Unfortunately we cannot do strict floats or ints.
The batch data models don't specify the value types, it instead relies on pydantic parsing. JSON doesn't differentiate between float and int, so a float `1.0` gets parsed as `1` in python.
As a result, we _must_ accept mixed floats and ints for BatchDatum.items.
Tests and validation updated to handle this.
Maybe we should update the BatchDatum model to have a `type` field? Then we could parse as float or int, depending on the inputs...
This is required to fix an issue with the MM UI's error handling.
Previously, we only included the model source as a string. That could be an arbitrary URL, file path or HF repo id, but the frontend has no parsing logic to differentiate between these different model sources.
Without access to the type of model source, it is difficult to determine how the user should proceed. For example, if it's HF URL with an HTTP unauthorized error, we should direct the user to log in to HF. But if it's a civitai URL with the same error, we should not direct the user to HF.
There are a variety of related edge cases.
With this change, the full `ModelSource` object is included in each model install event, including error events.
I had to fix some circular import issues, hence the import changes to files other than `events_common.py`.
Uvicorn's logging is rather verbose. This change adds a `log_level_network` config setting to independently control uvicorn's log outputs. The setting defaults to warning.
The change hides the helpful startup message that says the host and port we are running on.
For example: `Uvicorn running on http://0.0.0.0:9090 (Press CTRL+C to quit`
The ASGI lifespan handler is updated to log an equivalent message on startup, regardless of log level settings.
Besides being helpful, the launcher relies on a message like this to launch the app. So, previously, if the user set their log level to anything above info (e.g. warning or error), the launcher would fail to open the app. This change prevents that edge case.
