diff --git a/tests/test_autotranscript.py b/tests/test_autotranscript.py
new file mode 100644
index 0000000..475f4de
--- /dev/null
+++ b/tests/test_autotranscript.py
@@ -0,0 +1,120 @@
+import pytest
+from scraibe import Transcriber
+from unittest.mock import patch, mock_open
+import os
+
+def test_load_pyannote_model():
+    """
+    Test load_pyannote_test
+    """
+    from pyannote.audio.pipelines.speaker_diarization import SpeakerDiarization
+    from pyannote.audio import Pipeline
+
+    pipeline = Pipeline.from_pretrained("models/pyannote/speaker_diarization/config.yaml")
+    assert isinstance(pipeline, SpeakerDiarization)
+
+# Test Transcribtion class
+
+
+@pytest.fixture
+def transcriber():
+    """
+    Prepare Transcriber for testing
+    Returns: Transcriber Object
+    """
+
+    return Transcriber.load_model("medium", local=True)
+
+
+def test_Transcriber_init(transcriber):
+    """
+    Test Transcriber initialization with a whisper model 
+    """
+    
+    assert isinstance(transcriber, Transcriber)
+
+def test_transcription(transcriber):
+    """
+    Test transcription
+    """
+
+    transcript = transcriber.transcribe("tests/test.wav") 
+    assert isinstance(transcript, str)
+    
+def test_save_transcript_to_file(transcriber):
+    """
+    Test save_transcript_to_file
+    """
+    transcript = transcriber.transcribe("tests/test.wav")
+
+    Transcriber.save_transcript(transcript, "tests/output.txt")
+    
+    assert os.path.exists("tests/output.txt")
+
+    os.remove("tests/output.txt")
+    
+# Test Diaraization class
+
+from scraibe import Diariser
+
+@pytest.fixture
+def diarisation():
+    """
+    Prepare Diarisation for testing
+    Returns: Diarisation Object
+    """
+
+    return Diariser.load_model("models/pyannote/speaker_diarization/config.yaml", local=True)
+
+def test_Diarisation_init(diarisation):
+    """
+    Test Diarisation initialization with a pyannote model 
+    """
+    
+    assert isinstance(diarisation, Diariser)
+
+def test_diarisation(diarisation):
+    """
+    Test diarisation
+    """
+
+    diarisation = diarisation.diarization("tests/test.wav") 
+    assert isinstance(diarisation, dict)
+
+# Test AudioProcessor
+
+from scraibe import AudioProcessor , TorchAudioProcessor
+
+
+def test_AudioProcessor_init():
+    """
+    Test AudioProcessor initialization
+    """
+    audio = AudioProcessor("tests/test.wav")
+    assert isinstance(audio, AudioProcessor)
+
+def test_AudioProcessor_convert():
+    """
+    Test AudioProcessor convert
+    """
+    audio = AudioProcessor("tests/test.wav")
+    audio.convert_audio("tests/test.mp3", format="mp3")
+    assert os.path.exists("tests/test.mp3")
+    
+def test_TorchAudioProcessor_from_file():
+    """
+    Test TorchAudioProcessor initialization
+    """
+    audio = TorchAudioProcessor.from_file("tests/test.wav")
+    
+    assert isinstance(audio, TorchAudioProcessor)
+    
+    os.remove("tests/test.mp3")
+
+
+def test_TorchAudioProcessor_from_ffmpeg():
+    """
+    Test TorchAudioProcessor initialization
+    """
+    audio = TorchAudioProcessor.from_ffmpeg("tests/test.wav")
+    assert isinstance(audio, TorchAudioProcessor)