Local LLM Integration

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This skill provides expert-level guidance for deploying and optimizing local Large Language Models with a focus on privacy and performance. It enables seamless integration of tools like llama.cpp and Ollama into applications, offering specialized patterns for model quantization, memory management, and secure API design. By emphasizing a security-first approach, it helps developers prevent vulnerabilities such as prompt injection and denial of service while ensuring low-latency responses through streaming and efficient context management.

Características Principales

• Model quantization and memory optimization for hardware efficiency
• 4 GitHub stars
• Secure local deployment with llama.cpp and Ollama
• Implementation of resource-limited inference to prevent DoS attacks
• Advanced prompt injection prevention and input sanitization
• Streaming response generation with real-time output filtering

Casos de Uso

• Building privacy-preserving voice assistants without cloud dependencies
• Orchestrating multi-model AI workflows within secure boundaries
• Optimizing local AI performance for low-latency hardware environments