Showing 5 open source projects for "linux space invaders"

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    Ship Agents Faster

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  • 1
    VulnClaw

    VulnClaw

    Based on AI Agent + MCP toolchain + penetration Skill orchestration

    VulnClaw is an AI-powered penetration testing agent that turns natural language security goals into structured testing workflows. It combines LLM agents, MCP toolchains, penetration testing skills, and command-line automation to support authorized security assessments. The project can guide information gathering, vulnerability discovery, validation, and report generation while keeping the workflow organized through sessions and tools. Its newer architecture uses a goal-driven solving engine...
    Downloads: 2 This Week
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  • 2
    Semantic Router

    Semantic Router

    Superfast AI decision making and processing of multi-modal data

    Semantic Router is a superfast decision-making layer for your LLMs and agents. Rather than waiting for slow, unreliable LLM generations to make tool-use or safety decisions, we use the magic of semantic vector space — routing our requests using semantic meaning. Combining LLMs with deterministic rules means we can be confident that our AI systems behave as intended. Cramming agent tools into the limited context window is expensive, slow, and fundamentally limited. Semantic Router enables...
    Downloads: 2 This Week
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  • 3
    Monocolor Editorial Print

    Monocolor Editorial Print

    One-ink editorial print image skill

    Mono Color Skill is an editorial image-generation system for posters, zines, portraits, packaging, publications, and visual field notes. It transforms a theme, phrase, object, article idea, or supplied photograph into an original print-inspired composition. The default look uses two controlled inks with one dominant plate and a narrowly assigned accent, while explicit monochrome requests stay pure one-ink. Images can use halftone, risograph grain, cyanotype exposure, or photocopy-style...
    Downloads: 0 This Week
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  • 4
    Multi-Agent Particle Envs

    Multi-Agent Particle Envs

    Code for a multi-agent particle environment used in a paper

    Multiagent Particle Environments is a lightweight framework for simulating multi-agent reinforcement learning tasks in a continuous observation space with discrete action settings. It was originally developed by OpenAI and used in the influential paper Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments. The environment provides simple particle-based worlds with simulated physics, where agents can move, communicate, and interact with each other. Scenarios are designed to...
    Downloads: 5 This Week
    Last Update:
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    Cut Data Warehouse Costs by 54%

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  • 5
    A software toolkit that implements the CoSy Architecture Schema for developing integrated intelligent robotic systems. The toolkit focuses on supporting on a space of information-processing architectures based on shared working memories.
    Downloads: 0 This Week
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