[WIP] Universal (LLM-agnostic) context machinery to support runtime LLM switching.

- Added universal `LLMContext` and associated context aggregators.

src/pipecat/frames/frames.py

@@ -36,6 +36,7 @@ from pipecat.utils.time import nanoseconds_to_str
 from pipecat.utils.utils import obj_count, obj_id
 
 if TYPE_CHECKING:
+    from pipecat.processors.aggregators.llm_context import LLMContext
     from pipecat.processors.frame_processor import FrameProcessor
 
 
@@ -474,6 +475,20 @@ class TranscriptionUpdateFrame(DataFrame):
         return f"{self.name}(pts: {pts}, messages: {len(self.messages)})"
 
 
+@dataclass
+class LLMContextFrame(Frame):
+    """Frame containing a universal LLM context.
+
+    Used as a signal to LLM services to ingest the provided context and
+    generate a response based on it.
+
+    Parameters:
+        context: The LLM context containing messages, tools, and configuration.
+    """
+
+    context: "LLMContext"
+
+
 @dataclass
 class LLMMessagesFrame(DataFrame):
     """Frame containing LLM messages for chat completion.