Documentation Index
Fetch the complete documentation index at: https://docs.swarms.world/llms.txt
Use this file to discover all available pages before exploring further.
This example runs a turn-based debate between two agents, where each agent’s response is narrated in real time using a distinct voice. Voice differentiation makes it easy to follow who is speaking. You can also drive the opening prompt by speaking into a microphone, using the package’s STT helper.
Step 1: Install dependencies
pip install -U swarms voice-agents
export OPENAI_API_KEY=sk-...
Step 2: Set up two TTS callbacks with different voices
Each speaker gets its own callback so the audio is clearly attributable.
from voice_agents import StreamingTTSCallback
# Deeper voice for Socrates, softer voice for Simone de Beauvoir
tts_callback1 = StreamingTTSCallback(voice="onyx", model="openai/tts-1")
tts_callback2 = StreamingTTSCallback(voice="nova", model="openai/tts-1")
Step 3: Define the debate driver
The driver alternates speakers, runs each turn with the appropriate TTS callback, flushes the buffer, and feeds the prior response as the next agent’s input.
from swarms import Agent
from swarms.structs.conversation import Conversation
from swarms.utils.history_output_formatter import history_output_formatter
from voice_agents import speech_to_text, record_audio, StreamingTTSCallback
def debate_with_speech(
agents: list,
max_loops: int = 1,
task: str = None,
output_type: str = "str-all-except-first",
use_stt_for_input: bool = False,
):
if len(agents) != 2:
raise ValueError("There must be exactly two agents in the dialogue.")
conversation = Conversation()
agent1, agent2 = agents
tts_callback1 = StreamingTTSCallback(voice="onyx", model="openai/tts-1")
tts_callback2 = StreamingTTSCallback(voice="nova", model="openai/tts-1")
# Optional: capture the opening prompt by voice
if use_stt_for_input and task is None:
print("Please speak your question or topic for the debate...")
audio = record_audio(duration=10.0)
task = speech_to_text(audio_data=audio, sample_rate=16000)
print(f"Transcribed: {task}\n")
message = task
speaker, other = agent1, agent2
current_callback, other_callback = tts_callback1, tts_callback2
for i in range(max_loops):
print(f"\n--- Turn {i+1}: {speaker.agent_name} speaking ---\n")
response = speaker.run(task=message, streaming_callback=current_callback)
current_callback.flush()
conversation.add(speaker.agent_name, response)
message = response
# swap roles + callbacks
speaker, other = other, speaker
current_callback, other_callback = other_callback, current_callback
tts_callback1.flush()
tts_callback2.flush()
return history_output_formatter(conversation=conversation, type=output_type)
Step 4: Define the two debaters
Use distinct system prompts so the agents argue in character. Keeping the responses short produces a more natural-sounding back-and-forth.
socratic_prompt = """
You are Socrates, the Greek philosopher. Respond only with short and simple
questions or comments. Always question Simone de Beauvoir's answers. Never
agree, only point out problems or ask for clarification. Keep replies brief.
"""
existentialist_prompt = """
You are Simone de Beauvoir, an existentialist philosopher. Reply in short,
simple sentences. Always disagree with Socrates, question his reasoning, and
point out problems simply. Never agree. Keep your answers brief.
"""
agent1 = Agent(
agent_name="Socrates",
system_prompt=socratic_prompt,
max_loops=1,
model_name="gpt-4.1",
dynamic_temperature_enabled=True,
output_type="str-all-except-first",
streaming_on=True,
)
agent2 = Agent(
agent_name="Simone de Beauvoir",
system_prompt=existentialist_prompt,
max_loops=1,
model_name="gpt-4.1",
dynamic_temperature_enabled=True,
output_type="str-all-except-first",
streaming_on=True,
)
Step 5: Run the debate
result = debate_with_speech(
agents=[agent1, agent2],
max_loops=10,
task="What is the meaning of life?",
output_type="str-all-except-first",
use_stt_for_input=False, # set True to dictate the opening prompt
)
print(result)
See also
