Add Docker support and FastAPI inference endpoint

- Create .dockerignore to exclude unnecessary files from the Docker context
- Update Dockerfile for optimized image building and non-privileged user
- Add README.Docker.md for building and deploying instructions
- Implement FastAPI application with a text classification endpoint
- Update requirements.txt to include transformers and PyTorch dependencies

.dockerignore

@@ -0,0 +1,34 @@
+# Include any files or directories that you don't want to be copied to your
+# container here (e.g., local build artifacts, temporary files, etc.).
+#
+# For more help, visit the .dockerignore file reference guide at
+# https://docs.docker.com/go/build-context-dockerignore/
+
+**/.DS_Store
+**/__pycache__
+**/.venv
+**/.classpath
+**/.dockerignore
+**/.env
+**/.git
+**/.gitignore
+**/.project
+**/.settings
+**/.toolstarget
+**/.vs
+**/.vscode
+**/*.*proj.user
+**/*.dbmdl
+**/*.jfm
+**/bin
+**/charts
+**/docker-compose*
+**/compose.y*ml
+**/Dockerfile*
+**/node_modules
+**/npm-debug.log
+**/obj
+**/secrets.dev.yaml
+**/values.dev.yaml
+LICENSE
+README.md

Dockerfile

@@ -1,16 +1,55 @@
-# Read the doc: https://huggingface.co/docs/hub/spaces-sdks-docker
-# you will also find guides on how best to write your Dockerfile
+# syntax=docker/dockerfile:1
 
-FROM python:3.9
+# Comments are provided throughout this file to help you get started.
+# If you need more help, visit the Dockerfile reference guide at
+# https://docs.docker.com/go/dockerfile-reference/
 
-RUN useradd -m -u 1000 user
-USER user
-ENV PATH="/home/user/.local/bin:$PATH"
+# Want to help us make this template better? Share your feedback here: https://forms.gle/ybq9Krt8jtBL3iCk7
+
+ARG PYTHON_VERSION=3.9.0
+FROM python:${PYTHON_VERSION}-slim as base
+
+# Prevents Python from writing pyc files.
+
+# Keeps Python from buffering stdout and stderr to avoid situations where
+# the application crashes without emitting any logs due to buffering.
+ENV PYTHONUNBUFFERED=1
 
 WORKDIR /app
 
-COPY --chown=user ./requirements.txt requirements.txt
-RUN pip install --no-cache-dir --upgrade -r requirements.txt
+# Create a non-privileged user that the app will run under.
+# See https://docs.docker.com/go/dockerfile-user-best-practices/
+ARG UID=10001
+RUN adduser \
+    --disabled-password \
+    --gecos "" \
+    --home "/nonexistent" \
+    --shell "/sbin/nologin" \
+    --no-create-home \
+    --uid "${UID}" \
+    appuser
+
+ENV PATH="/home/appuser/.local/bin:$PATH"
+
+COPY --chown=appuser ./requirements.txt requirements.txt
+RUN mkdir -p /app/.cache \
+    && chown -R appuser:appuser /app/.cache
+ENV TRANSFORMERS_CACHE=/app/.cache/huggingface/hub
 
+# Download dependencies as a separate step to take advantage of Docker's caching.
+# Leverage a cache mount to /root/.cache/pip to speed up subsequent builds.
+# Leverage a bind mount to requirements.txt to avoid having to copy them into
+# into this layer.
+RUN python -m pip install -r requirements.txt
+
+# Switch to the non-privileged user to run the application.
+USER appuser
+
+# Copy the source code into the container.
 COPY --chown=user . /app
+
+# Expose the port that the application listens on.
+EXPOSE 7860
+
+# Run the application.
 CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"]

README.Docker.md

@@ -0,0 +1,22 @@
+### Building and running your application
+
+When you're ready, start your application by running:
+`docker compose up --build`.
+
+Your application will be available at http://localhost:6300.
+
+### Deploying your application to the cloud
+
+First, build your image, e.g.: `docker build -t myapp .`.
+If your cloud uses a different CPU architecture than your development
+machine (e.g., you are on a Mac M1 and your cloud provider is amd64),
+you'll want to build the image for that platform, e.g.:
+`docker build --platform=linux/amd64 -t myapp .`.
+
+Then, push it to your registry, e.g. `docker push myregistry.com/myapp`.
+
+Consult Docker's [getting started](https://docs.docker.com/go/get-started-sharing/)
+docs for more detail on building and pushing.
+
+### References
+* [Docker's Python guide](https://docs.docker.com/language/python/)

app.py

@@ -1,7 +1,17 @@
 from fastapi import FastAPI
+from transformers import pipeline
+
+pipe = pipeline("text-classification", model="JungleLee/bert-toxic-comment-classification")
 
 app = FastAPI()
 
 @app.get("/")
-def greet_json():
-    return {"Hello": "World!"}
+async def welcome():
+    return "Welcome to Hopeline - AI Inference API"
+
+@app.get('/predict')
+async def predict(text: str):
+    prediction = pipe(text)
+    return prediction
+
+

requirements.txt

@@ -1,2 +1,5 @@
 fastapi
 uvicorn[standard]
+transformers
+torch
+torchvision