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UPDATE: Thanks for all the feedback! I went outside to take a walk after posting this and just came back, and went through them to summarize what needs to be improved. Basically looks like it comes down to the following: - *customize features:* Should not be difficult (will add flag features)
- *path:* customize the home directory (instead of automatically storing to $HOME)
- *python:* some people are having issues with the python binary (since the package is essentially calling these shell commands). Maybe add a flag to specify the exact name of the python binary (such as "--python python3")
- *avoid downloading files:* I have this issue too when I just want to install the code instead of downloading the full model which takes a long time. Might add a flag to avoid downloading models in case you already have them (EDIT: actually upon thinking about it, it's better to just set the source model folder, something like --model)
- *other flags:* The rest of the flags natively supported by the llama.cpp project, such as top_k, top_p, temp, batch_size, threads, seed, n_predict, etc. (They are already in the code but just was not exposed for CLI and not documented)
- *documentation*
- document the machine spec
- document the storage spec: how much space is used?
- node version: which version of node.js is required?
- python version: which version of python doesn't work?
Am I missing anything? Feel free to leave comments, will try to roll out some updates as soon as I can. To stay updated, feel free to follow me on twitter https://twitter.com/cocktailpeanut (or you could create issues on GitHub too!) |
I only realized what was happening after trying to go the other route and use it in a package, where I then noticed the NPM install will give a node-gyp error about make missing.