FIX: Updated Dockerfile to explicitly install CPU PyTorch

Dockerfile

@@ -1,5 +1,5 @@
-# Use a Python base image
-FROM python:3.10-slim
+# Use a Debian-based Python image. This is often more stable for PyTorch than 'slim'.
+FROM python:3.10
 
 # Set the working directory
 WORKDIR /app
@@ -9,19 +9,26 @@ EXPOSE 8501
 
 # Copy the requirements file and install dependencies
 COPY requirements.txt .
+COPY main.py .
+COPY merged.py .
+COPY app.py .
 
-# Install dependencies. We use specific indexes for PyTorch to ensure compatibility 
-# and a general upgrade to avoid issues.
+# --- NEW INSTALLATION STEPS FOR ROBUST PYTORCH ---
+
+# 1. Upgrade pip for stability
 RUN pip install --upgrade pip
+
+# 2. Install PyTorch explicitly for CPU (as configured in merged.py)
+# This uses the specific CPU index URL, which is the most reliable way 
+# to ensure the CPU version of PyTorch is installed without relying on 
+# complex dependencies that might not be on the base image.
+RUN pip install torch --index-url https://download.pytorch.org/whl/cpu
+
+# 3. Install the rest of the dependencies
+# The original requirements.txt (excluding torch)
 RUN pip install -r requirements.txt
 
-# Copy the rest of the application code
-# Assuming the user saved the provided code blocks into these files
-COPY main.py . 
-COPY merged.py .
-COPY app.py .
+# --- END NEW INSTALLATION STEPS ---
 
 # Command to run the Streamlit application
-# We use --server.port 8501 to match the exposed port
-# and --server.address 0.0.0.0 to make it accessible outside the container
 CMD ["streamlit", "run", "app.py", "--server.port", "8501", "--server.address", "0.0.0.0"]

requirements.txt

@@ -1,6 +1,9 @@
 torch
 transformers
 streamlit
-fpdf
+fpdf2
 langchain-core
-langchain-huggingface
+langchain-huggingface
+huggingface-hub
+pyyaml
+regex