Merge pull request #17 from JSchmie/docker

Docker

Dockerfile

@@ -1,8 +1,20 @@
 #pytorch Image
 FROM pytorch/pytorch:1.11.0-cuda11.3-cudnn8-runtime
+
+# Labels
+
+LABEL maintainer="Jacob Schmieder"
+LABEL email="Jacob.Schmieder@dbfz.de"
+LABEL version="0.1.1.dev"
+LABEL description="Scraibe is a tool for automatic speech recognition and speaker diarization. \
+                    It is based on the Hugging Face Transformers library and the Pyannote library. \
+                    It is designed to be used with the Whisper model, a lightweight model for automatic \
+                    speech recognition and speaker diarization."
+LABEL url="https://github.com/JSchmie/ScrAIbe"
+
 # Install dependencies
 WORKDIR /app
-ARG hf_token
+ARG model_name=medium
 #Enviorment Dependncies
 ENV TRANSFORMERS_CACHE /app/models
 ENV HF_HOME /app/models
@@ -10,17 +22,25 @@ ENV AUTOT_CACHE /app/models
 ENV PYANNOTE_CACHE /app/models/pyannote
 #Copy all necessary files 
 COPY requirements.txt /app/requirements.txt
-COPY scraibe /app/Scraibe
+COPY README.md /app/README.md
+COPY models /app/models
+COPY scraibe /app/scraibe
 COPY setup.py /app/setup.py
+
 #Installing all necessary Dependencies and Running the Application with a personalised Hugging-Face-Token
+RUN apt update && apt-get install -y libsm6 libxrender1 libfontconfig1
+RUN conda update --all
+
 RUN conda install pip
 RUN conda install -y ffmpeg 
 RUN conda install -c conda-forge libsndfile
 RUN pip install torchaudio==0.11.0+cu113 -f https://download.pytorch.org/whl/torch_stable.html
-RUN pip install /app/ 
+RUN pip install -r requirements.txt
 RUN pip install markupsafe==2.0.1 --force-reinstall
-RUN Scraibe  --hf_token $hf_token
+
+RUN python3 -m 'scraibe.cli' --whisper-model-name $model_name
 # Expose port
 EXPOSE 7860
 # Run the application
-ENTRYPOINT ["scraibe"]  
+
+ENTRYPOINT ["python3", "-m",  "scraibe.cli" ,"--whisper-model-name", "$model_name"]