Showing 4 open source projects for "input-output model"

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  • 1
    Explainer.js

    Explainer.js

    CLI tool to process files and output the code blocks

    CLI tool to process files and output the code blocks along with explanation, using various configuration options like API key, base URL, model name, and temperature.
    Downloads: 0 This Week
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  • 2
    mcp-cli

    mcp-cli

    Lighweight CLI to interact with MCP servers

    mcp-cli is a lightweight, Bun-based command-line interface (CLI) tool that simplifies how developers discover, inspect, and interact with Model Context Protocol (MCP) servers from the terminal. The Model Context Protocol is an emerging open standard for connecting language models and external tools, and mcp-cli helps mitigate common pain points like context window bloat by dynamically discovering MCP servers and reducing token load during interactions. It’s designed to be fast and shell-friendly, compiling to a single standalone binary and producing machine-readable output (e.g., JSON) that plays well with other CLI tooling like jq and standard piping. mcp-cli supports both stdio and HTTP-based MCP servers, connection pooling with a lazy-spawn daemon to keep connections warm, and flexible tool filtering via easy configuration options.
    Downloads: 0 This Week
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  • 3
    Habfuzz

    Habfuzz

    A command-line tool for data-driven fuzzy modelling

    Input 1 - A training dataset (multiple observations) of up to four variables (predictors) against one (response variable) Input 2 - A test dataset (multiple observations) of the same four variables with unknown response variable Output - Calculation of the response variable for each test observation using fuzzy logic or fuzzy rule-based Bayesian algorithms HABFUZZ is a habitat model, which can be used in ecohydraulic modelling applications for the calculation of the instream habitat suitability in various discharge scenarios in a simulated river reach. ...
    Downloads: 0 This Week
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  • 4
    AI Commits

    AI Commits

    A CLI that writes your git commit messages for you with AI

    ...It supports configuration via environment variables or config files so you can set your API key, preferred model, message style, and more. There are also options to preview, edit, or regenerate the AI-proposed message before actually committing, giving developers control instead of blindly trusting the output. Because it’s published as an npm package and even as a Homebrew formula, installation is straightforward across platforms.
    Downloads: 0 This Week
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