limbic_system

Limbic System package initialization.

Exposes all public interfaces as well as legacy internal functions and constants to ensure complete backward compatibility with downstream modules, reset tools, and tests.

class limbic_system.LimbicSystem(redis_client=None, openrouter_api_key=None, openrouter_client=None, cache_redis_client=None)[source]

Bases: object

Shard-based limbic respiration backed by Redis DB12.

Parameters:: openrouter_api_key (Optional[str])

async inhale(channel_id)[source]

RESPIRATION PHASE 1: INHALE

Fetches local shard + global heart, mixes via osmosis, runs homeostatic regulation, returns the effective state.

Return type:: Dict[str, Any]
Parameters:: channel_id (str)

async exhale(channel_id, stimulus_delta, apply_decay=True, user_message='', star_reply='', user_id='', appraisal_dimensions=None, config=None, platform='')[source]

RESPIRATION PHASE 2: EXHALE

Updates local shard with new delta, applies metabolic decay, and pulses global heart.

Return type:

Dict[str, Any]

Parameters:

channel_id (str)
stimulus_delta (Dict[str, float])
apply_decay (bool)
user_message (str)
star_reply (str)
user_id (str)
appraisal_dimensions (List[str] | None)
config (Any | None)
platform (str)

async scan_triggers(text, query_embedding=None)[source]

Scan text for emotional triggers using semantic matching.

Return type:

List[tuple]

Parameters:

text (str)
query_embedding (list[float] | None)

classmethod classify_dominant_emotions(vector, top_n=3)[source]

Return type:

List[Dict[str, Any]]

Parameters:

vector (Dict[str, float])
top_n (int)

static metabolic_decay(vector, tau=0.92, baseline=None)[source]

Return type:

Dict[str, float]

Parameters:

vector (Dict[str, float])
tau (float)
baseline (Dict[str, float] | None)

static format_context_injection(vector, cues, dominant, cascade_cues=None, rdf_output=None, user_read='', self_reflection=None, high_ticks=None, prev_dominant_names=None, route_flags=None, appraisal_dimensions=None, local_vector=None)[source]

Return type:

Dict[str, Any]

Parameters:

vector (Dict[str, float])
cues (List[str])
dominant (List[Dict[str, Any]])
cascade_cues (List[str] | None)
rdf_output (Dict[str, Any] | None)
user_read (str)
self_reflection (Dict[str, Any] | None)
high_ticks (Dict[str, int] | None)
prev_dominant_names (List[str] | None)
route_flags (List[str] | None)
appraisal_dimensions (List[str] | None)
local_vector (Dict[str, float] | None)

class limbic_system.DecoupledRespirationEngine(limbic_system, heartbeat_interval=300.0)[source]

Bases: object

Runs psychological respiration cycles in the background, out-of-path from message loops.

Parameters:

limbic_system (Any)
heartbeat_interval (float)

async start()[source]

Return type:: None

async stop()[source]

Return type:: None

limbic_system.warm_ncm_caches()[source]

Pre-load all lazily-cached YAML files so first-touch doesn’t block.

Return type:: None