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127 lines
4.6 KiB
Plaintext
127 lines
4.6 KiB
Plaintext
---
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title: Sequential Processes
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description: A comprehensive guide to utilizing the sequential processes for task execution in CrewAI projects.
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icon: forward
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---
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## Introduction
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CrewAI offers a flexible framework for executing tasks in a structured manner, supporting both sequential and hierarchical processes.
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This guide outlines how to effectively implement these processes to ensure efficient task execution and project completion.
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## Sequential Process Overview
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The sequential process ensures tasks are executed one after the other, following a linear progression.
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This approach is ideal for projects requiring tasks to be completed in a specific order.
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### Key Features
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- **Linear Task Flow**: Ensures orderly progression by handling tasks in a predetermined sequence.
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- **Simplicity**: Best suited for projects with clear, step-by-step tasks.
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- **Easy Monitoring**: Facilitates easy tracking of task completion and project progress.
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## Implementing the Sequential Process
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To use the sequential process, assemble your crew and define tasks in the order they need to be executed.
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```python Code
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from crewai import Crew, Process, Agent, Task, TaskOutput, CrewOutput
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# Define your agents
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researcher = Agent(
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role='Researcher',
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goal='Conduct foundational research',
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backstory='An experienced researcher with a passion for uncovering insights'
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)
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analyst = Agent(
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role='Data Analyst',
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goal='Analyze research findings',
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backstory='A meticulous analyst with a knack for uncovering patterns'
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)
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writer = Agent(
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role='Writer',
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goal='Draft the final report',
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backstory='A skilled writer with a talent for crafting compelling narratives'
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)
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# Define your tasks
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research_task = Task(
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description='Gather relevant data...',
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agent=researcher,
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expected_output='Raw Data'
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)
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analysis_task = Task(
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description='Analyze the data...',
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agent=analyst,
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expected_output='Data Insights'
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)
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writing_task = Task(
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description='Compose the report...',
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agent=writer,
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expected_output='Final Report'
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)
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# Form the crew with a sequential process
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report_crew = Crew(
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agents=[researcher, analyst, writer],
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tasks=[research_task, analysis_task, writing_task],
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process=Process.sequential
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)
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# Execute the crew
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result = report_crew.kickoff()
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# Accessing the type-safe output
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task_output: TaskOutput = result.tasks[0].output
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crew_output: CrewOutput = result.output
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```
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### Note:
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Each task in a sequential process **must** have an agent assigned. Ensure that every `Task` includes an `agent` parameter.
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### Workflow in Action
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1. **Initial Task**: In a sequential process, the first agent completes their task and signals completion.
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2. **Subsequent Tasks**: Agents pick up their tasks based on the process type, with outcomes of preceding tasks or directives guiding their execution.
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3. **Completion**: The process concludes once the final task is executed, leading to project completion.
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## Advanced Features
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### Task Delegation
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In sequential processes, if an agent has `allow_delegation` set to `True`, they can delegate tasks to other agents in the crew.
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This feature is automatically set up when there are multiple agents in the crew.
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### Asynchronous Execution
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Tasks can be executed asynchronously, allowing for parallel processing when appropriate.
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To create an asynchronous task, set `async_execution=True` when defining the task.
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### Memory and Caching
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CrewAI supports both memory and caching features:
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- **Memory**: Enable by setting `memory=True` when creating the Crew. This allows agents to retain information across tasks.
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- **Caching**: By default, caching is enabled. Set `cache=False` to disable it.
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### Callbacks
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You can set callbacks at both the task and step level:
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- `task_callback`: Executed after each task completion.
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- `step_callback`: Executed after each step in an agent's execution.
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### Usage Metrics
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CrewAI tracks token usage across all tasks and agents. You can access these metrics after execution.
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## Best Practices for Sequential Processes
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1. **Order Matters**: Arrange tasks in a logical sequence where each task builds upon the previous one.
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2. **Clear Task Descriptions**: Provide detailed descriptions for each task to guide the agents effectively.
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3. **Appropriate Agent Selection**: Match agents' skills and roles to the requirements of each task.
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4. **Use Context**: Leverage the context from previous tasks to inform subsequent ones.
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This updated documentation ensures that details accurately reflect the latest changes in the codebase and clearly describes how to leverage new features and configurations.
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The content is kept simple and direct to ensure easy understanding. |