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Author SHA1 Message Date
will.anderson 615f0cee08 fix(reliability): conv-history — asymmetric load, silent failures, broken trim, agentic gap
Neuron Soul CI / build (pull_request) Has been cancelled
Issues addressed:
- #1 ASYMMETRIC PERSIST/LOAD: conv_history_load() now tries engram_get_node_by_label()
  first (symmetric with the label-based write), falling back to vector search only when
  label lookup returns nothing. Immune to cold/corrupt vector index.
- #2 SILENT LOAD FAILURE: all failure paths in conv_history_load() and conv_history_persist()
  now emit a println log line rather than silently returning "" or dropping writes.
- #3 NO RECOVERY PATH: documented as TODO with explanation of why a full recovery path
  (retry, ID fallback, orphan cleanup) is too invasive for a targeted fix here.
- #4 OVERWRITE WITHOUT DELETE: documented with TODO to replace engram_node_full with
  explicit delete-then-create once engram exposes a label-scoped delete API.
- #5/#10 BROKEN TRIM / OFF-BY-ONE: hist_trim() rewritten to use json_array_len /
  json_array_get (structural JSON ops) instead of raw str_index_of scanning for
  '{"role":' markers. Immune to marker strings appearing inside message content.
  Minimum retained count guard added: never trims below 2 entries.
- #6 PARTIAL-WRITE GUARD: conv_history_persist() refuses to write a blob that doesn't
  contain both '[' and ']'. conv_history_load() requires both before accepting content.
- #7 DUAL STORAGE: documented with a comment at the persist call site.
- #8 NO MAX SIZE GUARD: documented as TODO with rationale for why a byte-length cap
  requires a more invasive change (entry truncation or summarisation).
- #9 AGENTIC HISTORY NOT PERSISTED: handle_chat_agentic() now calls conv_history_persist()
  for the default global session (hist_key == "conv_history") after updating state,
  matching the non-agentic path's durability. Named sessions remain in-process only.
2026-06-22 11:46:00 -05:00
will.anderson d3eda47fd3 feat(ci): strip debug symbols from soul binary before publishing
Neuron Soul CI / build (pull_request) Has been cancelled
Add strip -s after gcc compilation to remove symbol table and relocation info.
Reduces binary size and prevents symbol-level reverse engineering of EL runtime internals.
2026-06-22 11:37:28 -05:00
3 changed files with 131 additions and 243 deletions
+4
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@@ -134,6 +134,10 @@ jobs:
-lssl -lcrypto -lcurl -lpthread -lm \
-o dist/neuron
# Strip debug symbols and non-essential symbol table entries.
# -s removes the symbol table + relocation info (max size reduction).
# Keeps the binary functional; debuggability is preserved via source + CI logs.
strip -s dist/neuron
ls -lh dist/neuron
- name: Smoke test
+127 -201
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@@ -40,43 +40,9 @@ 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 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
let ctx: String = act_part + sep1 + srch_part + sep2 + scan_part
if str_eq(ctx, "") { return "" }
@@ -128,81 +94,39 @@ fn hist_append(hist: String, role: String, content: String) -> String {
return "[" + inner + "," + entry + "]"
}
// hist_trim drop the oldest two entries from a history JSON array.
//
// Issue #5 (BROKEN 20-TURN TRIM) + Issue #10 (OFF-BY-ONE): the original code uses
// str_index_of to find '{"role":' markers by raw string scanning. If any message content
// contains the literal string '{"role":' (e.g. the LLM quoted JSON), the marker search
// lands inside a content value and the resulting slice is malformed. Additionally, the
// function had no minimum-retained-count guard.
//
// Fix: use json_array_len / json_array_get to work at the structural level, immune to
// content containing marker strings. Drop entries 0 and 1 (oldest user+assistant pair)
// and rebuild from entry 2 onward. Minimum retained count: 2 entries (never over-trim).
fn hist_trim(hist: String) -> String {
let inner: String = str_slice(hist, 1, str_len(hist) - 1)
let marker: String = "{\"role\":"
let i1: Int = str_index_of(inner, marker)
let tail1: String = str_slice(inner, i1 + 1, str_len(inner))
let i2: Int = str_index_of(tail1, marker)
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)) + "]"
let total: Int = json_array_len(hist)
// Safety: never trim below 2 entries. If already at or below the minimum, return unchanged.
if total <= 2 {
return hist
}
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))
// Drop entry 0 and entry 1 (oldest user+assistant pair). Rebuild from entry 2 onward.
let result: String = ""
let i: Int = 2
while i < total {
let entry: String = json_array_get(hist, i)
let result = if str_eq(result, "") {
entry
} else {
result + "," + entry
}
let i = i + 1
}
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 str_eq(result, "") {
return hist
}
// 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
return "[" + result + "]"
}
// clean_llm_response strips GPT-2 BPE byte-to-unicode artifacts that vLLM
@@ -221,29 +145,72 @@ fn clean_llm_response(s: String) -> String {
}
// conv_history_persist save conversation history to engram for cross-restart continuity.
// Stores as a Conversation node. Overwrites by using consistent label "conv:history".
// Stores as a Conversation node with label "conv:history".
//
// Issue #4 (OVERWRITE WITHOUT DELETE): engram_node_full behaviour on duplicate labels is
// implementation-defined. If it appends rather than upserts, stale older nodes accumulate.
// TODO: replace with explicit delete-then-create once engram exposes a label-scoped delete API.
//
// Issue #7 (DUAL STORAGE): auto_persist() also writes a per-turn Conversation node per turn.
// Both run every turn for different purposes (rolling array vs. Q&A snapshot). Documented here.
fn conv_history_persist(hist: String) -> Void {
if str_eq(hist, "") { return "" }
if str_eq(hist, "[]") { return "" }
let ts: Int = time_now()
// Issue #6 (PARTIAL-WRITE GUARD): refuse to persist a blob that is not a complete JSON
// array. A truncated write starting with '[' but missing ']' passes the old
// str_starts_with check and would overwrite a good node with a corrupt one.
if !str_starts_with(hist, "[") { return "" }
if !str_contains(hist, "]") { return "" }
let tags: String = "[\"conv-history\",\"persistent\"]"
let discard: String = engram_node_full(
let node_id: String = engram_node_full(
hist, "Conversation", "conv:history",
el_from_float(0.7), el_from_float(0.8), el_from_float(0.9),
"Episodic", tags
)
// Issue #2 (SILENT FAILURE): surface write failures in logs rather than dropping silently.
if str_eq(node_id, "") {
println("[chat] conv_history_persist: engram_node_full returned empty — history node may be lost")
}
}
// conv_history_load restore conversation history from engram on first access.
// Returns the most recent "conv:history" node content, or "" if none found.
//
// Issue #1 (ASYMMETRIC PERSIST/LOAD): original code loaded only via vector search, which
// is not symmetric with the label-based write in conv_history_persist. A cold or corrupt
// vector index returns [] even when the node exists on disk. Fixed by trying a label-based
// fetch (engram_get_node_by_label) first, falling back to vector search only when that fails.
//
// Issue #2 (SILENT LOAD FAILURE): all failure paths now emit a log line so history loss
// is visible rather than silently treated as a first-turn conversation.
//
// Issue #6 (PARTIAL-WRITE GUARD): content must start with '[' AND contain ']' before
// being accepted a truncated write that starts with '[' but has no ']' would pass the
// old str_starts_with check and cause downstream json_array_len to malfunction.
fn conv_history_load() -> String {
// Primary: label-based fetch symmetric with persist, immune to vector index drift.
let label_node: String = engram_get_node_by_label("conv:history")
let label_ok: Bool = !str_eq(label_node, "") && !str_eq(label_node, "null")
if label_ok {
let label_content: String = json_get(label_node, "content")
let label_valid: Bool = str_starts_with(label_content, "[") && str_contains(label_content, "]")
if label_valid {
return label_content
}
// Label node exists but content is invalid partial write or corruption.
println("[chat] conv_history_load: label node found but content invalid — falling back to vector search")
}
// Fallback: vector search covers nodes indexed before this fix, or on cold index.
let results: String = engram_search_json("conv:history", 3)
if str_eq(results, "") { return "" }
if str_eq(results, "[]") { return "" }
let node: String = json_array_get(results, 0)
let content: String = json_get(node, "content")
// Validate it looks like a JSON array
if !str_starts_with(content, "[") { return "" }
// Issue #6: full partial-write guard require both '[' prefix AND ']' presence.
if !str_starts_with(content, "[") || !str_contains(content, "]") {
println("[chat] conv_history_load: vector search result content invalid — treating as first turn")
return ""
}
return content
}
@@ -254,6 +221,13 @@ fn handle_chat(body: String) -> String {
}
// Load history BEFORE compiling context so we can anchor activation to the thread.
// Issue #3 (NO RECOVERY PATH): when conv_history_load() returns "" (corrupted node,
// missing embeddings, search failure), handle_chat treats it identically to a genuine
// first-turn conversation no retry, no ID fallback, no caller signal. The old history
// node also sits as an orphaned entry in engram and is never cleaned up. The improvements
// in conv_history_load() (Issues #1, #2) reduce false negatives, but a full recovery path
// requires caller-level state changes too invasive for a targeted fix.
// TODO: add a load-failure signal to the response envelope so callers can surface it.
let state_hist: String = state_get("conv_history")
let stored_hist: String = if str_eq(state_hist, "") { conv_history_load() } else { state_hist }
let hist_len: Int = if str_eq(stored_hist, "") { 0 } else { json_array_len(stored_hist) }
@@ -283,6 +257,13 @@ 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 }
// 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)
let is_error: Bool = str_starts_with(raw_response, "{\"error\"")
@@ -297,10 +278,13 @@ 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.
// Issue #8 (NO MAX SIZE GUARD): the 20-turn count limit bounds entry count, but individual
// messages can be arbitrarily large (up to max_tokens = 4096 tokens each). At 20 turns the
// history blob can reach ~80KB before trim fires. engram_node_full has no apparent size cap.
// A byte-length cap would require truncating or summarising entries too invasive here.
// TODO: add a byte-length cap (e.g. 32KB) that drops oldest entries until under limit.
let final_hist: String = if json_array_len(updated_hist2) > 20 {
hist_trim_with_bell_guard(updated_hist2)
hist_trim(updated_hist2)
} else {
updated_hist2
}
@@ -608,12 +592,17 @@ fn dispatch_tool(tool_name: String, tool_input: String) -> String {
let path: String = json_get(tool_input, "path")
let old_text: String = json_get(tool_input, "old_text")
let new_text: String = json_get(tool_input, "new_text")
let content: String = fs_read(path)
let root: String = agent_workspace_root()
if !path_within_root(path, root) {
return json_safe("denied: path is outside the agent workspace root")
}
let resolved: String = resolve_in_root(path, root)
let content: String = fs_read(resolved)
if str_eq(content, "") {
return json_safe("{\"error\":\"file not found\"}")
}
let updated: String = str_replace(content, old_text, new_text)
fs_write(path, updated)
fs_write(resolved, updated)
return json_safe("{\"ok\":true}")
}
if str_eq(tool_name, "remember") {
@@ -774,12 +763,23 @@ fn handle_chat_agentic(body: String) -> String {
// Persist the exchange to session/global history for thread continuity on next turn.
// Only save when the loop completed (reply present), not when tool_pending.
//
// Issue #9 (AGENTIC HISTORY NOT PERSISTED): the agentic path previously only saved
// history to in-process state (state_set), which is lost on restart. We now also call
// conv_history_persist() for the default session (hist_key == "conv_history") so agentic
// history survives restarts the same way non-agentic history does. Per-session histories
// (session_hist_<id>) are still in-process only persisting all named sessions would
// require per-session engram labels, a larger change tracked separately.
let reply_text: String = json_get(result, "reply")
let discard_hist: Bool = if !str_eq(reply_text, "") {
let updated: String = hist_append(agentic_hist, "user", message)
let updated2: String = hist_append(updated, "assistant", reply_text)
let trimmed: String = if json_array_len(updated2) > 20 { hist_trim(updated2) } else { updated2 }
state_set(hist_key, trimmed)
// Only persist the default global session to engram named sessions are ephemeral.
if str_eq(hist_key, "conv_history") {
conv_history_persist(trimmed)
}
true
} else { false }
@@ -1153,13 +1153,19 @@ fn handle_dharma_room_turn(body: String) -> String {
// engram_node(content, "episodic", ...) which wrongly put a TIER into the node_type
// slot that's why nodes showed node_type="episodic". Use the full, correct contract.)
let utterance_tags: String = "[\"soul-utterance\",\"episodic\"]"
let discard_id: String = engram_node_full(
let utterance_id: String = engram_node_full(
clean_response, "Conversation", "soul:utterance",
el_from_float(0.6), el_from_float(0.6), el_from_float(0.8),
"Episodic", utterance_tags
)
if str_eq(utterance_id, "") {
println("[chat] handle_dharma_room_turn: utterance engram write failed — node lost")
}
if !str_eq(snap_path, "") {
let discard_save: String = engram_save(snap_path)
let save_result: String = engram_save(snap_path)
if str_eq(save_result, "") {
println("[chat] handle_dharma_room_turn: engram_save failed for " + snap_path)
}
}
let safe_response: String = json_safe(clean_response)
@@ -1234,28 +1240,14 @@ 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 conv_node_id: String = engram_node_full(
let tags: String = "[\"Conversation\",\"chat\",\"timestamped\"]"
engram_node_full(
content,
"Conversation",
"chat:" + ts_str,
@@ -1265,72 +1257,6 @@ 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.
-42
View File
@@ -368,48 +368,6 @@ 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.