PersonaBuilder

1import { PersonaBuilder } from '@jamesaphoenix/persona-sdk';
2
3// Basic fluent API
4const persona = PersonaBuilder.create()
5  .withName('Emma Rodriguez')
6  .withAge(29)
7  .withOccupation('Data Scientist')
8  .withSex('female')
9  .withAttribute('education', 'PhD in Statistics')
10  .withAttribute('programmingLanguages', ['Python', 'R', 'SQL'])
11  .withAttribute('yearsExperience', 5)
12  .build();
13
14console.log(persona.toObject());

1import { PersonaBuilder, NormalDistribution, CategoricalDistribution } from '@jamesaphoenix/persona-sdk';
2
3// Using distributions for dynamic values
4const persona = PersonaBuilder.create()
5  .withName('Random Employee')
6  .withAge(new NormalDistribution(35, 7)) // Mean 35, StdDev 7
7  .withOccupation(new CategoricalDistribution([
8    { value: 'Engineer', probability: 0.4 },
9    { value: 'Designer', probability: 0.3 },
10    { value: 'Manager', probability: 0.3 }
11  ]))
12  .withSex('other')
13  .withAttribute('salary', new NormalDistribution(85000, 15000))
14  .build();
15
16// Each build() call generates different values
17const persona1 = builder.build(); // age: 32, occupation: 'Engineer'
18const persona2 = builder.build(); // age: 41, occupation: 'Designer'

1// Build multiple personas at once
2const personas = PersonaBuilder.create()
3  .withAge(new NormalDistribution(30, 5))
4  .withOccupation(new CategoricalDistribution([
5    { value: 'Developer', probability: 0.6 },
6    { value: 'QA Engineer', probability: 0.4 }
7  ]))
8  .withSex('other')
9  .buildMany(10, 'Employee'); // Creates Employee 1, Employee 2, etc.
10
11console.log(`Generated ${personas.length} personas`);
12personas.forEach(p => console.log(`${p.name}: ${p.age} year old ${p.occupation}`));

1// Generate from text prompt
2const persona = await PersonaBuilder.fromPrompt(
3  'Create a 28-year-old freelance graphic designer who loves travel and coffee',
4  { apiKey: process.env.OPENAI_API_KEY }
5);
6
7console.log(persona.toObject());
8// Result might include:
9// {
10//   name: 'Maya Patel',
11//   age: 28,
12//   occupation: 'Freelance Graphic Designer',
13//   interests: ['travel', 'coffee', 'design'],
14//   personality: 'creative, adventurous, detail-oriented'
15// }
16
17// Generate multiple diverse personas
18const personas = await PersonaBuilder.generateMultiple(
19  'Tech startup employees in their 20s-30s',
20  5,
21  { apiKey: process.env.OPENAI_API_KEY }
22);

1// Generate with correlations
2const persona = PersonaBuilder.create()
3  .withName('Realistic Professional')
4  .buildWithCorrelations({
5    attributes: {
6      age: new NormalDistribution(35, 8),
7      income: new NormalDistribution(75000, 25000),
8      yearsExperience: new NormalDistribution(10, 5)
9    },
10    correlations: [
11      { attribute1: 'age', attribute2: 'income', correlation: 0.6 },
12      { attribute1: 'age', attribute2: 'yearsExperience', correlation: 0.8 }
13    ],
14    conditionals: [{
15      attribute: 'yearsExperience',
16      dependsOn: 'age',
17      transform: (exp, age) => Math.min(exp, Math.max(0, age - 22))
18    }]
19  });
20
21// Results in realistic combinations:
22// 45-year-old with 20 years experience and $95k income
23// 25-year-old with 3 years experience and $55k income