Create Dockerfile

Dockerfile

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+# Dockerfile for Agent Worker / Learning Worker (adjust base image for GPU if needed)
+
+# Use a base image with Python and potentially CUDA for GPU support (for learning worker)
+# FROM python:3.10-slim
+FROM nvidia/cuda:11.8.0-cudnn8-runtime-ubuntu20.04 # Example GPU base image
+
+WORKDIR /app
+
+# Install system dependencies (e.g., for psycopg2, git)
+# RUN apt-get update && apt-get install -y --no-install-recommends gcc libpq-dev git && rm -rf /var/lib/apt/lists/*
+
+COPY requirements.txt .
+# Install Python dependencies (consider using a virtual environment)
+# Ensure torch is installed correctly for CPU/GPU
+RUN pip install --no-cache-dir -r requirements.txt
+# OR specific torch version:
+# RUN pip install --no-cache-dir torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118
+# RUN pip install --no-cache-dir -r requirements.txt
+
+COPY . .
+
+# Set environment variables (can also be done via docker-compose.yml)
+ENV OPENAI_API_KEY=your_openai_key
+ENV POSTGRES_DSN=postgresql://user:password@postgres:5432/agentdb # Use service name 'postgres'
+ENV REDIS_URL=redis://redis:6379/0 # Use service name 'redis'
+ENV BASE_MODEL_NAME=gpt-4o-mini
+# Add other ENV vars as needed (NUM_WORKERS, etc.)
+
+# Command to run the worker (or learning script)
+# CMD ["python", "your_main_script.py"]
+# Use different CMD for agent worker vs learning worker containers if separated