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Zhongwei Li
440
templates/structured-output.ts
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440
templates/structured-output.ts
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/**
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* OpenAI Structured Outputs - JSON Schema Examples
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*
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* This template demonstrates:
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* - JSON schema with strict mode
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* - Complex nested schemas
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* - Type-safe responses
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* - Validation patterns
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* - Common use cases (extraction, classification, formatting)
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*/
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import OpenAI from 'openai';
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const openai = new OpenAI({
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apiKey: process.env.OPENAI_API_KEY,
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});
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// =============================================================================
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// BASIC STRUCTURED OUTPUT
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// =============================================================================
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async function basicStructuredOutput() {
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const completion = await openai.chat.completions.create({
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model: 'gpt-4o', // Best for structured outputs
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messages: [
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{ role: 'user', content: 'Generate a person profile' }
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],
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response_format: {
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type: 'json_schema',
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json_schema: {
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name: 'person_profile',
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strict: true,
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schema: {
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type: 'object',
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properties: {
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name: { type: 'string' },
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age: { type: 'number' },
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email: { type: 'string' },
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},
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required: ['name', 'age', 'email'],
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additionalProperties: false,
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},
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},
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},
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});
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const person = JSON.parse(completion.choices[0].message.content!);
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console.log('Person:', person);
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return person;
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}
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// =============================================================================
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// COMPLEX NESTED SCHEMA
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// =============================================================================
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async function complexSchema() {
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const completion = await openai.chat.completions.create({
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model: 'gpt-4o',
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messages: [
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{ role: 'user', content: 'Generate a company organizational structure' }
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],
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response_format: {
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type: 'json_schema',
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json_schema: {
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name: 'org_structure',
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strict: true,
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schema: {
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type: 'object',
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properties: {
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company: { type: 'string' },
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founded: { type: 'number' },
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departments: {
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type: 'array',
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items: {
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type: 'object',
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properties: {
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name: { type: 'string' },
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head: { type: 'string' },
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employees: {
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type: 'array',
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items: {
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type: 'object',
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properties: {
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name: { type: 'string' },
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role: { type: 'string' },
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years: { type: 'number' },
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},
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required: ['name', 'role', 'years'],
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additionalProperties: false,
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},
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},
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},
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required: ['name', 'head', 'employees'],
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additionalProperties: false,
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},
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},
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},
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required: ['company', 'founded', 'departments'],
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additionalProperties: false,
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},
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},
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},
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});
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const org = JSON.parse(completion.choices[0].message.content!);
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console.log('Organization:', JSON.stringify(org, null, 2));
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return org;
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}
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// =============================================================================
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// DATA EXTRACTION
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// =============================================================================
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async function extractData() {
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const text = `
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John Doe is a 35-year-old software engineer living in San Francisco.
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He works at TechCorp and has been there for 5 years.
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His email is john.doe@example.com and his phone is (555) 123-4567.
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`;
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const completion = await openai.chat.completions.create({
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model: 'gpt-4o',
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messages: [
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{
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role: 'system',
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content: 'Extract structured information from the provided text.',
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},
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{
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role: 'user',
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content: text,
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},
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],
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response_format: {
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type: 'json_schema',
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json_schema: {
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name: 'extracted_info',
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strict: true,
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schema: {
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type: 'object',
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properties: {
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name: { type: 'string' },
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age: { type: 'number' },
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occupation: { type: 'string' },
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location: { type: 'string' },
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company: { type: 'string' },
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tenure_years: { type: 'number' },
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contact: {
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type: 'object',
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properties: {
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email: { type: 'string' },
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phone: { type: 'string' },
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},
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required: ['email', 'phone'],
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additionalProperties: false,
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},
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},
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required: ['name', 'age', 'occupation', 'location', 'company', 'tenure_years', 'contact'],
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additionalProperties: false,
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},
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},
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},
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});
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const extracted = JSON.parse(completion.choices[0].message.content!);
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console.log('Extracted:', JSON.stringify(extracted, null, 2));
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return extracted;
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}
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// =============================================================================
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// CLASSIFICATION
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// =============================================================================
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async function classifyText() {
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const text = 'This product is absolutely terrible. It broke after one day of use. Very disappointed!';
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const completion = await openai.chat.completions.create({
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model: 'gpt-4o',
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messages: [
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{
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role: 'system',
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content: 'Classify the sentiment and extract key information from product reviews.',
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},
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{
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role: 'user',
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content: text,
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},
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],
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response_format: {
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type: 'json_schema',
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json_schema: {
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name: 'review_classification',
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strict: true,
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schema: {
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type: 'object',
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properties: {
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sentiment: {
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type: 'string',
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enum: ['positive', 'negative', 'neutral'],
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},
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confidence: { type: 'number' },
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category: {
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type: 'string',
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enum: ['product_quality', 'customer_service', 'shipping', 'pricing', 'other'],
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},
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issues: {
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type: 'array',
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items: { type: 'string' },
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},
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rating_estimate: { type: 'number' },
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},
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required: ['sentiment', 'confidence', 'category', 'issues', 'rating_estimate'],
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additionalProperties: false,
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},
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},
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},
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});
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const classification = JSON.parse(completion.choices[0].message.content!);
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console.log('Classification:', JSON.stringify(classification, null, 2));
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return classification;
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}
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// =============================================================================
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// SIMPLE JSON MODE (Without Strict Schema)
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// =============================================================================
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async function simpleJsonMode() {
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const completion = await openai.chat.completions.create({
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model: 'gpt-5',
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messages: [
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{ role: 'user', content: 'List 3 programming languages and their use cases as JSON' }
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],
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response_format: { type: 'json_object' },
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});
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const data = JSON.parse(completion.choices[0].message.content!);
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console.log('JSON output:', data);
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return data;
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}
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// =============================================================================
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// ENUM VALUES
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// =============================================================================
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async function withEnums() {
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const completion = await openai.chat.completions.create({
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model: 'gpt-4o',
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messages: [
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{ role: 'user', content: 'Categorize this as a bug report: The app crashes on startup' }
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],
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response_format: {
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type: 'json_schema',
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json_schema: {
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name: 'issue_categorization',
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strict: true,
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schema: {
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type: 'object',
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properties: {
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type: {
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type: 'string',
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enum: ['bug', 'feature_request', 'question', 'documentation'],
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},
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severity: {
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type: 'string',
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enum: ['critical', 'high', 'medium', 'low'],
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},
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component: {
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type: 'string',
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enum: ['frontend', 'backend', 'database', 'infrastructure', 'unknown'],
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},
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},
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required: ['type', 'severity', 'component'],
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additionalProperties: false,
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},
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},
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},
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});
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const categorization = JSON.parse(completion.choices[0].message.content!);
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console.log('Categorization:', categorization);
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return categorization;
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}
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// =============================================================================
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// VALIDATION EXAMPLE
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// =============================================================================
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function validateSchema<T>(data: any, expectedFields: string[]): T {
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for (const field of expectedFields) {
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if (!(field in data)) {
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throw new Error(`Missing required field: ${field}`);
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}
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}
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return data as T;
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}
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async function withValidation() {
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const completion = await openai.chat.completions.create({
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model: 'gpt-4o',
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messages: [
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{ role: 'user', content: 'Generate a user profile with name and email' }
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],
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response_format: {
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type: 'json_schema',
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json_schema: {
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name: 'user_profile',
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strict: true,
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schema: {
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type: 'object',
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properties: {
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name: { type: 'string' },
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email: { type: 'string' },
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},
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required: ['name', 'email'],
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additionalProperties: false,
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},
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},
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},
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});
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const raw = JSON.parse(completion.choices[0].message.content!);
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// Validate before using
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interface UserProfile {
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name: string;
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email: string;
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}
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const validated = validateSchema<UserProfile>(raw, ['name', 'email']);
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console.log('Validated user:', validated);
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return validated;
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}
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// =============================================================================
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// BATCH EXTRACTION
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// =============================================================================
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async function batchExtraction(texts: string[]) {
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const results = [];
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for (const text of texts) {
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const completion = await openai.chat.completions.create({
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model: 'gpt-4o',
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messages: [
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{ role: 'system', content: 'Extract key information as structured data' },
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{ role: 'user', content: text },
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],
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response_format: {
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type: 'json_schema',
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json_schema: {
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name: 'extracted_data',
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strict: true,
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schema: {
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type: 'object',
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properties: {
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summary: { type: 'string' },
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key_points: {
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type: 'array',
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items: { type: 'string' },
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},
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},
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required: ['summary', 'key_points'],
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additionalProperties: false,
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},
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},
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},
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});
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const extracted = JSON.parse(completion.choices[0].message.content!);
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results.push({ text, extracted });
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// Rate limit protection
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await new Promise(resolve => setTimeout(resolve, 1000));
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}
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console.log(`Extracted ${results.length} items`);
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return results;
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}
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// =============================================================================
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// MAIN EXECUTION
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// =============================================================================
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async function main() {
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console.log('=== OpenAI Structured Outputs Examples ===\n');
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// Example 1: Basic
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console.log('1. Basic Structured Output:');
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await basicStructuredOutput();
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console.log();
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// Example 2: Complex schema
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console.log('2. Complex Nested Schema:');
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await complexSchema();
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console.log();
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// Example 3: Data extraction
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console.log('3. Data Extraction:');
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await extractData();
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console.log();
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// Example 4: Classification
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console.log('4. Text Classification:');
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await classifyText();
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console.log();
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// Example 5: Simple JSON mode
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console.log('5. Simple JSON Mode:');
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await simpleJsonMode();
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console.log();
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// Example 6: Enums
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console.log('6. Enum Values:');
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await withEnums();
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console.log();
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}
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// Run if executed directly
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if (require.main === module) {
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main().catch(console.error);
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}
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export {
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basicStructuredOutput,
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complexSchema,
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extractData,
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classifyText,
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simpleJsonMode,
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withEnums,
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withValidation,
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batchExtraction,
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};
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