Showing 6 open source projects for "support vector machine"

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  • 1
    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: 4 This Week
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  • 2
    AnythingLLM

    AnythingLLM

    The all-in-one Desktop & Docker AI application with full RAG and AI

    A full-stack application that enables you to turn any document, resource, or piece of content into a context that any LLM can use as references during chatting. This application allows you to pick and choose which LLM or Vector Database you want to use as well as supporting multi-user management and permissions. AnythingLLM is a full-stack application where you can use commercial off-the-shelf LLMs or popular open-source LLMs and vectorDB solutions to build a private ChatGPT with no...
    Downloads: 167 This Week
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  • 3
    DB-GPT

    DB-GPT

    Revolutionizing Database Interactions with Private LLM Technology

    DB-GPT is an experimental open-source project that uses localized GPT large models to interact with your data and environment. With this solution, you can be assured that there is no risk of data leakage, and your data is 100% private and secure.
    Downloads: 6 This Week
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  • 4
    Koog

    Koog

    Koog is the official Kotlin framework for building AI agents

    Koog is a Kotlin‑based framework for building and running AI agents entirely in idiomatic Kotlin, supporting both single‑run agents that process individual inputs and complex workflow agents with custom strategies and configurations. It features pure Kotlin implementation, seamless Model Control Protocol (MCP) integration for enhanced model management, vector embeddings for semantic search, and a flexible system for creating and extending tools that access external systems and APIs....
    Downloads: 4 This Week
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  • 5
    Phidata

    Phidata

    Build multi-modal Agents with memory, knowledge, tools and reasoning

    ...Phidata also allows developers to bring their own cloud infrastructure, offering flexibility for custom setups. The platform provides robust support for enterprises, including security features, agent guardrails, and automated DevOps for smoother deployment processes.
    Downloads: 8 This Week
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  • 6
    Ax

    Ax

    Build LLM powered Agents and "Agentic workflows"

    Build intelligent agents quickly — inspired by the power of "Agentic workflows" and the Stanford DSPy paper. Seamlessly integrates with multiple LLMs and VectorDBs to build RAG pipelines or collaborative agents that can solve complex problems. Advanced features streaming validation, multi-modal DSPy, etc. We've renamed from "llmclient" to "ax" to highlight our focus on powering agentic workflows. We agree with many experts like "Andrew Ng" that agentic workflows are the key to unlocking the...
    Downloads: 1 This Week
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