Showing 504 open source projects for "kde-connect"

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  • 1
    StackStorm

    StackStorm

    Connect all your apps, services, and workflows

    StackStorm is a platform for integration and automation for numerous services and tools. It takes actions in response to events, and is composed of a rules engine, workflow, and 160 integration packs with more than 6000 actions. This makes StackStorm very versatile, useful in a wide array of business applications. StackStorm can be used to automate and streamline nearly any part of a business. It can be used for automated remediation to immediately troubleshoot and fix problems when...
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  • 2
    ChatterBot

    ChatterBot

    Machine learning, conversational dialog engine for creating chat bots

    ChatterBot is a Python library that makes it easy to generate automated responses to a user’s input. ChatterBot uses a selection of machine learning algorithms to produce different types of responses. This makes it easy for developers to create chat bots and automate conversations with users. For more details about the ideas and concepts behind ChatterBot see the process flow diagram. The language independent design of ChatterBot allows it to be trained to speak any language. Additionally,...
    Downloads: 2 This Week
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  • 3
    Seldon Core

    Seldon Core

    An MLOps framework to package, deploy, monitor and manage models

    ...Seldon Core serves models built in any open-source or commercial model building framework. You can make use of powerful Kubernetes features like custom resource definitions to manage model graphs. And then connect your continuous integration and deployment (CI/CD) tools to scale and update your deployment. Built on Kubernetes, runs on any cloud and on-premises. Framework agnostic, supports top ML libraries, toolkits and languages. Advanced deployments with experiments, ensembles and transformers. Our open-source framework makes it easier and faster to deploy your machine learning models and experiments at scale on Kubernetes. ...
    Downloads: 1 This Week
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  • 4
    any-llm

    any-llm

    Communicate with an LLM provider using a single interface

    ...It includes a core SDK for direct usage as well as an optional gateway layer that adds enterprise features such as budget management, API key control, usage analytics, and multi-tenant support. The gateway exposes an OpenAI-compatible API, allowing existing tools and workflows to connect without modification. The system emphasizes developer experience with clear error handling, strong typing, and minimal configuration overhead.
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    Pathway AI Pipelines

    Pathway AI Pipelines

    Ready-to-run cloud templates for RAG

    Pathway AI Pipelines is a collection of ready-to-deploy AI pipeline templates designed to help developers rapidly build production-grade retrieval-augmented generation and enterprise search applications. The project provides end-to-end examples that connect live data sources to LLM workflows, enabling applications to stay synchronized with continuously changing information. It supports numerous connectors including local files, Google Drive, SharePoint, Kafka, PostgreSQL, and real-time APIs, making it suitable for enterprise data environments. The templates include built-in indexing, vector search, hybrid search, and caching capabilities that remove the need to assemble separate infrastructure components. ...
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  • 6
    SERA CLI

    SERA CLI

    A tool to use the Ai2 Open Coding Agents Soft-Verified Agents

    ...It provides a convenient interface for deploying, testing, and using SERA models without needing to write scaffold code from scratch, acting as both a proxy and utility wrapper to simplify workflows that involve large agent models. Through sera-cli, users can connect to local or cloud-hosted SERA deployments, including via Modal for quick GPU provisioning and model caching, which helps accelerate experiments. The project is targeted at practitioners and researchers in the AI space who need a flexible but powerful CLI interface for model invocation, endpoint configuration, and integration with development pipelines.
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  • 7
    ML for Beginners

    ML for Beginners

    12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all

    ...Organized as a multi-week course, it mixes short lectures with labs in notebooks so learners practice regression, classification, clustering, and recommendation techniques on real datasets. Each lesson aims to connect the algorithm to a relatable scenario, reinforcing intuition before diving into parameters, metrics, and trade-offs. The repository includes quizzes, solutions, and instructor materials to make the content usable in classrooms or self-study. It emphasizes ethical considerations and model evaluation—accuracy is not the only metric—so students learn to validate and communicate results responsibly. ...
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  • 8
    Superduper

    Superduper

    Superduper: Integrate AI models and machine learning workflows

    ...This allows developers to completely avoid implementing MLOps, ETL pipelines, model deployment, data migration, and synchronization. Using Superduper is simply "CAPE": Connect to your data, apply arbitrary AI to that data, package and reuse the application on arbitrary data, and execute AI-database queries and predictions on the resulting AI outputs and data.
    Downloads: 0 This Week
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  • 9
    HASS Configurator

    HASS Configurator

    Configuration UI for Home Assistant

    The HASS Configurator is a small web app (you access it via a web browser) that provides a filesystem browser and text-editor to modify files on the machine the configurator is running on. It has been created to allow easy configuration of Home Assistant. It is powered by Ace editor, which supports syntax highlighting for various code/markup languages. YAML files (the default language for Home Assistant configuration files) will be automatically checked for syntax errors while editing. The...
    Downloads: 0 This Week
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  • 10
    Open Source Vizier

    Open Source Vizier

    Python-based research interface for blackbox

    ...A wide collection of objective functions and methods to benchmark and compare algorithms. Define a problem statement and study configuration. Setup a local server, setup a client to connect to the server, perform a typical tuning loop, and use other client APIs.
    Downloads: 0 This Week
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  • 11
    Graphene-Django

    Graphene-Django

    Integrate GraphQL into your Django project

    ...Graphene Django has a number of additional features that are designed to make working with Django easy. Our primary focus in this tutorial is to give a good understanding of how to connect models from Django ORM to Graphene object types. GraphQL presents your objects to the world as a graph structure rather than a more hierarchical structure to which you may be accustomed. In order to create this representation, Graphene needs to know about each type of object which will appear in the graph.
    Downloads: 0 This Week
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  • 12
    Dynamiq

    Dynamiq

    An orchestration framework for agentic AI and LLM applications

    ...The framework focuses on simplifying the creation of complex AI workflows that involve multiple agents, retrieval systems, and reasoning steps. Instead of building each component manually, developers can use Dynamiq’s structured APIs and modular architecture to connect language models, vector databases, and external tools into cohesive pipelines. The framework supports the creation of multi-agent systems where different AI agents collaborate to solve tasks such as information retrieval, document analysis, or automated decision making. Dynamiq also includes built-in support for retrieval-augmented generation pipelines that allow models to access external documents and knowledge bases during inference.
    Downloads: 0 This Week
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  • 13
    DriveLM

    DriveLM

    Driving with Graph Visual Question Answering

    ...Instead of treating autonomous driving as a purely sensor-driven pipeline, DriveLM frames it as a reasoning problem where models answer structured questions about the environment to guide decision making. The system includes DriveLM-Data, a dataset built on driving environments such as nuScenes and CARLA, where human-written reasoning steps connect different layers of driving tasks. This design allows models to learn relationships between objects, behaviors, and navigation decisions through graph-structured logic.
    Downloads: 0 This Week
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  • 14
    Sage Chat

    Sage Chat

    Chat with any codebase in under two minutes | Fully local

    ...The project aims to act as a contextual knowledge layer for software teams by combining language models with repository indexing and documentation retrieval. Sage can operate locally or connect to external AI services, depending on the configuration, providing flexibility for privacy-sensitive environments.
    Downloads: 0 This Week
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  • 15
    E2M

    E2M

    E2M converts various file types (doc, docx, epub, html, htm, url

    ...The mirrored repository allows users to access the project’s codebase independently from its original hosting platform while preserving the development history and release artifacts. Systems like e2m often serve as middleware components that connect different software systems or facilitate data processing pipelines. By acting as a transformation layer, the software can support workflows such as converting data formats, integrating services, or bridging incompatible systems. The mirror hosted on SourceForge ensures that developers can continue accessing the project even if the primary repository becomes unavailable.
    Downloads: 0 This Week
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  • 16
    Lagent

    Lagent

    A lightweight framework for building LLM-based agents

    ...Instead of using LLMs only for text generation, Lagent enables developers to transform models into agents capable of performing actions such as retrieving data, executing code, or interacting with APIs. The system includes modular components that allow developers to connect different models and tools within the same agent architecture. Its design emphasizes simplicity and flexibility so that developers can experiment with different agent workflows without needing a complex infrastructure setup. Lagent can also be deployed as a web service to support distributed or multi-agent applications.
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  • 17
    Sandstorm

    Sandstorm

    One API call, pull Claude agent, completely sandboxed

    Sandstorm is an open-source project that wraps a powerful Claude-based AI agent within a completely sandboxed, ephemeral API service designed to make agentic AI workflows easy to deploy and scale without infrastructure complexity. The core idea is to provide “one API call” access to a robust Claude agent loop that runs inside a secure sandbox, so you can upload files, connect tools, and run long-running tasks — all managed behind a simple REST-style interface that disappears when the work is done. This approach lowers the friction of building autonomous agents by removing the need to provision servers, orchestrate distributed agents, or manage persistent tooling; agents can be spun up in parallel without manual setup and shut down when complete. ...
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  • 18
    sqlit

    sqlit

    A user friendly TUI for SQL databases

    sqlit is a keyboard-first terminal UI that lets you connect to, browse, and query SQL databases quickly without relying on heavyweight GUI clients. It positions itself as a “lazygit-style” experience for databases, aiming for fast startup, intuitive navigation, and developer-friendly workflows directly inside your terminal. The tool supports a wide range of database providers, so you can use one interface across local databases, remote servers, and cloud-hosted instances rather than juggling multiple clients. ...
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  • 19
    FATE

    FATE

    An industrial grade federated learning framework

    FATE (Federated AI Technology Enabler) is the world's first industrial grade federated learning open source framework to enable enterprises and institutions to collaborate on data while protecting data security and privacy. It implements secure computation protocols based on homomorphic encryption and multi-party computation (MPC). Supporting various federated learning scenarios, FATE now provides a host of federated learning algorithms, including logistic regression, tree-based algorithms,...
    Downloads: 0 This Week
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  • 20
    Mopidy

    Mopidy

    Mopidy is an extensible music server written in Python

    ...If you install the Mopidy-MPD extension, it becomes an MPD server too. Many additional frontends for controlling Mopidy are available as extensions. You and the people around you can all connect their favorite MPD or web client to the Mopidy server to search for music and manage the playlist together.
    Downloads: 0 This Week
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  • 21
    MindsDB

    MindsDB

    Making Enterprise Data Intelligent and Responsive for AI

    ...A federated query engine that tidies up your data-sprawl chaos while meticulously answering every single question you throw at it. MindsDB has an MCP server built in that enables your MCP applications to connect, unify and respond to questions over large-scale federated data—spanning databases, data warehouses, and SaaS applications.
    Downloads: 1 This Week
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  • 22
    OpenAGI

    OpenAGI

    When LLM Meets Domain Experts

    OpenAGI is a package for AI agent creation designed to connect large language models with domain-specific tools and workflows in the AIOS (AI Operating System) ecosystem. It provides a structured Python framework, pyopenagi, for defining agents as modular units that encapsulate execution logic, configuration, and dependency metadata. Agents are organized in a well-defined folder structure that includes code (agent.py), configuration (config.json), and extra requirements (meta_requirements.txt), which makes them easy to package, share, and reuse. ...
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  • 23
    Large Concept Model

    Large Concept Model

    Language modeling in a sentence representation space

    Large Concept Model is a research codebase centered on concept-centric representation learning at scale, aiming to capture shared structure across many categories and modalities. It organizes training around concepts (rather than just raw labels), encouraging models to understand attributes, relations, and compositional structure that transfer across tasks. The repository provides training loops, data tooling, and evaluation routines to learn and probe these concept embeddings, typically...
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  • 24
    VisualGLM-6B

    VisualGLM-6B

    Chinese and English multimodal conversational language model

    VisualGLM-6B is an open-source multimodal conversational language model developed by ZhipuAI that supports both images and text in Chinese and English. It builds on the ChatGLM-6B backbone, with 6.2 billion language parameters, and incorporates a BLIP2-Qformer visual module to connect vision and language. In total, the model has 7.8 billion parameters. Trained on a large bilingual dataset — including 30 million high-quality Chinese image-text pairs from CogView and 300 million English pairs — VisualGLM-6B is designed for image understanding, description, and question answering. Fine-tuning on long visual QA datasets further aligns the model’s responses with human preferences. ...
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  • 25
    mcp-use

    mcp-use

    A solution to build and deploy MCP agents and applications

    mcp-use is an open source development platform offering SDKs, cloud infrastructure, and a developer-friendly control plane for building, managing, and deploying AI agents that leverage the Model Context Protocol (MCP). It enables connection to multiple MCP servers, each exposing specific tool capabilities like browsing, file operations, or specialized integrations, through a unified MCPClient. Developers can create custom agents (via MCPAgent) that dynamically select the most appropriate...
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