Try micromamba

Dockerfile

@@ -1,16 +1,12 @@
 # read the doc: https://huggingface.co/docs/hub/spaces-sdks-docker
-# you will also find guides on how best to write your Dockerfile
-
 FROM python:3.9
 
 WORKDIR /code
 
 # Set up a new user named "user" with user ID 1000
 RUN useradd -m -u 1000 user
-
 # Switch to the "user" user
 USER user
-
 # Set home to the user's home directory
 ENV HOME=/home/user \
     PATH=/home/user/.local/bin:$PATH
@@ -18,35 +14,44 @@ ENV HOME=/home/user \
 # Set the working directory to the user's home directory
 WORKDIR $HOME/app
 
-# Install conda
+# --- CHANGED: Install Micromamba instead of Miniconda ---
+# Micromamba is a single binary (C++) that uses significantly less RAM than Conda + Python
+USER root
 RUN set -ex; \
     ARCH=$(uname -m); \
     if [ "$ARCH" = "x86_64" ]; then \
-        URL="https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh"; \
+        URL="https://micro.mamba.pm/api/micromamba/linux-64/latest"; \
     elif [ "$ARCH" = "aarch64" ]; then \
-        URL="https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-aarch64.sh"; \
+        URL="https://micro.mamba.pm/api/micromamba/linux-aarch64/latest"; \
     else \
         echo "Unsupported architecture: $ARCH"; exit 1; \
     fi; \
-    echo "Downloading Miniconda installer for $ARCH from $URL"; \
-    mkdir -p ~/miniconda3; \
-    wget --quiet "$URL" -O ~/miniconda3/miniconda.sh; \
-    bash ~/miniconda3/miniconda.sh -b -u -p ~/miniconda3; \
-    rm ~/miniconda3/miniconda.sh
-ENV PATH="$HOME/miniconda3/bin:${PATH}"
-
-RUN --mount=type=secret,id=GH_TOKEN,mode=0444,required=true \
-  git clone https://$(cat /run/secrets/GH_TOKEN)@github.com/squaresLab/idioms
+    # Install curl/tar if missing (python:3.9 usually has them, but good practice)
+    apt-get update && apt-get install -y curl tar bzip2 && rm -rf /var/lib/apt/lists/*; \
+    # Download and extract binary to /bin/micromamba
+    curl -Ls "$URL" | tar -xvj -C /usr/local/bin/ --strip-components=1 bin/micromamba; \
+    # Ensure it's executable
+    chmod +x /usr/local/bin/micromamba
+
+# Switch back to user
+USER user
 
-RUN conda tos accept --override-channels --channel https://repo.anaconda.com/pkgs/main && \
-    conda tos accept --override-channels --channel https://repo.anaconda.com/pkgs/r
+# Configure Micromamba root location
+ENV MAMBA_ROOT_PREFIX=/home/user/micromamba
 
-# solver uses too much memory
-RUN conda config --set solver libmamba
+# Clone the repo
+RUN --mount=type=secret,id=GH_TOKEN,mode=0444,required=true \
+    git clone https://$(cat /run/secrets/GH_TOKEN)@github.com/squaresLab/idioms
 
-RUN conda env create -f idioms/env.yml 
+# --- CHANGED: Create environment using Micromamba ---
+# Note: We removed 'conda tos accept' because Micromamba handles this differently/implicitly
+# We use 'create' to make the env named 'idioms'
+RUN micromamba create -y -n idioms -f idioms/env.yml && \
+    micromamba clean --all --yes
 
-ENV PATH="/home/user/miniconda3/envs/idioms/bin:${PATH}"
+# --- CHANGED: Update PATH to point to Micromamba env ---
+# Micromamba puts envs in $MAMBA_ROOT_PREFIX/envs
+ENV PATH="${MAMBA_ROOT_PREFIX}/envs/idioms/bin:${PATH}"
 ENV PYTHONPATH="${PYTHONPATH}:${HOME}/app/idioms"
 
 # Install the gradio app's requirements too