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Dockerfile

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+FROM python:3.12.3
+
+WORKDIR /app
+
+COPY ./requirements.txt /app/requirements.txt
+
+RUN pip install --no-cache-dir --upgrade -r /app/requirements.txt
+
+# 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
+
+# Set the working directory to the user's home directory
+WORKDIR $HOME/app
+
+# Copy the current directory contents into the container at $HOME/app setting the owner to the user
+COPY --chown=user ./export.pkl ./app.py ./
+
+CMD ["python", "app.py"]

app.py

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+import gradio as gr
+from fastai.vision.all import load_learner, PILImage
+
+# Load your exported fastai model
+model_path = "export.pkl"  # your exported .pkl
+learn = load_learner(model_path)
+
+# Prediction function
+def predict(image):
+    img = PILImage.create(image)  # ensure it's a fastai PILImage
+    pred_class, pred_idx, outputs = learn.predict(img)
+
+    return (str(pred_class))
+
+# Gradio interface
+iface = gr.Interface(
+    fn=predict,
+    inputs=gr.Image(type="pil"),
+    outputs=gr.Textbox(label="Prediction"),
+    title="FastAI Image Classification",
+    description="Upload an image to get prediction from your exported fastai model."
+)
+
+if __name__ == "__main__":
+    iface.launch(server_name="0.0.0.0", server_port=7860)

export.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:0f94fddede2a9a570ea61a396703a9120c402cd5028e7317d9f98af2482d1db6
+size 46986313

requirements.txt

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+fastai==2.8.6
+gradio==6.2.0
+torch==2.9.1
+IPython