MAESTRO adopts containerized deployment scheme, realizing one-click local deployment through Docker Compose, and all data processing is done on the user's own server. The first run of the system needs to download about 5GB of AI model files, and all subsequent document parsing, information retrieval and report generation operations are performed in an offline environment. In the .env configuration file, users can independently configure API keys, network ports and other key parameters, and the system defaults to the admin/adminpass123 dual authentication mechanism, it is recommended to modify the default credentials immediately after deployment to strengthen security.
This answer comes from the articleMAESTRO: In-depth research assistant with local knowledge base and multi-agent collaborationThe
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