Update examples, wherever possible, to use LLMContext and associated machinery instead of OpenAILLMContext and associated machinery.

With all these examples updated, we no longer need dedicated examples illustrating `LLMContext`, so they're removed.

Here’s where we *don’t* yet use `LLMContext` and associated machinery:
- Realtime services: OpenAI Realtime, Gemini Live, and AWS Nova Sonic (support coming soon)
- `GoogleLLMOpenAIBetaService` (it’s deprecated, so we didn’t bother adding support)
- `LLMLogObserver` (support coming soon)
- `GatedOpenAILLMContextAggregator` (support coming soon)
- `LangchainProcessor` (support coming soon)
- `Mem0MemoryService` (support coming soon)
- Examples that use LLM-specific tools definitions as opposed to `ToolsSchema` (these will be updated soon)
- Examples that rely `GoogleLLMContext.upgrade_to_google` (TBD what to do with these)

Examples that use `LLMLogObserver`:
- 30-

Examples that use `GatedOpenAILLMContextAggregator`:
- 22-

Examples that use `LangchainProcessor`:
- 07b-

Examples that use `Mem0MemoryService`:
- 37-

Examples that need updating to use `ToolsSchema`:
- 15-
- 15a-
- 20a-
- 20c-
- 20d-
- 22b-
- 22c-
- 33-
- 36-

Examples that use `GoogleLLMContext.upgrade_to_google`:
- 22d-
- 25-

examples/foundational/05a-local-sync-speech-and-image.py

@@ -15,6 +15,7 @@ from loguru import logger
 
 from pipecat.frames.frames import (
     Frame,
+    LLMContextFrame,
     OutputAudioRawFrame,
     TextFrame,
     TTSAudioRawFrame,
@@ -24,10 +25,8 @@ from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.sync_parallel_pipeline import SyncParallelPipeline
 from pipecat.pipeline.task import PipelineTask
-from pipecat.processors.aggregators.openai_llm_context import (
-    OpenAILLMContext,
-    OpenAILLMContextFrame,
-)
+from pipecat.processors.aggregators.llm_context import LLMContext
+from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
 from pipecat.processors.aggregators.sentence import SentenceAggregator
 from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
 from pipecat.services.cartesia.tts import CartesiaHttpTTSService
@@ -140,7 +139,7 @@ async def main():
             )
 
             task = PipelineTask(pipeline)
-            await task.queue_frame(OpenAILLMContextFrame(OpenAILLMContext(messages)))
+            await task.queue_frame(LLMContextFrame(LLMContext(messages)))
             await task.stop_when_done()
 
             await runner.run(task)