refactor(docker): improve server architecture and configuration
Complete overhaul of Docker deployment setup with improved architecture: - Add Redis integration for task management - Implement rate limiting and security middleware - Add Prometheus metrics and health checks - Improve error handling and logging - Add support for streaming responses - Implement proper configuration management - Add platform-specific optimizations for ARM64/AMD64 BREAKING CHANGE: Docker deployment now requires Redis and new config.yml structure
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# syntax=docker/dockerfile:1.4
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ARG TARGETPLATFORM
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ARG BUILDPLATFORM
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# Other build arguments
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ARG PYTHON_VERSION=3.10
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# Base stage with system dependencies
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FROM python:${PYTHON_VERSION}-slim as base
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# Declare ARG variables again within the build stage
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ARG INSTALL_TYPE=all
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ARG ENABLE_GPU=false
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# Platform-specific labels
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LABEL maintainer="unclecode"
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LABEL description="🔥🕷️ Crawl4AI: Open-source LLM Friendly Web Crawler & scraper"
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LABEL version="1.0"
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# Environment setup
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ENV PYTHONUNBUFFERED=1 \
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PYTHONDONTWRITEBYTECODE=1 \
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PIP_NO_CACHE_DIR=1 \
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PIP_DISABLE_PIP_VERSION_CHECK=1 \
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PIP_DEFAULT_TIMEOUT=100 \
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DEBIAN_FRONTEND=noninteractive
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# Install system dependencies
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RUN apt-get update && apt-get install -y --no-install-recommends \
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build-essential \
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curl \
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wget \
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gnupg \
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git \
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cmake \
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pkg-config \
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python3-dev \
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libjpeg-dev \
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libpng-dev \
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&& rm -rf /var/lib/apt/lists/*
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# Playwright system dependencies for Linux
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RUN apt-get update && apt-get install -y --no-install-recommends \
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libglib2.0-0 \
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libnss3 \
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libnspr4 \
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libatk1.0-0 \
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libatk-bridge2.0-0 \
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libcups2 \
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libdrm2 \
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libdbus-1-3 \
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libxcb1 \
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libxkbcommon0 \
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libx11-6 \
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libxcomposite1 \
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libxdamage1 \
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libxext6 \
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libxfixes3 \
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libxrandr2 \
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libgbm1 \
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libpango-1.0-0 \
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libcairo2 \
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libasound2 \
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libatspi2.0-0 \
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&& rm -rf /var/lib/apt/lists/*
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# GPU support if enabled and architecture is supported
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RUN if [ "$ENABLE_GPU" = "true" ] && [ "$TARGETPLATFORM" = "linux/amd64" ] ; then \
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apt-get update && apt-get install -y --no-install-recommends \
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nvidia-cuda-toolkit \
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&& rm -rf /var/lib/apt/lists/* ; \
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else \
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echo "Skipping NVIDIA CUDA Toolkit installation (unsupported platform or GPU disabled)"; \
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fi
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# Create and set working directory
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WORKDIR /app
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# Copy the entire project
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COPY . .
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# Install base requirements
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RUN pip install --no-cache-dir -r requirements.txt
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# Install required library for FastAPI
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RUN pip install fastapi uvicorn psutil
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# Install ML dependencies first for better layer caching
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RUN if [ "$INSTALL_TYPE" = "all" ] ; then \
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pip install --no-cache-dir \
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torch \
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torchvision \
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torchaudio \
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scikit-learn \
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nltk \
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transformers \
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tokenizers && \
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python -m nltk.downloader punkt stopwords ; \
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fi
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# Install the package
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RUN if [ "$INSTALL_TYPE" = "all" ] ; then \
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pip install ".[all]" && \
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python -m crawl4ai.model_loader ; \
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elif [ "$INSTALL_TYPE" = "torch" ] ; then \
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pip install ".[torch]" ; \
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elif [ "$INSTALL_TYPE" = "transformer" ] ; then \
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pip install ".[transformer]" && \
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python -m crawl4ai.model_loader ; \
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else \
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pip install "." ; \
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fi
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# Install MkDocs and required plugins
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RUN pip install --no-cache-dir \
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mkdocs \
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mkdocs-material \
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mkdocs-terminal \
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pymdown-extensions
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# Build MkDocs documentation
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RUN mkdocs build
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# Install Playwright and browsers
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RUN if [ "$TARGETPLATFORM" = "linux/amd64" ]; then \
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playwright install chromium; \
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elif [ "$TARGETPLATFORM" = "linux/arm64" ]; then \
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playwright install chromium; \
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fi
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# Expose port
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EXPOSE 8000 11235 9222 8080
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# Start the FastAPI server
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CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "11235"]
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