Sessions

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Introduction

Sessions in Helicone provide a powerful way to organize and analyze complex interactions within your LLM applications. By grouping related requests together, sessions offer a holistic view of user journeys, multi-step processes, or extended AI workflows. This feature is particularly valuable for applications that involve multiple back-and-forth exchanges or those that build upon previous context.

Example: A Session creating an outline for a book about space

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Why Sessions

Sessions, identified by a helicone-session-id header, allow you to:

• Reconstruct the flow of a conversation or a multi-stage task
• Analyze performance and outcomes across entire interaction sequences
• Identify bottlenecks or areas for improvement in your AI workflows
• Gain deeper insights into user behavior and application patterns

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Quick Start

Simply add a Helicone-Session-Id header to your request to start tracking your sessions and traces.

To represent parent and child traces we take advantange of a simple path syntax in the Helicone-Session-Path header. For example, if you have a parent trace parent and a child trace child, you can represent this as /parent/child.

Depending on your library you will need to add the following two headers to your request:

• Helicone-Session-Id - The session id you want to track
• Helicone-Session-Path - The path of the session

Here is an example is ts: see other languages

const openai = new OpenAI({
  apiKey: process.env.OPENAI_API_KEY,
  baseURL: "https://oai.helicone.ai/v1",
  defaultHeaders: {
    "Helicone-Auth": `Bearer ${process.env.HELICONE_API_KEY}`,
  },
});

const session = randomUUID();

openai.chat.completions.create(
  {
    messages: [
      {
        role: "user",
        content: "Generate an abstract for a course on space.",
      },
    ],
    model: "gpt-4",
  },
  {
    headers: {
      "Helicone-Session-Id": session,
      "Helicone-Session-Path": "/abstract",
    },
  }
);