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+# Human Input 
+
+Human inputs is important in many agent execution use cases, humans are AGI so they can can be prompted to step in and provide extra details ins necessary.
+Using it with crewAI is pretty straightforward and you can do it through a LangChain Tool. Check [LangChain Integration](https://python.langchain.com/docs/integrations/tools/human_tools) for more details:
+
+Example:
+
+```python
+import os
+from crewai import Agent, Task, Crew, Process
+from langchain.tools import DuckDuckGoSearchRun
+
+search_tool = DuckDuckGoSearchRun()
+
+# Loading Human Tools
+human_tools = load_tools(["human"])
+
+# Define your agents with roles and goals
+researcher = Agent(
+  role='Senior Research Analyst',
+  goal='Uncover cutting-edge developments in AI and data science in',
+  backstory="""You are a Senior Research Analyst at a leading tech think tank.
+  Your expertise lies in identifying emerging trends and technologies in AI and
+  data science. You have a knack for dissecting complex data and presenting
+  actionable insights.""",
+  verbose=True,
+  allow_delegation=False,
+  # Passing human tools to the agent
+  tools=[search_tool]+human_tools
+)
+writer = Agent(
+  role='Tech Content Strategist',
+  goal='Craft compelling content on tech advancements',
+  backstory="""You are a renowned Tech Content Strategist, known for your insightful
+  and engaging articles on technology and innovation. With a deep understanding of
+  the tech industry, you transform complex concepts into compelling narratives.""",
+  verbose=True,
+  allow_delegation=True
+)
+
+# Create tasks for your agents
+# Being explicit on the task to ask for human feedback.
+task1 = Task(
+  description="""Conduct a comprehensive analysis of the latest advancements in AI in 2024.
+  Identify key trends, breakthrough technologies, and potential industry impacts.
+  Compile your findings in a detailed report. Make sure to check with the human if the draft is good before returning your Final Answer.
+  Your final answer MUST be a full analysis report""",
+  agent=researcher
+)
+
+task2 = Task(
+  description="""Using the insights from the researcher's report, develop an engaging blog
+  post that highlights the most significant AI advancements.
+  Your post should be informative yet accessible, catering to a tech-savvy audience.
+  Aim for a narrative that captures the essence of these breakthroughs and their
+  implications for the future. Your final answer MUST be the full blog post of at least 3 paragraphs.""",
+  agent=writer
+)
+
+# Instantiate your crew with a sequential process
+crew = Crew(
+  agents=[researcher, writer],
+  tasks=[task1, task2],
+  verbose=2, # Crew verbose more will let you know what tasks are being worked on, you can set it to 1 or 2 to different logging levels
+  process=Process.sequential # Sequential process will have tasks executed one after the other and the outcome of the previous one is passed as extra content into this next.
+)
+
+# Get your crew to work!
+result = crew.kickoff()
+
+print("######################")
+print(result)
+```
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