Examples¶

This section contains practical examples demonstrating various features and patterns in LLMling-Agent.

Agent Patterns¶

Agent collaboration for documentation generation - demonstrates how multiple agents can work together to create structured documentation.

Adaptation of CrewAI-like workflow patterns - shows how to implement familiar workflow patterns from other frameworks.

PyTest-style example patterns - demonstrates testing patterns and function-based agent definitions.

Round-robin message passing between agents - shows how to implement circular communication patterns.

Using pick() for expert selection - demonstrates dynamic agent selection based on expertise.

Sequential vs parallel downloads comparison - compares different approaches to handling multiple download tasks.

Using agents as tools for downloads - shows how to use one agent as a tool for another.

MCP server integration with git tools - demonstrates how to integrate MCP servers via YAML configuration.

MCP server with sampling tools - shows advanced MCP features including sampling and elicitation.

Structured response type examples - demonstrates how to define and use typed response models.

AI-Human interaction patterns - shows how to implement human-in-the-loop workflows.

Comparing different models using parallel teams - demonstrates how to run the same task across multiple models simultaneously.

Each example includes:

You can find the full source code for these examples in the GitHub repository.