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Update website/blog/2024-11-15-CaptainAgent/index.mdx
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Co-authored-by: Qingyun Wu <[email protected]>
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LeoLjl and qingyun-wu authored Nov 19, 2024
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Expand Up @@ -18,7 +18,7 @@ Given an ad-hoc task, dynamically assembling a group of agents capable of effect
We design a two-step workflow for CaptainAgent to build a high quality team and solve the problem:
- (**Step 1**) CaptainAgent will first break down the task, recommend several roles needed for each subtask, and then create a team of agents accordingly. Each agent in the team is either generated from scratch or retrieved and selected from an agent library if provided. Each of them will also be equipped with predefined tools retrieved from a tool library if provided.
![Building workflow](img/build.png)
- (**Step 2**) this team of agents will attempt to solve the subtask via conversation with the free-form tool using. Once it's done, a reflector LLM will provide CaptainAgent with a reflection report for it to decide whether to adjust the team or subtask instruction or to terminate and output the results.
- (**Step 2**) For each subtask, the corresponding team of agents will jointly solve it. Once it's done, a summarization and reflection step will be triggered to generate a report based on the multi-agent conversation history. Based on the report, CaptainAgent will decide whether to adjust the subtasks and corresponding team or to terminate and output the results.
![Building workflow](img/chat.png)

We also provide an agent library and a tool library for CaptainAgent to choose from when building the team. In the following section, we demonstrate how to use CaptainAgent with or without the provided library.
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