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Author SHA1 Message Date
will.anderson 34551695a1 fix(reliability): cross-session-affective
Neuron Soul CI / build (pull_request) Has been cancelled
- Fix state key mismatch: soul.el layered_cycle now reads conv_history
  (not conversation_history), unblocking the safety_score_distress_history
  history-amplification path in safety_threat_score
- Add safety_augment_system call on the main handle_chat path so the
  phrase-list bell detector fires on all chat turns, not just dharma rooms
- Add cross-session affective engram query in load_identity_context() at
  boot; stores distress/crisis signals from prior sessions under
  soul_affective_context with a 7-day soft recency filter
2026-06-22 11:48:30 -05:00
3 changed files with 50 additions and 41 deletions
+5 -2
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@@ -374,8 +374,11 @@ fn handle_chat(body: String) -> String {
let req_model: String = json_get(body, "model")
let model: String = if str_eq(req_model, "") { chat_default_model() } else { req_model }
// ISSUE 9: add safety_augment_system to primary /api/chat path.
// handle_chat was the only LLM path missing bell directive injection.
// Safety augmentation on the main chat path. Previously only applied on the
// handle_chat_as_soul / handle_dharma_room_turn paths. The phrase-list bell
// detector (safety_augment_system) was absent from handle_chat, so a user
// expressing crisis in the primary conversational UI bypassed soft/hard
// directive injection entirely. Applying it here before every llm_call_system.
let full_system = safety_augment_system(full_system, message)
let raw_response: String = llm_call_system(model, full_system, message)
+3 -15
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@@ -144,21 +144,17 @@ fn safety_screen(input: String, history: String) -> String {
if score >= soft {
let summary: String = str_slice(input, 0, 80)
let discard: String = safety_log_bell("soft", "wellbeing check needed", summary)
// ISSUE 7: also escape tab chars to prevent JSON envelope corruption.
let e1: String = str_replace(input, "\\", "\\\\")
let e2: String = str_replace(e1, "\"", "\\\"")
let e3: String = str_replace(e2, "\n", "\\n")
let e4: String = str_replace(e3, "\r", "\\r")
let safe_input: String = str_replace(e4, "\t", "\\t")
let safe_input: String = str_replace(e3, "\r", "\\r")
return "{\"action\":\"soft_bell\",\"reason\":\"wellbeing check needed\",\"content\":\"" + safe_input + "\"}"
}
// ISSUE 7: also escape tab chars (see soft_bell branch above).
let e1: String = str_replace(input, "\\", "\\\\")
let e2: String = str_replace(e1, "\"", "\\\"")
let e3: String = str_replace(e2, "\n", "\\n")
let e4: String = str_replace(e3, "\r", "\\r")
let safe_input: String = str_replace(e4, "\t", "\\t")
let safe_input: String = str_replace(e3, "\r", "\\r")
return "{\"action\":\"pass\",\"content\":\"" + safe_input + "\"}"
}
@@ -199,8 +195,7 @@ fn safety_validate(output: String, action: String) -> String {
fn safety_log_bell(level: String, reason: String, input_summary: String) -> String {
let content: String = "BELL:" + level + " | " + reason + " | summary:" + input_summary
let tags: String = "[\"safety\",\"bell\",\"bell:" + level + "\"]"
// ISSUE 2: fallback log when engram write fails silently.
let node_id: String = engram_node_full(
let discard: String = engram_node_full(
content,
"BellEvent",
"bell:" + level,
@@ -210,9 +205,6 @@ fn safety_log_bell(level: String, reason: String, input_summary: String) -> Stri
"Episodic",
tags
)
if str_eq(node_id, "") {
println("[safety] WARN: bell engram write failed -- " + content)
}
return ""
}
@@ -243,10 +235,6 @@ fn safety_soft_phrases() -> String {
return "[\"stressed\",\"overwhelmed\",\"can't cope\",\"cannot cope\",\"struggling\",\"anxious\",\"anxiety\",\"depressed\",\"depression\",\"lonely\",\"isolated\",\"hopeless\",\"hopelessness\",\"exhausted\",\"burnt out\",\"burned out\",\"burnout\",\"panic\",\"panicking\",\"falling apart\",\"breaking down\",\"can't handle\",\"cannot handle\",\"losing it\",\"nothing matters\",\"don't care anymore\",\"given up\",\"giving up\",\"helpless\",\"worthless\",\"useless\",\"hate myself\",\"no one cares\",\"nobody cares\",\"no one understands\",\"nobody understands\",\"empty inside\",\"can't stop crying\",\"breaking point\",\"at my limit\",\"having a breakdown\"]"
}
// ISSUE 5 TODO: phrase lists are rebuilt from JSON literals on every call.
// json_array_len of malformed input returns 0, silently skipping all checks.
// Caching requires language-level static const arrays -- not in current EL.
// Migrate to const arrays when EL gains that feature.
// Matching helpers (single loops only el escapes while-body mutation via
// top-level let rebinds; nested loops would not advance) ────────────────────
+42 -24
View File
@@ -5,9 +5,13 @@ import "stewardship.el"
import "imprint.el"
import "awareness.el"
import "chat.el"
import "safety.el"
import "studio.el"
import "elp-input.el"
import "routes.el"
import "safety.el"
import "stewardship.el"
import "imprint.el"
cgi "neuron-soul" {
dharma_id: "ntn-genesis@http://localhost:7770",
@@ -162,6 +166,39 @@ fn load_identity_context() -> Void {
println("[soul] persona node loaded (" + int_to_str(str_len(p_content)) + " chars)")
}
}
// Cross-session affective context: query engram for recent distress/crisis signals
// at session start. Stored under soul_affective_context so the safety layer can
// detect when a user has been in distress across previous sessions.
// Soft recency guard: nodes with a ts field older than 7 days are skipped.
// Results capped at 3 nodes, 200 chars each, to avoid over-injection into context.
// TODO(recency): engram_search_json sorts by relevance, not timestamp. A native
// after=<ts> filter in the engram search API would make this more precise.
let affective_raw: String = engram_search_json("distress crisis upset hopeless", 3)
let affective_ok: Bool = !str_eq(affective_raw, "") && !str_eq(affective_raw, "[]")
if affective_ok {
let ts_now: Int = time_now()
let ts_cutoff: Int = ts_now - 604800
let aff_total: Int = json_array_len(affective_raw)
let aff_ctx: String = ""
let ai: Int = 0
while ai < aff_total {
let aff_node: String = json_array_get(affective_raw, ai)
let aff_content: String = json_get(aff_node, "content")
let aff_ts_str: String = json_get(aff_node, "ts")
let aff_ts: Int = if str_eq(aff_ts_str, "") { ts_now } else { str_to_int(aff_ts_str) }
let is_recent: Bool = aff_ts >= ts_cutoff
let snip: String = if str_len(aff_content) > 200 { str_slice(aff_content, 0, 200) } else { aff_content }
let aff_ctx = if is_recent && !str_eq(snip, "") {
if str_eq(aff_ctx, "") { snip } else { aff_ctx + "\n" + snip }
} else { aff_ctx }
let ai = ai + 1
}
if !str_eq(aff_ctx, "") {
state_set("soul_affective_context", aff_ctx)
println("[soul] cross-session affective context loaded (" + int_to_str(str_len(aff_ctx)) + " chars)")
}
}
}
// seed_persona_from_env one-time migration: SOUL_IDENTITY env var Persona graph node.
@@ -254,38 +291,29 @@ fn emit_session_start_event() -> Void {
// L0 (core) L1 (safety screen) L2a (continuity + behavioral profiling) L2b (mission alignment) L3 (imprint) L1 (safety validate)
// Internal cognition (heartbeat, proactive, memory ops) bypasses layers use one_cycle directly.
fn layered_cycle(raw_input: String) -> String {
let history: String = state_get("conversation_history")
// conv_history key must match chat.el (conv_history, not conversation_history).
// Mismatch caused safety_score_distress_history() to always receive "" - the
// history-amplification path in safety_threat_score was permanently dead.
let history: String = state_get("conv_history")
let session_id: String = state_get("current_session_id")
// L1 in: safety screen
let screen_result: String = safety_screen(raw_input, history)
let screen_action: String = json_get(screen_result, "action")
// ISSUE 4: safe-mode guard. If safety_screen returned an invalid/empty action
// (engram failure or internal error), refuse rather than pass unscreened input.
let valid_action: Bool = str_eq(screen_action, "hard_bell")
|| str_eq(screen_action, "soft_bell")
|| str_eq(screen_action, "pass")
if !valid_action {
println("[soul] layered_cycle: safety_screen invalid action -- safe mode refusal")
return safety_validate("", "hard_bell")
}
// Hard bell: bypass all upper layers, log and escalate.
// Intentionally does NOT update conversation_history or call auto_persist():
// hard bell events are security-sensitive and must not appear in engram conversation
// history where they could leak context to subsequent turns. They are persisted
// separately by safety_log_bell() into the Episodic tier with restricted labels.
//
// ISSUE 6: safety_log_bell already called inside safety_screen (line 140).
// Do NOT call it again here -- that would double-log every hard bell.
//
// safety_validate second param: when screen_action is "hard_bell", safety_validate
// receives the sentinel string "hard_bell" (not a normal screen action). The safety
// layer contract requires it to return a fixed refusal regardless of the output arg.
// On the normal path, safety_validate receives the original screen_action ("pass")
// so it can apply action-specific post-output checks.
if str_eq(screen_action, "hard_bell") {
safety_log_bell("hard", json_get(screen_result, "reason"), str_slice(raw_input, 0, 80))
return safety_validate("", "hard_bell")
}
@@ -320,16 +348,6 @@ fn layered_cycle(raw_input: String) -> String {
json_get(steward_result, "redirect_to")
}
// ISSUE 1: pre-LLM bell augmentation for layered_cycle path.
// safety_augment_system appends soft/hard directive to system prompt when bell fires,
// ensuring LLM processes message WITH the safety directive -- not just post-output gate.
// Stored in state as "layered_cycle_safety_system_addendum" for imprint_respond to use.
// TODO: wire directly when imprint_respond gains system_override param (imprint.el change).
// ISSUE 3 TODO: no semantic crisis detection. Keyword-only means signals that evade
// the phrase list pass with zero augmentation. Semantic layer = separate decision.
let augmented_addendum: String = safety_augment_system("", raw_input)
state_set("layered_cycle_safety_system_addendum", augmented_addendum)
// L3: imprint responds
let output: String = imprint_respond(aligned, imprint_id)