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

@@ -64,16 +64,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
params=AnthropicLLMService.InputParams(
thinking=AnthropicLLMService.ThinkingConfig(type="enabled", budget_tokens=2048)
),
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.",
)
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()),
@@ -104,15 +98,10 @@ 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": "user",
"content": "Say hello briefly.",
}
)
context.add_message({"role": "user", "content": "Say hello briefly."})
# Here are some example prompts conducive to demonstrating
# thinking (picked from Google and Anthropic docs).
# messages.append(
# context.add_message(
# {
# "role": "user",
# "content": "Analogize photosynthesis and growing up. Keep your answer concise.",