Examples

This section contains working examples of Gola agents with practical configurations that demonstrate key patterns and capabilities.

Available Examples

Minimal Agent

The simplest possible Gola configuration - just an agent name and LLM provider. Perfect for getting started and understanding the basics.

Features: Basic conversation, OpenAI integration
Use cases: Learning, prototyping, simple chatbots

MCP Tools Agent

Demonstrates external tool integration using Model Context Protocol (MCP) servers. Includes filesystem, git, and time tools.

Features: File operations, git commands, time utilities
Use cases: Development assistance, file management, git automation

Sherpa Agent

Advanced finite state machine pattern for complex multi-step workflows. Demonstrates travel planning with external API integration.

Features: State persistence, error recovery, external APIs, workflow orchestration
Use cases: Travel planning, e-commerce checkout, approval workflows

Example Philosophy

All examples follow these principles:

Production-Ready

Every example uses proven configurations:

• Configurations work reliably across different environments
• Examples follow best practices and conventions
• Patterns are suitable for real-world use cases

Progressive Complexity

Examples are ordered from simple to advanced:

1. Minimal - Pure LLM interaction
2. MCP Tools - External tool integration
3. Sherpa Agent - Complex state machine workflows

Copy-Paste Ready

All configurations are:

• Complete and self-contained
• Include setup instructions
• Provide troubleshooting guidance
• Show expected outputs

Real-World Focus

Examples demonstrate:

• Production-ready patterns
• Error handling approaches
• Performance considerations
• Security best practices

Getting Started

1. Choose an example that matches your use case
2. Follow the setup instructions for prerequisites
3. Copy the configuration and customize for your needs
4. Run and test to verify everything works
5. Extend and adapt for your specific requirements

Next Steps

• Start with Minimal Agent to understand basics
• Add tools with MCP Tools for enhanced capabilities
• Build complex workflows with Sherpa Agent patterns

Each example builds on the previous ones, creating a learning path from simple conversational agents to sophisticated workflow orchestration systems.