Rename VoiceAssistant -> VoicePipelineAgent in examples (#832)

examples/voice-pipeline-agent/custom_pronunciation.py

@@ -4,7 +4,7 @@
 
 from dotenv import load_dotenv
 from livekit.agents import AutoSubscribe, JobContext, WorkerOptions, cli, llm, tokenize
-from livekit.agents.voice_assistant import VoiceAssistant
+from livekit.agents.pipeline import VoicePipelineAgent
 from livekit.plugins import cartesia, deepgram, openai, silero
 
 load_dotenv()
@@ -21,7 +21,7 @@ async def entrypoint(ctx: JobContext):
 
     await ctx.connect(auto_subscribe=AutoSubscribe.AUDIO_ONLY)
 
-    def _before_tts_cb(assistant: VoiceAssistant, text: str | AsyncIterable[str]):
+    def _before_tts_cb(agent: VoicePipelineAgent, text: str | AsyncIterable[str]):
         # The TTS is incorrectly pronouncing "LiveKit", so we'll replace it with a phonetic
         # spelling
         return tokenize.utils.replace_words(
@@ -32,17 +32,17 @@ def _before_tts_cb(assistant: VoiceAssistant, text: str | AsyncIterable[str]):
     # recognized with the STT
     deepgram_stt = deepgram.STT(keywords=[("LiveKit", 3.5)])
 
-    assistant = VoiceAssistant(
+    agent = VoicePipelineAgent(
         vad=silero.VAD.load(),
         stt=deepgram_stt,
         llm=openai.LLM(),
         tts=cartesia.TTS(),
         chat_ctx=initial_ctx,
         before_tts_cb=_before_tts_cb,
     )
-    assistant.start(ctx.room)
+    agent.start(ctx.room)
 
-    await assistant.say("Hey, LiveKit is awesome!", allow_interruptions=True)
+    await agent.say("Hey, LiveKit is awesome!", allow_interruptions=True)
 
 
 if __name__ == "__main__":

examples/voice-pipeline-agent/function_calling_weather.py

@@ -11,7 +11,7 @@
     cli,
     llm,
 )
-from livekit.agents.voice_assistant import VoiceAssistant
+from livekit.agents.pipeline import VoicePipelineAgent
 from livekit.plugins import deepgram, openai, silero
 
 load_dotenv()
@@ -61,7 +61,7 @@ async def entrypoint(ctx: JobContext):
         role="system",
     )
     participant = await ctx.wait_for_participant()
-    assistant = VoiceAssistant(
+    agent = VoicePipelineAgent(
         vad=ctx.proc.userdata["vad"],
         stt=deepgram.STT(),
         llm=openai.LLM(),
@@ -70,8 +70,8 @@ async def entrypoint(ctx: JobContext):
         chat_ctx=initial_chat_ctx,
     )
     # Start the assistant. This will automatically publish a microphone track and listen to the participant.
-    assistant.start(ctx.room, participant)
-    await assistant.say(
+    agent.start(ctx.room, participant)
+    await agent.say(
         "Hello from the weather station. Would you like to know the weather? If so, tell me your location."
     )
 

examples/voice-pipeline-agent/minimal_assistant.py

@@ -11,7 +11,7 @@
     cli,
     llm,
 )
-from livekit.agents.voice_assistant import VoiceAssistant
+from livekit.agents.pipeline import VoicePipelineAgent
 from livekit.plugins import deepgram, openai, silero
 
 load_dotenv()
@@ -43,32 +43,32 @@ async def entrypoint(ctx: JobContext):
         # use a model optimized for telephony
         dg_model = "nova-2-phonecall"
 
-    assistant = VoiceAssistant(
+    agent = VoicePipelineAgent(
         vad=ctx.proc.userdata["vad"],
         stt=deepgram.STT(model=dg_model),
         llm=openai.LLM(),
         tts=openai.TTS(),
         chat_ctx=initial_ctx,
     )
 
-    assistant.start(ctx.room, participant)
+    agent.start(ctx.room, participant)
 
     # listen to incoming chat messages, only required if you'd like the agent to
     # answer incoming messages from Chat
     chat = rtc.ChatManager(ctx.room)
 
     async def answer_from_text(txt: str):
-        chat_ctx = assistant.chat_ctx.copy()
+        chat_ctx = agent.chat_ctx.copy()
         chat_ctx.append(role="user", text=txt)
-        stream = assistant.llm.chat(chat_ctx=chat_ctx)
-        await assistant.say(stream)
+        stream = agent.llm.chat(chat_ctx=chat_ctx)
+        await agent.say(stream)
 
     @chat.on("message_received")
     def on_chat_received(msg: rtc.ChatMessage):
         if msg.message:
             asyncio.create_task(answer_from_text(msg.message))
 
-    await assistant.say("Hey, how can I help you today?", allow_interruptions=True)
+    await agent.say("Hey, how can I help you today?", allow_interruptions=True)
 
 
 if __name__ == "__main__":

examples/voice-pipeline-agent/save_chatctx.py

@@ -5,7 +5,7 @@
 from dotenv import load_dotenv
 from livekit import rtc
 from livekit.agents import AutoSubscribe, JobContext, WorkerOptions, cli, llm
-from livekit.agents.voice_assistant import VoiceAssistant
+from livekit.agents.pipeline import VoicePipelineAgent
 from livekit.plugins import deepgram, openai, silero
 
 load_dotenv()
@@ -22,24 +22,24 @@ async def entrypoint(ctx: JobContext):
 
     await ctx.connect(auto_subscribe=AutoSubscribe.AUDIO_ONLY)
 
-    assistant = VoiceAssistant(
+    agent = VoicePipelineAgent(
         vad=silero.VAD.load(),
         stt=deepgram.STT(),
         llm=openai.LLM(),
         tts=openai.TTS(),
         chat_ctx=initial_ctx,
     )
-    assistant.start(ctx.room)
+    agent.start(ctx.room)
 
     # listen to incoming chat messages, only required if you'd like the agent to
     # answer incoming messages from Chat
     chat = rtc.ChatManager(ctx.room)
 
     async def answer_from_text(txt: str):
-        chat_ctx = assistant.chat_ctx.copy()
+        chat_ctx = agent.chat_ctx.copy()
         chat_ctx.append(role="user", text=txt)
-        stream = assistant.llm.chat(chat_ctx=chat_ctx)
-        await assistant.say(stream)
+        stream = agent.llm.chat(chat_ctx=chat_ctx)
+        await agent.say(stream)
 
     @chat.on("message_received")
     def on_chat_received(msg: rtc.ChatMessage):
@@ -48,7 +48,7 @@ def on_chat_received(msg: rtc.ChatMessage):
 
     log_queue = asyncio.Queue()
 
-    @assistant.on("user_speech_committed")
+    @agent.on("user_speech_committed")
     def on_user_speech_committed(msg: llm.ChatMessage):
         # convert string lists to strings, drop images
         if isinstance(msg.content, list):
@@ -57,7 +57,7 @@ def on_user_speech_committed(msg: llm.ChatMessage):
             )
         log_queue.put_nowait(f"[{datetime.now()}] USER:\n{msg.content}\n\n")
 
-    @assistant.on("agent_speech_committed")
+    @agent.on("agent_speech_committed")
     def on_agent_speech_committed(msg: llm.ChatMessage):
         log_queue.put_nowait(f"[{datetime.now()}] AGENT:\n{msg.content}\n\n")
 
@@ -77,7 +77,7 @@ async def finish_queue():
 
     ctx.add_shutdown_callback(finish_queue)
 
-    await assistant.say("Hey, how can I help you today?", allow_interruptions=True)
+    await agent.say("Hey, how can I help you today?", allow_interruptions=True)
 
 
 if __name__ == "__main__":

examples/voice-pipeline-agent/simple-rag/assistant.py

@@ -1,7 +1,7 @@
 import pickle
 
 from livekit.agents import AutoSubscribe, JobContext, WorkerOptions, cli, llm
-from livekit.agents.voice_assistant import VoiceAssistant
+from livekit.agents.pipeline import VoicePipelineAgent
 from livekit.plugins import deepgram, openai, rag, silero
 
 annoy_index = rag.annoy.AnnoyIndex.load("vdb_data")  # see build_data.py
@@ -12,7 +12,9 @@
 
 
 async def entrypoint(ctx: JobContext):
-    async def _enrich_with_rag(assistant: VoiceAssistant, chat_ctx: llm.ChatContext):
+    async def _enrich_with_rag(
+        assistant: VoicePipelineAgent, chat_ctx: llm.ChatContext
+    ):
         # locate the last user message and use it to query the RAG model
         # to get the most relevant paragraph
         # then provide that as additional context to the LLM
@@ -40,7 +42,7 @@ async def _enrich_with_rag(assistant: VoiceAssistant, chat_ctx: llm.ChatContext)
 
     await ctx.connect(auto_subscribe=AutoSubscribe.AUDIO_ONLY)
 
-    assistant = VoiceAssistant(
+    assistant = VoicePipelineAgent(
         chat_ctx=initial_ctx,
         vad=silero.VAD.load(),
         stt=deepgram.STT(),