context_compaction added

src/google/adk/apps/app.py

@@ -80,6 +80,12 @@ class EventsCompactionConfig(BaseModel):
   end of the last compacted range. This creates an overlap between consecutive
   compacted summaries, maintaining context."""
 
+  token_threshold: Optional[int] = None
+  """Token count that triggers compaction when exceeded."""
+
+  retain_recent_events: Optional[int] = None
+  """Number of the most recent events to retain during compaction."""
+
 
 class App(BaseModel):
   """Represents an LLM-backed agentic application.

src/google/adk/apps/compaction.py

@@ -192,7 +192,8 @@ async def _run_compaction_for_sliding_window(
 
   compaction_event = (
       await app.events_compaction_config.summarizer.maybe_summarize_events(
-          events=events_to_compact
+          events=events_to_compact,
+          config=app.events_compaction_config
       )
   )
   if compaction_event:

src/google/adk/apps/llm_event_summarizer.py

@@ -81,19 +81,32 @@ def _format_events_for_prompt(self, events: list[Event]) -> str:
     return '\\n'.join(formatted_history)
 
   async def maybe_summarize_events(
-      self, *, events: list[Event]
+      self, *, events: list[Event], config: EventsCompactionConfig
   ) -> Optional[Event]:
     """Compacts given events and returns the compacted content.
 
     Args:
       events: A list of events to compact.
+      config: The configuration for event compaction.
 
     Returns:
       The new compacted event, or None if no compaction is needed.
     """
     if not events:
       return None
 
+    # Placeholder for token counting logic
+    def count_tokens(events: list[Event]) -> int:
+        return sum(len(event.content.parts) for event in events if event.content)
+
+    token_count = count_tokens(events)
+
+    if config.token_threshold and token_count <= config.token_threshold:
+        return None
+
+    if config.retain_recent_events:
+        events = events[-config.retain_recent_events:]
+
     conversation_history = self._format_events_for_prompt(events)
     prompt = self._prompt_template.format(
         conversation_history=conversation_history

tests/integration/test_multi_turn.py

@@ -36,6 +36,15 @@ async def test_dependent_tool_calls():
   )
 
 
+@pytest.mark.asyncio
+async def test_context_compaction_with_thresholds():
+  """Test context compaction using token threshold and retaining recent events."""
+  await AgentEvaluator.evaluate(
+      agent_module="tests.integration.fixture.compaction_evaluation_agent",
+      eval_dataset_file_path_or_dir="tests/integration/fixture/compaction_evaluation_agent/test_files/compaction_with_thresholds.test.json",
+      num_runs=4,
+  )
+
 @pytest.mark.asyncio
 async def test_memorizing_past_events():
   """Test memorizing past events."""