Try Gemini 1.5 models, our newest multimodal models in Vertex AI, and see what you can build with a 1M token context window.Try Gemini 1.5 models, our newest multimodal models in Vertex AI, and see what you can build with a 1M token context window.
Stay organized with collections
Save and categorize content based on your preferences.
Writing a script in Docker to set up your environment
You can query a model directly and test the results returned when using
different parameter values with the Cloud console, or by calling the
Vertex AI API directly.
Generate a Docker script to create a simple linux machine that has python 3.10 (prebuilt) installed with following libraries: pandas, tensorflow, numpy
Response
# Base image with Python 3.10
FROM python:3.10-slim
# Install required libraries
RUN pip install pandas tensorflow numpy
# Set working directory
WORKDIR /app
# Copy your application code to the container
COPY . /app
# Expose port for your application (if needed)
# EXPOSE 8000
# Run your application
CMD ["python", "your_script.py"]
Explanation:
FROM python:3.10-slim: This line specifies the base image for the Docker container. We're using the official Python 3.10 image with the slim tag, which is a smaller and more efficient image.
RUN pip install pandas tensorflow numpy: This line installs the required Python libraries using pip.
WORKDIR /app: This line sets the working directory inside the container to /app. This is where your application code will be placed.
COPY . /app: This line copies all files from your current directory (where the Dockerfile is located) to the /app directory inside the container. This includes your application code.
EXPOSE 8000: This line exposes port 8000 on the container. You can change this to the port your application uses. This is optional and only needed if your application needs to be accessible from outside the container.
CMD ["python", "your_script.py"]: This line specifies the command to run when the container starts. In this case, it runs your Python script your_script.py. Replace your_script.py with the actual name of your script.
To build the Docker image:
Save the above Dockerfile in a file named Dockerfile.
Open a terminal in the same directory as the Dockerfile.
Run the following command:
docker build -t my-python-app .
This will build the Docker image and tag it as my-python-app.
To run the Docker container:
docker run -it my-python-app
This will start the container in interactive mode. Your application will now be running inside the container.
Note:
Replace your_script.py with the actual name of your Python script.
You can add more commands to the Dockerfile to customize your container further, such as installing additional libraries or setting environment variables.
This Dockerfile assumes you have your application code in the same directory as the Dockerfile. If your code is in a different directory, adjust the COPY command accordingly.
