From 93781f20af6afe497c70d1b87c7883b7f9f065da Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jo=C3=A3o=20Moura?= Date: Sat, 6 Jan 2024 01:32:53 -0300 Subject: [PATCH] Updated Human Input (markdown) --- Human-Input.md | 12 +++++++----- 1 file changed, 7 insertions(+), 5 deletions(-) diff --git a/Human-Input.md b/Human-Input.md index b1e05fd..dc2a602 100644 --- a/Human-Input.md +++ b/Human-Input.md @@ -1,7 +1,8 @@ # 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: +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: @@ -43,7 +44,8 @@ writer = Agent( 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. + 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 ) @@ -53,7 +55,8 @@ task2 = Task( 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.""", + implications for the future. + Your final answer MUST be the full blog post of at least 3 paragraphs.""", agent=writer ) @@ -61,8 +64,7 @@ task2 = Task( 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. + verbose=2 ) # Get your crew to work!