKING, EPISODIC, SEMANTIC, PROCEDURAL	Destination tier assigned to incoming text records when not explicitly specified.

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6. Synaptic Dynamics, Habituation & Inhibition

Biomimetic synaptic decay, habituation, and lateral inhibition under spector.memory.*:

Property	Type	Default	Range	Description
decay-enabled	Boolean	true	true, false	Activates Ebbinghaus power-law forgetting curves across memory records.
consolidation-interval	Duration	60s	Standard ISO duration	Cadence of the background Hippocampus sleep consolidation and replay thread.
consolidation.eager-queue-capacity	Integer	256	16–4096	In-memory priority queue limit for memories flagged for urgent immediate consolidation.
surprise-warmup	Integer	10	0–100	Warmup query count before Bayesian surprise detection activates.
flashbulb-threshold	Float	3.0	1.0–10.0	Surprise standard deviations above mean required to create an indelible "flashbulb" memory.
valence-learning-rate	Float	0.3	0.01–1.0	Learning rate ($\alpha$) for updating emotional valence upon human feedback.
deduplication-radius	Float	0.05	0.001–0.5	Maximum cosine distance threshold to treat two memories as duplicate concepts.
inhibition-ttl-ms	Long	300000	$\ge 0$ (ms)	Time-to-live for active lateral inhibition tags (prevents repetitive agent recall loops).
inhibition-floor	Float	0.1	0.0–1.0	Minimum retrieval score floor for suppressed memories.
habituation-decay-rate	Float	0.2	0.01–1.0	Rate at which frequently recalled memories lose novelty boost (anti-filter-bubble).
ltp-cooldown-ms	Long	300000	$\ge 0$ (ms)	Minimum cooldown between Long-Term Potentiation (Auto-LTP) synaptic weight increments.

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7. Hebbian & STDP Synaptic Plasticity

Configurations for associative Hebbian learning and Spike-Timing-Dependent Plasticity:

Property	Type	Default	Range	Description
hebbian.max-degree	Integer	24	4–128	Maximum synaptic co-occurrence connections permitted per memory node.
hebbian.session-boundary-ms	Long	300000	$\ge 0$ (ms)	Time window within which co-occurring memories trigger Hebbian fire-together wire-together bonding.
hebbian.promotion-min-weight	Float	3.0	0.5–20.0	Cumulative edge weight required to promote an episodic connection to permanent semantic status.
hebbian.decay-factor	Float	0.9	0.1–1.0	Synaptic edge weight retention multiplier applied during circadian sleep cycles.
stdp.a-plus	Float	0.1	0.01–1.0	Positive STDP potentiation factor for causal pre-then-post activations.
stdp.a-minus	Float	0.05	0.01–1.0	Negative STDP depression factor for acausal post-then-pre activations.
stdp.tau-plus	Long	30000	$\ge 1$ (ms)	Temporal time constant ($\tau_+$) for causal STDP potentiation window.
stdp.tau-minus	Long	30000	$\ge 1$ (ms)	Temporal time constant ($\tau_-$) for acausal STDP depression window.

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8. 4-Layer Cognitive Graph & Entity Resolution

Parameters governing graph expansion, entity linkage, and semantic bridging:

Property	Type	Default	Range	Description
graph.expansion-mode	String	GATED	GATED, OPEN, DISABLED	Multi-hop associative graph expansion strategy during retrieval.
graph.causal-boost	Float	0.3	0.0–2.0	Retrieval score multiplier for directed causal graph relationships.
graph.hebbian-boost	Float	0.3	0.0–2.0	Retrieval score multiplier for learned associative Hebbian edges.
graph.temporal-forward	Float	0.8	0.0–1.0	Directional weight discount for traversing forwards in time.
graph.temporal-backward	Float	0.7	0.0–1.0	Directional weight discount for traversing backwards in time.
graph.entity-attenuation	Float	0.25	0.0–1.0	Score dampening factor per hop across the entity knowledge graph.
graph.expansion-threshold	Float	0.40	0.0–1.0	Minimum composite edge weight required to traverse a graph connection.
entity.extraction-mode	String	NONE	NONE, HEURISTIC, LLM	Method used to extract named entities from newly remembered text.
entity.resolution-enabled	Boolean	false	true, false	Enables entity deduplication and canonical alias resolution.
entity.shadow-mode	Boolean	true	true, false	Runs entity extraction in shadow mode without modifying active graph state.
entity.max-degree	Integer	16	2–64	Maximum relationship connections allowed per extracted entity node.
entity.max-per-memory	Integer	10	1–50	Maximum entity mentions extracted per memory record.
entity.cosine-threshold	Float	0.85	0.5–1.0	Embedding similarity threshold for merging entity mentions into a single entity.
entity.retention-days	Integer	7	1–365	Time before unreferenced ephemeral entity mentions are pruned from the graph.
entity.decay-factor	Float	0.95	0.5–1.0	Daily retention factor for entity node salience.
entity.prune-threshold	Float	0.5	0.0–1.0	Salience cutoff below which stale entity nodes are removed.
bridge.sample-count	Integer	15	5–100	Number of intermediate bridge nodes sampled for lateral cognitive jumps.
bridge.budget-ms	Long	500	10–5000 (ms)	Time budget allocated for lateral exploratory retrieval.

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9. Active Inference (AISME), Dreaming & Circadian Cycles

Configurations for AISME (Active Inference Self-Model Engine) and dreaming:

Property	Type	Default	Range	Description
circadian.volume-trigger	Integer	100	10–10,000	Number of newly remembered items before a circadian sleep consolidation pass triggers.
circadian.time-trigger	Duration	1h	Standard ISO duration	Periodic sleep consolidation interval when volume threshold is not met.
circadian.tombstone-threshold	Float	0.30	0.01–1.0	Activation score below which decayed episodic memories are tombstoned.
circadian.decay-prune-threshold	Float	0.05	0.001–0.5	Absolute floor score below which tombstoned memories are permanently purged.
circadian.interference-threshold	Float	0.12	0.01–0.5	Cosine distance threshold triggering retroactive proactive interference dampening.
circadian.interference-decay-factor	Float	0.7	0.1–1.0	Retention multiplier applied to conflicting or obsolete prior memories.
reflect.min-cluster-size	Integer	5	2–50	Minimum episodic memory cluster size required to synthesize a semantic belief.
session.buffer-size	Integer	64	8–512	Ring buffer capacity for immediate conversation session turn history.
session.buffer-ttl-ms	Long	5000	$\ge 0$ (ms)	Turn buffer debounce window in milliseconds.
namespace.max-id-length	Integer	63	16–255	Maximum character length allowed for tenant namespace identifiers.
namespace.soft-warning-threshold	Float	0.70	0.1–1.0	Percentage of namespace capacity quota that generates audit warnings.
hyperfocus.ttl-ms	Long	1800000	$\ge 0$ (ms)	Duration (30m) of elevated attention bias towards a specific tag cluster.
icnu.threshold	Float	0.2	0.0–1.0	Minimum ICNU composite score required for auto-promotion to semantic tier.
icnu.steepness	Float	8.0	1.0–20.0	Logistic sigmoid slope for nonlinear importance curve mapping.
icnu.weight-interest	Float	0.30	0.0–1.0	Relative weight ($w_I$) for intrinsic agent interest.
icnu.weight-challenge	Float	0.10	0.0–1.0	Relative weight ($w_C$) for cognitive difficulty / challenge.
icnu.weight-novelty	Float	0.40	0.0–1.0	Relative weight ($w_N$) for semantic novelty / unexpectedness.
icnu.weight-urgency	Float	0.20	0.0–1.0	Relative weight ($w_U$) for execution urgency / time-sensitivity.

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10. Vector Index: HNSW, IVF/PQ & SPECTRUM

Configurations for vector indexing under spector.hnsw.*, spector.ivf.*, and spector.spectrum.*:

Property	Type	Default	Range	Description
hnsw.m	Integer	16	4–64	Maximum bidirectional connections per node per layer in the HNSW graph.
hnsw.ef-construction	Integer	200	16–800	Size of dynamic candidate list during graph index construction.
hnsw.ef-search	Integer	50	10–500	Size of dynamic candidate list during query retrieval.
memory.hnsw-prefilter	String	auto	auto, none, first	HNSW pre-filtering mode when combining vector search with synaptic tag bitmasks.
ivf.nlist	Integer	0	0–65536	Number of Voronoi partitioning centroids for IVF indexing (0 = disabled).
ivf.nprobe	Integer	0	0–1024	Number of IVF centroids inspected per vector query.
ivf.pq-subspaces	Integer	0	0–256	Number of Product Quantization sub-vectors (0 = unquantized).
spectrum.n-centroids	Integer	256	16–4096	Number of coarse quantization centroids for SPECTRUM adaptive indexing.
spectrum.n-probe	Integer	16	1–256	Centroids probed during SPECTRUM retrieval.
spectrum.shard-threshold	Integer	20000	1,000–1,000,000	Vector count threshold triggering dynamic shard split.
spectrum.oversampling-factor	Integer	3	1–10	Multiplier for coarse candidates retrieved before fine-grained distance rescoring.
spectrum.kmeans-iterations	Integer	25	5–100	Max iterations for centroid convergence during K-Means clustering.

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11. SVASQ Quantization & HDC Hypervectors

Configurations for zero-GC SIMD vector compression and hyperdimensional computing:

Property	Type	Default	Range	Description
quantization.svasq.seed	Long	42	Any 64-bit int	Pseudorandom seed for repeatable SVASQ calibration and randomized projection.
quantization.svasq.clip-percentile	Float	0.001	0.00001–0.05	Tail percentile outlier clipping threshold during quantizer calibration.
quantization.svasq.clip-sigmas	Float	3.0	1.5–5.0	Standard deviation cutoff for 8-bit scalar quantization bounding.
quantization.svasq.clip-sigmas-4bit	Float	2.5	1.5–4.0	Standard deviation cutoff for 4-bit scalar quantization bounding.
quantization.svasq.max-sample-size	Integer	10000	1,000–100,000	Maximum vector sample size used to compute calibration quantiles.
quantization.svasq.min-std	Float	1e-6	$> 0$	Minimum standard deviation floor to prevent division by zero on uniform dimensions.
hdc.dimensions	Integer	10000	1,000–100,000	Hyperdimensional computing binary / bipolar vector dimensionality.
hdc.ngram-size	Integer	3	1–8	Character n-gram window size for HDC text encoding and holographic projection.

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12. Query, Hybrid Retrieval & Recall Pipeline

Configurations for multi-stage search, hybrid fusion, and cognitive recall:

Property	Type	Default	Range	Description
query.default-top-k	Integer	10	1–500	Default number of ranked memory candidates returned when unspecified.
query.rrf-k	Integer	60	1–1000	Reciprocal Rank Fusion constant ($k$) for balancing dense and sparse result lists.
query.reranker.max-candidates	Integer	20	5–200	Maximum candidates passed to the neural cross-encoder or ColBERT reranker.
query.hybrid.fanout-multiplier	Integer	2	1–10	Multiplier applied to $K$ when gathering candidates from individual search indexes.
query.hybrid.min-retrieval-k	Integer	50	10–1000	Minimum candidate pool size required before reciprocal rank fusion.
recall.text-search.enabled	Boolean	true	true, false	Enables full hybrid text retrieval alongside pure vector similarity.
recall.text-search.mode	String	HYBRID	HYBRID, KEYWORD_ONLY, VECTOR_ONLY, SPLADE, SPLADE_HYBRID, LI_LSR, COLBERT_RERANK, FULL_STACK	Active retrieval layers executing during recall.
recall.scoring-mode	String	COGNITIVE	COGNITIVE, SIMILARITY, ASSOCIATIVE	Scoring formula applied: COGNITIVE applies the 6-phase scoring equation ($S_{composite}$); SIMILARITY isolates cosine distance.
recall.trace.enabled	Boolean	false	true, false	Emits detailed phase-by-phase scoring math breakdown in REST API responses.
recall.reranker.enabled	Boolean	false	true, false	Enables post-retrieval neural reranking step.
recall.reranker.depth	Integer	50	5–200	Depth of candidates evaluated during neural reranking.
recall.mmr.enabled	Boolean	false	true, false	Enables Maximal Marginal Relevance diversification to prevent redundant results.
recall.mmr.lambda	Float	0.5	0.0–1.0	MMR tradeoff parameter: 1.0 = pure relevance, 0.0 = maximal novelty/diversity.
recall.auto-profile.enabled	Boolean	false	true, false	Dynamically adapts cognitive retrieval weights based on query intent analysis.
recall.include-contradictions	Boolean	false	true, false	Whether to surface memories flagged with opposing belief tags for dialectic reasoning.
recall.lateral.enabled	Boolean	false	true, false	Enables creative multi-hop lateral retrieval through weak associative bridges.
recall.strictness-coefficient	Float	1.0	0.1–5.0	Exponent applied to composite scores to sharpen top-1 margin.
recall.valence-alignment.enabled	Boolean	false	true, false	Biases candidate selection towards memories matching current emotional state.
recall.mode	String	LEARN	LEARN, OBSERVE, REPLAY	LEARN strengthens synaptic pathways upon retrieval; OBSERVE reads passively without modifying memory weights.
recall.max-replay-events	Integer	100000	1,000–10,000,000	Maximum event capacity for retrospective replay evaluation.

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13. Persistence, WAL & Compaction

Storage file paths, Write-Ahead Logging (WAL), and compaction configurations:

Property	Type	Default	Options / Range	Description
persistence.files.index	String	index.spct	File name	File name for the serialized vector index structure.
persistence.files.vectors	String	vectors.mmap	File name	File name for the zero-GC off-heap Panama memory-mapped vector region.
persistence.files.documents	String	documents.dat	File name	File name for raw document texts and JSON payloads.
persistence.files.id-mappings	String	id-mappings.dat	File name	File name for external key to internal offset bidirectional mapping.
persistence.files.shard-dir-name	String	index_shards	Directory name	Subfolder name storing partition shards in distributed cluster mode.
memory.wal.max-chunk-bytes	Long	8388608 (8MB)	1MB–1GB	Maximum size of an active WAL segment file before rotating to a new chunk.
memory.vacuum.threshold	Float	0.20	0.05–0.80	Fragmentation ratio (tombstones / total nodes) that triggers background vacuum compaction.
namespace.tenant-rooted.enabled	Boolean	true	true, false	Enables tenant-rooted namespace sharding layout (tenants/XX/YY/tenantId/namespaces/ZZ/WW/namespaceId) for tenanted accounts (ADR-0033). Untenanted accounts resolve to flat sharded path.
namespace.dual-read.enabled	Boolean	true	true, false	Enables dual-read fallback from tenant-rooted layout to legacy flat layout during migration windows without dual-writing.

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14. Ingestion & Document Chunking

Configurations for batch document ingestion and recursive text chunking:

Property	Type	Default	Range	Description
ingestion.root-directory	Path	.	Directory path	Root folder recursively scanned for ingestible files.
ingestion.file-pattern	String	**/*.md	Glob expression	Comma-separated glob patterns matching target documents (e.g. **/*.md,**/*.txt,**/*.pdf).
ingestion.skip-dirs	String	.git,.idea,.mvn,target,node_modules,.github	Comma-separated strings	Directory names bypassed during file discovery.
ingestion.chunk-size	Integer	2500	100–32,000	Character length per recursive text chunk.
ingestion.chunk-overlap	Integer	200	0–1,000	Overlapping character boundary preserved between adjacent chunks.
ingestion.parallelism	Integer	4	1–64	Number of parallel worker threads processing and embedding documents.
ingestion.max-retries	Integer	3	0–10	Retry attempts for files encountering transient I/O or tokenization errors.
ingestion.retry-delay-ms	Long	2000	$\ge 0$ (ms)	Delay between ingestion retries.
chunking.text.size	Integer	512	64–8192	Standard character count for baseline sentence chunker.
chunking.text.overlap	Integer	64	0–1024	Standard character overlap for baseline chunker.
chunking.token.limit	Integer	128	16–2048	Max token length enforced when chunking for fixed-window embedding models.
chunking.token.overlap	Integer	16	0–256	Token overlap between adjacent token windows.
chunking.document.max-size	Long	104857600 (100MB)	1MB–1GB	Maximum single file size permitted for batch ingestion.

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15. Multimodal Sensory Media

Configurations for image, audio, and video sensory ingestion under spector.multimodal.*:

Property	Type	Default	Range	Description
enabled	Boolean	false	true, false	Master toggle for multimodal processing and sensory asset ingestion.
vision.model	String	moondream	Model identifier	Vision-language model for image captioning and visual semantic feature extraction.
vision.base-url	String	http://localhost:11434	HTTP/S URI	Endpoint URL for the vision model provider.
vision.timeout	Integer	120	10–600 (s)	Request timeout in seconds for visual inference.
vision.max-image-size	Long	20971520 (20MB)	1MB–100MB	Maximum image upload file size.
audio.model	String	gemma4	Model identifier	Audio transcription and acoustic feature model.
audio.timeout	Integer	180	10–600 (s)	Request timeout in seconds for audio processing.
audio.max-file-size	Long	52428800 (50MB)	1MB–500MB	Maximum audio upload file size.
video.keyframe-interval-seconds	Integer	10	1–60 (s)	Video sampling cadence for extracting sensory keyframe images.
video.max-keyframes	Integer	30	1–300	Maximum keyframes extracted from any single video file.
asset-store.type	String	local	local, s3, gcs	Storage engine for raw binary media assets.
asset-store.base-path	Path	.spector/assets	Path string	Base filesystem folder for locally stored media assets.
tika.max-content-length	Long	104857600 (100MB)	1MB–1GB	Content length limit for Apache Tika document text extraction.

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16. Memory Analytics & Stats (ADR-0083)

Namespace-scoped telemetry history and stats cache tuning under spector.memory.*:

Property	Type	Default	Range	Description
analytics.history.enabled	Boolean	true	true, false	Enables the background MemoryAnalyticsScheduler that captures per-namespace census and activity snapshots to the database. When false, the scheduler bean is not created; Prometheus scraping of live Micrometer metrics is unaffected.
analytics.history.interval	Integer	10000	$\ge 1000$ (ms)	Flush interval in milliseconds between analytics snapshot captures. Each tick iterates all cached namespaces and writes one row per namespace.
analytics.instance-id	String	local	Non-empty	Instance identifier written to the instance_id column of snapshot rows. Set to the pod hostname in Kubernetes ($HOSTNAME) for multi-replica disambiguation.
stats.cache-ttl	Duration	5s	Standard Spring duration	TTL for the namespace-scoped getStats() and getScoringStats() cache. Lower values increase engine scan frequency; higher values serve slightly staler data with lower CPU overhead.

# ── Memory Analytics (ADR-0083) ────────────────────────
spector:
  memory:
    analytics:
      history:
        enabled: true          # set false to disable H2 snapshot writes
        interval: 10000        # ms between snapshot flushes
      instance-id: local       # pod identity for composite PK
    stats:
      cache-ttl: 5s            # namespace stats cache TTL

Note

Disabling analytics.history.enabled only stops the database snapshot writes. All Micrometer Observation timers, gauges, and distribution summaries remain active and scrapeable via /actuator/prometheus. The Cortex dashboard falls back to live MeterRegistry data when history is disabled.

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17. Complete Production spector.yml Template

Here is a full, production-ready spector.yml template configured for an enterprise deployment with Ollama, Panama FFM zero-GC persistence, and hybrid cognitive search:

# ═══════════════════════════════════════════════════════════════════
# Spector Enterprise Production Configuration — spector.yml
# ═══════════════════════════════════════════════════════════════════

spector:
  mode: MEMORY

  concurrency:
    structured: true

  events:
    async: true

  # ── Multi-LLM Providers ──
  provider:
    embedding:
      type: ollama
      model: nomic-embed-text
      base-url: http://localhost:11434
      dimensions: 768
      batch-size: 64
      timeout: 30s
      max-retries: 3
      cache:
        enabled: true
        max-size: 10000
        ttl: 120m
    generation:
      type: ollama
      model: llama3.2
      base-url: http://localhost:11434
      timeout: 60s
      fallback-model: qwen3:0.6b

  # ── Cognitive Memory Engine ──
  memory:
    enabled: true
    persistence-mode: DISK
    persistence-path: /data/memory
    dimensions: 768
    capacity: 500000
    id-strategy: TSID
    nodes-per-partition: 10000
    checkpoint-interval-seconds: 30

    # Capacities
    working-capacity: 200
    episodic-partition-capacity: 5000
    semantic-capacity: 100000
    procedural-capacity: 5000
    entity-graph-capacity: 100000
    pinned-quota: 25000

    # Synaptic Dynamics & Plasticity
    decay-enabled: true
    consolidation-interval: 60s
    default-ingestion-tier: SEMANTIC
    surprise-warmup: 10
    flashbulb-threshold: 3.0
    valence-learning-rate: 0.3
    deduplication-radius: 0.05
    inhibition-ttl-ms: 300000
    habituation-decay-rate: 0.2

    # Hebbian Plasticity
    hebbian:
      max-degree: 32
      session-boundary-ms: 300000
      promotion-min-weight: 3.0
      decay-factor: 0.90

    # 4-Layer Cognitive Graph
    graph:
      expansion-mode: GATED
      causal-boost: 0.35
      hebbian-boost: 0.30
      expansion-threshold: 0.40

    # Circadian Sleep Cycle
    circadian:
      volume-trigger: 150
      time-trigger: 1h
      tombstone-threshold: 0.30
      decay-prune-threshold: 0.05
      interference-threshold: 0.12

    # ICNU Saliency Tuning
    icnu:
      threshold: 0.25
      steepness: 8.0
      weight-interest: 0.30
      weight-challenge: 0.10
      weight-novelty: 0.40
      weight-urgency: 0.20

  # ── HNSW Vector Index ──
  hnsw:
    m: 24
    ef-construction: 300
    ef-search: 80

  # ── Multi-Stage Recall ──
  recall:
    text-search:
      enabled: true
      mode: HYBRID
    scoring-mode: COGNITIVE
    trace:
      enabled: false
    mmr:
      enabled: true
      lambda: 0.65
    mode: LEARN

  # ── Batch Ingestion ──
  ingestion:
    root-directory: /data/docs
    file-pattern: "**/*.md,**/*.txt,**/*.pdf"
    skip-dirs: ".git,node_modules,target"
    chunk-size: 2000
    chunk-overlap: 200
    parallelism: 8