Infsh CLI

Install the belt CLI skill: npx skills add belt-sh/cli

inference.sh

Run AI apps in the cloud with a simple CLI. No GPU required.

Install CLI

curl -fsSL https://cli.inference.sh | sh
belt login

Agents / non-interactive shells: belt login --key <api-key>, or set INFSH_API_KEY (read on every command, no login needed). Without a TTY, belt login prints a URL; the browser then shows a claim code. Run belt login --code <code> on the same machine within 5 minutes.

What does the installer do? The install script detects your OS and architecture, downloads the correct binary from dist.inference.sh, verifies its SHA-256 checksum, and places it in your PATH. That's it — no elevated permissions, no background processes, no telemetry. If you have cosign installed, the installer also verifies the Sigstore signature automatically.

Manual install (if you prefer not to pipe to sh):

# Download the binary and checksums
curl -LO https://dist.inference.sh/cli/checksums.txt
curl -LO $(curl -fsSL https://dist.inference.sh/cli/manifest.json | grep -o '"url":"[^"]*"' | grep $(uname -s | tr A-Z a-z)-$(uname -m | sed 's/x86_64/amd64/;s/aarch64/arm64/') | head -1 | cut -d'"' -f4)
# Verify checksum
sha256sum -c checksums.txt --ignore-missing
# Extract and install
tar -xzf inferencesh-cli-*.tar.gz
mv inferencesh-cli-* ~/.local/bin/inferencesh

Quick Examples

# Generate an image
belt app run falai/flux-dev-lora --input '{"prompt": "a cat astronaut"}'

# Generate a video
belt app run google/veo-3-1-fast --input '{"prompt": "drone over mountains"}'

# Call Claude
belt app run openrouter/claude-sonnet-45 --input '{"prompt": "Explain quantum computing"}'

# Web search
belt app run tavily/search-assistant --input '{"query": "latest AI news"}'

# Post to Twitter
belt app run x/post-create --input '{"text": "Hello from AI!"}'

# Generate 3D model
belt app run infsh/rodin-3d-generator --input '{"prompt": "a wooden chair"}'

Local File Uploads

The CLI automatically uploads local files when you provide a path instead of a URL:

# Upscale a local image
belt app run falai/topaz-image-upscaler --input '{"image": "/path/to/photo.jpg", "upscale_factor": 2}'

# Image-to-video from local file
belt app run falai/wan-2-5-i2v --input '{"image": "./my-image.png", "prompt": "make it move"}'

# Avatar with local audio and image
belt app run bytedance/omnihuman-1-5 --input '{"audio": "/path/to/speech.mp3", "image": "/path/to/face.jpg"}'

# Post tweet with local media
belt app run x/post-create --input '{"text": "Check this out!", "media": ["./screenshot.png"]}'

Commands

What's Available

Related Skills

# Image generation (FLUX, Gemini, Grok, Seedream)
npx skills add inference-sh/skills@ai-image-generation

# Video generation (Veo, Seedance, Wan, OmniHuman)
npx skills add inference-sh/skills@ai-video-generation

# LLMs (Claude, Gemini, Kimi, GLM via OpenRouter)
npx skills add inference-sh/skills@llm-models

# Web search (Tavily, Exa)
npx skills add inference-sh/skills@web-search

# AI avatars & lipsync (OmniHuman, Fabric, PixVerse)
npx skills add inference-sh/skills@ai-avatar-video

# Twitter/X automation
npx skills add inference-sh/skills@twitter-automation

# Model-specific
npx skills add inference-sh/skills@flux-image
npx skills add inference-sh/skills@google-veo

# Utilities
npx skills add inference-sh/skills@image-upscaling
npx skills add inference-sh/skills@background-removal

Reference Files

• Authentication & Setup
• Discovering Apps
• Running Apps
• CLI Reference

Documentation

• Agent Skills Overview - The open standard for AI capabilities
• Getting Started - Introduction to inference.sh
• What is inference.sh? - Platform overview
• Apps Overview - Understanding the app ecosystem
• CLI Setup - Installing the CLI
• Workflows vs Agents - When to use each
• Why Agent Runtimes Matter - Runtime benefits