Merge pull request #77 from JSchmie/enhance_capability_with_webui

Enhance capability with webui

.gitignore

@@ -4,3 +4,239 @@ scraibe/app/*__pycache__
 scraibe/.pyannotetoken
 
 
+# Created by https://www.toptal.com/developers/gitignore/api/python,visualstudiocode,linux,windows
+# Edit at https://www.toptal.com/developers/gitignore?templates=python,visualstudiocode,linux,windows
+
+### Linux ###
+*~
+
+# temporary files which can be created if a process still has a handle open of a deleted file
+.fuse_hidden*
+
+# KDE directory preferences
+.directory
+
+# Linux trash folder which might appear on any partition or disk
+.Trash-*
+
+# .nfs files are created when an open file is removed but is still being accessed
+.nfs*
+
+### Python ###
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+.pybuilder/
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+#   For a library or package, you might want to ignore these files since the code is
+#   intended to run in multiple environments; otherwise, check them in:
+# .python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# poetry
+#   Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
+#   This is especially recommended for binary packages to ensure reproducibility, and is more
+#   commonly ignored for libraries.
+#   https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
+#poetry.lock
+
+# pdm
+#   Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
+#pdm.lock
+#   pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
+#   in version control.
+#   https://pdm.fming.dev/#use-with-ide
+.pdm.toml
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# pytype static type analyzer
+.pytype/
+
+# Cython debug symbols
+cython_debug/
+
+# PyCharm
+#  JetBrains specific template is maintained in a separate JetBrains.gitignore that can
+#  be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
+#  and can be added to the global gitignore or merged into this file.  For a more nuclear
+#  option (not recommended) you can uncomment the following to ignore the entire idea folder.
+#.idea/
+
+### Python Patch ###
+# Poetry local configuration file - https://python-poetry.org/docs/configuration/#local-configuration
+poetry.toml
+
+# ruff
+.ruff_cache/
+
+# LSP config files
+pyrightconfig.json
+
+### VisualStudioCode ###
+.vscode/*
+!.vscode/settings.json
+!.vscode/tasks.json
+!.vscode/launch.json
+!.vscode/extensions.json
+!.vscode/*.code-snippets
+
+# Local History for Visual Studio Code
+.history/
+
+# Built Visual Studio Code Extensions
+*.vsix
+
+### VisualStudioCode Patch ###
+# Ignore all local history of files
+.history
+.ionide
+
+### Windows ###
+# Windows thumbnail cache files
+Thumbs.db
+Thumbs.db:encryptable
+ehthumbs.db
+ehthumbs_vista.db
+
+# Dump file
+*.stackdump
+
+# Folder config file
+[Dd]esktop.ini
+
+# Recycle Bin used on file shares
+$RECYCLE.BIN/
+
+# Windows Installer files
+*.cab
+*.msi
+*.msix
+*.msm
+*.msp
+
+# Windows shortcuts
+*.lnk
+
+# End of https://www.toptal.com/developers/gitignore/api/python,visualstudiocode,linux,windows

scraibe/autotranscript.py

@@ -95,7 +95,7 @@ def __init__(self,
         elif isinstance(dia_model, str):
             self.diariser = Diariser.load_model(dia_model, **kwargs)
         else:
-            self.diariser = dia_model
+            self.diariser : Diariser = dia_model
 
         if kwargs.get("verbose"):
             print("Scraibe initialized all models successfully loaded.")
@@ -133,7 +133,7 @@ def autotranscribe(self, audio_file : Union[str, torch.Tensor, ndarray],
         if kwargs.get("verbose"):
             self.verbose = kwargs.get("verbose")
         # Get audio file as an AudioProcessor object
-        audio_file = self.get_audio_file(audio_file)
+        audio_file : AudioProcessor = self.get_audio_file(audio_file)
 
         # Prepare waveform and sample rate for diarization
         dia_audio = {
@@ -203,7 +203,7 @@ def diarization(self, audio_file : Union[str, torch.Tensor, ndarray],
         """
 
         # Get audio file as an AudioProcessor object
-        audio_file = self.get_audio_file(audio_file)
+        audio_file : AudioProcessor = self.get_audio_file(audio_file)
 
         # Prepare waveform and sample rate for diarization
         dia_audio = {
@@ -232,9 +232,56 @@ def transcribe(self, audio_file : Union[str, torch.Tensor, ndarray],
                 str:
                     The transcribed text from the audio source.
         """
-        audio_file = self.get_audio_file(audio_file)
+        audio_file : AudioProcessor  = self.get_audio_file(audio_file)
 
         return self.transcriber.transcribe(audio_file.waveform, **kwargs)      
+
+    def update_transcriber(self, whisper_model : Union[str, whisper], **kwargs) -> None:
+        """
+        Update the transcriber model.
+
+        Args:
+            whisper_model (Union[str, whisper]):
+                The new whisper model to use for transcription.
+            **kwargs:
+                Additional keyword arguments for the transcriber model.
+                
+            Returns:
+                None
+        """
+        _old_model = self.transcriber.model_name
+
+        if isinstance(whisper_model, str):
+            self.transcriber = Transcriber.load_model(whisper_model, **kwargs)
+        elif isinstance(whisper_model, Transcriber):
+            self.transcriber = whisper_model
+        else:
+            warn(f"Invalid model type. Please provide a valid model. Fallback to old {_old_model} Model.", RuntimeWarning)
+
+        return None
+
+    def update_diariser(self, dia_model : Union[str, DiarisationType], **kwargs) -> None:
+        """
+        Update the diariser model.
+
+        Args:
+            dia_model (Union[str, DiarisationType]):
+                The new diariser model to use for diarization.
+            **kwargs:
+                Additional keyword arguments for the diariser model.
+                
+            Returns:
+                None
+        """
+        if isinstance(dia_model, str):
+            self.diariser = Diariser.load_model(dia_model, **kwargs)
+        elif isinstance(dia_model, Diariser):
+            self.diariser = dia_model
+        else:
+            warn(f"Invalid model type. Please provide a valid model. Fallback to old Model.", RuntimeWarning)
+
+        return None
+
     @staticmethod
     def remove_audio_file(audio_file : str,
                           shred : bool = False) -> None:
@@ -269,7 +316,6 @@ def remove_audio_file(audio_file : str,
             print(f"Audiofile {audio_file} removed.")
 
 
-
     @staticmethod
     def get_audio_file(audio_file : Union[str, torch.Tensor, ndarray],
                         *args, **kwargs) -> AudioProcessor:
@@ -298,6 +344,7 @@ def get_audio_file(audio_file : Union[str, torch.Tensor, ndarray],
         if not isinstance(audio_file, AudioProcessor):
             raise ValueError(f'Audiofile must be of type AudioProcessor,' \
                              f'not {type(audio_file)}')     
+
         return audio_file
 
     def __repr__(self):

scraibe/transcriber.py

@@ -64,14 +64,18 @@ class Transcriber:
         The class supports various sizes and versions of Whisper models. Please refer to
         the load_model method for available options.
     """
-    def __init__(self, model: whisper ) -> None:
+    def __init__(self, model: whisper , model_name: str  ) -> None:
         """
         Initialize the Transcriber class with a Whisper model.
 
         Args:
             model (whisper): The Whisper model to use for transcription.
+            model_name (str): The name of the model.
         """
+
         self.model = model
+
+        self.model_name = model_name
 
     def transcribe(self, audio : Union[str, Tensor, ndarray] ,
                    *args, **kwargs) -> str:
@@ -137,6 +141,7 @@ def load_model(cls,
                         - 'medium'
                         - 'large-v1'
                         - 'large-v2'
+                        - 'large-v3'
                         - 'large'
                         
             download_root (str, optional): Path to download the model.
@@ -156,7 +161,7 @@ def load_model(cls,
         _model = load_model(model, download_root=download_root,
                             device=device, in_memory=in_memory)
 
-        return cls(_model)
+        return cls(_model, model_name=model)
 
     @staticmethod
     def _get_whisper_kwargs(**kwargs) -> dict:
@@ -179,4 +184,4 @@ def _get_whisper_kwargs(**kwargs) -> dict:
         return whisper_kwargs
 
     def __repr__(self) -> str:
-        return f"Transcriber(model={self.model})"
+        return f"Transcriber(model_name={self.model_name}, model={self.model})"