vllm-project/vllm

[Transformers v5] MiniCPMV cannot apply processor

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#38385 opened on Mar 27, 2026

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Description

This is a sub-issue forming part of the work in https://github.com/vllm-project/vllm/issues/38379, please read the description of this issue before beginning to work on this one.

Which test is failing?

If the model is relevant enough for us to keep supporting, this should be upstreamed to Transformers.

$ pytest tests/lora/test_minicpmv_tp.py::test_minicpmv_lora
...
ValueError: Failed to apply MiniCPMVProcessor on data={'text': '(<image>./</image>)', 'images': [<PIL.Image.Image image mode=RGB size=448x4032 at 0x7F7695579D60>]} with kwargs={'truncation': False, 'return_tensors': 'pt'}

How to configure my environment?

It's very important that you install both vLLM and Transformers from source so that your test results reflect the current state of both libraries.

# Or your fork
git clone https://github.com/huggingface/transformers.git
git clone https://github.com/vllm-project/vllm.git

cd vllm
VLLM_USE_PRECOMPILED=1 uv pip install -e .
uv pip install -e ../transformers

Contributor guide

Tech stack
pythonpytorch
Domain
backendmachine learning
Issue type
bug
DifficultyEstimated implementation difficulty for a new contributor, from 1 for very small changes to 5 for expert-level work.
3
Estimated timeA rough time range for an experienced contributor to investigate, implement, test, and prepare a pull request.
half day
Activity statusHow available the issue appears right now: fresh, active, stale, blocked, or waiting on maintainer input.
active
ClarityHow clearly the issue explains the expected change, acceptance criteria, and next step.
mostly clear
Prerequisites
Pythontesting experience
Newbie friendlinessA 1-100 score estimating how approachable this issue is for first-time contributors.
40
Research direction
Investigate why MiniCPMVProcessor.apply fails on the given input. Look at the test file tests/lora/test minicpmv tp.py and the processor implementation in the transformers library. Check if the issue is related to argument handling in the processor, possibly the 'truncation' or 'return tensors' kwargs. Since this is part of a larger migration, refer to the parent issue vllm project/vllm#38379 for context. The fix may involve updating the processor call or adjusting the test inputs to match the expected format.