Generate API

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Installation

npm install @helicone/generate

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Usage

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Simple usage with just a prompt ID

import { generate } from "@helicone/generate";

// model, temperature, messages inferred from id
const response = await generate("prompt-id");

console.log(response);

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With variables

const response = await generate({
  promptId: "prompt-id",
  inputs: {
    location: "Portugal",
    time: "2:43",
  },
});

console.log(response);

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With Helicone properties

const response = await generate({
  promptId: "prompt-id",
  userId: "ajwt2kcoe",
  sessionId: "21",
  cache: true,
});

console.log(response);

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In a chat

const promptId = "homework-helper";
const chat = [];

// User
chat.push("can you help me with my homework?");

// Assistant
chat.push(await generate({ promptId, chat }));
console.log(chat[chat.length - 1]);

// User
chat.push("thanks, the first question is what is 2+2?");

// Assistant
chat.push(await generate({ promptId, chat }));
console.log(chat[chat.length - 1]);

​

Supported Providers and Required Environment Variables

Always required: HELICONE_API_KEY

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API Reference

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generate(input)

Generates a response using a Helicone prompt.

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Parameters

• input (string | object): Either a prompt ID string or a parameters object:
  • promptId (string): The ID of the prompt to use, created in the Prompt Editor
  • version (number | “production”, optional): The version of the prompt to use. Defaults to “production”
  • inputs (object, optional): Variable inputs to use in the prompt, if any
  • chat (string[], optional): Chat history for chat-based prompts
  • userId (string, optional): User ID for tracking in Helicone
  • sessionId (string, optional): Session ID for tracking in Helicone Sessions
  • cache (boolean, optional): Whether to use Helicone’s LLM Caching

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Returns

• Promise<object>: The raw response from the LLM provider