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fix(pii): bump transformers to 5.5.0 for LightGlue RCE advisory #5662

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fix(pii): bump transformers to 5.5.0 for LightGlue RCE advisory #5662

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b3eb3b0
fix(pii): bump transformers to 5.5.0 for LightGlue RCE advisory
waleedlatif1 Jul 14, 2026
e6884fa
improvement(pii): assert real GLiNER inference in the image build
waleedlatif1 Jul 14, 2026
6dd8465
improvement(pii): require date detection in the GLiNER build smoke as…
waleedlatif1 Jul 14, 2026
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4 changes: 2 additions & 2 deletions apps/pii/requirements-gliner.txt
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Expand Up @@ -6,5 +6,5 @@
# torch is pinned in the Dockerfile instead: the CPU and CUDA targets install
# the same version from different wheel indexes.
gliner==0.2.27
transformers==5.3.0
huggingface_hub==1.3.0
transformers==5.5.0
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huggingface_hub==1.23.0
9 changes: 8 additions & 1 deletion docker/pii.Dockerfile
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Expand Up @@ -87,9 +87,16 @@ RUN --mount=type=cache,target=/root/.cache/pip \
# Bake the GLiNER weights at build time (cached layer) so startup never
# touches the network. HF_HUB_OFFLINE makes a missing/overridden
# PII_GLINER_MODEL fail fast at startup instead of silently downloading.
# The predict_entities smoke assert (labels from engines.py's
# GLINER_ENTITY_MAPPING) fails the build if a transformers/gliner bump loads
# the model fine but silently stops returning detections.
ENV HF_HOME=/opt/hf-cache
ARG GLINER_MODEL=urchade/gliner_multi_pii-v1
RUN python -c "from gliner import GLiNER; GLiNER.from_pretrained('${GLINER_MODEL}')" && \
RUN python -c "from gliner import GLiNER; \
model = GLiNER.from_pretrained('${GLINER_MODEL}'); \
ents = model.predict_entities('John Smith flew to Paris on 4 May 2021.', ['person', 'location', 'date']); \
labels = {e['label'] for e in ents}; \
assert {'person', 'location'} <= labels, f'GLiNER smoke inference failed, got: {ents}'" && \
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chmod -R a+rX /opt/hf-cache
ENV HF_HUB_OFFLINE=1

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