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Download Dockerfile from codey-lab/Multi-LLM-API-Gateway: direct link, hf CLI and curl.
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- Download file 1.01 kB
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https://huggingface.co/spaces/codey-lab/Multi-LLM-API-Gateway/resolve/refs%2Fpr%2F3/Dockerfile
- Command line
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hf download hf://spaces/codey-lab/Multi-LLM-API-Gateway@refs/pr/3/Dockerfile
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curl -L -o Dockerfile https://huggingface.co/spaces/codey-lab/Multi-LLM-API-Gateway/resolve/refs%2Fpr%2F3/Dockerfile
1.01 kB
| # Use an official Python runtime as a parent image. | |
| # We choose a slim version to keep the image size small. | |
| FROM python:3.10-slim | |
| # Set the working directory in the container. | |
| # All subsequent commands will be executed in this directory. | |
| WORKDIR /app | |
| # Copy the requirements file into the container. | |
| # We do this first to leverage Docker's layer caching. | |
| # If requirements.txt doesn't change, this step is skipped. | |
| COPY requirements.txt ./ | |
| # Install any needed packages specified in requirements.txt. | |
| # The --no-cache-dir flag helps to keep the image smaller. | |
| RUN pip install --no-cache-dir -r requirements.txt | |
| # Copy the rest of the application code into the working directory. | |
| COPY . . | |
| # Expose a port if your application is a web server. | |
| # For example, if your application runs on port 8000. | |
| # EXPOSE 8000 | |
| # Define the command to run your application. | |
| # This command will be executed when the container starts. | |
| # We use main.py as the entry point, as per our architecture. | |
| CMD ["python", "main.py"] | |