Disciplines · Training

Oshun AI Integration Exercises

Foundation skills for working with AI providers:

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Hands-on exercises for mastering the Oshun AI provider integrations. These exercises are designed to build skills progressively from beginner to advanced.

Exercise Structure#

Beginner Level (01-beginner-*.ts)#

Foundation skills for working with AI providers:

Exercise Topics
1. Initialization Provider setup, configuration
2. Basic TTS Synthesis, voice settings, voice listing
3. Basic Images Workflow execution, job management
4. Model Discovery Search, filtering, model details
5. Error Handling Safe operations, error classification, retry
6. Monitoring Statistics, health checks, reporting

Time estimate: 2-3 hours

Intermediate Level (02-intermediate-*.ts)#

Production patterns and resilience:

Exercise Topics
1. Streaming Real-time audio, buffering
2. Batch Processing Parallel execution, rate limiting, cancellation
3. Error Handling Exponential backoff, circuit breaker, fallback
4. Resource Management Connection pooling, cleanup
5. Monitoring Metrics collection, health monitoring
6. Caching LRU cache, memoization

Time estimate: 4-6 hours

Advanced Level (03-advanced-*.ts)#

Production-grade systems:

Exercise Topics
1. Orchestration Smart routing, workflow DAGs
2. Fault Tolerance Bulkhead pattern, adaptive retry
3. Observability Distributed tracing, dashboards
4. Optimization Deduplication, predictive prefetching
5. Security Audit logging, quota management
6. Integration Complete AI pipeline

Time estimate: 8-12 hours

Getting Started#

Prerequisites#

  1. Complete the code examples review
  2. Set up environment variables:
    bash
    export ELEVENLABS_API_KEY=your_key
export RUNCOMFY_API_KEY=your_key
export CIVITAI_API_KEY=your_key

Running Exercises#

bash
# Run beginner exercise tests
npx ts-node docs/training/exercises/01-beginner-exercises.ts

# Run intermediate exercise tests
npx ts-node docs/training/exercises/02-intermediate-exercises.ts

# Run advanced exercise tests
npx ts-node docs/training/exercises/03-advanced-exercises.ts

Exercise Format#

Each exercise file contains:

  1. Exercise function stubs - Functions you need to implement
  2. Requirements - What the implementation must do
  3. Tests - Automated tests to verify your solution
  4. Solutions - Reference implementations (in separate files)

Example:

typescript
/**
 * Exercise 1.1: Description
 *
 * Requirements:
 * - Requirement 1
 * - Requirement 2
 * - Requirement 3
 *
 * @param param1 - Description
 * @returns Description
 */
export function exercise_1_1_name(param1: Type): ReturnType {
  // YOUR CODE HERE
  throw new Error('Not implemented');
}

Week 1: Foundations#

  1. Day 1-2: Complete beginner exercises 1-3
  2. Day 3-4: Complete beginner exercises 4-6
  3. Day 5: Review solutions, practice variations

Week 2: Production Patterns#

  1. Day 1-2: Complete intermediate exercises 1-2
  2. Day 3-4: Complete intermediate exercises 3-4
  3. Day 5: Complete intermediate exercises 5-6

Week 3: Advanced Concepts#

  1. Day 1-2: Complete advanced exercises 1-2
  2. Day 3-4: Complete advanced exercises 3-4
  3. Day 5: Complete advanced exercises 5-6

Tips for Success#

Before Starting#

  • Read the exercise description completely
  • Understand all requirements before coding
  • Review related examples if needed

While Implementing#

  • Start with the simplest case
  • Add complexity incrementally
  • Test frequently with small inputs
  • Use console.log for debugging

When Stuck#

  • Re-read the requirements carefully
  • Check the examples for similar patterns
  • Review the solution file for hints
  • Take a break and return fresh

After Completing#

  • Compare with the reference solution
  • Note alternative approaches
  • Consider edge cases you might have missed
  • Refactor for clarity if needed

Self-Assessment#

After completing all exercises, you should be able to:

Beginner Level#

  • Initialize any provider with proper configuration
  • Synthesize speech with custom voice settings
  • Execute image generation workflows
  • Search and filter models
  • Handle errors gracefully
  • Monitor provider health

Intermediate Level#

  • Implement streaming audio synthesis
  • Process batches with concurrency control
  • Implement retry with exponential backoff
  • Build a circuit breaker
  • Create a connection pool
  • Implement an LRU cache

Advanced Level#

  • Build a multi-provider router
  • Orchestrate complex workflows
  • Implement distributed tracing
  • Optimize with deduplication
  • Create audit logging
  • Build a complete AI pipeline

Exercise Solutions#

Solutions are provided in separate files:

  • 01-beginner-solutions.ts
  • 02-intermediate-solutions.ts
  • 03-advanced-solutions.ts (partial - advanced exercises are open-ended)

Important: Try to complete exercises before checking solutions. The learning comes from the struggle, not just seeing the answer.

Additional Challenges#

After completing all exercises, try these challenges:

Challenge 1: Multi-Modal Pipeline#

Build a pipeline that takes a text story, generates images for key scenes, and creates an audio narration.

Challenge 2: Cost Optimizer#

Create a system that automatically selects providers based on a cost budget, balancing quality with expense.

Challenge 3: A/B Testing Framework#

Build a framework for A/B testing different models/providers and tracking quality metrics.

Challenge 4: Webhook Integration#

Implement webhook handlers for long-running jobs, including retry logic and state management.

Challenge 5: Rate Limit Coordinator#

Build a coordinator that manages rate limits across multiple concurrent processes.

Contributing#

To add new exercises:

  1. Follow the existing format and naming convention
  2. Include clear requirements and documentation
  3. Provide comprehensive tests
  4. Include reference solutions
  5. Update this README