Multi-step Reasoning (ReAct)

Complex reasoning agent using ReAct framework for multi-step information synthesis.

Table of contents

  1. Overview
    1. What is Multi-step Reasoning?
    2. Why Use Multi-step Reasoning?
    3. When to Use
  2. ReAct Framework
    1. Think-Act-Observe Loop
    2. Available Actions
  3. Example Execution
  4. Usage Guide
  5. Configuration
  6. Best Practices
  7. Related Resources

Overview

What is Multi-step Reasoning?

Multi-step reasoning mode uses the ReAct (Reasoning + Acting) framework to break down complex questions into multiple steps, iteratively searching and synthesizing information.

Key Concept: Unlike simple Q&A that answers in one step, multi-step reasoning:

  • Decomposes complex questions into sub-problems
  • Iteratively searches for information
  • Synthesizes information from multiple sources
  • Reasons about the relationships between pieces of information

Why Use Multi-step Reasoning?

When Simple RAG Fails:

  • ❌ Question requires information from multiple documents
  • ❌ Need to compare or synthesize different sources
  • ❌ Question has implicit sub-questions
  • ❌ Requires iterative refinement of understanding

Benefits of Multi-step Reasoning:

  • ✅ Comprehensive Answers: Can gather information from multiple sources
  • ✅ Complex Queries: Handles questions that can’t be answered in one step
  • ✅ Transparency: Shows reasoning process (Thought-Action-Observation)
  • ✅ Adaptive: Can refine search strategy based on intermediate results

When to Use

✅ Complex information synthesis
✅ Multi-document comparison
✅ Step-by-step reasoning required
✅ Exploratory research

ReAct Framework

Think-Act-Observe Loop 

graph LR
    A[Question] --> B[Thought]
    B --> C[Action]
    C --> D[Observation]
    D --> E{Done?}
    E -->|No| B
    E -->|Yes| F[Answer]

Available Actions

  • SEARCH(query): Retrieve relevant documents
  • FINISH(answer): Output final answer and stop

Example Execution

Question: “Compare Python and Java for web development”

Reasoning Trace:

Thought 1: I need to find information about Python for web development
Action 1: SEARCH["Python web development"]
Observation 1: Found 3 documents about Django, Flask...

Thought 2: Now I need Java web development info
Action 2: SEARCH["Java web development"]
Observation 2: Found 3 documents about Spring, Jakarta EE...

Thought 3: I have enough information to compare
Action 3: FINISH["Python excels in rapid development with frameworks 
like Django and Flask, offering simplicity and extensive libraries. 
Java provides enterprise-grade solutions with Spring and Jakarta EE, 
offering strong typing and better performance at scale..."]

Usage Guide

  1. Navigate to “🤖 RAG Retrieval Enhancement” tab
  2. Enable “Enable Context Engineering” ✅
  3. Enable “Enable Multi-step Reasoning” ✅
  4. Enter complex question
  5. Click “🚀 Execute Query”

Configuration 

REACT_CONFIG = {
    "max_iterations": 5,        # Max reasoning steps
    "top_k_per_search": 3,      # Documents per SEARCH
    "max_context_length": 2000, # Total context limit
    "temperature": 0.0          # Deterministic reasoning
}

Best Practices

  • ✅ Use for complex, multi-part questions
  • ✅ Monitor reasoning trace for debugging
  • ✅ Limit max iterations to prevent loops
  • ❌ Don’t use for simple factual questions