Comments (2)
I think I should open some kind of infrastructure planing thread.
With the introduction of "chat mode" I think there is a nice way to handle the expert LLM thing.
What are your thoughts on this:
We have a "chat layer" which has a history of the user's prompts and messages (green and purple). If needed, this chat chain can call other chains, which run autonomous without user interaction by using a self critique loop.
It would be very easy to add more chains to this, like a "programming chain" using deepseek-coder as the LLM.
I would have to come up with a config format for these chains, but essentially they are just a couple of conditions and strings in / strings out.
In the meantime, I can add a simple HTML select for the models loaded on the user's ollama instance. The only problem with this is, that different llms need different parameters and prompts, which currently aren't configurable through the webui.
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Working on a model switch popup
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Related Issues (20)
- error maxIterations must be a number with the docker version HOT 1
- Search cards hides LLM response in mobile browser
- Error on question HOT 1
- How can I change the app's root path?
- Why doesn't my search process have source boost on the left?
- searxng.engines.wikidata: Fail to initialize HOT 1
- Update ollama to allow parallel model load
- Couldnt acess the localhost port 3000 HOT 2
- `maxIterations must be a number` HOT 2
- Error/warning on Apple Silicon HOT 2
- error in installation on MAC HOT 3
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- limit db result size to not "overflow" context
- Error: Post 'host.docker.internal:11434': unsupported protocol scheme 'host.docker.internal' HOT 11
- support for more than one ollama backend HOT 1
- Improve rendering for sources and the relevant text chunks
- add used tools to main context window
- make dev exception
- Vllm support (open-ai compatible api)
- Not seeming to work on M1 Mac?
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