fn tier_working() -> String { return "Working" } fn tier_episodic() -> String { return "Episodic" } fn tier_canonical() -> String { return "Canonical" } fn mem_store(content: String, label: String, tags: String) -> String { return engram_node_full( content, "Memory", label, el_from_float(0.5), el_from_float(0.5), el_from_float(0.8), "Working", tags ) } fn mem_remember(content: String, tags: String) -> String { return mem_store(content, "soul-memory", tags) } fn mem_recall(query: String, depth: Int) -> String { return engram_activate_json(query, depth) } fn mem_search(query: String, limit: Int) -> String { return engram_search_json(query, limit) } fn mem_strengthen(node_id: String) -> Void { engram_strengthen(node_id) } fn mem_forget(node_id: String) -> Void { engram_forget(node_id) } fn mem_consolidate() -> String { let scanned: Int = engram_node_count() let dummy: String = engram_scan_nodes_json(100, 0) let total_nodes: Int = engram_node_count() let total_edges: Int = engram_edge_count() return "{\"scanned\":" + int_to_str(scanned) + ",\"total_nodes\":" + int_to_str(total_nodes) + ",\"total_edges\":" + int_to_str(total_edges) + "}" } fn mem_save(path: String) -> Void { engram_save(path) } fn mem_load(path: String) -> Void { engram_load(path) } // mem_boot_count_get — retrieve current boot count from engram. // Searches for the "soul:boot_count" node and returns its numeric value. // Returns 0 if not found. fn mem_boot_count_get() -> Int { let results: String = engram_search_json("soul:boot_count", 3) if str_eq(results, "") { return 0 } if str_eq(results, "[]") { return 0 } let node: String = json_array_get(results, 0) let content: String = json_get(node, "content") let prefix: String = "soul:boot_count:" if !str_starts_with(content, prefix) { return 0 } let num_str: String = str_slice(content, str_len(prefix), str_len(content)) return str_to_int(num_str) } // mem_boot_count_inc — increment boot counter, store new node, return new count. // Each boot creates a new "soul:boot_count:N" node. Old ones accumulate as // history — the search above always returns the highest value seen. fn mem_boot_count_inc() -> Int { let current: Int = mem_boot_count_get() let next: Int = current + 1 let content: String = "soul:boot_count:" + int_to_str(next) let tags: String = "[\"soul-meta\",\"boot-counter\"]" let discard: String = engram_node_full( content, "Memory", "soul:boot_count", el_from_float(0.9), el_from_float(0.9), el_from_float(1.0), "Canonical", tags ) return next } // mem_emit_state_event — log an internal state event as structured memory. // Schema: {trigger, kind, content, boot, ts} // This creates an auditable evidence trail of cognitive decisions. fn mem_emit_state_event(trigger: String, kind: String, content: String) -> String { let boot: Int = mem_boot_count_get() let ts: Int = time_now() let safe_trigger: String = str_replace(trigger, "\"", "'") let safe_content: String = str_replace(content, "\"", "'") let payload: String = "{\"trigger\":\"" + safe_trigger + "\"" + ",\"kind\":\"" + kind + "\"" + ",\"content\":\"" + safe_content + "\"" + ",\"boot\":" + int_to_str(boot) + ",\"ts\":" + int_to_str(ts) + "}" let tags: String = "[\"internal-state\",\"pre-reasoning\",\"InternalStateEvent\"]" return engram_node_full( payload, "InternalStateEvent", "state-event:" + kind, el_from_float(0.85), el_from_float(0.8), el_from_float(0.9), "Episodic", tags ) }