At least in terms of integration, TensorForce aims to be a "plug and play" library. However, RL is not at a stage right now where you can just plug an algorithm to any kind of problem and expect it to learn. Hyperparameter tuning is always necessary.

Still, TensorForce does provide pluggable implementations of state-of-the-art algorithms as well as runner utilities and environment abstractions to make it easy to connect your learning problem to it.