feat(memory): emotional salience tagging and cross-session distress persistence
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- 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.
This commit is contained in:
2026-06-22 11:23:15 -05:00
parent ddd858d2ec
commit b2008f4894
2 changed files with 209 additions and 4 deletions
+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.