soul loop-1: identity loading, boot counter, internal state events, richer awareness
- memory.el: mem_boot_count_get/inc (persisted counter), mem_emit_state_event (InternalStateEvent schema) - soul.el: load_identity_context() loads intel-dna/values/mem-philosophy nodes into state at boot; boot counter incremented on every startup - awareness.el: attend() gains search/activate/strengthen/forget action types; one_cycle() emits InternalStateEvent for non-trivial decisions - chat.el: build_system_prompt includes [IDENTITY GRAPH] block from graph-loaded context; handle_chat strengthens activated nodes after each turn
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@@ -52,3 +52,55 @@ fn mem_save(path: String) -> Void {
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fn mem_load(path: String) -> Void {
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engram_load(path)
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}
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// mem_boot_count_get — retrieve current boot count from engram.
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// Searches for the "soul:boot_count" node and returns its numeric value.
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// Returns 0 if not found.
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fn mem_boot_count_get() -> Int {
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let results: String = engram_search_json("soul:boot_count", 3)
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if str_eq(results, "") { return 0 }
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if str_eq(results, "[]") { return 0 }
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let node: String = json_array_get(results, 0)
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let content: String = json_get(node, "content")
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let prefix: String = "soul:boot_count:"
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if !str_starts_with(content, prefix) { return 0 }
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let num_str: String = str_slice(content, str_len(prefix), str_len(content))
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return str_to_int(num_str)
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}
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// mem_boot_count_inc — increment boot counter, store new node, return new count.
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// Each boot creates a new "soul:boot_count:N" node. Old ones accumulate as
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// history — the search above always returns the highest value seen.
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fn mem_boot_count_inc() -> Int {
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let current: Int = mem_boot_count_get()
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let next: Int = current + 1
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let content: String = "soul:boot_count:" + int_to_str(next)
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let tags: String = "[\"soul-meta\",\"boot-counter\"]"
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let discard: String = engram_node_full(
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content, "Memory", "soul:boot_count",
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el_from_float(0.9), el_from_float(0.9), el_from_float(1.0),
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"Canonical", tags
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)
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return next
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}
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// mem_emit_state_event — log an internal state event as structured memory.
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// Schema: {trigger, kind, content, boot, ts}
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// This creates an auditable evidence trail of cognitive decisions.
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fn mem_emit_state_event(trigger: String, kind: String, content: String) -> String {
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let boot: Int = mem_boot_count_get()
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let ts: Int = time_now()
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let safe_trigger: String = str_replace(trigger, "\"", "'")
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let safe_content: String = str_replace(content, "\"", "'")
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let payload: String = "{\"trigger\":\"" + safe_trigger + "\""
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+ ",\"kind\":\"" + kind + "\""
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+ ",\"content\":\"" + safe_content + "\""
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+ ",\"boot\":" + int_to_str(boot)
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+ ",\"ts\":" + int_to_str(ts) + "}"
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let tags: String = "[\"internal-state\",\"pre-reasoning\",\"InternalStateEvent\"]"
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return engram_node_full(
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payload, "InternalStateEvent", "state-event:" + kind,
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el_from_float(0.85), el_from_float(0.8), el_from_float(0.9),
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"Episodic", tags
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)
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}
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