Newest 오픈 소스 플랫폼 Solutions for 2024

Explore cutting-edge 오픈 소스 플랫폼 tools launched in 2024. Perfect for staying ahead in your field.

오픈 소스 플랫폼

  • APIPark is an open-source LLM gateway enabling efficient and secure integration of AI models.
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    What is APIPark?
    APIPark serves as a comprehensive LLM gateway offering efficient and secure management of large language models. It supports over 200 LLMs, enabling fine-grained visual management, and integrates seamlessly into production environments. The platform provides load balancing, real-time traffic monitoring, and intelligent semantic caching. Additionally, APIPark facilitates prompt management and API transformation, offering robust security features such as data masking to protect sensitive information. Its open-source nature and developer-centric design make it a versatile tool for businesses looking to streamline their AI model deployment and management.
  • UseThisPrompt.io enhances productivity with powerful AI-driven prompt sharing.
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    What is UseThisPrompt?
    UseThisPrompt.io is an open-source and free community platform where users can share, upvote, and discuss productivity prompts that leverage AI technology. This platform allows individuals to save time and enhance their work efficiency by utilizing tailored prompts suited to various use cases, from content creation to social media strategy.
  • AI-powered customer support platform combining AI agents with human oversight.
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    What is ChatterMate – The Open-Source AI Chatbot?
    ChatterMate is an AI-powered customer support platform designed to provide round-the-clock assistance. It combines AI agents with human oversight to handle a wide range of customer queries. The platform features context-aware AI, seamless human handoff, deep integration with major tools, customizable theming, and real-time analytics. Whether you are a small business seeking a self-hosted solution or a large enterprise requiring custom development, ChatterMate offers flexible pricing plans to meet your needs.
  • Fetch.ai is an open-source autonomous agent framework enabling secure decentralized coordination and digital twin transactions.
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    What is Fetch.ai Autonomous Agent Framework?
    Fetch.ai is an open-source platform and software development kit designed for building autonomous agents that represent digital twins on a decentralized network. It provides a Python and Rust SDK, an Open Economic Framework (OEF) for peer discovery, and seamless integration with its ledger for secure transactions. Developers can define custom agent skills—such as market making, data provision, or task bidding—and deploy them to testnets or mainnets. Fetch.ai agents autonomously communicate, negotiate, and execute smart contracts, enabling powerful multi-agent coordination for supply chains, IoT ecosystems, mobility services, energy grids, and beyond.
  • JaCaMo is a multi-agent system platform integrating Jason, CArtAgO, and Moise for scalable, modular agent-based programming.
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    What is JaCaMo?
    JaCaMo provides a unified environment for designing and running multi-agent systems (MAS) by integrating three core components: the Jason agent programming language for BDI-based agents, CArtAgO for artifact-based environmental modeling, and Moise for specifying organizational structures and roles. Developers can write agent plans, define artifacts with operations, and organize groups of agents under normative frameworks. The platform includes tooling for simulation, debugging, and visualization of MAS interactions. With support for distributed execution, artifact repositories, and flexible messaging, JaCaMo enables rapid prototyping and research in areas like swarm intelligence, collaborative robotics, and distributed decision-making. Its modular design ensures scalability and extensibility across academic and industrial projects.
  • A scalable, flexible workflow orchestration platform for data and ML workflows.
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    What is Flyte v1.3.0?
    Flyte is a flexible, scalable open-source workflow orchestration platform. It integrates seamlessly into your data and ML stack, allowing you to define, deploy, and manage robust data and ML workflows effortlessly. Its powerful and extensible features help in creating production-grade workflows that are reproducible and highly concurrent, making it an essential tool for data scientists, engineers, and analysts.
  • Open source playground to test LLMs.
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    What is nat.dev?
    OpenPlayground is an open-source platform that allows users to experiment with and compare different large language models (LLMs). It's designed to help users understand the strengths and weaknesses of various LLMs by providing a user-friendly and interactive environment. The platform can be particularly useful for developers, researchers, and anyone interested in the capabilities of artificial intelligence. Users can sign up easily using their Google account or email.
  • Revolutionize your browsing experience with customizable AI assistance.
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    What is OpenGPTs?
    OpenGPTs serves as a robust platform for integrating various AI models into a single browser interface. This extension allows users to interact with powerful language models tailored to their specific needs, offering a seamless browsing experience with intelligent suggestions and automation. Whether you're looking to enhance productivity, streamline tasks, or obtain instant information, OpenGPTs provides the tools needed to achieve these goals effortlessly. With its open-source framework and flexibility, users can easily customize and manage their interactions with AI, ensuring optimal performance and usability.
  • rag-services is an open-source microservices framework enabling scalable retrieval-augmented generation pipelines with vector storage, LLM inference, and orchestration.
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    What is rag-services?
    rag-services is an extensible platform that breaks down RAG pipelines into discrete microservices. It offers a document store service, a vector index service, an embedder service, multiple LLM inference services, and an orchestrator service to coordinate workflows. Each component exposes REST APIs, allowing you to mix and match databases and model providers. With Docker and Docker Compose support, you can deploy locally or in Kubernetes clusters. The framework enables scalable, fault-tolerant RAG solutions for chatbots, knowledge bases, and automated document Q&A.
  • Virtual Scientists provides AI Agents simulating expert researchers in physics, chemistry, biology, and more for scientific Q&A and exploration.
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    What is Virtual Scientists?
    Virtual Scientists leverages GPT-based language models to create specialized AI Agents that replicate expert scientists across various fields. Each virtual researcher is configured with tailored prompt engineering to provide accurate, context-aware answers, propose experimental protocols, interpret scientific data, and generate insights. Users select a scientific persona, input their questions or project details, and receive detailed, discipline-specific guidance supported by references and reasoning for educational or research purposes. The platform is hosted on GitHub Pages and is fully open-source. The codebase supports easy customization and extension of new scientific personas by modifying JSON configuration files. Ideal for collaborative research, teaching demonstrations, or personal study, Virtual Scientists bridges the gap between AI language models and practical scientific problem-solving by offering a dynamic, interactive environment for exploring complex topics with expert-like guidance.
  • WanderMind is an open-source AI agent framework for autonomous brainstorming, tool integration, persistent memory, and customizable workflows.
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    What is WanderMind?
    WanderMind provides a modular architecture for building self-guided AI agents. It manages a persistent memory store to retain context across sessions, integrates with external tools and APIs for extended functionality, and orchestrates multi-step reasoning through customizable planners. Developers can plug in different LLM providers, define asynchronous tasks, and extend the system with new tool adapters. This framework accelerates experimentation with autonomous workflows, enabling applications from idea exploration to automated research assistants without heavy engineering overhead.
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