Showing 8 open source projects for "netfilter-layer"

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    AnyTool

    AnyTool

    AnyTool: Universal Tool-Use Layer for AI Agents

    AnyTool is an open-source universal tool-use layer for AI agents that addresses the critical problem of how autonomous agents reliably interact with external tools and environments. Rather than having each agent handle tool invocation logic on its own, AnyTool provides a standardized interface and orchestrator that intelligently selects and manages tools, reduces context overhead, and improves execution reliability across diverse capabilities like web APIs, local commands, and GUI automation. ...
    Downloads: 0 This Week
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  • 2
    Mem0

    Mem0

    The Memory layer for AI Agents

    Mem0 is a self-improving memory layer designed for Large Language Model (LLM) applications, enabling personalized AI experiences that save costs and delight users. It remembers user preferences, adapts to individual needs, and continuously improves over time. Key features include enhancing future conversations by building smarter AI that learns from every interaction, reducing LLM costs by up to 80% through intelligent data filtering, delivering more accurate and personalized AI outputs by leveraging historical context, and offering easy integration compatible with platforms like OpenAI and Claude. ...
    Downloads: 6 This Week
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  • 3
    cognee

    cognee

    Deterministic LLMs Outputs for AI Applications and AI Agents

    We build for developers who need a reliable, production-ready data layer for AI applications. Cognee implements scalable, modular data pipelines that allow for creating the LLM-enriched data layer using graph and vector stores. Cognee acts a semantic memory layer, unveiling hidden connections within your data and infusing it with your company's language and principles. This self-optimizing process ensures ultra-relevant, personalized, and contextually aware LLM retrievals. ...
    Downloads: 0 This Week
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  • 4
    OAGI Python SDK

    OAGI Python SDK

    Python SDK for the Computer Use model Lux, developed by OpenAGI

    OAGI Python SDK is a Python client library for the Lux computer-use model that turns Lux into a programmable automation layer for operating human-facing software via vision and actions. It exposes the OAGI API in an ergonomic way, letting you trigger Lux in three main modes: Tasker for precise scripted sequences, Actor for fast one-shot tasks, and Thinker for open-ended, multi-step objectives. The SDK is designed around “computer use” as a paradigm, where the AI actually navigates interfaces, clicks, types, scrolls, and reads the screen through screenshots instead of only calling APIs. ...
    Downloads: 2 This Week
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  • 5
    Notte

    Notte

    Opensource browser using agents

    Notte is an open-source browser framework that enables the development and deployment of web-based AI agents. It introduces a perception layer that transforms web pages into structured, navigable maps described in natural language, allowing agents to interact with the internet more effectively. Notte is designed for building scalable and efficient browser-based AI applications.
    Downloads: 3 This Week
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  • 6
    Continuous Claude v3

    Continuous Claude v3

    Context management for Claude Code. Hooks maintain state via ledgers

    Continuous Claude v3 is a persistent, multi-agent development environment built around the Claude Code CLI that aims to overcome the limitations of standard LLM context windows. Rather than relying on a single session’s context, Continuous Claude uses mechanisms like ledgers, YAML handoffs, and a memory system to preserve and recall state across multiple sessions, ensuring that learned insights and plans are not lost when context compaction occurs. The project orchestrates many specialized...
    Downloads: 1 This Week
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  • 7
    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.
    Downloads: 0 This Week
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  • 8
    OpenAGI

    OpenAGI

    When LLM Meets Domain Experts

    ...The project includes tooling for registering agents with AIOS by uploading them via a command-line interface, enforcing a consistent naming scheme that matches the local folder layout. A companion tooling layer lets agents call external tools described in the tools.md documentation, enabling them to orchestrate APIs, retrieval pipelines, and other utilities in response to LLM decisions.
    Downloads: 0 This Week
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