ReAct Patterns

ReAct (Reasoning + Acting) combines reasoning with tool execution for interactive problem solving.

Overview

ReAct enables agents to reason about problems while interacting with tools and the environment.

Usage

See DSPy Strategies for implementing ReAct patterns with DSPy.

from recoagent.reasoning import DSPyReasoningEngine, DSPyStrategy

engine = DSPyReasoningEngine()

result = engine.reason(
    query="Find and analyze information",
    strategy=DSPyStrategy.REACT,
    context={"available_tools": ["web_search", "calculator"]}
)

Benefits

• Interactive Reasoning: Combine thinking with action
• Tool Integration: Use tools during reasoning
• Better Results: Leverage external information

Best Practices

1. Provide Tool Context: Make tools available to the reasoner
2. Monitor Tool Usage: Track which tools are being used
3. Validate Results: Verify tool outputs