Configuration

Runtime behavior lives in <PERSOME_ROOT>/config.toml (~/.persome/config.toml by default). Provider secrets live beside it in env, never in TOML. A default file is created on first initialization.

persome config   # print the path and current file
persome doctor   # offline prerequisites; no LLM call
persome llm status --check  # live completion and tool-call check

The daemon loads configuration once. Restart it after editing.

Providers and stage models

One profile powers the semantic stages. Persome supports native Anthropic Messages and OpenAI-compatible Chat Completions. Use the guided path instead of editing secrets by hand:

persome llm providers       # provider names and locally detected keys
persome llm setup           # choose provider, enter key, probe, then save
persome llm status --check  # inspect the effective route and retest it

setup checks the current profile first, auto-selects when exactly one known credential is found, prompts when several are available, and accepts keyless local providers. For a normal hosted provider, the only inputs are the provider and its API key; Persome owns the endpoint and default model. It then makes a small completion call and a forced tool call before saving. A failed connectivity/authentication probe writes nothing. A model that completes but cannot call tools requires an explicit degraded-mode confirmation.

Azure deployments and custom-openai / custom-anthropic are explicitly advanced because their endpoint and model or deployment name are user-specific. Automation can also override a preset with --base-url and --model, or import a key from an existing variable with --api-key-env. Imported keys are still stored under Persome’s provider-neutral PERSOME_LLM_API_KEY name. Run persome llm providers --details to inspect routing defaults; they are not part of regular onboarding.

The resulting non-secret configuration has this shape:

[models.default]
provider = "openrouter"
protocol = "openai"
model = "anthropic/claude-sonnet-4"
base_url = "https://openrouter.ai/api/v1"
api_key_env = "PERSOME_LLM_API_KEY"
# max_tokens = 4096

[models.timeline]
# inherits every unset field from models.default

[models.reducer]

[models.memory_delta]

[models.schema_miner]

The active provider key is stored in <PERSOME_ROOT>/env under one stable, provider-neutral name:

PERSOME_LLM_API_KEY=...

# Optional dense retrieval:
OPENAI_API_KEY=...
# OPENAI_BASE_URL=https://example.test/v1

The daemon and initialized CLI commands, including persome model build, load this file before resolving provider credentials. An explicitly exported shell variable takes precedence for that one command; the durable env file is not rewritten by such an override. The owner-local PERSOME_LOCAL_API_TOKEN is the one exception: persome start persists a valid exported value as the canonical bearer so the daemon and later CLI processes cannot end up with different credentials.

Common model stages are timeline, reducer, classifier, memory_delta, pattern_detector, case_extractor, compact, schema_miner, cross_domain_sweeper, root_synthesis, contradiction_check, and memory_decay. Tool-loop stages require function/tool calling; JSON stages require reliable structured output. Without a hosted credential or keyless local endpoint, Persome still captures and serves BM25, but semantic model stages remain degraded.

Hosted presets currently include Anthropic, OpenAI, DeepSeek, OpenRouter, Gemini, Groq, Mistral, xAI, Qwen, Moonshot/Kimi, Zhipu GLM, SiliconFlow, Together, Fireworks, Cerebras, and Azure OpenAI. Keyless local presets cover Ollama, LM Studio, and vLLM. Presets describe endpoint defaults, not a blanket capability guarantee for every model. Use custom-openai or custom-anthropic for another compatible gateway.

During onboarding, Persome can discover common provider-specific variables such as keys exported by provider CLIs or existing shell profiles. They are import sources only; the saved Runtime profile always references PERSOME_LLM_API_KEY.

For migration, existing provider-specific api_key_env values and the former pre-provider route remain readable as compatibility fallbacks. Running persome llm setup tests the current route, copies the selected key to PERSOME_LLM_API_KEY, and writes an explicit provider profile.

Capture

[capture]
source = "daemon"                 # daemon | ingest
event_driven = true
heartbeat_minutes = 10
debounce_seconds = 3.0
min_capture_gap_seconds = 2.0
dedup_interval_seconds = 1.0
same_window_dedup_seconds = 5.0

buffer_retention_hours = 168
screenshot_retention_hours = 24
screenshot_thumbnail_hours = 0
buffer_max_mb = 2000

include_screenshot = true
screenshot_max_width = 1920
screenshot_jpeg_quality = 80
ax_depth = 100
ax_timeout_seconds = 3

enable_ocr_fallback = true
ocr_policy = "enabled"               # auto | enabled | disabled
ocr_tier = "tiny"                 # tiny | small | medium
ocr_min_gap_seconds = 15.0
ocr_structured = true
cmux_source_enabled = true

• source is validated and must be "daemon" or "ingest". source="daemon" owns macOS AX capture. source="ingest" accepts records from the trusted bearer-authenticated /captures/ingest producer and starts no OS watcher. The producer must obtain PERSOME_LOCAL_API_TOKEN through an owner-approved local secret channel and must never put it in a URL.
• Accessibility is required for the source-versioned mac-ax-helper and, when event_driven=true, mac-ax-watcher in daemon mode. A terminal or Python daemon grant does not replace either native principal. install.sh runs persome onboard in interactive sessions: it asks for each Accessibility principal and, when screenshots or effective OCR need pixels, Screen Recording separately. It persists the selected OCR policy, starts the final daemon owner, waits for that daemon’s isolated worker, and proves a mode-aware capture receipt.
• source="ingest" requires mcp.auto_start=true and an HTTP transport because /captures/ingest is its only authenticated input channel. Its trusted producer owns the OS permissions; onboarding proves ingest readiness instead of requiring daemon Accessibility.
• ocr_policy is also validated. auto means a fresh or older configuration has not recorded intent; enabled and disabled are durable user choices. Ordinary persome onboard and updates preserve that choice and ocr_tier. persome onboard --tier tiny or persome ocr setup explicitly enables OCR; persome ocr disable records the opt-out. Do not toggle only enable_ocr_fallback when representing user intent.
• Paddle inference runs in a local worker subprocess so a native crash does not kill the daemon. OCR text is backfilled into capture search and consumed by timeline/modeling; pixels are not sent to an LLM stage. The source-level config default is enable_ocr_fallback=false, ocr_policy="auto" for unsupported/direct-library environments; a supported fresh macOS install records the enabled state shown above after explicit onboarding.
• PERSOME_DISABLE_OCR=1 is the deployment kill switch.
• PERSOME_OCR_IN_PROCESS=1 is a debugging escape hatch that gives up crash isolation and should not be used for normal operation.
• Age-based retention only removes captures already absorbed by a closed timeline block. buffer_max_mb remains a hard cap and may evict the oldest unabsorbed frame to prevent unbounded disk growth. Screenshots degrade before AX/OCR text and whole-record deletion.
• cmux_source_enabled reads visible terminal text through cmux’s local, read-only socket because GPU terminal content is AX-poor.

Timeline and sessions

[timeline]
window_minutes = 1
cold_lookback_minutes = 30
max_parallel_windows = 4
attention_locus_enabled = true

[session]
gap_minutes = 5
soft_cut_minutes = 3
max_session_hours = 2
tick_seconds = 30
flush_minutes = 5

[reducer]
enabled = true
daily_tick_hour = 23
daily_tick_minute = 55

[classifier]
interval_minutes = 30

Timeline windows are wall-clock aligned and idempotent. flush_minutes and classifier.interval_minutes have a five-minute effective floor. A successful flush also models its new Point/Line window under default delta apply. Terminal reducer failures use persisted 5/15/30/60/120 minute backoff; a daemon task checks the queue every minute and the daily safety net ignores backoff to catch anything stranded.

Disabling the reducer preserves capture/session rows but prevents event and incremental personal-model writes.

Incremental personal modeling

[memory_delta]
enabled = true
max_blocks = 120
roster_max = 60
owner_aliases = []
min_confidence = 0.5
apply_enabled = true
apply_assertions = true
cooccurrence_knows = true

[pattern_detector]
enabled = true
structured_filter = true
lookback_days = 7
min_occurrences = 2

With the shipped defaults, memory_delta is the Point/Line producer. It persists one gated payload per newly flushed active-session window before deterministic apply and advances sessions.delta_end; terminal finalization only catches the remaining tail. Disabling apply_enabled keeps the audit row but stops it from changing the model and reactivates the classifier’s legacy terminal write role. This switch is for diagnosis/migration, not a second normal operating mode.

The runtime normally learns owner names and handles from evidence already produced by the windowed modeling pass. Explicit first-person identity evidence can activate an alias immediately; account-ownership evidence requires two independent sessions. Pending aliases enter a seven-day person-creation quarantine; active owner aliases remain excluded from the person roster. This prevents an uncertain first observation from becoming a self-reinforcing collaborator Point without suppressing an ordinary person forever.

owner_aliases is an optional trusted override for deployments that already know the owner’s identities. It is not required for ordinary onboarding or Day-1 modeling. Configured and learned aliases both resolve to reserved self.

The pattern detector requires repeated evidence and writes observed behavioral memory under memory/skills/skill-*.md. It does not propose or execute automation.

Additional top-level enrichment flags:

person_graph_enabled = true
case_extraction_enabled = true
relation_extraction_enabled = false
edge_promote_fanout = 20

Person-graph ingest is deterministic. Case extraction distills reusable problem/solution evidence. Experimental relation extraction remains off; the memory-delta relation path is already active.

Higher geometry

[schema]
enabled = true
refresh_minutes = 30
daily_tick_hour = 0
daily_tick_minute = 15
cross_domain_enabled = true
cross_domain_behavior_max_distance = 0.5
cross_domain_min_confidence = 0.6
cross_domain_max_probes = 8
root_synthesis_enabled = true
root_token_budget = 1500

After new Point/Line evidence, the Runtime calls the same ModelBuildCoordinator as persome model build at the bounded refresh_minutes cadence. The 00:15 tick remains an unconditional daily pass. Both run pending state formation, enrichment, Face mining, Volume synthesis, Root synthesis, vectors, and layout. Forming schemas are excluded from active snapshots. Each build makes at most cross_domain_max_probes cross-domain LLM calls. A shadow Volume is retried first only while its latest persisted result remains stable/promotable, so the two-observation evidence gate can make progress. A negative, failed, or forming retry demotes that pair behind every never-probed pair; older retries then rotate oldest-first. Thus stale shadows cannot monopolize the budget, and every finite unseen queue is reached in later builds. Any remainder is reported as deferred for a later build. Collisions below cross_domain_min_confidence remain dormant forming Markdown and cannot enter the Face/Volume promotion table. Missing repeated evidence yields a truthful degraded build.

Writer and maintenance

[writer]
soft_limit_tokens = 20000
max_tool_iterations = 12
context_token_limit = 80000
llm_retry_attempts = 6
llm_rate_limit_wait_s = 30
llm_fallback_model = ""
tool_result_max_bytes = 16384
tool_result_total_budget = 131072
max_output_tokens_recovery_limit = 65536
max_output_tokens_recovery_count = 3
use_token_count_api = false
contradiction_strategy = "abstract"
consolidation_cadence = 8

[memory_decay]
enabled = false
after_days = 90
max_clusters_per_night = 3
cluster_min = 4
cluster_max = 12
shrink_ceiling = 0.5
line_max_chars = 80

[orphan_reaper]
enabled = false
ttl_days = 30
max_per_night = 200
engaged_keep = 2

consolidation_cadence runs pending per-file compaction. Memory decay and orphan reaping are lossy maintenance and therefore remain explicit opt-ins.

Storage authority and integrity

[evomem]
snapshot_enabled = true
snapshot_keep_daily = 7
snapshot_keep_weekly = 4
integrity_check_enabled = true
freeze_writes_on_failure = false
shadow_write_enabled = true
write_authority = "markdown"       # markdown | evomem
contradiction_check_enabled = false
contradiction_max_pairs = 10

markdown is the default authority and shadows current state to evomem. evomem makes the graph authoritative and projects Markdown/FTS from it. An operator flips this manually. Integrity recovery may temporarily write unknown when a damaged/missing config leaves both Markdown and evomem as plausible sources; writes and model builds remain frozen until the operator chooses markdown or evomem. That explicit choice is reconciled into the retrieval index before the guard journal is removed, and choosing evomem also reprojects its canonical state to Markdown. Before a normal rollback, project current evomem state to Markdown, then rebuild the index.

Snapshots are verified before atomic promotion. Integrity failures are emitted as structured error logs. The old runtime SSE event bus no longer exists. freeze_writes_on_failure is intentionally off because a false positive under Markdown authority should not halt observation.

Retrieval

[search]
default_top_k = 5
hybrid_enabled = true
hybrid_recall_n = 50
hybrid_rrf_k = 20
slot_pool_weight = 0.3
relation_pool_weight = 1.0
associative_read_enabled = true
relation_include_shadow = true
contains_pool_rerank = true
tags_matchable = false
recency_half_life_days = 14.0
recency_decay_floor = 0.2
embed_model = "text-embedding-3-large"
embed_batch_size = 64
embed_tick_max = 512

Hybrid retrieval automatically degrades to BM25 when no embeddings endpoint is configured. Query-time consumers use one associative entrance; absent entity, scene, time, or relation slots simply contribute no votes.

MCP

[mcp]
auto_start = true
transport = "streamable-http"
host = "127.0.0.1"
port = 8742
read_receipt_enabled = true
entity_graph_enabled = true

The daemon HTTP transport hosts MCP, REST routes, and /model on the same loopback port. stdio is started explicitly with persome mcp; do not use it as an in-daemon transport. HTTP requires the dedicated PERSOME_LOCAL_API_TOKEN provisioned in <PERSOME_ROOT>/env; automatic client installers prefer stdio so the token is not duplicated.

A stale [chat] table left behind by a release that still shipped the removed Chat feature is silently ignored.

Privacy and API flags

Top-level API/model defaults include:

api_require_local_origin = true

Capture privacy defaults, configured inside the [capture] table, are:

pause_on_lock = true
suppress_secure_input = true
encrypt_screenshots = true
extended_retention_enabled = true
actionable_retention_days = 7

install.sh provisions PERSOME_SCREENSHOT_KEY automatically. When screenshot encryption is enabled but that key is unavailable, the capture remains usable for AX/text modeling but its screenshot is not persisted.

Old top-level capture_* names are read as compatibility fallbacks, but new configuration should use the nested names.

Keep the bearer boundary, local-origin guard, and screenshot encryption enabled. Exposing the plain-HTTP server through a tunnel or copying its bearer to another machine changes the security boundary and is unsupported.