Showing 9 open source projects for "engineering"

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  • 1
    OpenHands

    OpenHands

    Open-source autonomous AI software engineer

    Welcome to OpenHands (formerly OpenDevin), an open-source autonomous AI software engineer who is capable of executing complex engineering tasks and collaborating actively with users on software development projects. Use AI to tackle the toil in your backlog, so you can focus on what matters: hard problems, creative challenges, and over-engineering your dotfiles We believe agentic technology is too important to be controlled by a few corporations. So we're building all our agents in the open on GitHub, under the MIT license. ...
    Downloads: 16 This Week
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  • 2
    CopilotKit

    CopilotKit

    Build in-app AI chatbots, and AI-powered Textareas

    A bridge between your copilot and your app. A programmable 2-way bridge between your copilot, and your application state (client & cloud). Supports 3rd party integrations (e.g. Salesforce, Zendesk, etc.). Plug-and-play, fully customizable, copilot infrastructure. Build in-app AI chatbots that can "see" the current app state + take action inside your app. The AI chatbot can talk to your app frontend & backend, and to 3rd party services (Salesforce, Dropbox, etc.) via plugins. Autocompletion +...
    Downloads: 14 This Week
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  • 3
    Dify

    Dify

    One API for plugins and datasets, one interface for prompt engineering

    ...With visual orchestration for various application types, Dify offers out-of-the-box, ready-to-use applications that can also serve as Backend-as-a-Service APIs. Unify your development process with one API for plugins and datasets integration, and streamline your operations using a single interface for prompt engineering, visual analytics, and continuous improvement. Out-of-the-box web sites supporting form mode and chat conversation mode A single API encompassing plugin capabilities, context enhancement, and more, saving you backend coding effort Visual data analysis, log review, and annotation for applications
    Downloads: 5 This Week
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  • 4
    Langchainrb

    Langchainrb

    Build LLM-powered applications in Ruby

    LangchainRB is a Ruby implementation of LangChain, allowing developers to build AI-driven applications using large language models (LLMs) and knowledge graphs.
    Downloads: 1 This Week
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  • 5
    Coze Studio

    Coze Studio

    An AI agent development platform with all-in-one visual tools

    Coze Studio is ByteDance’s open‑source, visual AI agent development platform. It offers no-code/low-code workflows to build, debug, and deploy conversational agents, integrating prompting, RAG-based knowledge bases, plugin systems, and workflow orchestration. Developed in Go (backend) and React/TypeScript (frontend), it uses a containerized microservices architecture suitable for enterprise deployment.
    Downloads: 1 This Week
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  • 6
    Potpie

    Potpie

    Create custom engineering agents for your codebase

    Potpie is an AI-powered data analysis tool that automates the exploration and visualization of datasets, assisting users in uncovering insights without extensive coding.
    Downloads: 0 This Week
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  • 7
    DSPy

    DSPy

    DSPy: The framework for programming—not prompting—language models

    Developed by the Stanford NLP Group, DSPy (Declarative Self-improving Python) is a framework that enables developers to program language models through compositional Python code rather than relying solely on prompt engineering. It facilitates the construction of modular AI systems and provides algorithms for optimizing prompts and weights, enhancing the quality and reliability of language model outputs.
    Downloads: 0 This Week
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  • 8
    kagent

    kagent

    Kubernetes native framework for building AI agents

    ...A major focus is tool integration via MCP: agents can connect to MCP servers for tool access, and kagent includes an MCP server with tools for common Kubernetes and platform engineering systems.
    Downloads: 0 This Week
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  • 9
    Koog

    Koog

    Koog is the official Kotlin framework for building AI agents

    ...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. Ready‑to‑use components address common AI engineering challenges, while intelligent history compression optimizes token usage and preserves context. A powerful streaming API enables real‑time response processing and parallel tool calls. Persistent memory allows agents to retain knowledge across sessions and between agents, and comprehensive tracing facilities provide detailed debugging and monitoring.
    Downloads: 0 This Week
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