fix: patch summarizer and add tests (#6457)

letta/services/summarizer/summarizer_sliding_window.py

@@ -73,8 +73,8 @@ async def summarize_via_sliding_window(
 
     # Starts at N% (eg 70%), and increments up until 100%
     message_count_cutoff_percent = max(
-        1 - summarizer_config.sliding_window_percentage, 10
-    )  # Some arbitrary minimum value to avoid negatives from badly configured summarizer percentage
+        1 - summarizer_config.sliding_window_percentage, 0.10
+    )  # Some arbitrary minimum value (10%) to avoid negatives from badly configured summarizer percentage
     found_cutoff = False
 
     # Count tokens with system prompt, and message past cutoff point
@@ -98,8 +98,8 @@ async def summarize_via_sliding_window(
         if post_summarization_buffer_tokens <= summarizer_config.sliding_window_percentage * llm_config.context_window:
             found_cutoff = True
         else:
-            message_count_cutoff_percent += 10
-            if message_count_cutoff_percent >= 100:
+            message_count_cutoff_percent += 0.10
+            if message_count_cutoff_percent >= 1.0:
                 message_cutoff_index = total_message_count
                 break
 

tests/integration_test_summarizer.py

@@ -663,3 +663,137 @@ async def test_summarize_with_mode(server: SyncServer, actor, llm_config: LLMCon
         assert isinstance(result, list)
         assert len(result) >= 1
         print(f"{mode.value} with {llm_config.model}: {len(in_context_messages)} -> {len(result)} messages")
+
+
+# ======================================================================================================================
+# Sliding Window Summarizer Unit Tests
+# ======================================================================================================================
+
+
+@pytest.mark.asyncio
+async def test_sliding_window_cutoff_index_does_not_exceed_message_count():
+    """
+    Test that the sliding window summarizer correctly calculates cutoff indices.
+
+    This test verifies the fix for a bug where the cutoff percentage was treated as
+    a whole number (10) instead of a decimal (0.10), causing:
+      message_cutoff_index = round(10 * 65) = 650
+    when there were only 65 messages, resulting in an empty range loop and the error:
+      "No assistant message found from indices 650 to 65"
+
+    The fix changed:
+      - max(..., 10) -> max(..., 0.10)
+      - += 10 -> += 0.10
+      - >= 100 -> >= 1.0
+    """
+    from unittest.mock import MagicMock, patch
+
+    from letta.schemas.enums import MessageRole
+    from letta.schemas.letta_message_content import TextContent
+    from letta.schemas.llm_config import LLMConfig
+    from letta.schemas.message import Message as PydanticMessage
+    from letta.schemas.user import User
+    from letta.services.summarizer.summarizer_sliding_window import summarize_via_sliding_window
+
+    # Create a mock user (using proper ID format pattern)
+    mock_actor = User(
+        id="user-00000000-0000-0000-0000-000000000000", name="Test User", organization_id="org-00000000-0000-0000-0000-000000000000"
+    )
+
+    # Create a mock LLM config
+    mock_llm_config = LLMConfig(
+        model="gpt-4",
+        model_endpoint_type="openai",
+        context_window=128000,
+    )
+
+    # Create a mock summarizer config with sliding_window_percentage = 0.3
+    mock_summarizer_config = MagicMock()
+    mock_summarizer_config.sliding_window_percentage = 0.3
+    mock_summarizer_config.summarizer_model = mock_llm_config
+    mock_summarizer_config.prompt = "Summarize the conversation."
+    mock_summarizer_config.prompt_acknowledgement = True
+    mock_summarizer_config.clip_chars = 2000
+
+    # Create 65 messages (similar to the failing case in the bug report)
+    # Pattern: system + alternating user/assistant messages
+    messages = [
+        PydanticMessage(
+            role=MessageRole.system,
+            content=[TextContent(type="text", text="You are a helpful assistant.")],
+        )
+    ]
+
+    # Add 64 more messages (32 user-assistant pairs)
+    for i in range(32):
+        messages.append(
+            PydanticMessage(
+                role=MessageRole.user,
+                content=[TextContent(type="text", text=f"User message {i}")],
+            )
+        )
+        messages.append(
+            PydanticMessage(
+                role=MessageRole.assistant,
+                content=[TextContent(type="text", text=f"Assistant response {i}")],
+            )
+        )
+
+    assert len(messages) == 65, f"Expected 65 messages, got {len(messages)}"
+
+    # Mock count_tokens to return a value that would trigger summarization
+    # Return a high token count so that the while loop continues
+    async def mock_count_tokens(actor, llm_config, messages):
+        # Return tokens that decrease as we cut off more messages
+        # This simulates the token count decreasing as we evict messages
+        return len(messages) * 100  # 100 tokens per message
+
+    # Mock simple_summary to return a fake summary
+    async def mock_simple_summary(messages, llm_config, actor, include_ack, prompt):
+        return "This is a mock summary of the conversation."
+
+    with (
+        patch(
+            "letta.services.summarizer.summarizer_sliding_window.count_tokens",
+            side_effect=mock_count_tokens,
+        ),
+        patch(
+            "letta.services.summarizer.summarizer_sliding_window.simple_summary",
+            side_effect=mock_simple_summary,
+        ),
+    ):
+        # This should NOT raise "No assistant message found from indices 650 to 65"
+        # With the fix, message_count_cutoff_percent starts at max(0.7, 0.10) = 0.7
+        # So message_cutoff_index = round(0.7 * 65) = 46, which is valid
+        try:
+            summary, remaining_messages = await summarize_via_sliding_window(
+                actor=mock_actor,
+                llm_config=mock_llm_config,
+                summarizer_config=mock_summarizer_config,
+                in_context_messages=messages,
+                new_messages=[],
+            )
+
+            # Verify the summary was generated
+            assert summary == "This is a mock summary of the conversation."
+
+            # Verify remaining messages is a valid subset
+            assert len(remaining_messages) < len(messages)
+            assert len(remaining_messages) > 0
+
+            print(f"Successfully summarized {len(messages)} messages to {len(remaining_messages)} remaining")
+
+        except ValueError as e:
+            if "No assistant message found from indices" in str(e):
+                # Extract the indices from the error message
+                import re
+
+                match = re.search(r"from indices (\d+) to (\d+)", str(e))
+                if match:
+                    start_idx, end_idx = int(match.group(1)), int(match.group(2))
+                    pytest.fail(
+                        f"Bug detected: cutoff index ({start_idx}) exceeds message count ({end_idx}). "
+                        f"This indicates the percentage calculation bug where 10 was used instead of 0.10. "
+                        f"Error: {e}"
+                    )
+            raise