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93 lines
3.5 KiB
Markdown
93 lines
3.5 KiB
Markdown
---
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title: Human Input on Execution
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description: Integrating CrewAI with human input during execution in complex decision-making processes and leveraging the full capabilities of the agent's attributes and tools.
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---
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# Human Input in Agent Execution
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Human input is critical in several agent execution scenarios, allowing agents to request additional information or clarification when necessary. This feature is especially useful in complex decision-making processes or when agents require more details to complete a task effectively.
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## Using Human Input with CrewAI
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To integrate human input into agent execution, set the `human_input` flag in the task definition. When enabled, the agent prompts the user for input before delivering its final answer. This input can provide extra context, clarify ambiguities, or validate the agent's output.
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### Example:
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```shell
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pip install crewai
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```
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```python
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import os
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from crewai import Agent, Task, Crew
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from crewai_tools import SerperDevTool
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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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# Loading Tools
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search_tool = SerperDevTool()
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# Define your agents with roles, goals, tools, and additional attributes
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researcher = Agent(
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role='Senior Research Analyst',
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goal='Uncover cutting-edge developments in AI and data science',
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backstory=(
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"You are a Senior Research Analyst at a leading tech think tank. "
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"Your expertise lies in identifying emerging trends and technologies in AI and data science. "
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"You have a knack for dissecting complex data and presenting actionable insights."
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),
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verbose=True,
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allow_delegation=False,
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tools=[search_tool]
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)
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writer = Agent(
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role='Tech Content Strategist',
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goal='Craft compelling content on tech advancements',
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backstory=(
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"You are a renowned Tech Content Strategist, known for your insightful and engaging articles on technology and innovation. "
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"With a deep understanding of the tech industry, you transform complex concepts into compelling narratives."
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),
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verbose=True,
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allow_delegation=True,
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tools=[search_tool],
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cache=False, # Disable cache for this agent
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)
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# Create tasks for your agents
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task1 = Task(
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description=(
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"Conduct a comprehensive analysis of the latest advancements in AI in 2024. "
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"Identify key trends, breakthrough technologies, and potential industry impacts. "
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"Compile your findings in a detailed report. "
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"Make sure to check with a human if the draft is good before finalizing your answer."
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),
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expected_output='A comprehensive full report on the latest AI advancements in 2024, leave nothing out',
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agent=researcher,
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human_input=True
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)
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task2 = Task(
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description=(
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"Using the insights from the researcher\'s report, develop an engaging blog post that highlights the most significant AI advancements. "
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"Your post should be informative yet accessible, catering to a tech-savvy audience. "
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"Aim for a narrative that captures the essence of these breakthroughs and their implications for the future."
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),
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expected_output='A compelling 3 paragraphs blog post formatted as markdown about the latest AI advancements in 2024',
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agent=writer
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)
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# Instantiate your crew with a sequential process
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crew = Crew(
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agents=[researcher, writer],
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tasks=[task1, task2],
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verbose=2,
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memory=True,
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)
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# Get your crew to work!
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result = crew.kickoff()
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print("######################")
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print(result)
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``` |