- asking to use a plugin for which you do not have a version defined - tools to easily select versions
- goal not found in a plugin (probably could list the ones that are)

 */

// PluginNotFoundException, PluginResolutionException, PluginDescriptorParsingException,
// CycleDetectedInPluginGraphException;

/**
 * Transform an exception into useful end-user message.
 */

`ModelServer` collates all computation graphs exposed to it (from multiple
`SavedModel`) and executes them in parallel on available executors. Running
TensorFlow in a multitenant design mixes the risks described above with the
inherent ones from multitenant configurations. The primary areas of concern are
tenant isolation, resource allocation, model sharing and hardware attacks.

### Tenant isolation

  /**
   * When we need a new thread to run tasks, we call [Backend.execute]. A few microseconds later we
   * expect a newly-started thread to call [Runnable.run]. We shouldn't request new threads until
   * the already-requested ones are in service, otherwise we might create more threads than we need.
   *
   * We use [executeCallCount] and [runCallCount] to defend against starting more threads than we
   * need. Both fields are guarded by [lock].
   */

   *         .build();
   * }</pre>
   *
   * <p>Builder instances can be reused; it is safe to call {@link #build} multiple times to build
   * multiple graphs in series. Each new graph contains all the elements of the ones created before
   * it.
   *
   * @since 28.0
   */
  public static class Builder<N, V> {

    private final MutableValueGraph<N, V> mutableValueGraph;

This can be used as a quick shortcut if you have only one Pydantic model and want to remove some data from the output.

/// tip

But it is still recommended to use the ideas above, using multiple classes, instead of these parameters.

* Response payloads.

You would also have **inline errors** for everything.

And whenever you update the backend code, and **regenerate** the frontend, it would have any new *path operations* available as methods, the old ones removed, and any other change would be reflected on the generated code. 🤓

Create a PassLib "context". This is what will be used to hash and verify passwords.

/// tip

The PassLib context also has functionality to use different hashing algorithms, including deprecated old ones only to allow verifying them, etc.

For example, you could use it to read and verify passwords generated by another system (like Django) but hash any new passwords with a different algorithm like Bcrypt.

   * invoked in the same order as the underlying service enters those states. Additionally, at most
   * one of the listener's callbacks will execute at once. However, multiple listeners' callbacks
   * may execute concurrently, and listeners may execute in an order different from the one in which
   * they were registered.
   *
   * <p>RuntimeExceptions thrown by a listener will be caught and logged. Any exception thrown

So, you can confirm if you are in the correct virtual environment.

/// tip

It's easy to activate one virtual environment, get one Python, and then **go to another project**.

And the second project **wouldn't work** because you are using the **incorrect Python**, from a virtual environment for another project.

 *    Messages in either direction are enqueued for immediate transmission.
 *
 *  * **Closing:** one of the peers on the web socket has initiated a graceful shutdown. The web
 *    socket will continue to transmit already-enqueued messages but will refuse to enqueue new
 *    ones.
 *
 *  * **Closed:** the web socket has transmitted all of its messages and has received all messages
 *    from the peer.
 *