feat: Improve documentation for Conditional Tasks in crewAI

docs/how-to/Conditional-Tasks.md

@@ -1,87 +1,112 @@
 ---
 title: Conditional Tasks
-description: Learn how to use conditional tasks in a crewAI kickoff
+description: Learn how to use conditional tasks in a crewAI workflow
 ---
 
+# Conditional Tasks in crewAI
+
 ## Introduction
 
-Conditional Tasks in crewAI allow for dynamic workflow adaptation based on the outcomes of previous tasks. This powerful feature enables crews to make decisions and execute tasks selectively, enhancing the flexibility and efficiency of your AI-driven processes.
+Conditional Tasks in crewAI enable dynamic workflow adaptation based on the outcomes of previous tasks. This powerful feature allows crews to make decisions and execute tasks selectively, enhancing the flexibility and efficiency of your AI-driven processes.
+
+## Key Concepts
+
+1. **ConditionalTask**: A special type of task that executes only if a specified condition is met.
+2. **Condition Function**: A custom function that determines whether the conditional task should be executed.
+3. **Task Output**: The result of a previous task, which can be used to make decisions for conditional tasks.
+
+## How It Works
+
+1. Define a condition function that takes a `TaskOutput` as input and returns a boolean.
+2. Create a `ConditionalTask` with the condition function.
+3. Add the conditional task to your crew's workflow.
+4. The crew will evaluate the condition and execute the task only if the condition is met.
 
 ## Example Usage
 
+Here's a step-by-step example of how to implement conditional tasks in your crewAI workflow:
+
 ```python
 from typing import List
 from pydantic import BaseModel
-from crewai import Agent, Crew
+from crewai import Agent, Crew, Task
 from crewai.tasks.conditional_task import ConditionalTask
 from crewai.tasks.task_output import TaskOutput
-from crewai.task import Task
 from crewai_tools import SerperDevTool
 
-# Define a condition function for the conditional task
-# if false task will be skipped, true, then execute task
+# 1. Define the condition function
 def is_data_missing(output: TaskOutput) -> bool:
-    return len(output.pydantic.events) < 10  # this will skip this task
+    return len(output.pydantic.events) < 10
 
-# Define the agents
+# 2. Define the output model
+class EventOutput(BaseModel):
+    events: List[str]
+
+# 3. Create agents
 data_fetcher_agent = Agent(
     role="Data Fetcher",
     goal="Fetch data online using Serper tool",
-    backstory="Backstory 1",
+    backstory="Expert in retrieving online information",
     verbose=True,
     tools=[SerperDevTool()],
 )
 
 data_processor_agent = Agent(
     role="Data Processor",
-    goal="Process fetched data",
-    backstory="Backstory 2",
+    goal="Process and augment fetched data",
+    backstory="Specialist in data analysis and enrichment",
     verbose=True,
 )
 
 summary_generator_agent = Agent(
     role="Summary Generator",
-    goal="Generate summary from fetched data",
-    backstory="Backstory 3",
+    goal="Generate concise summaries from processed data",
+    backstory="Experienced in creating informative summaries",
     verbose=True,
 )
 
-class EventOutput(BaseModel):
-    events: List[str]
-
-task1 = Task(
+# 4. Define tasks
+initial_fetch_task = Task(
     description="Fetch data about events in San Francisco using Serper tool",
-    expected_output="List of 10 things to do in SF this week",
+    expected_output="List of events in SF this week",
     agent=data_fetcher_agent,
     output_pydantic=EventOutput,
 )
 
-conditional_task = ConditionalTask(
-    description="""
-        Check if data is missing. If we have less than 10 events,
-        fetch more events using Serper tool so that
-        we have a total of 10 events in SF this week..
-        """,
-    expected_output="List of 10 Things to do in SF this week",
+conditional_fetch_task = ConditionalTask(
+    description="Fetch additional events if the initial list is incomplete",
+    expected_output="Complete list of 10 events in SF this week",
     condition=is_data_missing,
     agent=data_processor_agent,
 )
 
-task3 = Task(
-    description="Generate summary of events in San Francisco from fetched data",
-    expected_output="summary_generated",
+summary_task = Task(
+    description="Generate a summary of events in San Francisco from the fetched data",
+    expected_output="Concise summary of SF events",
     agent=summary_generator_agent,
 )
 
-# Create a crew with the tasks
+# 5. Create and run the crew
 crew = Crew(
     agents=[data_fetcher_agent, data_processor_agent, summary_generator_agent],
-    tasks=[task1, conditional_task, task3],
+    tasks=[initial_fetch_task, conditional_fetch_task, summary_task],
     verbose=True,
     planning=True  # Enable planning feature
 )
 
-# Run the crew
 result = crew.kickoff()
-print("results", result)
-```
+print("Final Result:", result)
+```
+
+## Best Practices
+
+1. **Clear Conditions**: Ensure your condition functions are clear and specific.
+2. **Error Handling**: Implement proper error handling in your condition functions.
+3. **Task Dependencies**: Consider the dependencies between tasks when using conditional tasks.
+4. **Testing**: Thoroughly test your conditional workflows with various scenarios.
+
+## Conclusion
+
+Conditional Tasks in crewAI provide a powerful way to create dynamic and adaptive AI workflows. By leveraging this feature, you can build more intelligent and efficient systems that respond to changing conditions and data.
+
+For more advanced usage and additional features, refer to the crewAI documentation or reach out to the community for support.