Vapi Integration

Vapi natively integrates with Langfuse, allowing you to send traces directly to Langfuse for enhanced telemetry monitoring. This integration enables you to gain deeper insights into your voice AI applications and improve their performance and reliability.

Vapi integration

What is Vapi?

Vapi is a Voice AI platform for developers. It enables you to build, test, and deploy voice AI agents in minutes by abstracting away the complexities of:

  • Simulating Natural Human Conversation: Handling turn-taking, interruption, backchanneling, and more.
  • Realtime/Low Latency Demands: Ensuring responsive conversations with low latency (< 500-800ms voice-to-voice).
  • Function Calling: Taking actions during conversations and interfacing with your services for custom actions.
  • Extracting Conversation Data: Reviewing conversation audio, transcripts, and metadata.

What is Langfuse?

Langfuse is an open source LLM engineering platform designed to provide better observability and evaluations into AI applications. It helps developers track, analyze, and visualize traces from AI interactions, enabling better performance tuning, debugging, and optimization of AI agents.

Get Started

Get your Langfuse Credentials

First, you’ll need your Langfuse credentials:

  • Secret Key
  • Public Key
  • Host URL

You can obtain these by signing up for Langfuse Cloud or self-hosting Langfuse.

Add Langfuse Credentials

Log in to your Vapi dashboard and navigate to the Provider Credentials page.

Under the Observability Providers section, you’ll find an option for Langfuse. Enter your Langfuse credentials:

  • Secret Key
  • Public Key
  • Host URL (US data region: https://us.cloud.langfuse.com, EU data region: https://cloud.langfuse.com)

Click Save to update your credentials.

Vapi Provider Credentials

See Traces in Langfuse

Once you’ve added your credentials, you should start seeing traces in your Langfuse dashboard for every conversation your agents have.

Example trace of Vapi conversation in Langfuse

Example trace in Langfuse: https://cloud.langfuse.com/project/cloramnkj0002jz088vzn1ja4/traces/50163c14-9784-4cb9-b18e-23e924d0bb66

Evaluate and Debug your Agent

To make the most out of this integration, you can now use Langfuse’s evaluation and debugging tools to analyze and improve the performance of your voice AI agents.

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