GCP-Dental-Caries-Detection-Cloud-Deployment: A Python repository from Saba-Gul

Here’s a step-by-step guide to deploying your Gradio application on Google Cloud Platform (GCP) using Cloud Run, including all necessary steps, configurations, and commands.

Step-by-Step Guide to Deploy a Gradio App on GCP

Prerequisites

A Google Cloud account.
Google Cloud SDK installed (if deploying from local).
Docker installed (if building the image locally).
Your Gradio app code ready.

1. Set Up Your GCP Project

Create a New Project:
- Go to the Google Cloud Console.
- Click on the project dropdown at the top and select New Project.
- Enter a project name and click Create.
Set the Project ID:
- After creating the project, take note of your Project ID. You’ll use it in commands.
Enable Billing:
- Ensure that billing is enabled for your project. You can set this up in the Billing section of the Cloud Console.
Enable Required APIs:
- Go to the APIs & Services > Library.
- Enable the Cloud Run API and the Cloud Build API.

2. Prepare Your Application

Organize Your Files:

Structure your application with the following files:

/app
  ├── gradio-app.py
  └── requirements.txt
Dockerfile

Create requirements.txt:
- List all necessary Python packages in requirements.txt, including Gradio and any other dependencies.

Create Dockerfile:

Use the following Dockerfile:

# Use an official Python runtime as a parent image
FROM python:3.10-slim

# Set the working directory in the container
WORKDIR /app

# Install system dependencies required by OpenCV and other libraries
RUN apt-get update && apt-get install -y \
    libgl1-mesa-glx \
    libglib2.0-0 \
    libsm6 \
    libxext6 \
    libxrender1

# Upgrade pip and setuptools to avoid dependency issues
RUN pip install --upgrade pip setuptools

# Copy requirements.txt first
COPY requirements.txt /app

# Install any needed packages specified in requirements.txt
RUN pip install --no-cache-dir -r requirements.txt

# Copy the application code incrementally
COPY app/ /app

# Expose the port defined by the PORT environment variable
EXPOSE 8080

# Define environment variable for Gradio app
ENV GRADIO_SERVER_NAME="0.0.0.0"

# Set the PORT environment variable to 8080 (default for Cloud Run)
ENV PORT=8080

# Run the application
CMD ["python", "gradio-app.py"]

3. Build and Push Your Docker Image

Open Cloud Shell (or your terminal if you have the SDK installed):
- Click the Activate Cloud Shell button in the Google Cloud Console or open your terminal.
Authenticate with GCP (if using local terminal):
```
gcloud auth login
```

Set the Project:

gcloud config set project YOUR_PROJECT_ID

Build the Docker Image:
- If using Cloud Shell, you can use the built-in Docker, or if using local Docker:
```
gcloud builds submit --tag gcr.io/YOUR_PROJECT_ID/gradio-app
```
- This command builds the Docker image and uploads it to Google Container Registry.

4. Deploy the Docker Image to Cloud Run

Deploy to Cloud Run:

gcloud run deploy gradio-app \
    --image gcr.io/YOUR_PROJECT_ID/gradio-app \
    --platform managed \
    --region YOUR_REGION \
    --allow-unauthenticated

Replace YOUR_REGION with the preferred region (e.g., us-central1).

Confirm Deployment:
- Once the deployment is complete, you’ll see a URL where your Gradio app is hosted.

5. Access Your Gradio App

Open the URL provided in the deployment confirmation to access your Gradio app.

6. Clean Up Resources

To avoid incurring charges, remember to delete your Cloud Run service and any other associated resources when you’re done testing.

Delete Cloud Run Service:

Navigate to Cloud Run in the Google Cloud Console.
Select your service and click Delete.

Additional Considerations

Memory and Scaling: Adjust the memory limit and scaling settings during deployment if your app needs more resources.
Environment Variables: Set any environment variables your app requires using the --set-env-vars flag during deployment.

By following these steps, you should be able to successfully deploy your Gradio application on Google Cloud Platform using Cloud Run. If you encounter any issues, consult the GCP documentation for further assistance.

Saba-Gul/GCP-Dental-Caries-Detection-Cloud-Deployment