Feature/active memory actions

README.md

@@ -86,7 +86,7 @@ Completed thinking blocks are also scanned for direct citations from trusted pro
 
 If generation is aborted, the runtime captures the partial answer and schedules an interrupted memory update. The memory summarizer is instructed to mark the turn as incomplete and not treat it as resolved.
 
-When the user signals the end of a session — explicitly or through natural closing phrases — the brain emits a `REMEMBER_SESSION` action. The runtime builds a compact L3 digest from the current snapshot history and sends it to the browser for local storage. On the next connection, the browser sends the digest back as part of the bootstrap payload and the runtime injects it as trusted session context before the first turn.
+When the user signals the end of a session — explicitly or through natural closing phrases — the brain emits a `SAVE_SESSION` action. The runtime builds a compact L3 digest from the current snapshot history and sends it to the browser for local storage. On the next connection, the browser sends the digest back as part of the bootstrap payload and the runtime injects it as trusted session context before the first turn.
 
 ## Runtime Memory
 
@@ -151,7 +151,7 @@ A rendered runtime snapshot also carries metadata used by the right-side timelin
 }
 ```
 
-`active_memory` lifecycle suffixes are owned by runtime, not L1. L1 sees the contract value and `[ status: ... ]`; runtime reattaches `[ creation_time ]`, `[ created_jin_message_number ]`, `[ elapsed_time ]`, and `[ elapsed_jin_message_number ]` after each update. Memory lines may also have temporary trace strength such as `[ trace: 0.50 ]` or inject `user_idle: 9s` into the displayed context. Those are runtime metadata signals, not durable memory facts.
+`active_memory` lifecycle suffixes are owned by runtime, not L1. L1 sees the contract value and `[ status: ... ]`; runtime reattaches `[ creation_time ]`, `[ created_jin_message_number ]`, `[ elapsed_time ]`, and `[ elapsed_jin_message_number ]` after each runtime refresh. Memory lines may also have temporary trace strength such as `[ trace: 0.50 ]` or inject `user_idle: 9s` into the displayed context. Those are runtime metadata signals, not durable memory facts.
 
 ### L2 memory snapshot (patterns)
 
@@ -410,15 +410,14 @@ TRANSLATION_MAX_TOKENS = 2048
 
 L3 session memory lets context survive across browser sessions without a server-side database.
 
-To save a session, say something that signals you are done: "save the session", "that's all for today", "wrap it up", "I'm going to sleep", or the Russian equivalents. The brain emits a `REMEMBER_SESSION` action and the runtime builds a compressed digest from the current snapshot history. The browser stores this digest in `localStorage` and also writes it back to `saved_runtime.txt` if that path is configured.
+To save a session, say something that signals you are done: "save the session", "that's all for today", "wrap it up", "I'm going to sleep", or the Russian equivalents. The brain emits a `SAVE_SESSION` action and the runtime builds a compressed digest from the current snapshot history. The browser stores this digest in `localStorage` and also writes it back to `saved_runtime.txt` if that path is configured.
 
 On the next page load or reconnect, the browser includes the saved digest in its bootstrap payload. The runtime receives it, validates it against any fresh L1 memory that may have accumulated, and injects the session context into the brain prompt before the first turn.
 
 The sidebar shows a distinct indicator when a session was restored from a saved digest rather than built from live L1 memory.
 
 `saved_runtime.example.txt` shows the expected format for a pre-populated session memory file. Copy it to `saved_runtime.txt` and edit the contents to seed JIN with static facts that should survive every session.
 
-Important events — a major decision, a strong insight, a correction that changes how JIN understands the user — can also be saved mid-session with a `REMEMBER_EVENT` action. The brain emits this automatically when the conversation reaches a clear milestone.
 
 ## Tests
 
@@ -587,6 +586,5 @@ The following capabilities are planned but not yet implemented.
 
 **Brain fallback on low repair score.** When a service-model code/diff attempt scores below a configurable threshold (default 50), the next repair attempt is routed to the brain model with a clean snapshot containing only the original task, the current file state, the failed patch, and the exact error. The brain model does not receive the previous model's reasoning chain.
 
-**Memory event temperature.** Episodic key moments saved via `REMEMBER_EVENT` will carry emotional temperature (`positive`, `negative`, `mixed`), intensity, and initiator (`user_marked` or `jin_detected`). The service model infers these fields from natural language rather than requiring the user to fill a form. JIN may occasionally propose saving a moment it judges significant, but does so rarely.
 
 **Safe memory key normalization.** All memory keys arriving from model output or runtime updates are normalized before storage: trimmed, capped at 120 characters, and stripped of characters outside `[a-zA-Z0-9_\-:.]`. When normalization changes a key, the original is preserved as `raw_label` metadata. Conflicts from key collisions after normalization get numeric suffixes. Keys and values are rendered as `textContent` in the UI, never as `innerHTML`.

agent/nodes/brain.py

@@ -8,15 +8,15 @@
     ask_brain_stream,
     build_brain_payload,
     build_brain_system_prompt,
-    record_deep_thought_calls,
+    emit_active_memory_records_update_if_dirty,
 )
 
 from clients.search_client import (
     build_search_result_fallback_answer,
     run_search_service,
 )
 
-from utils.brain import (
+from clients.brain_client_utils import (
     get_brain_runtime_config,
 )
 
@@ -145,9 +145,14 @@ async def run(
             build_brain_system_prompt(
                 context,
                 runtime_actions=runtime_actions,
+                commit_active_memory_refresh=True,
             )
         )
 
+        await emit_active_memory_records_update_if_dirty(
+            context
+        )
+
         context.runtime_zero_diff_alert = None
 
         brain_payload = (
@@ -170,11 +175,6 @@ async def run(
             ),
         )
 
-        record_deep_thought_calls(
-            context,
-            reasoning,
-        )
-
         if context.runtime_search_queries:
 
             search_call = (
@@ -233,9 +233,14 @@ async def run(
                 build_brain_system_prompt(
                     context,
                     runtime_actions=followup_runtime_actions,
+                    commit_active_memory_refresh=True,
                 )
             )
 
+            await emit_active_memory_records_update_if_dirty(
+                context
+            )
+
             followup_payload = (
                 "User request:\n"
                 f"{state.translated_input}\n\n"
@@ -258,11 +263,6 @@ async def run(
                 ),
             )
 
-            record_deep_thought_calls(
-                context,
-                reasoning,
-            )
-
             if not text.strip():
                 text = build_search_result_fallback_answer(
                     search_result