AI-Powered Interviews

Automated Technical Interviews

AI-powered interview generation and evaluation

Interview Generation

from sjm import SJM

client = SJM(api_key="your_api_key")

# Generate interview questions
interview = client.interview(
  freelancer_id="f123",
  project_description="Build a modern React Native app with TypeScript",
  required_skills=["React Native", "TypeScript", "Mobile Development"],
  job_title="Senior Mobile Developer",
  mode="ai_questions"
)

# Get the session ID for later use
session_id = interview["data"]["session_id"]

# Access questions
questions = interview["data"]["interview_data"]["questions"]
for i, q in enumerate(questions, 1):
  print(f"Q{i}: {q['text']}")
  print(f"Scoring Criteria: {q['scoring_criteria']}")

Response Evaluation

# Collect candidate answers
answers = [
  "I have 5 years of experience with React Native...",
  "For TypeScript integration, I typically start with strict mode...",
  "My approach to state management in mobile apps involves..."
]

# Evaluate responses
evaluation = client.interview(
  freelancer_id="f123",
  project_description="Build a modern React Native app with TypeScript",
  required_skills=["React Native", "TypeScript", "Mobile Development"],
  job_title="Senior Mobile Developer",
  mode="ai_full",
  session_id=session_id,
  provided_answers=answers
)

# Access evaluation results
eval_data = evaluation["data"]["evaluation"]
print(f"Technical Score: {eval_data['scores'][0]}")
print(f"Overall: {eval_data['overall_score']}/100")
print(f"Recommendation: {'Hire' if eval_data['hiring_recommendation'] else 'Do Not Hire'}")

Interview Modes

SJM provides four interview modes for different use cases:

# AI generates both questions and evaluates answers
interview = client.interview(
  freelancer_id="f123",
  project_description="Build a modern web application",
  required_skills=["React.js", "Node.js", "TypeScript"],
  job_title="Full Stack Developer",
  mode="ai_full"
)

Integration Example

import { SJM } from 'sjm';
import * as readline from 'readline';

// Initialize client
const client = new SJM({ apiKey: "your_api_key" });

// Create readline interface for user input
const rl = readline.createInterface({
input: process.stdin,
output: process.stdout
});

// Promisify question method
function question(query) {
return new Promise(resolve => rl.question(query, resolve));
}

async function conductInterview() {
try {
  // 1. Generate interview questions
  console.log("Generating interview questions...");
  const interview = await client.interview({
    freelancer_id: "f123",
    project_description: "Build a modern web application with React",
    required_skills: ["React.js", "Node.js", "TypeScript"],
    job_title: "Full Stack Developer",
    mode: "ai_questions"
  });

  // 2. Get session ID and questions
  const sessionId = interview.data.session_id;
  const questions = interview.data.interview_data.questions;
  console.log(`\nGenerated ${questions.length} interview questions:\n`);

  // 3. Collect answers from candidate
  const answers = [];
  for (let i = 0; i < questions.length; i++) {
    console.log(`Q${i+1}: ${questions[i].text}`);
    const answer = await question("Answer: ");
    answers.push(answer);
  }

  // 4. Submit answers for evaluation
  console.log("\nEvaluating responses...");
  const evaluation = await client.interview({
    freelancer_id: "f123",
    project_description: "Build a modern web application with React",
    required_skills: ["React.js", "Node.js", "TypeScript"],
    job_title: "Full Stack Developer",
    mode: "ai_full",
    session_id: sessionId,
    provided_answers: answers
  });

  // 5. Process evaluation results
  const evalData = evaluation.data.evaluation;
  console.log("\nEvaluation Results:");
  console.log(`Overall Score: ${evalData.overall_score}/100`);
  
  console.log("\nStrengths:");
  for (const strength of evalData.strengths) {
    console.log(`- ${strength}`);
  }
  
  console.log("\nAreas for Improvement:");
  for (const area of evalData.areas_for_improvement) {
    console.log(`- ${area}`);
  }
  
  console.log(`\nRecommendation: ${evalData.hiring_recommendation ? 'Hire' : 'Do Not Hire'}`);
  console.log(`Reason: ${evalData.recommendation_reason}`);
  
  rl.close();
} catch (error) {
  console.error(`Error: ${error.message}`);
  rl.close();
}
}

conductInterview();