Merge pull request #2717 from pipecat-ai/pk/mem0-support-univeral-context

Add support for universal `LLMContext` to `Mem0MemoryService`

examples/foundational/37-mem0.py

@@ -55,7 +55,8 @@ from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
+from pipecat.processors.aggregators.llm_context import LLMContext
+from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
 from pipecat.processors.frameworks.rtvi import RTVIConfig, RTVIObserver, RTVIProcessor
 from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
@@ -244,8 +245,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
 
     # Set up conversation context and management
     # The context_aggregator will automatically collect conversation context
-    context = OpenAILLMContext(messages)
+    context = LLMContext(messages)
-    context_aggregator = llm.create_context_aggregator(context)
+    context_aggregator = LLMContextAggregatorPair(context)
     rtvi = RTVIProcessor(config=RTVIConfig(config=[]))
 
     pipeline = Pipeline(

src/pipecat/services/mem0/memory.py

@@ -16,7 +16,8 @@ from typing import Any, Dict, List, Optional
 from loguru import logger
 from pydantic import BaseModel, Field
 
-from pipecat.frames.frames import ErrorFrame, Frame, LLMMessagesFrame
+from pipecat.frames.frames import ErrorFrame, Frame, LLMContextFrame, LLMMessagesFrame
+from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.openai_llm_context import (
     OpenAILLMContext,
     OpenAILLMContextFrame,
@@ -180,11 +181,11 @@ class Mem0MemoryService(FrameProcessor):
             logger.error(f"Error retrieving memories from Mem0: {e}")
             return []
 
-    def _enhance_context_with_memories(self, context: OpenAILLMContext, query: str):
+    def _enhance_context_with_memories(self, context: LLMContext | OpenAILLMContext, query: str):
         """Enhance the LLM context with relevant memories.
 
         Args:
-            context: The OpenAILLMContext to enhance with memory information.
+            context: The LLM context to enhance with memory information.
             query: The query to search for relevant memories.
         """
         # Skip if this is the same query we just processed
@@ -222,11 +223,11 @@ class Mem0MemoryService(FrameProcessor):
         context = None
         messages = None
 
-        if isinstance(frame, OpenAILLMContextFrame):
+        if isinstance(frame, (LLMContextFrame, OpenAILLMContextFrame)):
             context = frame.context
         elif isinstance(frame, LLMMessagesFrame):
             messages = frame.messages
-            context = OpenAILLMContext.from_messages(messages)
+            context = LLMContext(messages)
 
         if context:
             try: