examples(foundational): use system_instruction in all examples

This commit is contained in:
Aleix Conchillo Flaqué
2026-03-04 15:36:48 -08:00
parent 01f0caf252
commit 0004a116d8
192 changed files with 1118 additions and 1916 deletions

View File

@@ -84,7 +84,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady
)
llm = GoogleLLMService(api_key=os.getenv("GOOGLE_API_KEY"))
llm = GoogleLLMService(
api_key=os.getenv("GOOGLE_API_KEY"),
system_instruction="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. You have access to tools to get the current weather - use them when relevant.",
)
# Register tool functions
llm.register_function("get_current_weather", get_current_weather)
@@ -107,14 +110,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
)
tools = ToolsSchema(standard_tools=[weather_function])
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. You have access to tools to get the current weather - use them when relevant.",
},
]
context = LLMContext(messages, tools=tools)
context = LLMContext(tools=tools)
# Create aggregators with summarization enabled
user_aggregator, assistant_aggregator = LLMContextAggregatorPair(
@@ -175,7 +171,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
async def on_client_connected(transport, client):
logger.info("Client connected")
# Kick off the conversation.
messages.append({"role": "system", "content": "Please introduce yourself to the user."})
context.add_message({"role": "system", "content": "Please introduce yourself to the user."})
await task.queue_frames([LLMRunFrame()])
@transport.event_handler("on_client_disconnected")