Multi label regression summed to 1

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I have data of renovation jobs - each job requires at least one of 3 skills - carpenter, painter and ceramics. For each row my labels are share of time each skill is required for each job (summed to 1). Sample:

Job Description (free text)     Location     Estimated Cost      Main material    Carpenter   Painter   Ceramics
Paint Smiths' House and Parquet  Chicago      4000                 Parquet            0.1       0.15      0.75
Total renovation and pool        New York     15700                Metal              0.6       0.2       0.2
Pink decorations                 New York     12000                Wallpaper          0.7       0.05      0.25

I want to train the model to predict the shares of the skills. I was thinking about MultiOutputRegressor of scikit-learn, but my main issue is to oblige the predictions to be >=0 and summed to 1. Is there an off the shelf solution?

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