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v7: huggingface_hub<1.0 (Gradio 5.5 oauth still imports HfFolder)

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  1. requirements.txt +7 -7
requirements.txt CHANGED
@@ -1,17 +1,17 @@
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- # Gradio 5 escapes the 4.x dep-pinning rabbit hole.
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- # 4.44.1 + new Starlette (0.40+) is broken: 4.x calls TemplateResponse with
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- # the pre-0.40 positional-args signature, so jinja2's cache lookup gets a
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- # dict as a key → TypeError. Gradio 5 uses the new Starlette API.
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  gradio>=5.5,<6.0
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  matplotlib>=3.7
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  numpy>=1.24
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  torch>=2.0
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  pillow>=10.0
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- # huggingface_hub stays <2.0 (pinning broad — Gradio 5 handles 1.x+).
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- huggingface_hub>=0.24,<2.0
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-
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  # Prebuilt llama-cpp-python wheel from AIencoder/llama-cpp-wheels.
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  # CPU-only, AVX2 + FMA + F16C — works on every HF Space x86_64 host.
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  https://huggingface.co/datasets/AIencoder/llama-cpp-wheels/resolve/main/llama_cpp_python-0.3.16%2Bbasic_avx2_fma_f16c-cp312-cp312-manylinux_2_31_x86_64.whl
 
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+ # Gradio 5 (avoids 4.x's Starlette template signature breakage).
 
 
 
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  gradio>=5.5,<6.0
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+ # CRITICAL: gradio 5.5's oauth.py still does `from huggingface_hub import
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+ # HfFolder` — HfFolder was removed in huggingface_hub 1.0. Pin <1.0.
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+ # (Newer gradio 5.20+ uses get_token instead, but the 5.5 LTS line we use
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+ # is more conservative and well-tested on Spaces.)
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+ huggingface_hub>=0.24,<1.0
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+
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  matplotlib>=3.7
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  numpy>=1.24
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  torch>=2.0
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  pillow>=10.0
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  # Prebuilt llama-cpp-python wheel from AIencoder/llama-cpp-wheels.
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  # CPU-only, AVX2 + FMA + F16C — works on every HF Space x86_64 host.
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  https://huggingface.co/datasets/AIencoder/llama-cpp-wheels/resolve/main/llama_cpp_python-0.3.16%2Bbasic_avx2_fma_f16c-cp312-cp312-manylinux_2_31_x86_64.whl