Initial commit: LocalAI-backed ScrAIbe with summarization

Dockerfile

@@ -1,44 +1,43 @@
-#pytorch Image
-FROM pytorch/pytorch:2.3.1-cuda12.1-cudnn8-runtime
+# Lightweight Python base image (no GPU/PyTorch needed)
+FROM python:3.11-slim
 
 # 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 description="Scraibe: LocalAI-backed transcription and diarization client with summarization. \
+                    Sends audio to a LocalAI server running vibevoice.cpp and uses a second LLM for summarization."
 LABEL url="https://github.com/JSchmie/ScrAIbe"
 
-# Install dependencies
-WORKDIR /app
-#Enviorment dependencies
-ENV TRANSFORMERS_CACHE=/app/models
-ENV HF_HOME=/app/models
-ENV AUTOT_CACHE=/app/models
-ENV PYANNOTE_CACHE=/app/models/pyannote
-#Copy all necessary files 
-COPY requirements.txt /app/requirements.txt
-COPY README.md /app/README.md
-COPY scraibe /app/scraibe
-
-#Installing all necessary dependencies and running the application with a personalised Hugging-Face-Token
-RUN apt update -y && apt upgrade -y && \
-    apt install -y libsm6 libxrender1 libfontconfig1 && \
+# Install system dependencies (ffmpeg required)
+RUN apt update -y && \
+    apt install -y --no-install-recommends ffmpeg && \
     apt clean && \
     rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/*
 
-RUN conda update --all && \
-    # conda install -y pip ffmpeg && \
-    conda install -c conda-forge libsndfile && \
-    conda clean --all -y
-# RUN pip install torchaudio==0.11.0+cu113 -f https://download.pytorch.org/whl/torch_stable.html
+# Working directory
+WORKDIR /app
+
+# Environment variables for LocalAI (transcription/diarization)
+# Set these via docker run -e or docker-compose
+ENV LOCALAI_API_URL=http://localhost:8080
+ENV LOCALAI_API_KEY=
+ENV LOCALAI_MODEL=vibevoice-diarize
+
+# Environment variables for Summarizer LLM
+ENV SUMMARIZER_API_URL=http://localhost:8080
+ENV SUMMARIZER_API_KEY=
+ENV SUMMARIZER_MODEL=llama-3.1-8b-instruct
+
+# Copy and install Python dependencies
+COPY requirements.txt /app/requirements.txt
 RUN pip install --no-cache-dir -r requirements.txt
 
-# Expose port
-EXPOSE 7860
-# Run the application
+# Copy application code
+COPY scraibe /app/scraibe
 
-ENTRYPOINT ["python3", "-m",  "scraibe.cli"]  
+# Expose port (if UI is served)
+EXPOSE 7860
+
+# Run the application
+ENTRYPOINT ["python3", "-m", "scraibe.cli"]