Local AI assistant with optional integrations and mobile companion
Description
Setup a local AI assistant for research, brainstorming and proof reading. Look into SurfSense, Open WebUI and possibly alternatives. Explore integration with services like openQA. There should be no cloud dependencies. Mobile phone support or an additional companion app would be a bonus. The goal is not to develop everything from scratch.
User Story
- Allison Average wants a one-click local AI assistent on their openSUSE laptop.
- Ash Awesome wants AI on their phone without an expensive subscription.
Goals
- Evaluate a local SurfSense setup for day to day productivity
- Test opencode for vibe coding and tool calling
Timeline
Day 1
- Took a look at SurfSense and started setting up a local instance.
- Unfortunately the container setup did not work well. Tho this was a great opportunity to learn some new podman commands and refresh my memory on how to recover a corrupted btrfs filesystem.
Day 2
- Due to its sheer size and complexity SurfSense seems to have triggered btrfs fragmentation. Naturally this was not visible in any podman-related errors or in the journal. So this took up much of my second day.
Day 3
- Trying out opencode with Qwen3-Coder and Qwen2.5-Coder.
Day 4
- Context size is a thing, and models are not equally usable for vibe coding.
- Through arduous browsing for ollama models I did find some like
myaniu/qwen2.5-1m:7bwith 1m but even then it is not obvious if they are meant for tool calls.
Day 5
- Whilst trying to make opencode usable I discovered ramalama which worked instantly and very well.
Outcomes
surfsense
I could not easily set this up completely. Maybe in part due to my filesystem issues. Was expecting this to be less of an effort.
opencode
Installing opencode and ollama in my distrobox container along with the following configs worked for me.
When preparing a new project from scratch it is a good idea to start out with a template.
opencode.json
{
"$schema": "https://opencode.ai/config.json",
"theme": "catppuccin",
"model": "ollama/qwen2.5-coder:1.5b",
"mode": {
"plan": {
"temperature": 0.0
},
"build": {
"temperature": 0.0
}
},
"provider": {
"ollama": {
"npm": "[@ai-sdk](/users/ai-sdk)/openai-compatible",
"name": "Ollama (local)",
"options": {
"baseURL": "http://localhost:11434/v1"
},
"models": {
"qwen2.5-coder:1.5b": {
"name": "Qwem2.5-Coder"
}
}
}
},
"mcp": {
"openqa": {
"type": "remote",
"enabled": true,
"url": "https://openqa.opensuse.org/experimental/mcp",
"headers": {
"Authorization": "Bearer {env:OPENQA_USER}:{env:OPENQA_APIKEY}:{env:OPENQA_APISECRET}"
}
},
"gh_grep": {
"type": "remote",
"url": "https://mcp.grep.app"
}
}
}
The models need to be ollama pulled first, and ollama needs to be serving.
AGENTS.md
Agents can be instruced per project or globally like so:
When you need to lookup openQA jobs or job groups, use `openqa` tools.
If you are unsure how to do something, use `gh_grep` to search code examples from github.
Note: My results varied a lot between models. Available context length e.g. OLLAMA_CONTEXT_LENGTH=8192 ollama serve & gives it more wiggle room and lowering the temerature should also help, but I found myself tweaking the configuration a lot.
Horrible performance even with small models
Normally I don't hear the fan in this laptop much. Responses were processed so slowly by opencode that I barely got much done. Even figuring out why responses were unreliable took longer because I had to wait a lot for useless responses.
Airgapped models
While Investigating the horrible performance of opencode I stumbled upon ramalama which runs models in containers optimized for different cpu's which are also isolated:
ramalama serve --ctx-size 8192 -p 8080 -d kirito1/qwen3-coder:1.7b
I could not get it to work with opencode which just silently failed to communicate with it. Even so, ramalama is awesome.
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