Include deprecation warnings for LLMUserResponseAggregator and LLMAssistantResponseAggregator

CHANGELOG.md

@@ -458,7 +458,7 @@ async def on_audio_data(processor, audio, sample_rate, num_channels):
 ### Deprecated
 
 - `LLMUserResponseAggregator` and `LLMAssistantResponseAggregator` are
-  mostly deprecated, use `OpenAILLMContext` instead.
+  deprecated. Use `OpenAILLMContext` instead.
 
 - The `vad` package is now deprecated and `audio.vad` should be used
   instead. The `avd` package will get removed in a future release.

examples/foundational/07p-interruptible-krisp.py

@@ -14,14 +14,10 @@ from loguru import logger
 from runner import configure
 
 from pipecat.audio.filters.krisp_filter import KrispFilter
-from pipecat.frames.frames import LLMMessagesFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_response import (
-    LLMAssistantResponseAggregator,
-    LLMUserResponseAggregator,
-)
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
 from pipecat.services.deepgram import DeepgramSTTService, DeepgramTTSService
 from pipecat.services.openai import OpenAILLMService
 from pipecat.transports.services.daily import DailyParams, DailyTransport
@@ -63,18 +59,18 @@ async def main():
             },
         ]
 
-        tma_in = LLMUserResponseAggregator(messages)
-        tma_out = LLMAssistantResponseAggregator(messages)
+        context = OpenAILLMContext(messages)
+        context_aggregator = llm.create_context_aggregator(context)
 
         pipeline = Pipeline(
             [
                 transport.input(),  # Transport user input
                 stt,  # STT
-                tma_in,  # User responses
+                context_aggregator.user(),  # User responses
                 llm,  # LLM
                 tts,  # TTS
                 transport.output(),  # Transport bot output
-                tma_out,  # Assistant spoken responses
+                context_aggregator.assistant(),  # Assistant spoken responses
             ]
         )
 
@@ -84,7 +80,7 @@ async def main():
         async def on_first_participant_joined(transport, participant):
             # Kick off the conversation.
             messages.append({"role": "system", "content": "Please introduce yourself to the user."})
-            await task.queue_frames([LLMMessagesFrame(messages)])
+            await task.queue_frames([context_aggregator.user().get_context_frame()])
 
         runner = PipelineRunner()
 

examples/foundational/21-tavus-layer.py

@@ -14,14 +14,10 @@ from dotenv import load_dotenv
 from loguru import logger
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.frames.frames import LLMMessagesFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_response import (
-    LLMAssistantResponseAggregator,
-    LLMUserResponseAggregator,
-)
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
 from pipecat.services.cartesia import CartesiaTTSService
 from pipecat.services.deepgram import DeepgramSTTService
 from pipecat.services.openai import OpenAILLMService
@@ -74,19 +70,19 @@ async def main():
             },
         ]
 
-        tma_in = LLMUserResponseAggregator(messages)
-        tma_out = LLMAssistantResponseAggregator(messages)
+        context = OpenAILLMContext(messages)
+        context_aggregator = llm.create_context_aggregator(context)
 
         pipeline = Pipeline(
             [
                 transport.input(),  # Transport user input
                 stt,  # STT
-                tma_in,  # User responses
+                context_aggregator.user(),  # User responses
                 llm,  # LLM
                 tts,  # TTS
                 tavus,  # Tavus output layer
                 transport.output(),  # Transport bot output
-                tma_out,  # Assistant spoken responses
+                context_aggregator.assistant(),  # Assistant spoken responses
             ]
         )
 
@@ -120,7 +116,7 @@ async def main():
                 messages.append(
                     {"role": "system", "content": "Please introduce yourself to the user."}
                 )
-                await task.queue_frames([LLMMessagesFrame(messages)])
+                await task.queue_frames([context_aggregator.user().get_context_frame()])
 
         runner = PipelineRunner()
 

src/pipecat/processors/aggregators/llm_response.py

@@ -4,6 +4,7 @@
 # SPDX-License-Identifier: BSD 2-Clause License
 #
 
+import warnings
 from typing import List, Type
 
 from pipecat.frames.frames import (
@@ -28,6 +29,16 @@ from pipecat.processors.aggregators.openai_llm_context import (
 from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
 
 
+def _deprecation_warning(old_class: str):
+    warnings.warn(
+        f"{old_class} is deprecated and will be removed in a future version. "
+        f"Instead, create an OpenAILLMContext and use llm.create_context_aggregator(context) "
+        f"to get context-aware aggregators via .user() and .assistant() methods.",
+        DeprecationWarning,
+        stacklevel=2,
+    )
+
+
 class LLMResponseAggregator(FrameProcessor):
     def __init__(
         self,
@@ -175,7 +186,10 @@ class LLMResponseAggregator(FrameProcessor):
 
 
 class LLMAssistantResponseAggregator(LLMResponseAggregator):
+    """DEPRECATED: Create an OpenAILLMContext and use llm.create_context_aggregator(context).assistant() instead."""
+
     def __init__(self, messages: List[dict] = []):
+        _deprecation_warning("LLMAssistantResponseAggregator")
         super().__init__(
             messages=messages,
             role="assistant",
@@ -187,7 +201,10 @@ class LLMAssistantResponseAggregator(LLMResponseAggregator):
 
 
 class LLMUserResponseAggregator(LLMResponseAggregator):
+    """DEPRECATED: Create an OpenAILLMContext and use llm.create_context_aggregator(context).user() instead."""
+
     def __init__(self, messages: List[dict] = []):
+        _deprecation_warning("LLMUserResponseAggregator")
         super().__init__(
             messages=messages,
             role="user",