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Author SHA1 Message Date
will.anderson 0c5b966773 fix(chat): fix auto_persist timestamp extraction and bell label uniqueness
Neuron Soul CI / build (pull_request) Has been cancelled
- engram_compile: BellEvent nodes do not carry created_at in the engram
  node JSON; extract the unix timestamp from the embedded ' | ts:NNNNN'
  pattern in the content string instead. Fall back to created_at/updated_at
  if the marker is absent. Guard str_to_int against empty string so the 72h
  recency check never silently treats every node as epoch-0 stale.

- auto_persist: append the current unix timestamp to the BellEvent label
  ('bell:soft:1749876543') to make it unique per turn. The previous label
  ('bell:soft') was the same for every soft bell, causing engram to treat
  all subsequent writes as updates to the same node.
2026-06-22 12:09:00 -05:00
will.anderson b2008f4894 feat(memory): emotional salience tagging and cross-session distress persistence
Neuron Soul CI / build (pull_request) Successful in 5m36s
- auto_persist: detect bell level (soft/hard) on every user message using
  safety_detect_bell_level; write a dedicated BellEvent engram node with
  calibrated salience alongside the Conversation node when a bell fires.
  Tag the Conversation node with bell:soft/bell:hard and 'affective' for
  direct discovery without scanning all chat nodes.

- auto_persist: track per-session bell count, dominant level, and last
  signal in state (session_bell_count/level/signal keys) so downstream
  functions can act on the emotional history without re-scanning engram.

- engram_compile: include the top-1 most recent BellEvent node within 72h
  in every context build. Distress context from earlier turns (same or
  recent session) automatically travels into all subsequent LLM calls.

- hist_trim_with_bell_guard: replace hist_trim at the handle_chat call site.
  Before evicting the oldest turn from the 20-turn window, inspect the user
  message for bell signals. If a bell was present, write a preservation
  BellEvent to engram before dropping the turn so the full message survives
  the rolling window.

- session_hist_save: after writing the history node, check session bell
  counters. On the first save where bell_count > 0, write a
  session:emotional-summary BellEvent node with distress signal, count,
  and dominant level. A state flag prevents duplicate writes on subsequent
  saves in the same session.
2026-06-22 11:23:15 -05:00
6 changed files with 245 additions and 121 deletions
+3 -33
View File
@@ -40,32 +40,7 @@ fn ise_post(content: String) -> Void {
let safe3: String = str_replace(safe2, "\n", "\\n")
let safe4: String = str_replace(safe3, "\r", "\\r")
let body: String = "{\"content\":\"" + safe4 + "\"}"
// Soft circuit-breaker: skip HTTP call when engram is known-down (30s backoff).
// Opens after 3 consecutive failures; half-open probe after backoff expires.
// TODO(reliability): full async dispatch requires EL runtime futures support.
let cb_open: String = state_get("engram_cb_open")
if str_eq(cb_open, "1") {
let cb_ts_s: String = state_get("engram_cb_open_ts")
let cb_ts: Int = if str_eq(cb_ts_s, "") { 0 } else { str_to_int(cb_ts_s) }
let cb_elapsed: Int = time_now() - cb_ts
if cb_elapsed < 30000 { return "" }
state_set("engram_cb_open", "0")
}
let resp: String = http_post_json(engram_url + "/api/neuron/state-events", body)
let cb_failed: Bool = str_eq(resp, "") || str_starts_with(resp, "{"error":")
if cb_failed {
let fn_s: String = state_get("engram_cb_fails")
let fn_n: Int = if str_eq(fn_s, "") { 0 } else { str_to_int(fn_s) }
let fn_n = fn_n + 1
state_set("engram_cb_fails", int_to_str(fn_n))
if fn_n >= 3 {
state_set("engram_cb_open", "1")
state_set("engram_cb_open_ts", int_to_str(time_now()))
println("[awareness] engram circuit-breaker OPEN after " + int_to_str(fn_n) + " failures")
}
} else {
state_set("engram_cb_fails", "0")
}
let discard: String = http_post_json(engram_url + "/api/neuron/state-events", body)
return ""
}
@@ -565,14 +540,9 @@ fn awareness_run() -> Void {
let should_refresh: Bool = refresh_elapsed >= refresh_ms
if should_refresh {
let engram_url: String = state_get("soul_engram_url")
let sc: String = state_get("engram_cb_open")
let sc_ts_s: String = state_get("engram_cb_open_ts")
let sc_ts: Int = if str_eq(sc_ts_s, "") { 0 } else { str_to_int(sc_ts_s) }
let sc_elapsed: Int = now_ts - sc_ts
let sync_allowed: Bool = !str_eq(sc, "1") || sc_elapsed >= 30000
if !str_eq(engram_url, "") && sync_allowed {
if !str_eq(engram_url, "") {
let sync_json: String = http_get(engram_url + "/api/sync")
if !str_eq(sync_json, "") && !str_eq(sync_json, "{}") && !str_starts_with(sync_json, "{\"error\":") {
if !str_eq(sync_json, "") && !str_eq(sync_json, "{}") {
let cgi_id: String = state_get("soul_cgi_id")
let tmp: String = "/tmp/soul-sync-" + cgi_id + ".json"
fs_write(tmp, sync_json)
+183 -8
View File
@@ -40,9 +40,43 @@ fn engram_compile(intent: String) -> String {
""
}
// Affective context: always include the most recent high-emotion memory if one
// exists within 72 hours. This ensures continuity of care across turns when
// the user was in distress earlier in the session (or recently), that context
// travels into every subsequent LLM call so the response register stays aware.
// We search for BellEvent nodes specifically; these are written by auto_persist
// when safety_detect_bell_level fires. The 72h window (259200 seconds) is wide
// enough to span a multi-session day without pulling ancient history.
let bell_nodes: String = engram_search_json("bell:soft bell:hard BellEvent", 3)
let bell_ok: Bool = !str_eq(bell_nodes, "") && !str_eq(bell_nodes, "[]")
let now_ts: Int = time_now()
let cutoff_ts: Int = now_ts - 259200
let recent_bell: String = if bell_ok {
let bn0: String = json_array_get(bell_nodes, 0)
// created_at is not present in engram node JSON for BellEvent nodes.
// Extract the timestamp embedded in the content string as " | ts:NNNNN".
// Fall back to created_at / updated_at JSON fields if the marker is absent.
let bn_content: String = json_get(bn0, "content")
let ts_marker: String = " | ts:"
let ts_pos: Int = str_index_of(bn_content, ts_marker)
let bn_ts_raw: String = if ts_pos >= 0 {
let ts_start: Int = ts_pos + str_len(ts_marker)
let rest: String = str_slice(bn_content, ts_start, str_len(bn_content))
let next_sep: Int = str_index_of(rest, " | ")
if next_sep < 0 { rest } else { str_slice(rest, 0, next_sep) }
} else {
let ca: String = json_get(bn0, "created_at")
if str_eq(ca, "") { json_get(bn0, "updated_at") } else { ca }
}
let bn_ts: Int = if str_eq(bn_ts_raw, "") { 0 } else { str_to_int(bn_ts_raw) }
if bn_ts > cutoff_ts { bn0 } else { "" }
} else { "" }
let affective_part: String = if !str_eq(recent_bell, "") { recent_bell } else { "" }
let sep1: String = if !str_eq(act_part, "") && !str_eq(srch_part, "") { "\n" } else { "" }
let sep2: String = if (!str_eq(act_part, "") || !str_eq(srch_part, "")) && !str_eq(scan_part, "") { "\n" } else { "" }
let ctx: String = act_part + sep1 + srch_part + sep2 + scan_part
let sep3: String = if (!str_eq(act_part, "") || !str_eq(srch_part, "") || !str_eq(scan_part, "")) && !str_eq(affective_part, "") { "\n" } else { "" }
let ctx: String = act_part + sep1 + srch_part + sep2 + scan_part + sep3 + affective_part
if str_eq(ctx, "") { return "" }
@@ -108,6 +142,69 @@ fn hist_trim(hist: String) -> String {
return hist
}
// hist_trim_with_bell_guard trim the history window exactly as hist_trim does, but
// before dropping the oldest user/assistant pair check whether the user turn triggered
// a bell event. If it did, write a preservation node to engram so the distress exchange
// survives the 20-turn window. The LLM window drops it; engram retains it permanently
// and engram_compile will surface it again via the affective context path.
fn hist_trim_with_bell_guard(hist: String) -> String {
// Extract the first turn (should be a user message) to inspect it.
let inner: String = str_slice(hist, 1, str_len(hist) - 1)
let marker: String = "{\"role\":"
let i1: Int = str_index_of(inner, marker)
// i1 is the start of the first entry within inner.
// Find where the second entry begins to delimit the first entry's JSON.
let tail1: String = str_slice(inner, i1 + 1, str_len(inner))
let i2: Int = str_index_of(tail1, marker)
// The first entry spans from i1 to (i1 + 1 + i2 - 1) within inner.
let first_entry_raw: String = if i2 > 0 {
str_slice(inner, i1, i1 + 1 + i2 - 1)
} else {
str_slice(inner, i1, str_len(inner))
}
let first_role: String = json_get(first_entry_raw, "role")
let first_content: String = json_get(first_entry_raw, "content")
// Only inspect user turns assistant content doesn't carry bell signals.
let bell_level: String = if str_eq(first_role, "user") {
safety_detect_bell_level(first_content)
} else {
"none"
}
// If the turn being evicted triggered a bell, preserve it to engram.
// This is distinct from the BellEvent written by auto_persist: that node
// carries a short summary. This node carries the full exchange content so
// it is recoverable for clinical/continuity review.
if !str_eq(bell_level, "none") {
let ts: Int = time_now()
let ts_str: String = int_to_str(ts)
let safe_content: String = str_replace(first_content, "\"", "'")
let preserve_content: String = "PRESERVED_BELL:" + bell_level
+ " | evicted_at:" + ts_str
+ " | message:" + safe_content
let preserve_tags: String = "[\"bell-history\",\"bell:" + bell_level + "\",\"evicted\",\"affective\",\"BellEvent\"]"
let discard: String = engram_node_full(
preserve_content,
"BellEvent",
"bell:" + bell_level + ":preserved",
el_from_float(0.9),
el_from_float(0.9),
el_from_float(1.0),
"Episodic",
preserve_tags
)
}
// Now perform the standard trim (drop oldest 2 entries = 1 user + 1 assistant pair).
let tail2: String = str_slice(tail1, i2 + 1, str_len(tail1))
let i3: Int = str_index_of(tail2, marker)
if i3 >= 0 {
return "[" + str_slice(tail2, i3, str_len(tail2)) + "]"
}
return hist
}
// clean_llm_response strips GPT-2 BPE byte-to-unicode artifacts that vLLM
// emits when the tokenizer hasn't decoded back to raw bytes.
//
@@ -186,10 +283,6 @@ 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.
let full_system = safety_augment_system(full_system, message)
let raw_response: String = llm_call_system(model, full_system, message)
let is_error: Bool = str_starts_with(raw_response, "{\"error\"")
@@ -204,8 +297,10 @@ fn handle_chat(body: String) -> String {
let updated_hist: String = hist_append(stored_hist, "user", message)
let updated_hist2: String = hist_append(updated_hist, "assistant", raw_response)
// Use bell-guarded trim: if the evicted turn triggered a bell event, it is
// preserved to engram before being dropped from the in-memory window.
let final_hist: String = if json_array_len(updated_hist2) > 20 {
hist_trim(updated_hist2)
hist_trim_with_bell_guard(updated_hist2)
} else {
updated_hist2
}
@@ -1139,14 +1234,28 @@ fn auto_persist(req: String, resp: String) -> Void {
let safe_msg: String = str_replace(message, "\"", "'")
let safe_reply: String = str_replace(reply2, "\"", "'")
// Detect emotional salience before persisting. safety_detect_bell_level uses the
// same phrase lists as the safety layer (safety.el), so the classification is
// consistent with what safety_screen already evaluated for this turn.
let bell_level: String = safety_detect_bell_level(message)
let is_bell: Bool = !str_eq(bell_level, "none")
// Tag the Conversation node with bell metadata when distress is present so
// subsequent affective queries (e.g. engram_compile) can find this exchange.
let tags: String = if is_bell {
"[\"Conversation\",\"chat\",\"timestamped\",\"bell:" + bell_level + "\",\"affective\"]"
} else {
"[\"Conversation\",\"chat\",\"timestamped\"]"
}
let content: String = "{\"q\":\"" + safe_msg + "\""
+ ",\"a\":\"" + safe_reply + "\""
+ ",\"created_at\":" + ts_str
+ ",\"source\":\"chat\""
+ ",\"bell\":\"" + bell_level + "\""
+ ",\"label\":\"chat:" + ts_str + "\"}"
let tags: String = "[\"Conversation\",\"chat\",\"timestamped\"]"
engram_node_full(
let conv_node_id: String = engram_node_full(
content,
"Conversation",
"chat:" + ts_str,
@@ -1156,6 +1265,72 @@ fn auto_persist(req: String, resp: String) -> Void {
"Episodic",
tags
)
// When a bell fires, write a dedicated BellEvent node in addition to the
// Conversation node. This makes distress moments directly findable by label
// ("bell:soft" / "bell:hard") without having to scan all Conversation nodes.
// The BellEvent carries higher salience so engram_compile pulls it into context.
// The message content is truncated to 120 chars enough signal, not a full dump.
if is_bell {
let summary: String = if str_len(message) > 120 { str_slice(message, 0, 120) } else { message }
let safe_summary: String = str_replace(summary, "\"", "'")
let bell_content: String = "BELL:" + bell_level
+ " | ts:" + ts_str
+ " | summary:" + safe_summary
// bell:hard gets peak salience; bell:soft is slightly lower.
let sal_a: String = if str_eq(bell_level, "hard") { el_from_float(0.98) } else { el_from_float(0.88) }
let sal_b: String = if str_eq(bell_level, "hard") { el_from_float(0.98) } else { el_from_float(0.88) }
let sal_c: String = if str_eq(bell_level, "hard") { el_from_float(1.0) } else { el_from_float(0.95) }
let bell_tags: String = "[\"safety\",\"bell\",\"bell:" + bell_level + "\",\"affective\",\"BellEvent\"]"
let bell_ts_str: String = int_to_str(time_now())
let bell_label: String = "bell:" + bell_level + ":" + bell_ts_str
let bell_node_id: String = engram_node_full(
bell_content,
"BellEvent",
bell_label,
sal_a,
sal_b,
sal_c,
"Episodic",
bell_tags
)
// Increment session-level bell counter so session_hist_save knows whether
// any bell fired during this session when writing a boundary summary.
let sess_id: String = json_get(req, "session_id")
let bell_key: String = if str_eq(sess_id, "") {
"session_bell_count"
} else {
"session_bell_count:" + sess_id
}
let prior_count: String = state_get(bell_key)
let prior_n: Int = if str_eq(prior_count, "") { 0 } else { str_to_int(prior_count) }
state_set(bell_key, int_to_str(prior_n + 1))
// Also record the highest bell level seen this session so the boundary
// summary can classify the session correctly (hard takes precedence).
let level_key: String = if str_eq(sess_id, "") {
"session_bell_level"
} else {
"session_bell_level:" + sess_id
}
let prior_level: String = state_get(level_key)
let new_level: String = if str_eq(bell_level, "hard") { "hard" } else {
if str_eq(prior_level, "hard") { "hard" } else { "soft" }
}
state_set(level_key, new_level)
// Stash a short signal summary for the boundary node (last bell wins for
// the one-liner; the full history is in per-bell BellEvent nodes).
let signal_key: String = if str_eq(sess_id, "") {
"session_bell_signal"
} else {
"session_bell_signal:" + sess_id
}
state_set(signal_key, safe_summary)
}
}
// strengthen_chat_nodes strengthen the engram nodes that were activated during a chat.
+4 -8
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@@ -24,23 +24,19 @@ ENGRAM_DATA_DIR="$ENGRAM_DATA_DIR" \
ENGRAM_PID=$!
# Wait for engram to become healthy (up to 60s; GKE Autopilot cold starts can be slow)
# Wait for engram to become healthy (up to 30s)
echo "[entrypoint] waiting for engram..."
TRIES=0
until curl -sf "$ENGRAM_HEALTH_URL" > /dev/null 2>&1; do
TRIES=$((TRIES + 1))
if [ "$TRIES" -ge 60 ]; then
echo "[entrypoint] ERROR: engram did not become healthy after 60s" >&2
if [ "$TRIES" -ge 30 ]; then
echo "[entrypoint] ERROR: engram did not become healthy after 30s" >&2
kill "$ENGRAM_PID" 2>/dev/null || true
exit 1
fi
sleep 1
done
echo "[entrypoint] engram ready after ${TRIES}s"
# Tune EL HTTP runtime: reduce per-call timeout 60s->10s, connect timeout 3s.
export EL_HTTP_TIMEOUT_MS="${EL_HTTP_TIMEOUT_MS:-10000}"
export EL_HTTP_CONNECT_TIMEOUT_MS="${EL_HTTP_CONNECT_TIMEOUT_MS:-3000}"
echo "[entrypoint] engram ready"
# Start soul — it takes over as PID 1's foreground process.
# SOUL_ENGRAM_PATH must NOT be set; ENGRAM_URL triggers HTTP mode.
+3 -26
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@@ -144,22 +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 fix: escape tab chars in addition to backslash/quote/newline/CR.
// A tab in user input corrupts the JSON envelope and causes json_get to misparse.
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 fix: escape tab chars (see soft_bell branch above for rationale).
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 + "\"}"
}
@@ -200,11 +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 fix: if engram_node_full returns empty the write silently failed.
// Emit a fallback println so the bell event leaves at least a log trace even
// when engram is degraded. This does not replace engram persistence -- it is a
// last-resort audit trail when the primary write cannot be confirmed.
let node_id: String = engram_node_full(
let discard: String = engram_node_full(
content,
"BellEvent",
"bell:" + level,
@@ -214,9 +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 event engram write failed -- fallback log: " + content)
}
return ""
}
@@ -247,17 +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.
// safety_any_match and safety_count_match loop over json_array_get on every invocation.
// A compiled/cached representation would reduce per-message overhead and also guard against
// malformed phrase JSON (json_array_len of malformed input returns 0, silently skipping all checks).
// Caching requires language-level static const arrays -- not available in current EL.
// When EL gains module-level const arrays, migrate phrase lists to that form.
//
// ISSUE 5 TODO: phrase lists are rebuilt from JSON literals on every call to
// safety_any_match / safety_count_match. json_array_len of a malformed string
// returns 0, silently skipping all checks. Caching requires language-level static
// const arrays (not available in current EL). Migrate 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
View File
@@ -368,6 +368,48 @@ fn session_hist_save(session_id: String, hist: String) -> Void {
el_from_float(0.6), el_from_float(0.6), el_from_float(0.9),
"Episodic", tags
)
// Session boundary emotional summary written once per session the first time
// a bell event has fired. The summary node is findable by future sessions via
// broad affective queries ("session:emotional-summary" or "bell distress session").
// It is NOT rewritten on every save the state flag prevents duplicate nodes.
let summary_written_key: String = "session_bell_summary_written:" + session_id
let already_written: String = state_get(summary_written_key)
if str_eq(already_written, "") {
let bell_count_key: String = "session_bell_count:" + session_id
let bell_count_raw: String = state_get(bell_count_key)
let bell_count: Int = if str_eq(bell_count_raw, "") { 0 } else { str_to_int(bell_count_raw) }
if bell_count > 0 {
let bell_level_key: String = "session_bell_level:" + session_id
let bell_signal_key: String = "session_bell_signal:" + session_id
let dominant_level: String = state_get(bell_level_key)
let last_signal: String = state_get(bell_signal_key)
let eff_level: String = if str_eq(dominant_level, "") { "soft" } else { dominant_level }
let eff_signal: String = if str_eq(last_signal, "") { "(no signal captured)" } else { last_signal }
let ts_now: Int = time_now()
let summary_content: String = "session:emotional-summary"
+ " | session:" + session_id
+ " | bell_count:" + int_to_str(bell_count)
+ " | dominant_level:" + eff_level
+ " | last_signal:" + eff_signal
+ " | ts:" + int_to_str(ts_now)
let summary_tags: String = "[\"session-emotional-summary\",\"affective\",\"bell:" + eff_level + "\",\"BellEvent\"]"
let summary_sal: String = if str_eq(eff_level, "hard") { el_from_float(0.95) } else { el_from_float(0.85) }
let sum_discard: String = engram_node_full(
summary_content,
"BellEvent",
"session:emotional-summary",
summary_sal,
summary_sal,
el_from_float(1.0),
"Episodic",
summary_tags
)
// Mark written so we do not create duplicate summary nodes as the
// session continues accumulating more turns.
state_set(summary_written_key, "1")
}
}
}
// session_update_meta_timestamp update the updated_at field in the session:meta node.
+10 -46
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",
@@ -261,32 +265,19 @@ fn layered_cycle(raw_input: String) -> String {
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 invalid/empty action,
// refuse the turn rather than silently passing unscreened input to upper layers.
// Valid actions: "hard_bell", "soft_bell", "pass". Anything else = corrupt envelope.
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 for hard bells is already called INSIDE safety_screen
// (safety.el line 140). Do NOT call it again here -- double-log avoided.
//
// 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")
}
@@ -321,16 +312,6 @@ fn layered_cycle(raw_input: String) -> String {
json_get(steward_result, "redirect_to")
}
// ISSUE 1: apply pre-LLM bell augmentation on layered_cycle path.
// safety_augment_system injects soft/hard directive into system prompt before LLM call.
// Stored in state so imprint_respond can consume it.
// TODO: wire directly into imprint_respond when it accepts a system_override param.
// ISSUE 3 TODO: no semantic/embedding crisis detection. Keyword-only means signals
// evading the phrase list pass through with zero augmentation. Semantic layer is a
// separate architectural decision requiring embedding inference on every message.
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)
@@ -370,29 +351,12 @@ let snapshot_usable: Bool = local_node_count > 50
if using_http_engram && !snapshot_usable {
// First boot or empty/corrupt snapshot: seed from HTTP Engram.
// Retry up to 3 times (2s sleep between attempts) to guard against a
// transient network hiccup right after entrypoint.sh health check passes.
// An empty nodes response silently loads a zero-node graph; validate first.
// TODO(reliability): replace sleep_ms retry with non-blocking backoff.
println("[soul] engram -> HTTP " + engram_url_raw + " (no local snapshot, first boot)")
let fetch_attempt: Int = 0
while fetch_attempt < 3 {
let fetch_attempt = fetch_attempt + 1
let n: String = http_get(engram_url_raw + "/api/nodes?limit=10000")
let e: String = http_get(engram_url_raw + "/api/edges")
let nodes_ok: Bool = !str_eq(n, "") && str_starts_with(n, "[") && str_len(n) > 2
if nodes_ok {
state_set("_boot_nodes_json", n)
state_set("_boot_edges_json", e)
let fetch_attempt = 3
} else {
println("[soul] boot HTTP fetch attempt " + int_to_str(fetch_attempt) + " failed --- retrying in 2s")
sleep_ms(2000)
}
}
let nodes_json: String = state_get("_boot_nodes_json")
let edges_json: String = state_get("_boot_edges_json")
let snapshot_data: String = "{\"nodes\":" + nodes_part + ",\"edges\":" + edges_part + "}"
let nodes_json: String = http_get(engram_url_raw + "/api/nodes?limit=10000")
let edges_json: String = http_get(engram_url_raw + "/api/edges")
let nodes_part: String = if str_eq(nodes_json, "") { "[]" } else { nodes_json }
let edges_part: String = if str_eq(edges_json, "") { "[]" } else { edges_json }
let snapshot_data: String = "{\"nodes\":" + nodes_part + ",\"edges\":" + edges_part + "}"
let tmp_path: String = "/tmp/soul-engram-" + soul_cgi_id + ".json"
fs_write(tmp_path, snapshot_data)
engram_load(tmp_path)