LangChain Voice Agents: Complete Tutorial

LangChain is the most popular framework for building AI applications. This tutorial shows you how to add voice capabilities to your LangChain agents.

Why Add Voice to LangChain?

• Convert agent outputs to natural speech
• Build accessible AI applications
• Create podcast and audio content generators
• Enable hands-free interaction

Prerequisites

pip install langchain langchain-openai langvoice-sdk

Basic Integration

from langchain_openai import ChatOpenAI
from langchain.agents import AgentExecutor, create_openai_tools_agent
from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
from langvoice_sdk.tools.langchain_tools import LangVoiceLangChainToolkit

# Initialize LangVoice toolkit
toolkit = LangVoiceLangChainToolkit(api_key="your-langvoice-key")
tools = toolkit.get_tools()

# Create prompt
prompt = ChatPromptTemplate.from_messages([
    ("system", "You are a helpful assistant that can speak. Use the LangVoice tool to generate audio."),
    ("human", "{input}"),
    MessagesPlaceholder(variable_name="agent_scratchpad"),
])

# Create agent
llm = ChatOpenAI(model="gpt-4o")
agent = create_openai_tools_agent(llm, tools, prompt)
executor = AgentExecutor(agent=agent, tools=tools)

# Run it!
result = executor.invoke({
    "input": "Say 'Hello from LangChain!' in a friendly voice"
})

Available LangVoice Tools

Tool	Description
langvoice_tts	Generate speech from text
langvoice_voices	List available voices
langvoice_languages	Get supported languages

Advanced: Multi-Voice Conversations

# Create a podcast-style conversation
script = """
Generate a 2-minute podcast intro with:
- Host (use 'heart' voice): Welcome message
- Co-host (use 'michael' voice): Topic introduction
"""

result = executor.invoke({"input": script})

Best Practices

1. Keep spoken text concise
2. Choose appropriate voices for context
3. Handle errors gracefully
4. Cache frequent generations

Start building voice-enabled LangChain agents with LangVoice today!