Honor RAMALAMA_IMAGE if set

[rhatdan]

Currently on my cuda laptop, if I set RAMALAMA_IMAGE to something, ramalama ignores it and forces cuda image.

Summary by Sourcery

Bug Fixes:

• Fixed a bug where the RAMALAMA_IMAGE environment variable was being ignored, and the CUDA image was always being used.

[sourcery-ai]

Reviewer's Guide by Sourcery

This PR ensures that the RAMALAMA_IMAGE environment variable is respected, preventing the application from defaulting to the CUDA image when a custom image is specified via the environment variable. It also introduces a DEFAULT_IMAGE constant to avoid hardcoding the default image.

Class diagram showing the updated image handling

classDiagram
    class common {
        +DEFAULT_IMAGE: string
        +default_image(): string
        +container_manager()
    }
    class model {
        -_image(args)
        +attempt_to_use_versioned(conman, image, vers, args)
    }
    note for common "DEFAULT_IMAGE constant added"
    note for model "Updated image comparison logic"

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Flow diagram for image selection logic after changes

graph TD
    A[Start] --> B{RAMALAMA_IMAGE set?}
    B -->|Yes| C[Use RAMALAMA_IMAGE]
    B -->|No| D{args.image != DEFAULT_IMAGE?}
    D -->|Yes| E[Use args.image]
    D -->|No| F[Use DEFAULT_IMAGE]
    C --> G[End]
    E --> G
    F --> G

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File-Level Changes

Change	Details	Files
Respect RAMALAMA_IMAGE environment variable.	Added DEFAULT_IMAGE constant. Modified default_image() to return DEFAULT_IMAGE if no image is set. Modified _image() to check against DEFAULT_IMAGE instead of hardcoded image.	ramalama/common.py ramalama/model.py

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[sourcery-ai]

Hey @rhatdan - I've reviewed your changes - here's some feedback:

Overall Comments:

• In model.py, comparing against DEFAULT_IMAGE instead of default_image() bypasses the environment variable check. This will prevent RAMALAMA_IMAGE from being honored. Please continue using default_image() for the comparison.

Here's what I looked at during the review

• 🟢 General issues: all looks good
• 🟢 Security: all looks good
• 🟢 Testing: all looks good
• 🟢 Complexity: all looks good
• 🟢 Documentation: all looks good

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