Update OpenAIRealtimeLLMService to work with LLMContext and LLMContextAggregatorPair (cont'd).

Update 20b example to use new `LLMContext` pattern.

examples/foundational/20b-persistent-context-openai-realtime.py

@@ -13,11 +13,15 @@ from datetime import datetime
 from dotenv import load_dotenv
 from loguru import logger
 
+from pipecat.adapters.schemas.function_schema import FunctionSchema
+from pipecat.adapters.schemas.tools_schema import ToolsSchema
 from pipecat.audio.vad.silero import SileroVADAnalyzer
 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.llm_context import LLMContext
+from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
 from pipecat.processors.aggregators.openai_llm_context import (
     OpenAILLMContext,
 )
@@ -97,14 +101,12 @@ async def load_conversation(params: FunctionCallParams):
     asyncio.create_task(_reset())
 
 
-tools = [
+tools = ToolsSchema(
-    {
+    standard_tools=[
-        "type": "function",
+        FunctionSchema(
-        "name": "get_current_weather",
+            name="get_current_weather",
-        "description": "Get the current weather",
+            description="Get the current weather",
-        "parameters": {
+            properties={
-            "type": "object",
-            "properties": {
                 "location": {
                     "type": "string",
                     "description": "The city and state, e.g. San Francisco, CA",
@@ -115,45 +117,33 @@ tools = [
                     "description": "The temperature unit to use. Infer this from the users location.",
                 },
             },
-            "required": ["location", "format"],
+            required=["location", "format"],
-        },
+        ),
-    },
+        FunctionSchema(
-    {
+            name="save_conversation",
-        "type": "function",
+            description="Save the current conversatione. Use this function to persist the current conversation to external storage.",
-        "name": "save_conversation",
+            properties={},
-        "description": "Save the current conversatione. Use this function to persist the current conversation to external storage.",
+            required=[],
-        "parameters": {
+        ),
-            "type": "object",
+        FunctionSchema(
-            "properties": {},
+            name="get_saved_conversation_filenames",
-            "required": [],
+            description="Get a list of saved conversation histories. Returns a list of filenames. Each filename includes a date and timestamp. Each file is conversation history that can be loaded into this session.",
-        },
+            properties={},
-    },
+            required=[],
-    {
+        ),
-        "type": "function",
+        FunctionSchema(
-        "name": "get_saved_conversation_filenames",
+            name="load_conversation",
-        "description": "Get a list of saved conversation histories. Returns a list of filenames. Each filename includes a date and timestamp. Each file is conversation history that can be loaded into this session.",
+            description="Load a conversation history. Use this function to load a conversation history into the current session.",
-        "parameters": {
+            properties={
-            "type": "object",
-            "properties": {},
-            "required": [],
-        },
-    },
-    {
-        "type": "function",
-        "name": "load_conversation",
-        "description": "Load a conversation history. Use this function to load a conversation history into the current session.",
-        "parameters": {
-            "type": "object",
-            "properties": {
                 "filename": {
                     "type": "string",
                     "description": "The filename of the conversation history to load.",
                 }
             },
-            "required": ["filename"],
+            required=["filename"],
-        },
+        ),
-    },
+    ]
-]
+)
 
 
 # We store functions so objects (e.g. SileroVADAnalyzer) don't get
@@ -224,8 +214,8 @@ Remember, your responses should be short. Just one or two sentences, usually."""
     llm.register_function("get_saved_conversation_filenames", get_saved_conversation_filenames)
     llm.register_function("load_conversation", load_conversation)
 
-    context = OpenAILLMContext([], tools)
+    context = LLMContext([], tools)
-    context_aggregator = llm.create_context_aggregator(context)
+    context_aggregator = LLMContextAggregatorPair(context)
 
     pipeline = Pipeline(
         [

src/pipecat/adapters/services/open_ai_realtime_adapter.py

@@ -93,7 +93,7 @@ class OpenAIRealtimeLLMAdapter(BaseLLMAdapter):
         # message as a single input.
 
         if not universal_context_messages:
-            return self.ConvertedMessages()
+            return self.ConvertedMessages(messages=[])
 
         messages = copy.deepcopy(universal_context_messages)
         system_instruction = None