Run and manage cloud AI apps via the inference.sh CLI.
npx skills add https://github.com/Norfolk-Group/H-Analytics --skill agent-tools-norfolk-group
Please help me install this Agent Skill. Skill: agent-tools Source: https://github.com/Norfolk-Group/H-Analytics/tree/main/.agents/skills/agent-tools Command: npx skills add https://github.com/Norfolk-Group/H-Analytics --skill agent-tools-norfolk-group
Provides a unified, lightweight command-line interface to run and manage hundreds of remote AI apps without needing local GPUs or bespoke integrations, eliminating the overhead of switching between multiple model providers and manual file uploads.
Install the inference.sh CLI, authenticate, and run an app with the CLI to generate an image or video using infsh app run with an appropriate JSON input file.
High-intent search queries and answers about installing and using this skill.
You can run cloud AI apps from a single command-line interface by installing the inference.sh CLI, authenticating with your INFSH_API_KEY, and executing remote applications using the infsh app run command with a JSON input file.
Yes, you can upload local files for image and video generation via CLI. The inference.sh CLI automatically uploads local images, audio, and video files for remote processing and retrieves cloud-hosted result URLs for the generated outputs.
No, you do not need a local GPU to run LLM inference and 3D model generation. The inference.sh CLI executes hundreds of remote AI apps on cloud infrastructure, eliminating local hardware requirements and bespoke integrations.
The best way to automate social media posts using AI is through the inference.sh CLI, which supports social automation workflows. You can programmatically automate Twitter/X posts by running dedicated cloud apps directly from your command line.
Yes, the inference.sh CLI works with OpenRouter-compatible LLM models. You can run LLM prompts via these compatible models directly through the unified command-line endpoint without needing manual provider switching.
CLI cloud AI app execution fails without network access because the inference.sh CLI requires outbound network access to inference.sh endpoints for task execution, user authentication, and retrieving cloud-hosted result URLs.
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