ExceptionDispatchInfo. The JSON-RPC connection with the remote party was lost before the request could complete.

**System Information (please complete the following information):**
- Model Builder or CLI Version: 17.17.0
- Visual Studio Version (if applicable): 17.8.5
- .NET version: 8.0.101

**Describe the bug**
- page of the tutorial: https://learn.microsoft.com/en-us/training/modules/predictive-maintenance-model-builder/3-choose-scenario-data
- Clear description of the problem:

Stack:
at System.Runtime.ExceptionServices.ExceptionDispatchInfo.Throw()
at System.Runtime.CompilerServices.TaskAwaiter.HandleNonSuccessAndDebuggerNotification(Task task)
at StreamJsonRpc.JsonRpc.d__162.MoveNext()
--- End of stack trace from previous location where exception was thrown ---
at System.Runtime.ExceptionServices.ExceptionDispatchInfo.Throw()
at System.Runtime.CompilerServices.TaskAwaiter.HandleNonSuccessAndDebuggerNotification(Task task)
at StreamJsonRpc.JsonRpc.d__151`1.MoveNext()
--- End of stack trace from previous location where exception was thrown ---
at System.Runtime.ExceptionServices.ExceptionDispatchInfo.Throw()
at System.Runtime.CompilerServices.TaskAwaiter.HandleNonSuccessAndDebuggerNotification(Task task)
at Microsoft.ML.ModelBuilder.ViewModels.TrainViewModel.<b__92_0>d.MoveNext()

**To Reproduce**
Steps to reproduce the behavior:
1. Create and open cross-platform console project
2. Solution Explorer -> right click on *project name* -> Add -> Machine Learning Model
3. Scenario is "Text classification"
4. Environment is "Local CPU" (Intel Core i3-8130U, 8 GB RAM)
5. Data source type is CSV file, column to predict is "respondent", text column is "question" (see screenshots)
6. Click train

**Expected behavior**
Training is finished without exceptions.

**Screenshots**
If applicable, add screenshots to help explain your problem.

Error:

CSV file content:

**Additional context**
Add any other context about the problem here.

Non sono indicati né un file sorgente né un test. Inizia riproducendo il flusso di training di Text classification con il CSV elencato e l’ambiente Local CPU, quindi traccia il failure da TrainViewModel attraverso lo stack StreamJsonRpc; il lavoro è completato quando il training termina senza l’eccezione segnalata.

Scritto dal modello di indicizzazione a partire dal testo della issue.