API Client (TypeScript)

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

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

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

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

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