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fix: pre-download GGUF and embedding models at build time to eliminate cold-start delay
Browse files- Dockerfile +14 -12
- src/utils.py +8 -3
Dockerfile
CHANGED
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@@ -8,26 +8,28 @@ RUN apt-get update && apt-get install -y \
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WORKDIR /app
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# Set at build time so pip uses them when compiling llama-cpp-python
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ENV CMAKE_ARGS="-DGGML_BLAS=OFF -DGGML_METAL=OFF -DGGML_OPENMP=OFF -DGGML_NATIVE=OFF -DLLAMA_BUILD_TESTS=OFF -DLLAMA_BUILD_EXAMPLES=OFF -DLLAMA_BUILD_SERVER=OFF"
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ENV CMAKE_BUILD_PARALLEL_LEVEL=4
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COPY requirements.txt .
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RUN pip install --no-cache-dir -r requirements.txt
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COPY . .
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# Pre-download
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RUN python -
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from huggingface_hub import hf_hub_download
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hf_hub_download(
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RUN useradd -m -u 1000 user
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USER user
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ENV HOME=/home/user PATH=/home/user/.local/bin:$PATH
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WORKDIR /app
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ENV CMAKE_ARGS="-DGGML_BLAS=OFF -DGGML_METAL=OFF -DGGML_OPENMP=OFF -DGGML_NATIVE=OFF -DLLAMA_BUILD_TESTS=OFF -DLLAMA_BUILD_EXAMPLES=OFF -DLLAMA_BUILD_SERVER=OFF"
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ENV CMAKE_BUILD_PARALLEL_LEVEL=4
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ENV HF_HUB_CACHE=/app/model
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COPY requirements.txt .
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RUN pip install --no-cache-dir -r requirements.txt
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COPY . .
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# Pre-download GGUF model (~2.5 GB) at build time
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RUN python -c "\
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from huggingface_hub import hf_hub_download; \
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hf_hub_download(repo_id='Jackrong/Qwen3.5-4B-Neo-GGUF', filename='Qwen3.5-4B.Q4_K_S.gguf', cache_dir='/app/model')"
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# Pre-download embedding model at build time
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RUN python -c "\
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from huggingface_hub import snapshot_download; \
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snapshot_download('BAAI/bge-small-en-v1.5')"
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RUN useradd -m -u 1000 user \
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&& chown -R 1000:1000 /app/model
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USER user
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ENV HOME=/home/user PATH=/home/user/.local/bin:$PATH
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src/utils.py
CHANGED
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@@ -17,12 +17,17 @@ class UTF8LocalFileSystem(LocalFileSystem):
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def resolve_gguf_model_path(status_callback=None) -> str:
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"""Return local path to the GGUF model file, downloading from HF Hub if needed."""
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if direct.exists():
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return str(direct)
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snapshots_root = (
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-
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/ f"models--{'--'.join(MODEL_REPO_ID.split('/'))}"
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/ "snapshots"
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)
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@@ -35,5 +40,5 @@ def resolve_gguf_model_path(status_callback=None) -> str:
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return hf_hub_download(
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repo_id=MODEL_REPO_ID,
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filename=MODEL_FILENAME,
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cache_dir=
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)
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def resolve_gguf_model_path(status_callback=None) -> str:
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"""Return local path to the GGUF model file, downloading from HF Hub if needed."""
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import os
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# Respect HF_HUB_CACHE env var (set in Dockerfile to /app/model)
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cache_dir = Path(os.environ.get("HF_HUB_CACHE", "./model"))
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direct = cache_dir / MODEL_FILENAME
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if direct.exists():
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return str(direct)
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snapshots_root = (
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cache_dir
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/ f"models--{'--'.join(MODEL_REPO_ID.split('/'))}"
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/ "snapshots"
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)
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return hf_hub_download(
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repo_id=MODEL_REPO_ID,
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filename=MODEL_FILENAME,
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cache_dir=str(cache_dir),
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)
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