Update Together services to use canonical settings pattern

- STT/TTS: Use NOT_GIVEN sentinel, Settings alias, and apply_update()
- TTS: Add output_format and encoding params, use audio context
  management, push_start_frame=True, handle binary + JSON audio
- LLM: Update default model to Llama-4-Maverick
- Update examples to use new settings API

examples/foundational/07e-interruptible-together.py

@@ -21,7 +21,6 @@ from pipecat.processors.aggregators.llm_response_universal import (
 )
 from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
-from pipecat.services.openai.llm import OpenAILLMService
 from pipecat.services.together.llm import TogetherLLMService
 from pipecat.services.together.stt import TogetherSTTService
 from pipecat.services.together.tts import TogetherTTSService
@@ -57,19 +56,20 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
 
     tts = TogetherTTSService(
         api_key=os.getenv("TOGETHER_API_KEY"),
-        voice="tara",
+        settings=TogetherTTSService.Settings(
+            model="canopylabs/orpheus-3b-0.1-ft",
+            voice="tara",
+        ),
     )
 
-    llm = TogetherLLMService(api_key=os.getenv("TOGETHER_API_KEY"))
+    llm = TogetherLLMService(
+        api_key=os.getenv("TOGETHER_API_KEY"),
+        settings=TogetherLLMService.Settings(
+            system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.",
+        ),
+    )
 
-    messages = [
-        {
-            "role": "system",
-            "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.",
-        },
-    ]
-
-    context = LLMContext(messages)
+    context = LLMContext()
     user_aggregator, assistant_aggregator = LLMContextAggregatorPair(
         context,
         user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()),
@@ -100,7 +100,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     async def on_client_connected(transport, client):
         logger.info(f"Client connected")
         # Kick off the conversation.
-        messages.append({"role": "system", "content": "Please introduce yourself to the user."})
+        context.add_message({"role": "user", "content": "Please introduce yourself to the user."})
         await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")

examples/foundational/14c-function-calling-together.py

@@ -72,7 +72,6 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     llm = TogetherLLMService(
         api_key=os.getenv("TOGETHER_API_KEY"),
         settings=TogetherLLMService.Settings(
-            model="meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo",
             system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.",
         ),
     )