Update Dockerfile

Dockerfile

@@ -1,49 +1,66 @@
 FROM python:3.11-slim
 
+
 # Install required system dependencies
 RUN apt-get update && apt-get install -y \
     git curl build-essential cmake \
     && rm -rf /var/lib/apt/lists/*
 
+
 # Set working directory
 WORKDIR /app
 
+
 # Create writable directories
 RUN mkdir -p /app/.cache /app/vector_database && chmod -R 777 /app
 
+
 # Set environment variables
 ENV TRANSFORMERS_CACHE=/app/.cache \
     HF_HOME=/app/.cache \
     CHROMADB_DISABLE_TELEMETRY=true
 
+
 # Install dependencies from requirements.txt first
 COPY requirements.txt .
 RUN pip install --no-cache-dir -r requirements.txt
 
+
 # Install nltk and download punkt tokenizer once during build
 RUN python -m nltk.downloader punkt punkt_tab
 
+
 # ✅ STEP 1: Copy the source data and the Python script into the image
 COPY ./combined_context.jsonl .
 COPY ./create_granular_chunks.py .
 
+
 # ✅ STEP 2: Run the script to generate the chunks file inside the image
 RUN python create_granular_chunks.py
 
+
+# ✅ STEP 3: The 'granular_chunks_improved.jsonl' now exists inside the image.
+# We no longer need to copy it from our local machine.
+
+
 # Note: As recommended before, 'llama-cpp-python' should be removed from requirements.txt
 # to rely on the more stable, version-pinned installation below.
 RUN pip install --no-cache-dir llama-cpp-python==0.2.61
 
-# ✅ FIXED: Copy the application files directly to /app (not /app/app/)
+
+# Copy the rest of the application code
 COPY ./app ./app
 
+
 # Download your fine-tuned TinyLlama GGUF model
 RUN curl -fL -o /app/tinyllama_dop_q4_k_m.gguf \
     https://huggingface.co/Kalpokoch/FinetunedQuantizedTinyLama/resolve/main/tinyllama_dop_q4_k_m.gguf \
     && echo "✅ TinyLlama model downloaded."
 
+
 # Expose the application port
 EXPOSE 7860
 
-# ✅ FIXED: Run the FastAPI application with correct module path
-CMD ["uvicorn", "app.app:app", "--host", "0.0.0.0", "--port", "7860"]
+
+# Run the FastAPI application
+CMD ["uvicorn", "app.app:app", "--host", "0.0.0.0", "--port", "7860"]