standalone build example

build/Dockerfile

@@ -15,13 +15,17 @@ RUN apt-get update \
     && apt-get install -y --no-install-recommends python3 python3-pip ca-certificates \
     && rm -rf /var/lib/apt/lists/*
 
-# rmbg-as-a-service from TestPyPI; its deps from real PyPI; CUDA torch from the PyTorch index.
-# pip prefers torch's +cu126 build because the local version label outranks the plain wheel.
-RUN pip install \
-    --index-url https://test.pypi.org/simple/ \
-    --extra-index-url https://pypi.org/simple/ \
-    --extra-index-url https://download.pytorch.org/whl/cu126 \
-    "rmbg-as-a-service==0.0.2" hf-transfer
+# Fetch only the rmbg-as-a-service wheel from TestPyPI (--no-deps), so TestPyPI never takes
+# part in dependency resolution -- otherwise junk squatted packages there (e.g. "FASTAPI")
+# outrank the real ones. Then install it with real PyPI as the index, CUDA torch from the
+# PyTorch index (its +cu126 build outranks the plain wheel by local-version ordering).
+RUN pip download --no-deps --dest /tmp/pkg \
+        --index-url https://test.pypi.org/simple/ \
+        "rmbg-as-a-service==0.0.2" \
+    && pip install \
+        --extra-index-url https://download.pytorch.org/whl/cu126 \
+        /tmp/pkg/*.whl hf-transfer \
+    && rm -rf /tmp/pkg
 
 EXPOSE 8000
 CMD ["rmbg-as-a-service"]

build/compose.yml

@@ -7,7 +7,7 @@ services:
     image: mindthemath/rmbg:${TAG:-latest}
     container_name: rmbg
     ports:
-      - "${PORT:-8000}:8000"
+      - "${PORT:-8001}:8000"
     environment:
       - NVIDIA_VISIBLE_DEVICES=all
       - NVIDIA_DRIVER_CAPABILITIES=compute,utility