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docs/core-concepts/Tasks.md

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+---
+title: crewAI Tasks
+description: Overview and management of tasks within the crewAI framework.
+---
+
+## Overview of a Task
+!!! note "What is a Task?"
+    In the CrewAI framework, tasks are individual assignments that agents complete. They encapsulate necessary information for execution, including a description, assigned agent, and required tools, offering flexibility for various action complexities.
+
+Tasks in CrewAI can be designed to require collaboration between agents. For example, one agent might gather data while another analyzes it. This collaborative approach can be defined within the task properties and managed by the Crew's process.
+
+## Task Attributes
+
+| Attribute      | Description                          |
+| :---------- | :----------------------------------- |
+| **Description**       | A clear, concise statement of what the task entails.  |
+| **Agent**    | Optionally, you can specify which agent is responsible for the task. If not, the crew's process will determine who takes it on. |
+| **Expected Output** *(optional)*      | Clear and detailed definition of expected output for the task.  |
+| **Tools** *(optional)*   | These are the functions or capabilities the agent can utilize to perform the task. They can be anything from simple actions like 'search' to more complex interactions with other agents or APIs. |
+| **Context**  *(optional)*     | Other tasks that will have their output used as context for this task. |
+| **Callback**  *(optional)*  | A function to be executed after the task is completed. |
+
+## Creating a Task
+
+This is the simpliest example for creating a task, it involves defining its scope and agent, but there are optional attributes that can provide a lot of flexibility:
+
+```python
+from crewai import Task
+
+task = Task(
+	description='Find and summarize the latest and most relevant news on AI',
+	agent=sales_agent
+)
+```
+!!! note "Task Assignment"
+	Tasks can be assigned directly by specifying an `agent` to them, or they can be assigned in run time if you are using the `hierarchical` through CrewAI's process, considering roles, availability, or other criteria.
+
+
+## Integrating Tools with Tasks
+
+Tools from the [crewAI Toolkit](https://github.com/joaomdmoura/crewai-tools) and [LangChain Tools](https://python.langchain.com/docs/integrations/tools) enhance task performance, allowing agents to interact more effectively with their environment. Assigning specific tools to tasks can tailor agent capabilities to particular needs.
+
+## Creating a Task with Tools
+
+```python
+import os
+os.environ["OPENAI_API_KEY"] = "Your Key"
+
+from crewai import Agent, Task, Crew
+from langchain.agents import Tool
+from langchain_community.tools import DuckDuckGoSearchRun
+
+research_agent = Agent(
+	role='Researcher',
+	goal='Find and summarize the latest AI news',
+	backstory="""You're a researcher at a large company.
+	You're responsible for analyzing data and providing insights
+	to the business."""
+	verbose=True
+)
+
+# Install duckduckgo-search for this example:
+# !pip install -U duckduckgo-search
+search_tool = DuckDuckGoSearchRun()
+
+task = Task(
+  description='Find and summarize the latest AI news',
+	expected_output='A bullet list summary of the top 5 most important AI news',
+	agent=research_agent,
+  tools=[search_tool]
+)
+
+crew = Crew(
+	agents=[research_agent],
+	tasks=[task],
+	verbose=2
+)
+
+result = crew.kickoff()
+print(result)
+```
+
+This demonstrates how tasks with specific tools can override an agent's default set for tailored task execution.
+
+## Refering other Tasks
+
+In crewAI the output of one task is automatically relayed into the next one, but you can specifically define what tasks output should be used as context for another task.
+
+This is useful when you have a task that depends on the output of another task that is not performed immediately after it. This is done through the `context` attribute of the task:
+
+```python
+# ...
+
+research_task = Task(
+  description='Find and summarize the latest AI news',
+	expected_output='A bullet list summary of the top 5 most important AI news',
+	agent=research_agent,
+  tools=[search_tool]
+)
+
+write_blog_task = Task(
+  description="Write a full blog post about the importante of AI and it's latest news",
+	expected_output='Full blog post that is 4 paragraphs long',
+	agent=writer_agent,
+  context=[research_task]
+)
+
+#...
+```
+
+## Callback Mechanism
+
+You can define a callback function that will be executed after the task is completed. This is useful for tasks that need to trigger some side effect after they are completed, while the crew is still running.
+
+```python
+# ...
+
+def callback_function(output: TaskOutput):
+	# Do something after the task is completed
+	# Example: Send an email to the manager
+	print(f"""
+		Task completed!
+		Task: {output.description}
+		Output: {output.result}
+	""")
+
+research_task = Task(
+  description='Find and summarize the latest AI news',
+	expected_output='A bullet list summary of the top 5 most important AI news',
+	agent=research_agent,
+  tools=[search_tool],
+	callback=callback_function
+)
+
+#...
+```
+
+## Tool Override Mechanism
+
+Specifying tools in a task allows for dynamic adaptation of agent capabilities, emphasizing CrewAI's flexibility.
+
+## Conclusion
+
+Tasks are the driving force behind the actions of agents in crewAI. By properly defining tasks and their outcomes, you set the stage for your AI agents to work effectively, either independently or as a collaborative unit.
+Equipping tasks with appropriate tools is crucial for maximizing CrewAI's potential, ensuring agents are effectively prepared for their assignments.