agents

Agent Examples

This directory contains examples of implementing agent patterns with Mellea, specifically the ReACT (Reasoning and Acting) pattern.

Files

react.py

A complete implementation of the ReACT agent pattern that combines reasoning and action in an iterative loop. The agent:

• Thinks about what to do next
• Selects an appropriate tool/action
• Generates arguments for the tool
• Observes the result
• Determines if the goal is achieved

Key Features:

• Custom ReactTool and ReactToolbox classes for tool management
• Dynamic tool selection using Pydantic schemas
• Iterative thought-action-observation loop
• Example with weather lookup tools

Usage:

python docs/examples/agents/react.py

react_instruct.py

An alternative implementation of the ReACT pattern using Mellea's instruct-validate-repair paradigm.

Concepts Demonstrated

• Tool Management: Creating and organizing tools for agent use
• Dynamic Prompting: Building system prompts with tool descriptions
• Chat Context: Using ChatContext for multi-turn conversations
• Structured Output: Using Pydantic models for type-safe responses
• Iterative Reasoning: Implementing thought-action-observation loops

Related Documentation

• See docs/dev/tool_calling.md for more on tool integration
• See mellea/stdlib/requirements/tool_reqs.py for tool requirements