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113 lines
3.7 KiB
Markdown
113 lines
3.7 KiB
Markdown
---
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title: Assembling and Activating Your CrewAI Team
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description: A step-by-step guide to creating a cohesive CrewAI team for your projects.
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---
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## Introduction
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Embarking on your CrewAI journey involves a few straightforward steps to set up your environment and initiate your AI crew. This guide ensures a seamless start.
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## Step 0: Installation
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Begin by installing CrewAI and any additional packages required for your project. For instance, the `duckduckgo-search` package is used in this example for enhanced search capabilities.
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```shell
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pip install crewai
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pip install duckduckgo-search
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```
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## Step 1: Assemble Your Agents
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Begin by defining your agents with distinct roles and backstories. These elements not only add depth but also guide their task execution and interaction within the crew.
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```python
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import os
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os.environ["OPENAI_API_KEY"] = "Your Key"
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from crewai import Agent
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# Topic that will be used in the crew run
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topic = 'AI in healthcare'
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# Creating a senior researcher agent
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researcher = Agent(
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role='Senior Researcher',
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goal=f'Uncover groundbreaking technologies around {topic}',
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verbose=True,
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backstory="""Driven by curiosity, you're at the forefront of
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innovation, eager to explore and share knowledge that could change
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the world."""
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)
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# Creating a writer agent
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writer = Agent(
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role='Writer',
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goal=f'Narrate compelling tech stories around {topic}',
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verbose=True,
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backstory="""With a flair for simplifying complex topics, you craft
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engaging narratives that captivate and educate, bringing new
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discoveries to light in an accessible manner."""
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)
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```
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## Step 2: Define the Tasks
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Detail the specific objectives for your agents. These tasks guide their focus and ensure a targeted approach to their roles.
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```python
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from crewai import Task
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# Install duckduckgo-search for this example:
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# !pip install -U duckduckgo-search
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from langchain_community.tools import DuckDuckGoSearchRun
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search_tool = DuckDuckGoSearchRun()
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# Research task for identifying AI trends
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research_task = Task(
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description=f"""Identify the next big trend in {topic}.
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Focus on identifying pros and cons and the overall narrative.
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Your final report should clearly articulate the key points,
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its market opportunities, and potential risks.
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""",
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expected_output='A comprehensive 3 paragraphs long report on the latest AI trends.',
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max_inter=3,
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tools=[search_tool],
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agent=researcher
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)
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# Writing task based on research findings
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write_task = Task(
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description=f"""Compose an insightful article on {topic}.
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Focus on the latest trends and how it's impacting the industry.
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This article should be easy to understand, engaging and positive.
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""",
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expected_output=f'A 4 paragraph article on {topic} advancements.',
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tools=[search_tool],
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agent=writer
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)
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```
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## Step 3: Form the Crew
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Combine your agents into a crew, setting the workflow process they'll follow to accomplish the tasks.
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```python
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from crewai import Crew, Process
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# Forming the tech-focused crew
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crew = Crew(
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agents=[researcher, writer],
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tasks=[research_task, write_task],
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process=Process.sequential # Sequential task execution
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)
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```
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## Step 4: Kick It Off
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With your crew ready and the stage set, initiate the process. Watch as your agents collaborate, each contributing their expertise to achieve the collective goal.
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```python
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# Starting the task execution process
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result = crew.kickoff()
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print(result)
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```
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## Conclusion
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Building and activating a crew in CrewAI is a seamless process. By carefully assigning roles, tasks, and a clear process, your AI team is equipped to tackle challenges efficiently. The depth of agent backstories and the precision of their objectives enrich the collaboration, leading to successful project outcomes.
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