diff --git a/src/pipecat/frames/frames.py b/src/pipecat/frames/frames.py
index 13bf2eaa7..0fe41240a 100644
--- a/src/pipecat/frames/frames.py
+++ b/src/pipecat/frames/frames.py
@@ -337,11 +337,14 @@ class TextFrame(DataFrame):
     # mandatory fields of theirs to have defaults to preserve
     # non-default-before-default argument order)
     includes_inter_frame_spaces: bool = field(init=False)
+    # Whether this text frame should be appended to the LLM context.
+    append_to_context: bool = field(init=False)
 
     def __post_init__(self):
         super().__post_init__()
         self.skip_tts = False
         self.includes_inter_frame_spaces = False
+        self.append_to_context = True
 
     def __str__(self):
         pts = format_pts(self.pts)
diff --git a/src/pipecat/processors/aggregators/llm_response.py b/src/pipecat/processors/aggregators/llm_response.py
index afc091d5a..2b1fb0894 100644
--- a/src/pipecat/processors/aggregators/llm_response.py
+++ b/src/pipecat/processors/aggregators/llm_response.py
@@ -22,6 +22,7 @@ from pipecat.audio.interruptions.base_interruption_strategy import BaseInterrupt
 from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
 from pipecat.audio.vad.vad_analyzer import VADParams
 from pipecat.frames.frames import (
+    AggregatedLLMTextFrame,
     BotStartedSpeakingFrame,
     BotStoppedSpeakingFrame,
     CancelFrame,
@@ -1001,7 +1002,7 @@ class LLMAssistantContextAggregator(LLMContextResponseAggregator):
         await self.push_aggregation()
 
     async def _handle_text(self, frame: TextFrame):
-        if not self._started:
+        if not self._started or not frame.append_to_context:
             return
 
         if self._params.expect_stripped_words:
diff --git a/src/pipecat/processors/aggregators/llm_response_universal.py b/src/pipecat/processors/aggregators/llm_response_universal.py
index d4d9ad7da..460b00288 100644
--- a/src/pipecat/processors/aggregators/llm_response_universal.py
+++ b/src/pipecat/processors/aggregators/llm_response_universal.py
@@ -814,7 +814,7 @@ class LLMAssistantAggregator(LLMContextAggregator):
         await self.push_aggregation()
 
     async def _handle_text(self, frame: TextFrame):
-        if not self._started:
+        if not self._started or not frame.append_to_context:
             return
 
         # Make sure we really have text (spaces count, too!)
diff --git a/src/pipecat/services/tts_service.py b/src/pipecat/services/tts_service.py
index 93276254a..88d0c8847 100644
--- a/src/pipecat/services/tts_service.py
+++ b/src/pipecat/services/tts_service.py
@@ -523,7 +523,9 @@ class TTSService(AIService):
                     # is being spoken. Here, we assume this flag is used when the TTS
                     # provider supports word timestamps and the TTSTextFrames will be
                     # generated in the word_task_handler.
-                    await self.push_frame(AggregatedLLMTextFrame(text, aggregated_by=aggregated_by))
+                    frame = AggregatedLLMTextFrame(text, aggregated_by=aggregated_by)
+                    frame.append_to_context = False
+                    await self.push_frame(frame)
                 await self.process_generator(self.run_tts(text))
 
             await self.stop_processing_metrics()