Trubrics

Changed
- Added trubrics_platform_auth into titanic example app
- Upgrade streamlit>=1.18.0

Fixed
- Fix `Unauthenticated` error in Trubrics platform auth with refresh function parameter

Fixed
- Fixed `trubrics run` with new .json file corresponding to new `Trubric` data model

Added
- Functionality to fail a Trubric run (cli or notebook) based on the severity of validations
- New integration with MlFlow 🎉 - you can now:
- Validate an mlflow run with Trubrics with `mlflow.evaluate(evaluators="trubrics")`
- Save all validation results to the MLflow UI
- Write custom python functions to validate your data or models with MLflow

Changed
- Changed data model of `Trubric` object
- Tutorials for classification and regression models added to docs, ready to run in google colab
- Removed notebook run in the docs CI

Fixed
- Users can now trubrics init with environment variables
- Clearer trubrics init documentation

Added
- New methods of `FeedbackCollector` to allow for the use of standalone Trubrics UI components. E.g. `collector.st_faces_ui()`
- Open question feedback option to collect with feedback types "issue" & "faces"
- Disable on click functionality for a smoother user experience with feedback types
- `Feedback` pydantic model returned from `st_feedback()` method

Changed
- Updated data model for the Feedback object
- Add a note to the demo app explaining the experiment features
- Changed order of feedback and validations in README
- `Feedback` components are now decoupled from the data context