| """ |
| Task definitions for the AI Interview Simulator. |
| |
| Three tasks with increasing difficulty: |
| Task 1 — junior_behavioral (EASY) |
| Task 2 — mid_technical (MEDIUM) |
| Task 3 — senior_system_design (HARD) |
| """ |
| from __future__ import annotations |
|
|
| from dataclasses import dataclass, field |
| from typing import List |
|
|
| from interview_env.models import DifficultyLevel, InterviewStage |
|
|
|
|
| @dataclass |
| class InterviewQuestion: |
| text: str |
| stage: InterviewStage |
| key_topics: List[str] |
| ideal_length: int = 150 |
| weight: float = 1.0 |
|
|
|
|
| @dataclass |
| class TaskDefinition: |
| task_id: str |
| name: str |
| difficulty: DifficultyLevel |
| job_title: str |
| company_context: str |
| questions: List[InterviewQuestion] |
| description: str |
|
|
| @property |
| def total_questions(self) -> int: |
| return len(self.questions) |
|
|
|
|
| |
| |
| |
| TASK_JUNIOR_BEHAVIORAL = TaskDefinition( |
| task_id = "junior_behavioral", |
| name = "Junior Software Engineer — Behavioral Interview", |
| difficulty = DifficultyLevel.EASY, |
| job_title = "Junior Software Engineer", |
| company_context = ( |
| "TechStart Inc. is a Series-A startup building developer tools. " |
| "The team is 20 engineers, culture is collaborative, and they value " |
| "learning, ownership, and clear communication." |
| ), |
| description = ( |
| "Entry-level behavioral interview with 4 questions. " |
| "Answers are evaluated on the STAR framework (Situation, Task, " |
| "Action, Result), relevance, and professionalism. " |
| "Good answers are 100–200 words with concrete examples." |
| ), |
| questions = [ |
| InterviewQuestion( |
| text = ( |
| "Tell me about yourself and why you're interested in " |
| "this Junior Software Engineer role at TechStart." |
| ), |
| stage = InterviewStage.INTRO, |
| key_topics = [ |
| "background", "education", "experience", "motivation", |
| "interest", "skills", "goal", "passionate", "learn", |
| ], |
| ideal_length = 120, |
| weight = 0.8, |
| ), |
| InterviewQuestion( |
| text = ( |
| "Describe a time when you had to debug a challenging problem. " |
| "What was the situation, what did you try, and what did you learn?" |
| ), |
| stage = InterviewStage.BEHAVIORAL, |
| key_topics = [ |
| "debug", "problem", "error", "solution", "fixed", "learned", |
| "log", "test", "stack trace", "isolate", "reproduce", |
| "situation", "result", "action", |
| ], |
| ideal_length = 180, |
| weight = 1.2, |
| ), |
| InterviewQuestion( |
| text = ( |
| "Tell me about a project you're proud of. " |
| "What did you build, what was your role, and what impact did it have?" |
| ), |
| stage = InterviewStage.BEHAVIORAL, |
| key_topics = [ |
| "project", "built", "developed", "designed", "team", |
| "role", "impact", "users", "result", "outcome", |
| "feature", "deployed", "shipped", |
| ], |
| ideal_length = 180, |
| weight = 1.0, |
| ), |
| InterviewQuestion( |
| text = ( |
| "How do you handle feedback on your code during a code review? " |
| "Give a specific example." |
| ), |
| stage = InterviewStage.BEHAVIORAL, |
| key_topics = [ |
| "feedback", "code review", "comment", "improve", "change", |
| "open", "learn", "collaborate", "understand", "appreciate", |
| "review", "PR", "pull request", |
| ], |
| ideal_length = 150, |
| weight = 1.0, |
| ), |
| ], |
| ) |
|
|
|
|
| |
| |
| |
| TASK_MID_TECHNICAL = TaskDefinition( |
| task_id = "mid_technical", |
| name = "Mid-Level Full-Stack Engineer — Technical Interview", |
| difficulty = DifficultyLevel.MEDIUM, |
| job_title = "Mid-Level Full-Stack Engineer", |
| company_context = ( |
| "FinFlow Ltd. builds B2B fintech SaaS used by 500+ companies. " |
| "Stack: React, Node.js, PostgreSQL, AWS. " |
| "The team ships weekly and values reliability, code quality, and velocity." |
| ), |
| description = ( |
| "5-question interview mixing technical knowledge and behavioral depth. " |
| "Technical questions expect accurate, specific answers with trade-offs. " |
| "Behavioral questions require the STAR method with measurable results. " |
| "Good answers are 150–250 words with concrete examples and numbers." |
| ), |
| questions = [ |
| InterviewQuestion( |
| text = ( |
| "Explain the difference between REST and GraphQL APIs. " |
| "When would you choose one over the other?" |
| ), |
| stage = InterviewStage.TECHNICAL, |
| key_topics = [ |
| "rest", "graphql", "endpoint", "query", "schema", |
| "over-fetching", "under-fetching", "flexibility", |
| "mutation", "http", "stateless", "client", "tradeoff", |
| ], |
| ideal_length = 200, |
| weight = 1.0, |
| ), |
| InterviewQuestion( |
| text = ( |
| "How does the JavaScript event loop work? " |
| "Explain the call stack, task queue, and microtask queue." |
| ), |
| stage = InterviewStage.TECHNICAL, |
| key_topics = [ |
| "event loop", "call stack", "task queue", "microtask", |
| "asynchronous", "promise", "setTimeout", "blocking", |
| "non-blocking", "single thread", "callback", "execution", |
| ], |
| ideal_length = 200, |
| weight = 1.2, |
| ), |
| InterviewQuestion( |
| text = ( |
| "Describe your approach to database query optimisation. " |
| "Walk me through how you'd diagnose and fix a slow SQL query." |
| ), |
| stage = InterviewStage.TECHNICAL, |
| key_topics = [ |
| "index", "explain", "query plan", "N+1", "join", |
| "slow query log", "cache", "pagination", "analyse", |
| "execution plan", "select", "table scan", "optimise", |
| ], |
| ideal_length = 220, |
| weight = 1.2, |
| ), |
| InterviewQuestion( |
| text = ( |
| "Tell me about a time you had to meet a tight deadline " |
| "without sacrificing quality. What trade-offs did you make?" |
| ), |
| stage = InterviewStage.BEHAVIORAL, |
| key_topics = [ |
| "deadline", "priority", "scope", "tradeoff", "quality", |
| "technical debt", "stakeholder", "communicate", "plan", |
| "shipped", "delivered", "result", |
| ], |
| ideal_length = 180, |
| weight = 1.0, |
| ), |
| InterviewQuestion( |
| text = ( |
| "How do you ensure your front-end React components remain " |
| "performant as the application scales?" |
| ), |
| stage = InterviewStage.TECHNICAL, |
| key_topics = [ |
| "memo", "useMemo", "useCallback", "virtualisation", |
| "lazy load", "code split", "re-render", "profiler", |
| "bundle size", "lighthouse", "key", "state", "performance", |
| ], |
| ideal_length = 200, |
| weight = 0.9, |
| ), |
| ], |
| ) |
|
|
|
|
| |
| |
| |
| TASK_SENIOR_SYSTEM_DESIGN = TaskDefinition( |
| task_id = "senior_system_design", |
| name = "Senior Software Engineer — System Design & Leadership", |
| difficulty = DifficultyLevel.HARD, |
| job_title = "Senior Software Engineer", |
| company_context = ( |
| "ScaleUp Corp is a Series-C e-commerce platform processing 50 million " |
| "orders per year. Stack: microservices, Kubernetes, Kafka, " |
| "PostgreSQL, Redis, AWS. " |
| "Engineers are expected to own systems end-to-end, mentor juniors, " |
| "and drive architectural decisions." |
| ), |
| description = ( |
| "6-question interview covering system design, distributed systems, " |
| "leadership, and conflict resolution. " |
| "System design answers must include scalability, fault tolerance, " |
| "and trade-offs. Leadership answers must show influence and impact. " |
| "Good answers are 200–350 words with specifics, numbers, and alternatives considered." |
| ), |
| questions = [ |
| InterviewQuestion( |
| text = ( |
| "Design a distributed rate limiter that can handle " |
| "100,000 requests per second across multiple servers. " |
| "Walk me through your architecture, storage choice, and failure modes." |
| ), |
| stage = InterviewStage.TECHNICAL, |
| key_topics = [ |
| "redis", "token bucket", "sliding window", "fixed window", |
| "distributed", "race condition", "atomic", "lua script", |
| "consistency", "availability", "latency", "failure", |
| "fallback", "partition", "replication", "cache", |
| ], |
| ideal_length = 300, |
| weight = 1.5, |
| ), |
| InterviewQuestion( |
| text = ( |
| "How would you design the order processing system for " |
| "an e-commerce platform that must guarantee no orders are lost, " |
| "even if services go down? Focus on event-driven design." |
| ), |
| stage = InterviewStage.TECHNICAL, |
| key_topics = [ |
| "kafka", "message queue", "idempotent", "outbox pattern", |
| "saga", "event sourcing", "retry", "dead letter queue", |
| "exactly once", "at least once", "transaction", "durability", |
| "consumer group", "offset", "ack", |
| ], |
| ideal_length = 300, |
| weight = 1.5, |
| ), |
| InterviewQuestion( |
| text = ( |
| "Tell me about the most technically complex system you've " |
| "designed or owned. What were the biggest risks, and how did you " |
| "mitigate them in production?" |
| ), |
| stage = InterviewStage.BEHAVIORAL, |
| key_topics = [ |
| "designed", "owned", "risk", "mitigation", "production", |
| "monitoring", "alert", "rollback", "canary", "feature flag", |
| "incident", "postmortem", "scale", "bottleneck", |
| ], |
| ideal_length = 280, |
| weight = 1.3, |
| ), |
| InterviewQuestion( |
| text = ( |
| "Describe a situation where you disagreed with your tech lead " |
| "or manager on a technical decision. How did you handle it, " |
| "and what was the outcome?" |
| ), |
| stage = InterviewStage.SITUATIONAL, |
| key_topics = [ |
| "disagree", "decision", "data", "evidence", "compromise", |
| "respected", "escalate", "influence", "RFC", "proposal", |
| "outcome", "learned", "relationship", "align", |
| ], |
| ideal_length = 220, |
| weight = 1.1, |
| ), |
| InterviewQuestion( |
| text = ( |
| "How do you approach mentoring junior engineers? " |
| "Give a concrete example of how you helped someone grow significantly." |
| ), |
| stage = InterviewStage.BEHAVIORAL, |
| key_topics = [ |
| "mentor", "junior", "growth", "feedback", "pair programming", |
| "review", "goal", "1:1", "autonomy", "confidence", |
| "promoted", "improved", "impact", "coaching", |
| ], |
| ideal_length = 220, |
| weight = 1.0, |
| ), |
| InterviewQuestion( |
| text = ( |
| "ScaleUp's checkout latency has increased by 300ms over the last " |
| "month after a Kubernetes cluster upgrade. Walk me through exactly " |
| "how you would diagnose and resolve this in production." |
| ), |
| stage = InterviewStage.TECHNICAL, |
| key_topics = [ |
| "apm", "tracing", "jaeger", "datadog", "prometheus", |
| "metrics", "latency", "p99", "kubernetes", "resource limit", |
| "cpu", "memory", "network", "service mesh", "ingress", |
| "rollback", "profiling", "flamegraph", "baseline", |
| ], |
| ideal_length = 300, |
| weight = 1.5, |
| ), |
| ], |
| ) |
|
|
|
|
| |
| |
| |
| TASK_REGISTRY: dict[str, TaskDefinition] = { |
| TASK_JUNIOR_BEHAVIORAL.task_id: TASK_JUNIOR_BEHAVIORAL, |
| TASK_MID_TECHNICAL.task_id: TASK_MID_TECHNICAL, |
| TASK_SENIOR_SYSTEM_DESIGN.task_id: TASK_SENIOR_SYSTEM_DESIGN, |
| } |
|
|
|
|
| def get_task(task_id: str) -> TaskDefinition: |
| if task_id not in TASK_REGISTRY: |
| raise ValueError( |
| f"Unknown task_id '{task_id}'. " |
| f"Available: {list(TASK_REGISTRY.keys())}" |
| ) |
| return TASK_REGISTRY[task_id] |
|
|
