User Feedback
Collect and analyze user feedback on LLM responses. Evaluate output quality, identify trends, and optimize your AI application’s performance based on user satisfaction.
Who can use this feature: Anyone on any plan.
Introduction
User feedback is a feature that allows users to evaluate the responses generated by the LLM. This feedback can be either positive
or negative
, offering crucial insights into the effectiveness and relevance of the LLM’s outputs based on user’s satisfaction.
Why User Feedback
User feedback allows you to:
- Gauge the efficacy of the LLM’s responses.
- Optimize the user experience of your LLM app as you modify your prompts or models based on the received feedback.
- Identify trends in feedback to make informed decisions about model training or fine-tuning.
Quick Start
Option 1: Logging Feedback using Helicone’s Node Package
If you’re using Helicone’s Node package, here’s a simplified example to log feedback:
Option 2: Logging Feedback using Fetch
Without Helicone’s Node package, you can still log feedback using the Fetch API. For detailed documentation, refer to:
Fetch API for Feedback
Not using Helicone’s Node Package? We got you, too.
In some packages or scenarios, you may not be able to retrieve headers to get
the helicone-id
. However, you can still log feedback by supplying a UUID as
the helicone-id
.
Here’s a simple example:
import OpenAI from "openai";
// Initialize the OpenAI client with Helicone integration
const openai = new OpenAI({
apiKey: process.env.OPENAI_API_KEY,
baseURL: "https://oai.helicone.ai/v1",
defaultHeaders: {
"Helicone-Auth": `Bearer ${process.env.HELICONE_API_KEY}`,
},
});
// Generate a chat completion
const {
data: completions,
response,
}: { data: ChatCompletion, response: Response } = await openai.chat
.completions({
model: "gpt-3.5-turbo",
messages: [{ role: "user", content: "Say hi!" }],
})
.withResponse();
// Retrieve the heliconeId header
const heliconeId = response.headers.get("helicone-id");
// Log feedback
const options = {
method: "POST",
headers: {
"Helicone-Auth": "YOUR_HELICONE_AUTH_HEADER",
"Content-Type": "application/json",
},
body: JSON.stringify({
rating: true, // true for positive, false for negative
}),
};
const response = await fetch(
`https://api.helicone.ai/v1/request/${heliconeId}/feedback`,
options
);