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examples(foundational): use system_instruction in all examples

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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
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16
examples/foundational/14d-function-calling-moondream-video.py
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@@ -124,7 +124,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady
)
llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"))
llm = OpenAILLMService(
api_key=os.getenv("OPENAI_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 are able to describe images from the user camera.",
)
llm.register_function("fetch_user_image", fetch_user_image)
@llm.event_handler("on_function_calls_started")
@@ -148,14 +151,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
)
tools = ToolsSchema(standard_tools=[fetch_image_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 are able to describe images from the user camera.",
},
]
context = LLMContext(messages, tools)
context = LLMContext(tools=tools)
user_aggregator, assistant_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()),
@@ -200,7 +196,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
client_id = get_transport_client_id(transport, client)
# Kick off the conversation.
messages.append(
context.add_message(
{
"role": "system",
"content": f"Please introduce yourself to the user. Use '{client_id}' as the user ID during function calls.",