Basic Speech Agent

The simplest voice-agent pattern: let the agent finish thinking, then hand the final text to stream_tts_openai for narration. This is ideal when you only care about the final answer, not intermediate tokens.

Step 1: Install dependencies

pip install -U swarms voice-agents
export OPENAI_API_KEY=sk-...

Step 2: Build the agent

Use any LiteLLM-compatible model. Here we use a quantitative trading agent.

from swarms import Agent

agent = Agent(
    agent_name="Quantitative-Trading-Agent",
    agent_description="Advanced quantitative trading and algorithmic analysis agent",
    model_name="gpt-4.1",
    dynamic_temperature_enabled=True,
    max_loops=1,
    dynamic_context_window=True,
    top_p=None,
)

Step 3: Run the agent

The agent runs to completion and returns the full response as a string.

out = agent.run(
    task="What are the top five best energy stocks across nuclear, solar, gas, and other energy sources?",
)

Step 4: Stream the result through TTS

stream_tts_openai accepts a list of strings and streams them through OpenAI’s TTS engine. With stream_mode=True, audio chunks play as they’re synthesised.

from voice_agents.main import stream_tts_openai

stream_tts_openai(
    [out],
    stream_mode=True,
)

Full example

from swarms import Agent
from voice_agents.main import stream_tts_openai

agent = Agent(
    agent_name="Quantitative-Trading-Agent",
    agent_description="Advanced quantitative trading and algorithmic analysis agent",
    model_name="gpt-4.1",
    dynamic_temperature_enabled=True,
    max_loops=1,
    dynamic_context_window=True,
    top_p=None,
)

out = agent.run(
    task="What are the top five best energy stocks across nuclear, solar, gas, and other energy sources?",
)

stream_tts_openai(
    [out],
    stream_mode=True,
)

Source: examples/guides/voice_agents/voice_agents_examples/agent_speech.py

When to use this pattern

You only need to narrate the final answer.
Latency to first audio is not critical (you wait for the agent to finish before any speech).
Simplicity wins — no callback wiring, no flush() calls.

For sentence-by-sentence narration as the agent generates, see Streaming Voice Agent.

Index

Basic Examples

Model Providers

Single Agent

Multi-Agent Examples

Auto Agent Builder

Applications

Research

Technical Analysis

Use Cases

Finance

Voice Agents

Integrations

Deployment

CLI

Basic Speech Agent

Step 1: Install dependencies

Step 2: Build the agent

Step 3: Run the agent

Step 4: Stream the result through TTS

Full example

When to use this pattern

​Step 1: Install dependencies

​Step 2: Build the agent

​Step 3: Run the agent

​Step 4: Stream the result through TTS

​Full example

​When to use this pattern

Step 1: Install dependencies

Step 2: Build the agent

Step 3: Run the agent

Step 4: Stream the result through TTS

Full example

When to use this pattern