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Currently, with every new model architecture supported, we need to manually add a conversation template object in c++, i.e. here. This is not very scalable, and we also need to make sure web-llm is catching up with every conversation template added, i.e. here.
We should instead create a uniform json schema for all conversation templates (we already have one here for MLC serve: https://github.com/mlc-ai/mlc-llm/blob/main/python/mlc_chat/protocol/conversation_protocol.py) and embed it into mlc-chat-config.json. This way both mlc-llm and web-llm can read the conversation template directly from mlc-chat-config.json, without needing to add a c++ template every time with a new model support.
Action Items
Create a uniform json schema for all conversation templates and embed it into mlc-chat-config.json
Update the current HF prebuilt weights with the new mlc-chat-config.json
Overview
Currently, with every new model architecture supported, we need to manually add a conversation template object in c++, i.e. here. This is not very scalable, and we also need to make sure web-llm is catching up with every conversation template added, i.e. here.
We should instead create a uniform json schema for all conversation templates (we already have one here for MLC serve: https://github.com/mlc-ai/mlc-llm/blob/main/python/mlc_chat/protocol/conversation_protocol.py) and embed it into
mlc-chat-config.json
. This way both mlc-llm and web-llm can read the conversation template directly frommlc-chat-config.json
, without needing to add a c++ template every time with a new model support.Action Items
mlc-chat-config.json
mlc-chat-config.json
conv_template.cc
Links to Related Issues and PRs
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