API Client (TypeScript)

import { RespanClient } from "@respan/respan-api";
const client = new RespanClient({
    authorization: "Bearer YOUR_API_KEY",
});

// Create a span
const span = await client.spans.create({
    model: "gpt-4o",
    input: '[{"role": "user", "content": "Hello"}]',
    output: '{"role": "assistant", "content": "Hi!"}',
    logType: "chat",
});
// List spans
const spans = await client.spans.list({
    operator: "AND",
    filters: { model: { operator: "", value: ["gpt-4o"] } },
});

// List prompts
const prompts = await client.prompts.list();
// Create a prompt
const prompt = await client.prompts.create({
    name: "customer-support",
    description: "Support chatbot prompt",
});
// Create a version
const version = await client.prompts.createPromptVersion("prompt_abc123", {
    messages: [{ role: "system", content: "You are a helpful {{role}}." }],
    model: "gpt-4o",
});
// Deploy a version
await client.prompts.deployPromptVersion("prompt_abc123", { version: 3 });

// Create an evaluator
const evaluator = await client.evaluators.create({
    name: "Response Quality",
    type: "llm",
    scoreValueType: "numerical",
    llmConfig: {
        model: "gpt-4o-mini",
        evaluatorDefinition: "Rate the quality: {{input}} {{output}}",
    },
});
// Run an evaluator
await client.evaluators.run("eval_abc123", {
    datasetId: "ds_abc123",
});

// Create a score on a span
await client.scores.createSpanScore("log_abc123", {
    evaluatorSlug: "quality",
    numericalValue: 4.5,
});