leehwui
26f8e0c648
Major additions: - All-in-One Docker image with Ollama + models bundled - Separate deployment option for existing Ollama installations - Changed default model from qwen3:8b to qwen3:14b - Comprehensive deployment documentation Files added: - Dockerfile: Basic app-only image - Dockerfile.allinone: Complete image with Ollama + models - docker-compose.yml: Easy deployment configuration - docker-entrypoint.sh: Startup script for all-in-one image - requirements.txt: Python dependencies - .dockerignore: Exclude unnecessary files from image Scripts: - export-ollama-models.sh: Export models from local Ollama - build-allinone.sh: Build complete offline-deployable image - build-and-export.sh: Build and export basic image Documentation: - DEPLOYMENT.md: Comprehensive deployment guide - QUICK_START.md: Quick reference for common tasks Configuration: - Updated config.py: DEFAULT_CHAT_MODEL = qwen3:14b - Updated frontend/opro.html: Page title to 系统提示词优化
106 lines
2.8 KiB
Bash
Executable File
106 lines
2.8 KiB
Bash
Executable File
#!/bin/bash
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# Export Ollama models for offline deployment
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# This script copies Ollama models from your local machine
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# so they can be bundled into the Docker image
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#
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# Required models:
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# - qwen3:14b (main chat model)
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# - qwen3-embedding:4b (embedding model)
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set -e
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MODELS_DIR="ollama-models"
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OLLAMA_MODELS_PATH="$HOME/.ollama"
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echo "=========================================="
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echo "Exporting Ollama models for offline deployment"
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echo "=========================================="
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# Check if Ollama is installed
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if ! command -v ollama &> /dev/null; then
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echo "ERROR: Ollama is not installed or not in PATH"
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exit 1
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fi
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# Check if required models are available
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echo ""
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echo "Checking for required models..."
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MISSING_MODELS=0
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if ! ollama list | grep -q "qwen3:14b"; then
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echo "ERROR: qwen3:14b model not found!"
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echo "Please run: ollama pull qwen3:14b"
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MISSING_MODELS=1
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fi
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if ! ollama list | grep -q "qwen3-embedding:4b"; then
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echo "ERROR: qwen3-embedding:4b model not found!"
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echo "Please run: ollama pull qwen3-embedding:4b"
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MISSING_MODELS=1
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fi
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if [ $MISSING_MODELS -eq 1 ]; then
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echo ""
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echo "Please download the required models first:"
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echo " ollama pull qwen3:14b"
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echo " ollama pull qwen3-embedding:4b"
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exit 1
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fi
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echo "✓ All required models found"
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# Check if Ollama directory exists
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if [ ! -d "$OLLAMA_MODELS_PATH" ]; then
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echo "ERROR: Ollama directory not found at $OLLAMA_MODELS_PATH"
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exit 1
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fi
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# Create export directory
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echo ""
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echo "Creating export directory: $MODELS_DIR"
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rm -rf "$MODELS_DIR"
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mkdir -p "$MODELS_DIR"
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echo ""
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echo "Copying Ollama data from $OLLAMA_MODELS_PATH to $MODELS_DIR..."
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echo "This may take several minutes (models are large)..."
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# Copy the entire .ollama directory structure
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cp -r "$OLLAMA_MODELS_PATH"/* "$MODELS_DIR/"
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echo ""
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echo "=========================================="
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echo "Models exported successfully!"
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echo "=========================================="
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du -sh "$MODELS_DIR"
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echo ""
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echo "Directory structure:"
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ls -lh "$MODELS_DIR/"
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echo ""
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echo "Models included:"
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if [ -d "$MODELS_DIR/models/manifests/registry.ollama.ai/library" ]; then
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ls -lh "$MODELS_DIR/models/manifests/registry.ollama.ai/library/"
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fi
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echo ""
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echo "=========================================="
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echo "Next steps:"
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echo "=========================================="
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echo "1. Build the all-in-one Docker image:"
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echo " ./build-allinone.sh"
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echo ""
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echo "2. Or manually:"
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echo " docker build -f Dockerfile.allinone -t system-prompt-optimizer:allinone ."
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echo ""
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echo "3. Export the image:"
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echo " docker save -o system-prompt-optimizer-allinone.tar system-prompt-optimizer:allinone"
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echo ""
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echo "4. Transfer to target server:"
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echo " scp system-prompt-optimizer-allinone.tar user@server:/path/"
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echo ""
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echo "Note: The final Docker image will be very large (10-20GB) due to the models."
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