Feature Category
AI Assistant Enhancement
Problem Statement
If you have a complex GPU config or require customization requirements on the host that Nomad is to be installed on, the AI assistant install requires the ollama docker container to be installed. This conflicts with other LLM hosting software running on the host including customized ollama configs, vLLM, llama.cpp, etc.
The AI assistant install will fail if there is anything already running on the default ollama port.
The AI assistant will have random issues and will cause random issues for other LLM services by trying to utilize the same GPU's at the same time.
Proposed Solution
Possible, solution. Remove the ollama requirement for the AI Assistant install. If the ollama service is optional, then it won't be present to conflict for ports or GPU resources.
Alternative Solutions
Run the nomad_ollama container as default CPU only, and on a non-standard port to avoid conflicting with services that may already be in place.
It is possible to run Nomad on a totally different host just fine. IF you have additional hardware, and are willing to was the resources for it.
Use Case
This would allow more complex LLM configuration and deployments on the same host nomad is installed on. Allowing for more functionality outside of nomad on the same hardware.
Who would benefit from this feature?
All Users
How important is this feature to you?
High - Would significantly improve my experience
Implementation Ideas (Optional)
No response
Examples or References
Example, I utilize a single host machine to run Openclaw, Agent Zero, Nomad, vLLM, and ollama. All my GPU's and storage/memory are all on a single platform and run inside docker containers.
This allows me to fully utilize the hardware I have. Additional hardware would require more cost, more electricity, more cooling, etc.
Would you be willing to help implement this?
Yes - I can write the code
Additional Context
I am willing to help with a solution. I'm fully capable of coding and solution engineering. My GitHub experience is limited however. I have room to learn how to properly work with it to contribute correctly.
Pre-submission Checklist
Feature Category
AI Assistant Enhancement
Problem Statement
If you have a complex GPU config or require customization requirements on the host that Nomad is to be installed on, the AI assistant install requires the ollama docker container to be installed. This conflicts with other LLM hosting software running on the host including customized ollama configs, vLLM, llama.cpp, etc.
The AI assistant install will fail if there is anything already running on the default ollama port.
The AI assistant will have random issues and will cause random issues for other LLM services by trying to utilize the same GPU's at the same time.
Proposed Solution
Possible, solution. Remove the ollama requirement for the AI Assistant install. If the ollama service is optional, then it won't be present to conflict for ports or GPU resources.
Alternative Solutions
Run the nomad_ollama container as default CPU only, and on a non-standard port to avoid conflicting with services that may already be in place.
It is possible to run Nomad on a totally different host just fine. IF you have additional hardware, and are willing to was the resources for it.
Use Case
This would allow more complex LLM configuration and deployments on the same host nomad is installed on. Allowing for more functionality outside of nomad on the same hardware.
Who would benefit from this feature?
All Users
How important is this feature to you?
High - Would significantly improve my experience
Implementation Ideas (Optional)
No response
Examples or References
Example, I utilize a single host machine to run Openclaw, Agent Zero, Nomad, vLLM, and ollama. All my GPU's and storage/memory are all on a single platform and run inside docker containers.
This allows me to fully utilize the hardware I have. Additional hardware would require more cost, more electricity, more cooling, etc.
Would you be willing to help implement this?
Yes - I can write the code
Additional Context
I am willing to help with a solution. I'm fully capable of coding and solution engineering. My GitHub experience is limited however. I have room to learn how to properly work with it to contribute correctly.
Pre-submission Checklist