Showing 10 open source projects for "multi-system"

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  • Train ML Models With SQL You Already Know Icon
    Train ML Models With SQL You Already Know

    BigQuery automates data prep, analysis, and predictions with built-in AI assistance.

    Build and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
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    Secure File Transfer for Windows with Cerberus by Redwood

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  • 1
    Every Code

    Every Code

    Local AI coding agent CLI with multi-agent orchestration tools

    ...It is a community-driven fork of the Codex CLI, with a strong emphasis on improving real-world developer ergonomics and workflows. Every Code enhances the traditional coding assistant model by introducing multi-agent orchestration, allowing multiple AI agents to collaborate, compare solutions, and refine outputs in parallel. It supports integration with various AI providers, enabling users to route tasks across different models depending on their needs. Every Code also includes browser integration and automation capabilities, extending its usefulness beyond simple code generation into more complex development tasks. ...
    Downloads: 3 This Week
    Last Update:
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  • 2
    mac code

    mac code

    Claude Code, but it runs on your Mac for free

    ...The project focuses on enabling models that traditionally exceed available RAM to run efficiently by streaming model weights from SSD storage, thereby overcoming hardware limitations through innovative memory management techniques. It operates as a CLI-based assistant that routes user prompts into different execution paths such as chat, shell commands, or web search, functioning as a multi-purpose development agent. The system integrates with inference engines like llama.cpp and Apple’s MLX framework, allowing users to run models up to 35B parameters locally with varying performance trade-offs.
    Downloads: 1 This Week
    Last Update:
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  • 3
    CUDA Agent

    CUDA Agent

    Large-Scale Agentic RL for High-Performance CUDA Kernel Generation

    ...The system operates in a ReAct-style loop where the agent profiles baseline implementations, writes CUDA code, compiles it in a sandbox, and iteratively refines performance. CUDA-Agent has demonstrated strong benchmark results, achieving high pass rates and significant speedups compared with compiler baselines such as torch.compile.
    Downloads: 0 This Week
    Last Update:
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  • 4
    Ditto

    Ditto

    The simplest self-building coding agent

    Ditto is a simple self-building coding agent that generates multi-file Flask applications from natural language descriptions. Users describe the app they want, and the system attempts to plan and create routes, templates, static assets, and supporting files. It uses an LLM loop with basic tools to automate part of the coding process. The project is intentionally lightweight and experimental, making it easier to understand than larger agentic coding platforms.
    Downloads: 0 This Week
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  • Error to trace to log to deploy. One click. No SSH. Icon
    Error to trace to log to deploy. One click. No SSH.

    Catch the cause before the pager goes off.

    AppSignal links every error to the trace, the trace to the log, the log to the deploy that shipped it.
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  • 5
    Mistral Vibe CLI

    Mistral Vibe CLI

    Minimal CLI coding agent by Mistral

    Mistral Vibe is an AI-powered “vibe-coding” command-line interface (CLI) and coding-assistant framework built by Mistral AI to let developers write, refactor, search, and manage code through natural language and context-aware automation, rather than manual typing only. It aims to take developers out of repetitive boilerplate and let them stay “in the flow”: you can ask the tool to generate functions, refactor code, search across the codebase, manipulate files, commit changes via Git, or run...
    Downloads: 15 This Week
    Last Update:
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  • 6
    deepclaude

    deepclaude

    Use Claude Code's agent loop with DeepSeek V4 Pro, OpenRouter & more

    deepclaude is a lightweight proxy tool that enables developers to run Claude Code’s autonomous coding agent loop using alternative AI backends like DeepSeek V4 Pro, OpenRouter, or other Anthropic-compatible models. It preserves the full Claude Code experience—including file editing, terminal execution, and multi-step agent workflows—while dramatically reducing operational costs. By swapping out the underlying model instead of the interface, deepclaude delivers the same familiar UX with significantly cheaper token pricing. The platform supports seamless backend switching in real time, allowing users to choose between cost efficiency and higher reasoning power when needed. ...
    Downloads: 0 This Week
    Last Update:
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  • 7
    nanocode

    nanocode

    Minimal Claude Code alternative. Single Python file, zero dependencies

    ...It implements a full agentic loop where the model can reason, decide when to use tools, execute those tools, and iterate until producing a final answer, making it useful for simple AI-assisted coding workflows. It includes a set of integrated tools such as read, write, edit, glob, grep, and bash that let the agent interact with the file system and shell commands directly from the terminal, and it keeps a conversation history with colored terminal output for readability. The project exemplifies how lightweight architectures can still support practical agent workflows without complex infrastructure, making it suitable for developers exploring agent frameworks or building custom coding assistants.
    Downloads: 1 This Week
    Last Update:
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  • 8
    AutoCoder

    AutoCoder

    A long-running autonomous coding agent powered by the Claude Agent

    ...Rather than hand-writing boilerplate or repetitive patterns, users supply a specification—such as a description of a feature, a function prototype, or a module outline—and Autocoder fills in complete implementations that compile and run. It is built to support iterative refinement: after generating an initial draft, you can provide feedback or corrections, and the system will adjust the output to match evolving intentions. The core idea is to accelerate software production while preserving correctness and readability, minimizing the cognitive overhead that comes from switching between concept and implementation. Its architecture typically integrates language models with static analysis and template logic so that generated code is not only syntactically valid but also idiomatic and testable.
    Downloads: 1 This Week
    Last Update:
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  • 9
    Aden Hive

    Aden Hive

    Outcome driven agent development framework that evolves

    ...The framework also includes human-in-the-loop nodes, credential management, cost and budget controls, and real-time observability so teams can monitor execution and intervene as needed. Hive is designed for production environments and supports a wide range of large language models, local models, and business system connectivity.
    Downloads: 1 This Week
    Last Update:
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  • Custom VMs From 1 to 96 vCPUs With 99.95% Uptime Icon
    Custom VMs From 1 to 96 vCPUs With 99.95% Uptime

    General-purpose, compute-optimized, or GPU/TPU-accelerated. Built to your exact specs.

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  • 10
    MathCode

    MathCode

    A Frontier Mathematical Coding Agent

    ...The project combines AI agents with Lean Language Server Protocol integration, allowing it to inspect compiler feedback, search for lemmas, and iteratively repair failed proof attempts. It supports an agentic proving workflow where the system behaves more like an interactive mathematical engineer than a one-shot text generator. MathCode also includes visualization-oriented tooling such as theorem graph generation for Obsidian knowledge workflows. Its main value is bridging natural-language mathematics with formal verification systems in a way that is more automated, inspectable, and iterative than traditional theorem-proving pipelines.
    Downloads: 0 This Week
    Last Update:
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