Update reasoning interval example with comprehensive documentation

Co-Authored-By: Joe Moura <joao@crewai.com>

examples/reasoning_interval_example.py

@@ -1,56 +1,91 @@
 """
-Example demonstrating the new reasoning interval and adaptive reasoning features.
+Example demonstrating the new reasoning interval and adaptive reasoning features in CrewAI.
 
 This example shows how to:
-1. Use reasoning_interval to make an agent reason every X steps
+1. Create an agent with a fixed reasoning interval (reason every X steps)
-2. Use adaptive_reasoning to let the agent decide when to reason
+2. Create an agent with adaptive reasoning (agent decides when to reason)
+3. Configure and run tasks with these reasoning capabilities
 """
 
 from crewai import Agent, Task, Crew
-from crewai.tools import WebBrowserTool
+from crewai.tools import SerperDevTool, WebBrowserTool
 
+search_tool = SerperDevTool()
 browser_tool = WebBrowserTool()
 
-interval_agent = Agent(
+interval_reasoning_agent = Agent(
     role="Research Analyst",
-    goal="Find and analyze information about a specific topic",
+    goal="Find comprehensive information about a topic",
-    backstory="You are a skilled researcher who methodically analyzes information.",
+    backstory="""You are a skilled research analyst who methodically 
+    approaches information gathering with periodic reflection.""",
     verbose=True,
+    allow_delegation=False,
     reasoning=True,
     reasoning_interval=3,
-    tools=[browser_tool]
+    tools=[search_tool, browser_tool]
 )
 
-adaptive_agent = Agent(
+adaptive_reasoning_agent = Agent(
-    role="Research Analyst",
+    role="Strategic Advisor",
-    goal="Find and analyze information about a specific topic",
+    goal="Provide strategic advice based on market research",
-    backstory="You are a skilled researcher who methodically analyzes information.",
+    backstory="""You are an experienced strategic advisor who adapts your 
+    approach based on the information you discover.""",
     verbose=True,
+    allow_delegation=False,
     reasoning=True,
     adaptive_reasoning=True,
-    tools=[browser_tool]
+    tools=[search_tool, browser_tool]
 )
 
-research_task = Task(
+interval_task = Task(
-    description="""
+    description="""Research the latest developments in renewable energy 
-    Research the latest developments in renewable energy technology.
+    technologies. Focus on solar, wind, and hydroelectric power. 
+    Identify key innovations, market trends, and future prospects.""",
+    expected_output="""A comprehensive report on the latest developments 
+    in renewable energy technologies, including innovations, market trends, 
+    and future prospects.""",
+    agent=interval_reasoning_agent
+)
 
-    1. Find information about recent breakthroughs in solar energy
+adaptive_task = Task(
-    2. Research advancements in wind power technology
+    description="""Analyze the competitive landscape of the electric vehicle 
-    3. Analyze trends in energy storage solutions
+    market. Identify key players, their market share, recent innovations, 
-    4. Compare the cost-effectiveness of different renewable energy sources
+    and strategic moves. Provide recommendations for a new entrant.""",
-    5. Summarize your findings in a comprehensive report
+    expected_output="""A strategic analysis of the electric vehicle market 
-    """,
+    with recommendations for new entrants.""",
-    expected_output="A comprehensive report on the latest developments in renewable energy technology",
+    agent=adaptive_reasoning_agent
-    agent=interval_agent  # Use the interval_agent for this example
 )
 
 crew = Crew(
-    agents=[interval_agent],
+    agents=[interval_reasoning_agent, adaptive_reasoning_agent],
-    tasks=[research_task],
+    tasks=[interval_task, adaptive_task],
-    verbose=2
+    verbose=2  # Set to 2 to see reasoning events in the output
 )
 
-result = crew.kickoff()
+results = crew.kickoff()
-print("\nResult:")
+
-print(result)
+print("\n==== RESULTS ====\n")
+for i, result in enumerate(results):
+    print(f"Task {i+1} Result:")
+    print(result)
+    print("\n")
+
+"""
+How the reasoning features work:
+
+1. Interval-based reasoning (reasoning_interval=3):
+   - The agent will reason after every 3 steps of task execution
+   - This creates a predictable pattern of reflection during task execution
+   - Useful for complex tasks where periodic reassessment is beneficial
+
+2. Adaptive reasoning (adaptive_reasoning=True):
+   - The agent decides when to reason based on execution context
+   - Reasoning is triggered when:
+     a) Multiple different tools are used recently (indicating a change in approach)
+     b) The task is taking longer than expected (iterations > max_iter/2)
+     c) Recent errors or failures are detected in the execution
+   - This creates a more dynamic reasoning pattern adapted to the task's needs
+
+Both approaches enhance the agent's ability to handle complex tasks by allowing
+mid-execution planning and strategy adjustments.
+"""