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ReAct Loop

The ReAct Loop block implements the Reasoning and Acting pattern, enabling agents to think step-by-step about problems, use tools to gather information, and adjust their approach based on observations.

Overview

ReAct (Reason and Act) combines reasoning and acting in language models to create more reliable and interpretable AI workflows. The agent alternates between thinking about the problem and taking actions to gather information or make progress.

Think: The agent analyzes the current situation and plans its next action

Act: The agent executes a specific action using available tools or functions

Observe: The agent processes the results and decides whether to continue or conclude

How It Works

graph LR
    A[User Query] --> B[Think]
    B --> C[Act]
    C --> D[Observe]
    D --> E{Goal Achieved?}
    E -->|No| B
    E -->|Yes| F[Final Answer]

Configuration

Reasoning Model

The AI model used for the thinking step. Choose models optimized for reasoning like GPT-4, Claude Sonnet, or Gemini Pro.

Action Tools

Available tools the agent can use during the Act phase. Include search engines, APIs, databases, or custom functions.

Max Iterations

Maximum number of think-act-observe cycles to prevent infinite loops. Recommended range: 5-15 iterations.

Stop Conditions

Criteria that trigger the loop to conclude, such as finding a definitive answer or reaching confidence thresholds.

Use Cases

  • Research Tasks: Systematically gathering and analyzing information from multiple sources
  • Problem Solving: Breaking down complex problems into manageable steps
  • Troubleshooting: Diagnosing issues through iterative testing and analysis

Example Workflow

[User Question] → [ReAct Loop] → [Research Agent] → [Response]

The user asks "What are the latest developments in quantum computing?" The ReAct Loop:

  1. Think: Need to search for recent quantum computing news and developments
  2. Act: Use web search tool to find recent articles and papers
  3. Observe: Found several breakthroughs from the past 6 months
  4. Think: Need more specific information about IBM and Google's latest chips
  5. Act: Search specifically for IBM Condor and Google Willow processors
  6. Observe: Gathered comprehensive information about recent developments
  7. Conclude: Synthesize findings into comprehensive answer

Best Practice: Set appropriate max iterations based on task complexity. Simple fact-finding might need 3-5 iterations, while complex research could require 10-15.

When to Use This vs Other Blocks

BlockWhen to Use
ReAct LoopComplex multi-step problems requiring iterative reasoning
AgentSimple question-answering or single-step tasks
RouterRouting decisions based on content classification