Showing 11 open source projects for "lifecycle"

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  • 1
    MLflow

    MLflow

    Open source platform for the machine learning lifecycle

    MLflow is a platform to streamline machine learning development, including tracking experiments, packaging code into reproducible runs, and sharing and deploying models. MLflow offers a set of lightweight APIs that can be used with any existing machine learning application or library (TensorFlow, PyTorch, XGBoost, etc), wherever you currently run ML code (e.g. in notebooks, standalone applications or the cloud).
    Downloads: 9 This Week
    Last Update:
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  • 2
    Wanwu AI Agent Platform

    Wanwu AI Agent Platform

    Enterprise AI agent platform for workflows, models, and RAG apps

    ...Wanwu integrates large language models with business process automation, allowing developers to design complex, production-ready AI solutions tailored to enterprise needs. It includes comprehensive model lifecycle management capabilities, enabling users to configure, monitor, and manage different models efficiently. Wanwu also supports knowledge base construction, allowing organizations to incorporate structured and unstructured data into their AI applications. With a focus on openness and extensibility, it encourages developers to build on top of its ecosystem while maintaining a secure and compliant architecture for business use cases.
    Downloads: 4 This Week
    Last Update:
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  • 3
    BMad Method

    BMad Method

    Breakthrough Method for Agile Ai Driven Development

    BMad Method is a comprehensive AI-driven software development framework that structures the entire lifecycle of building applications through coordinated agent workflows and agile methodologies. It transforms AI from a reactive assistant into a structured team of specialized roles such as product manager, architect, developer, and QA, each operating within predefined workflows. The system guides users through phases including analysis, planning, solution design, and implementation, ensuring that projects are approached systematically rather than through ad hoc prompting. ...
    Downloads: 2 This Week
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  • 4
    SynaBun

    SynaBun

    Persistent vector memory for AI assistants

    ...The system integrates tightly with developer workflows by running alongside tools like Claude Code, enabling automatic memory capture, retrieval, and contextual augmentation through lifecycle hooks and commands. One of its defining characteristics is its Neural Interface, a browser-based 3D visualization that represents stored memories as nodes in an interactive graph, allowing users to explore relationships, edit entries, and manage knowledge visually.
    Downloads: 0 This Week
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    OpenShorts

    OpenShorts

    Free & open source AI video platform

    ...Its architecture uses modern technologies such as FastAPI, FFmpeg, and AI models for transcription, analysis, and rendering. Designed for creators and businesses, it automates the entire lifecycle of short-form video production.
    Downloads: 12 This Week
    Last Update:
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  • 6
    Evolver

    Evolver

    The GEP-Powered Self-Evolution Engine for AI Agents

    ...It also depends on Git as part of its operating model, using repository state for rollback, blast-radius calculation, and solidification workflows, which makes it especially relevant for code-centric agent environments. The CLI integrates with external agent runtimes through setup hooks, including support for platforms such as Cursor, where hooks can fire at specific lifecycle moments like session start or after file edits.
    Downloads: 3 This Week
    Last Update:
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  • 7
    ComfyUI-Copilot

    ComfyUI-Copilot

    AI assistant for ComfyUI workflow generation, debugging, and tuning

    ...ComfyUI-Copilot focuses on reducing the complexity of building node-based pipelines for generative AI tasks such as image generation, making it more accessible to both beginners and experienced users. It supports the entire workflow lifecycle, including generation, debugging, rewriting, and parameter optimization, helping users iterate more efficiently. ComfyUI-Copilot leverages large language model capabilities to analyze user intent, recommend nodes, and suggest models that match specific requirements. It also provides automated error detection and repair suggestions, improving reliability during development.
    Downloads: 1 This Week
    Last Update:
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  • 8
    Get Shit Done

    Get Shit Done

    A light-weight and powerful meta-prompting, context engineering

    Get Shit Done is a high-impact, open-source meta-prompting and spec-driven development system designed to streamline building software with AI assistants like Claude Code, OpenCode, and Gemini CLI. It solves “context rot” — the degradation of AI quality as a chat session grows — by structuring your idea into precise, context-engineered steps that are researched, scoped, planned, executed, and verified with clear commands and outputs instead of ad-hoc prompts. The project emphasizes...
    Downloads: 2 This Week
    Last Update:
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  • 9
    Devon

    Devon

    Open source AI pair programmer for coding, debugging, automation

    Devon is an open source AI-powered pair programming tool designed to assist developers with software engineering tasks through natural language interaction. It operates as an agent-based system that can explore codebases, edit files, and execute development workflows with minimal manual intervention. Devon uses a client-server architecture with a Python backend and multiple user interfaces, including a terminal interface and an Electron-based desktop application. Devon integrates with...
    Downloads: 1 This Week
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  • 10
    Machine Learning Systems

    Machine Learning Systems

    Introduction to Machine Learning Systems

    ...Rather than concentrating only on model training, the material emphasizes the broader discipline of AI engineering, covering efficiency, reliability, deployment, and evaluation across the full lifecycle of intelligent systems. The repository includes textbook content, supporting labs, and companion tools such as TinyTorch to help learners move from theory to hands-on experimentation. Its mission is to establish AI systems engineering as a foundational discipline alongside traditional software and computer engineering. The project is structured to guide users through reading, building, and deploying workflows, including running labs on edge devices like Arduino and Raspberry Pi.
    Downloads: 0 This Week
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  • 11
    XIAOJUSURVEY

    XIAOJUSURVEY

    Powerful survey system for creating, managing, and analyzing forms

    ...Its architecture supports high availability and scalability, making it suitable for enterprise-level deployments. Overall, Xiaoju Survey aims to streamline the entire lifecycle of survey management from creation to actionable insights.
    Downloads: 0 This Week
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