Tutorials

These hands-on tutorials will guide you through building increasingly complex pipelines with Orchestrator. Each tutorial includes complete code, explanations, and exercises.

Tutorial Contents

• Web Research Automation
  • What You’ll Build
  • Prerequisites
  • Tutorial 1: Basic Web Search
  • Tutorial 2: Multi-Source Research
  • Tutorial 3: Fact-Checking Pipeline
  • Tutorial 4: Automated Report Generator
  • Advanced Exercises
  • Solutions
  • Next Steps
  • Tips for Production Use
• Data Processing Pipelines
  • What You’ll Build
  • Prerequisites
  • Tutorial 1: Basic ETL Pipeline
  • Tutorial 2: Multi-Source Data Integration
  • Tutorial 3: Data Quality Assessment Pipeline
  • Tutorial 4: Real-Time Data Processing
  • Advanced Examples
  • Exercises
  • Solutions and Next Steps
  • Best Practices for Production

Tutorial Overview

Our tutorials are organized by complexity and use case:

Beginner Tutorials

1. Pipeline Basics (tutorial_basics)

   • Your first pipeline

   • Understanding inputs and outputs

   • Using templates and references

   • Basic error handling

2. Web Research Automation (Web Research Automation)

   • Searching the web

   • Scraping content

   • Validating information

   • Generating reports

3. Data Processing Pipelines (Data Processing Pipelines)

   • Loading data from multiple sources

   • Transforming and cleaning data

   • Validation and quality checks

   • Exporting results

Intermediate Tutorials

4. Content Generation System (tutorial_content_generation)

   • AI-powered content creation

   • Multi-format output

   • Style adaptation

   • Quality control

5. Workflow Automation (tutorial_automation)

   • File monitoring

   • Scheduled execution

   • Event-driven pipelines

   • Notification systems

Advanced Tutorials

6. Advanced Techniques (tutorial_advanced)

   • Pipeline composition

   • Custom tool development

   • Performance optimization

   • Production deployment

What You’ll Learn

By completing these tutorials, you’ll master:

Core Concepts:

• Creating reusable, input-agnostic pipelines

• Using AUTO tags for intelligent decision-making

• Chaining tools for complex workflows

• Managing pipeline state and recovery

Practical Skills:

• Web scraping and research automation

• Data ETL (Extract, Transform, Load) pipelines

• AI-powered content generation

• System integration and automation

Advanced Techniques:

• Performance optimization strategies

• Custom tool development

• Error handling and recovery

• Production deployment patterns

Prerequisites

Before starting the tutorials:

1. Install Orchestrator - Follow the Installation guide

2. Basic Python Knowledge - Familiarity with Python syntax

3. YAML Understanding - Basic knowledge of YAML format

4. Command Line - Comfort with terminal/command prompt

Tutorial Format

Each tutorial follows a consistent structure:

1. Overview - What you’ll build and learn

2. Prerequisites - Required knowledge and setup

3. Step-by-Step Guide - Detailed implementation

4. Code Explanation - Understanding each component

5. Exercises - Practice activities

6. Solutions - Complete working examples

7. Next Steps - Where to go from here

Getting Help

If you get stuck:

• Check the Troubleshooting section in each tutorial

• Review the ../troubleshooting guide

• Search our GitHub Discussions

• Create a GitHub issue for specific problems

Ready to Start?

Begin with tutorial_basics to build your first pipeline, or jump to a specific tutorial that matches your use case.

Tip

Learning Path Recommendations:

• New to Orchestrator? Start with Basics → Web Research → Data Processing

• Experienced Developer? Jump to Content Generation or Automation

• Looking for specific use case? Check the tutorial that best matches your needs

Note

All tutorial code is available in the examples/tutorials/ directory of the Orchestrator repository.