2 projects for "read" with 2 filters applied:

  • Host LLMs in Production With On-Demand GPUs Icon
    Host LLMs in Production With On-Demand GPUs

    NVIDIA L4 GPUs. 5-second cold starts. Scale to zero when idle.

    Deploy your model, get an endpoint, pay only for compute time. No GPU provisioning or infrastructure management required.
    Start Free
  • Build Agents and Models on One Platform Icon
    Build Agents and Models on One Platform

    Everything you need to build production-ready agents and models. Access 200+ Google and third-party AI models and tools.

    Gemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
    Start Free
  • 1
    CodexPro

    CodexPro

    Use ChatGPT Developer Mode as a local coding agent for your repo

    CodexPro is a local MCP bridge that lets ChatGPT Developer Mode work inside a specific code repository. It starts a local server for the current workspace so ChatGPT can read files, search code, apply scoped edits, run guarded shell checks, and review changes. The project is designed around local control rather than hosting code or proxying model access through a third-party service. It supports setup, start, doctor, settings, handoff, and pro modes for different levels of agent involvement. Public access can be routed through options such as Cloudflare tunnels, ngrok, Tailscale Funnel, or local-only mode. ...
    Downloads: 10 This Week
    Last Update:
    See Project
  • 2
    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: 0 This Week
    Last Update:
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