Let's start by creating a simple prompt in Phoenix using the TypeScript client:
import { createClient } from "@arizeai/phoenix-client";
import { createPrompt, promptVersion } from "@arizeai/phoenix-client/prompts";
// Create a Phoenix client
// (optional, the createPrompt function will create one if not provided)
const client = createClient({
options: {
baseUrl: "http://localhost:6006", // Change to your Phoenix server URL
// If your Phoenix instance requires authentication:
// headers: {
// Authorization: "bearer YOUR_API_KEY",
// }
}
});
// Define a simple summarization prompt
const summarizationPrompt = await createPrompt({
client,
name: "article-summarizer",
description: "Summarizes an article into concise bullet points",
version: promptVersion({
description: "Initial version",
templateFormat: "MUSTACHE",
modelProvider: "OPENAI", // Could also be ANTHROPIC, GEMINI, etc.
modelName: "gpt-3.5-turbo",
template: [
{
role: "system",
content: "You are an expert summarizer. Create clear, concise bullet points highlighting the key information."
},
{
role: "user",
content: "Please summarize the following {{topic}} article:\n\n{{article}}"
}
],
})
});
console.dir(summarizationPrompt);
Getting a Prompt
You can retrieve prompts by name, ID, version, or tag:
import { getPrompt } from "@arizeai/phoenix-client/prompts";
// Get by name (latest version)
const latestPrompt = await getPrompt({
prompt: {
name: "article-summarizer",
}
});
// Get by specific version ID
const specificVersionPrompt = await getPrompt({
prompt: {
versionId: "abcd1234",
},
});
// Get by tag (e.g., "production", "staging", "development")
const productionPrompt = await getPrompt({
prompt: {
name: "article-summarizer",
tag: "production",
}
});
Using a Prompt with SDKs
Phoenix makes it easy to use your prompts with various SDKs, no proprietary SDK necessary! Here's how to use a prompt with OpenAI:
import { getPrompt, toSDK } from "@arizeai/phoenix-client/prompts";
import OpenAI from "openai";
// Initialize your OpenAI client
const openai = new OpenAI({
apiKey: process.env.OPENAI_API_KEY,
});
// Get your prompt
const prompt = await getPrompt({
prompt: {
name: "article-summarizer",
},
});
// Make sure the prompt was properly fetched
if (!prompt) {
throw new Error("Prompt not found");
}
// Transform the prompt to OpenAI format with variable values
const openaiParameters = toSDK({
sdk: "openai",
prompt,
variables: {
topic: "technology",
article:
"Artificial intelligence has seen rapid advancement in recent years. Large language models like GPT-4 can now generate human-like text, code, and even create images from descriptions. This technology is being integrated into many industries, from healthcare to finance, transforming how businesses operate and people work.",
},
});
// Make sure the prompt was successfully converted to parameters
if (!openaiParameters) {
throw new Error("OpenAI parameters not found");
}
// Use the transformed parameters with OpenAI
const response = await openai.chat.completions.create({
...openaiParameters,
// You can override any parameters here
model: "gpt-4o-mini", // Override the model if needed
stream: false,
});
console.log("Summary:", response.choices[0].message.content);
Next Steps
Check out the How to: Prompts section for details on how to test prompt changes
The Phoenix client natively supports passing your prompts to OpenAI, Anthropic, and the.
Take a look a the TypeScript examples in the Phoenix client ()
Try out some Deno notebooks to experiment with prompts ()
