skipping provider-specific messages during summarization

src/pipecat/utils/context/llm_context_summarization.py

@@ -15,7 +15,7 @@ from typing import List, Optional
 
 from loguru import logger
 
-from pipecat.processors.aggregators.llm_context import LLMContext
+from pipecat.processors.aggregators.llm_context import LLMContext, LLMSpecificMessage
 
 # Token estimation constants
 CHARS_PER_TOKEN = 4  # Industry-standard heuristic: 1 token ≈ 4 characters
@@ -188,6 +188,9 @@ class LLMContextSummarizationUtil:
         total = 0
 
         for message in context.messages:
+            if isinstance(message, LLMSpecificMessage):
+                continue
+
             # Role and structure overhead
             total += TOKEN_OVERHEAD_PER_MESSAGE
 
@@ -248,6 +251,9 @@ class LLMContextSummarizationUtil:
 
         for i in range(start_idx, len(messages)):
             msg = messages[i]
+            if isinstance(msg, LLMSpecificMessage):
+                continue
+
             role = msg.get("role")
 
             # Check for tool calls in assistant messages
@@ -298,7 +304,12 @@ class LLMContextSummarizationUtil:
 
         # Find first system message index
         first_system_index = next(
-            (i for i, msg in enumerate(messages) if msg.get("role") == "system"), -1
+            (
+                i
+                for i, msg in enumerate(messages)
+                if not isinstance(msg, LLMSpecificMessage) and msg.get("role") == "system"
+            ),
+            -1,
         )
 
         # Messages to summarize are between first system and recent messages
@@ -356,6 +367,9 @@ class LLMContextSummarizationUtil:
         transcript_parts = []
 
         for msg in messages:
+            if isinstance(msg, LLMSpecificMessage):
+                continue
+
             role = msg.get("role", "unknown")
             content = msg.get("content", "")
 

tests/test_context_summarization.py

@@ -10,7 +10,7 @@ import unittest
 from unittest.mock import AsyncMock, MagicMock, patch
 
 from pipecat.frames.frames import LLMContextSummaryRequestFrame
-from pipecat.processors.aggregators.llm_context import LLMContext
+from pipecat.processors.aggregators.llm_context import LLMContext, LLMSpecificMessage
 from pipecat.services.llm_service import LLMService
 from pipecat.utils.context.llm_context_summarization import (
     LLMContextSummarizationConfig,
@@ -602,5 +602,77 @@ class TestSummaryGenerationExceptions(unittest.IsolatedAsyncioTestCase):
         self.assertEqual(last_index, 1)  # Should be the index of the last summarized message
 
 
+class TestLLMSpecificMessageHandling(unittest.TestCase):
+    """Tests that LLMSpecificMessage objects are correctly skipped in summarization."""
+
+    def test_estimate_context_tokens_skips_specific_messages(self):
+        """Test that estimate_context_tokens skips LLMSpecificMessage objects."""
+        context = LLMContext()
+        context.add_message({"role": "user", "content": "Hello"})
+        context.add_message(LLMSpecificMessage(llm="google", message={}))
+        context.add_message({"role": "assistant", "content": "Hi there"})
+
+        tokens_with_specific = LLMContextSummarizationUtil.estimate_context_tokens(context)
+
+        context_without = LLMContext()
+        context_without.add_message({"role": "user", "content": "Hello"})
+        context_without.add_message({"role": "assistant", "content": "Hi there"})
+        tokens_without = LLMContextSummarizationUtil.estimate_context_tokens(context_without)
+
+        self.assertEqual(tokens_with_specific, tokens_without)
+
+    def test_get_messages_to_summarize_with_specific_messages(self):
+        """Test that get_messages_to_summarize handles LLMSpecificMessage objects."""
+        context = LLMContext()
+        context.add_message({"role": "system", "content": "System prompt"})
+        context.add_message(LLMSpecificMessage(llm="google", message={}))
+        context.add_message({"role": "user", "content": "Message 1"})
+        context.add_message({"role": "assistant", "content": "Response 1"})
+        context.add_message(LLMSpecificMessage(llm="google", message={}))
+        context.add_message({"role": "user", "content": "Message 2"})
+        context.add_message({"role": "assistant", "content": "Response 2"})
+
+        result = LLMContextSummarizationUtil.get_messages_to_summarize(context, 2)
+
+        self.assertGreater(len(result.messages), 0)
+        self.assertGreater(result.last_summarized_index, 0)
+
+    def test_format_messages_skips_specific_messages(self):
+        """Test that format_messages_for_summary skips LLMSpecificMessage objects."""
+        messages = [
+            {"role": "user", "content": "Hello"},
+            LLMSpecificMessage(llm="google", message={}),
+            {"role": "assistant", "content": "Hi there"},
+        ]
+
+        transcript = LLMContextSummarizationUtil.format_messages_for_summary(messages)
+
+        self.assertIn("USER: Hello", transcript)
+        self.assertIn("ASSISTANT: Hi there", transcript)
+
+    def test_function_call_tracking_skips_specific_messages(self):
+        """Test that _get_function_calls_in_progress_index skips LLMSpecificMessage."""
+        messages = [
+            {"role": "user", "content": "What time is it?"},
+            LLMSpecificMessage(llm="google", message={}),
+            {
+                "role": "assistant",
+                "content": "",
+                "tool_calls": [
+                    {
+                        "id": "call_123",
+                        "type": "function",
+                        "function": {"name": "get_time", "arguments": "{}"},
+                    }
+                ],
+            },
+            LLMSpecificMessage(llm="google", message={}),
+            {"role": "tool", "tool_call_id": "call_123", "content": '{"time": "10:30 AM"}'},
+        ]
+
+        result = LLMContextSummarizationUtil._get_function_calls_in_progress_index(messages, 0)
+        self.assertEqual(result, -1)
+
+
 if __name__ == "__main__":
     unittest.main()