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Updating Docs
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@@ -7,12 +7,11 @@ description: A comprehensive guide to creating a dynamic CrewAI team for your pr
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Embark on your CrewAI journey by setting up your environment and initiating your AI crew with enhanced features. This guide ensures a seamless start, incorporating the latest updates.
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## Step 0: Installation
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Install CrewAI and any necessary packages for your project. The `duckduckgo-search` package is highlighted here for enhanced search capabilities.
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Install CrewAI and any necessary packages for your project.
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```shell
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pip install crewai
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pip install crewai[tools]
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pip install duckduckgo-search
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pip install 'crewai[tools]'
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```
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## Step 1: Assemble Your Agents
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@@ -20,24 +19,24 @@ Define your agents with distinct roles, backstories, and now, enhanced capabilit
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```python
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import os
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os.environ["SERPER_API_KEY"] = "Your Key" # serper.dev API key
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os.environ["OPENAI_API_KEY"] = "Your Key"
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from crewai import Agent
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from langchain_community.tools import DuckDuckGoSearchRun
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search_tool = DuckDuckGoSearchRun()
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# Topic for the crew run
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topic = 'AI in healthcare'
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from crewai_tools import SerperDevTool
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search_tool = SerperDevTool()
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# Creating a senior researcher agent with memory and verbose mode
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researcher = Agent(
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role='Senior Researcher',
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goal=f'Uncover groundbreaking technologies in {topic}',
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goal='Uncover groundbreaking technologies in {topic}',
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verbose=True,
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memory=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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backstory=(
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"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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tools=[search_tool],
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allow_delegation=True
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)
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@@ -45,12 +44,14 @@ researcher = Agent(
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# Creating a writer agent with custom tools and delegation capability
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writer = Agent(
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role='Writer',
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goal=f'Narrate compelling tech stories about {topic}',
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goal='Narrate compelling tech stories about {topic}',
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verbose=True,
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memory=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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backstory=(
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"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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tools=[search_tool],
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allow_delegation=False
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)
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@@ -64,10 +65,12 @@ from crewai import Task
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# Research task
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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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description=(
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"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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tools=[search_tool],
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agent=researcher,
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@@ -75,10 +78,12 @@ research_task = Task(
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# Writing task with language model configuration
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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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expected_output=f'A 4 paragraph article on {topic} advancements fromated as markdown.',
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description=(
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"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='A 4 paragraph article on {topic} advancements formatted as markdown.',
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tools=[search_tool],
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agent=writer,
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async_execution=False,
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@@ -101,11 +106,11 @@ crew = Crew(
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```
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## Step 4: Kick It Off
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Initiate the process with your enhanced crew ready. Observe as your agents collaborate, leveraging their new capabilities for a successful project outcome.
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Initiate the process with your enhanced crew ready. Observe as your agents collaborate, leveraging their new capabilities for a successful project outcome. You can also pass the inputs that will be interpolated into the agents and tasks.
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```python
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# Starting the task execution process with enhanced feedback
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result = crew.kickoff()
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result = crew.kickoff(inputs={'topic': 'AI in healthcare'})
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print(result)
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```
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