Enhance README.md with Docker installation instructions and update Ollama API endpoint to be configurable via environment variable.

docker.env.example

@@ -0,0 +1,63 @@
+# VideoTranscriber Docker Configuration
+# Copy this file to .env and modify the values as needed
+
+# =============================================================================
+# DOCKER VOLUME PATHS (Host Directories)
+# =============================================================================
+
+# Path to your video files directory on the host
+# This directory will be mounted into the container at /app/data/videos
+VIDEO_PATH=./videos
+
+# Path where outputs (transcripts, summaries) will be saved on the host
+# This directory will be mounted into the container at /app/data/outputs
+OUTPUT_PATH=./outputs
+
+# Path for caching ML models and processed files (improves performance)
+# This directory will be mounted into the container at /app/data/cache
+CACHE_PATH=./cache
+
+# Optional: Configuration directory for custom settings
+CONFIG_PATH=./config
+
+# =============================================================================
+# OLLAMA CONFIGURATION
+# =============================================================================
+
+# Ollama API URL - how the container accesses your host Ollama service
+# For Windows/Mac with Docker Desktop: use host.docker.internal
+# For Linux: use host networking or the actual host IP
+OLLAMA_API_URL=http://host.docker.internal:11434/api
+
+# =============================================================================
+# ML MODEL CONFIGURATION
+# =============================================================================
+
+# HuggingFace token for advanced features (speaker diarization, etc.)
+# Get your token at: https://huggingface.co/settings/tokens
+# Leave empty if not using advanced features
+HF_TOKEN=
+
+# GPU Configuration
+# Specify which GPU devices to use (leave empty for all available)
+# Examples: "0" for first GPU, "0,1" for first two GPUs
+CUDA_VISIBLE_DEVICES=
+
+# =============================================================================
+# DOCKER-SPECIFIC SETTINGS
+# =============================================================================
+
+# Container name (change if you want to run multiple instances)
+CONTAINER_NAME=videotranscriber
+
+# Port mapping (host:container)
+HOST_PORT=8501
+
+# =============================================================================
+# EXAMPLE USAGE
+# =============================================================================
+# 1. Copy this file: cp docker.env.example .env
+# 2. Edit the paths to match your system
+# 3. Make sure Ollama is running on your host: ollama serve
+# 4. Start the container: docker-compose up -d
+# 5. Access the app at: http://localhost:8501