This can be achieved quickly with the SuperAGI open source framework:
- Clone the project repository and enter the catalog (
git clone https://github.com/TransformerOptimus/SuperAGI.git+cd SuperAGI) - Copying configuration template files
config_template.yamlbecause ofconfig.yamland fill in the API key - After ensuring that Docker Desktop is running, execute the
docker-compose upLaunch Container - interviews
http://localhost:3000Enter the graphical interface and click "New Agent" to select a template (e.g. SuperCoder). - Set the agent name, target task and toolkit (e.g. Google Analytics/Notion), and finally click "Run" to deploy.
The whole process takes about 10 minutes to complete and supports concurrent execution of different complex tasks by multiple agents.
This answer comes from the articleSuperAGI: An Open Source Framework for Rapidly Building and Running Autonomous AI AgentsThe
May not be reproduced without permission:AI productivity tools " How do you quickly build and deploy an autonomous AI agent that can perform complex tasks?
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