Docker deployment is divided into two key steps:
- mirror construction: Implementation
docker build -t gbc-madai .command, which automatically installs all dependencies - Container Running: By
docker run -d -p 8000:8000 --env-file .env gbc-madaiStart the service, where--env-fileparameter is used to load a configuration file containing sensitive information such as API keys
After successful deployment, the front-end service runs on port 8000 by default. Compared to source code deployment, the Docker approach can better solve the problem of environment dependency, especially suitable for production environments. Note that before running, you need to make sure that you have correctly configured all the required parameters in the .env file.
This answer comes from the articleGBC MedAI: An Intelligent Medical Assistant with Access to Multiple AI Models and Search EnginesThe
May not be reproduced without permission:AI productivity tools " How to deploy GBC MedAI via Docker?
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