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Description
Feature request / 功能建议
Sorry but please allow me to use some AI to summary my findings and request. Im not sure who should I send this feature request to vllm team, transformer team, zai team? :D May be with your connection you can onboard more developer using your surprisingly good model
Request: Add support for tool calling (glm45 parser) when using transformers 5.x with GLM-4.6V models.
Current Limitation: GLM-4.6V models require transformers 5.0.0rc1 for vision/multimodal support, but vLLM v0.13's tool calling parser (glm45) is incompatible with transformers 5.x, forcing users to choose between tool calling OR vision.
Environment
- vLLM Version: v0.13.0
- Model:
zai-org/GLM-4.6V-FP8,zai-org/GLM-4.6V-Flash - Transformers 4.56.0: Tool calling works, vision not supported
- Transformers 5.0.0rc1: Vision works, tool calling broken
- Tool Call Parser:
glm45 - GPU: 2x NVIDIA RTX 6000 Pro (96GB each)
Current Behavior
With transformers 4.56.0 (Tool Calling Works)
vllm serve zai-org/GLM-4.6V-FP8 \
--tool-call-parser glm45 \
--limit-mm-per-prompt '{"image": 0, "video": 0}'Response includes tool_calls:
{
"choices": [{
"message": {
"tool_calls": [{
"id": "call_abc",
"function": {
"name": "get_weather",
"arguments": "{\"location\": \"Tokyo\"}"
}
}]
}
}]
}With transformers 5.0.0rc1 (Tool Calling Broken)
pip install --upgrade 'transformers==5.0.0rc1'
vllm serve zai-org/GLM-4.6V-FP8 \
--tool-call-parser glm45 \
--limit-mm-per-prompt '{"image": 1, "video": 0}'Response has tool_calls: null:
{
"choices": [{
"message": {
"content": "I should use the get_weather function...",
"tool_calls": null
}
}]
}Why transformers 5.0.0rc1 is Required
GLM-4.6V models have a multimodal vision processor that only exists in transformers 5.0.0rc1:
Error: Cannot find module 'transformers.models.glm.visualizing_glm'
The GLMVisionProcessor class was added in transformers 5.0.0rc1 and is required for image support.
Motivation / 动机
Just let the team knew something broken but not a bug from zai :D rather an ecosystem
Your contribution / 您的贡献
No