forked from MCP/llm-fusion-mcp
Ryan Malloy
c335ba0e1e
- Unified access to 4 major LLM providers (Gemini, OpenAI, Anthropic, Grok) - Real-time streaming support across all providers - Multimodal capabilities (text, images, audio) - Intelligent document processing with smart chunking - Production-ready with health monitoring and error handling - Full OpenAI ecosystem integration (Assistants, DALL-E, Whisper) - Vector embeddings and semantic similarity - Session-based API key management - Built with FastMCP and modern Python tooling 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
48 lines
1.0 KiB
Docker
48 lines
1.0 KiB
Docker
# LLM Fusion MCP - Production Docker Image
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FROM python:3.12-slim
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# Set environment variables
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ENV PYTHONUNBUFFERED=1
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ENV PYTHONDONTWRITEBYTECODE=1
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ENV UV_CACHE_DIR=/tmp/uv-cache
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# Install system dependencies
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RUN apt-get update && apt-get install -y \
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curl \
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git \
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&& rm -rf /var/lib/apt/lists/*
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# Install uv
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RUN curl -LsSf https://astral.sh/uv/install.sh | sh
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ENV PATH="/root/.cargo/bin:$PATH"
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# Create app directory
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WORKDIR /app
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# Copy dependency files
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COPY pyproject.toml uv.lock ./
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# Install dependencies
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RUN uv sync --frozen --no-dev
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# Copy application code
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COPY src/ ./src/
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COPY run_server.sh ./
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COPY .env.example ./
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# Make run script executable
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RUN chmod +x run_server.sh
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# Create non-root user for security
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RUN useradd -m -u 1000 llmfusion && chown -R llmfusion:llmfusion /app
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USER llmfusion
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# Health check
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HEALTHCHECK --interval=30s --timeout=10s --start-period=5s --retries=3 \
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CMD python -c "import sys; sys.exit(0)"
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# Expose port (if running HTTP server in future)
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EXPOSE 8000
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# Run the server
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CMD ["./run_server.sh"] |