add note that these environments are designed for short-long bots only.

docs/freqai-reinforcement-learning.md

@@ -224,3 +224,6 @@ FreqAI provides two base environments, `Base4ActionEnvironment` and `Base5Action
 * the actions consumed by the user strategy
 
 Both of the FreqAI provided environments inherit from an action/position agnostic environment object called the `BaseEnvironment`, which contains all shared logic. The architecture is designed to be easily customized. The simplest customization is the `calculate_reward()` (see details [here](#creating-the-reward)). However, the customizations can be further extended into any of the functions inside the environment. You can do this by simply overriding those functions inside your `MyRLEnv` in the prediction model file. Or for more advanced customizations, it is encouraged to create an entirely new environment inherited from `BaseEnvironment`. 
+
+!!! Note
+    FreqAI does not provide by default, a long-only training environment. However, creating one should be as simple as copy-pasting one of the built in environments and removing the `short` actions (and all associated references to those).