mirror of
https://github.com/NousResearch/hermes-agent.git
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db22efbe88
Extends the Windows-gating work to the optional-skills/ tree. Every
SKILL.md that previously omitted the platforms: field now carries an
explicit declaration, which Hermes's loader (agent.skill_utils.
skill_matches_platform) honors to skip-load on incompatible OSes.
58 skills declared cross-platform (platforms: [linux, macos, windows]):
autonomous-ai-agents/blackbox, autonomous-ai-agents/honcho
blockchain/base, blockchain/solana
communication/one-three-one-rule
creative/blender-mcp, creative/concept-diagrams, creative/hyperframes,
creative/kanban-video-orchestrator, creative/meme-generation
devops/cli (inference-sh-cli), devops/docker-management
dogfood/adversarial-ux-test
email/agentmail
finance/3-statement-model, finance/comps-analysis, finance/dcf-model,
finance/excel-author, finance/lbo-model, finance/merger-model,
finance/pptx-author
health/fitness-nutrition, health/neuroskill-bci
mcp/fastmcp, mcp/mcporter
migration/openclaw-migration
mlops/accelerate, mlops/chroma, mlops/clip, mlops/guidance,
mlops/hermes-atropos-environments, mlops/huggingface-tokenizers,
mlops/instructor, mlops/lambda-labs, mlops/llava, mlops/modal,
mlops/peft, mlops/pinecone, mlops/pytorch-lightning, mlops/qdrant,
mlops/saelens, mlops/simpo, mlops/stable-diffusion
productivity/canvas, productivity/shop-app, productivity/shopify,
productivity/siyuan, productivity/telephony
research/domain-intel, research/drug-discovery, research/duckduckgo-search,
research/gitnexus-explorer, research/parallel-cli, research/scrapling
security/1password, security/oss-forensics, security/sherlock
web-development/page-agent
5 skills gated from Windows (platforms: [linux, macos]):
mlops/flash-attention - Flash Attention wheels are Linux-first; Windows
install requires building from source with CUDA
mlops/faiss - faiss-gpu has no Windows wheel; gate rather than
leak partial (faiss-cpu) support
mlops/nemo-curator - NVIDIA NeMo ecosystem has no first-class Windows path
mlops/slime - Megatron+SGLang RL stack is Linux-only in practice
mlops/whisper - openai-whisper + ffmpeg setup on Windows is
non-trivial; gate until Windows install stanza lands
Methodology: scanned every SKILL.md for Windows-hostile signals
(apt-get, brew, systemd, osascript, ptrace, X11 binaries, POSIX-only
Python APIs, Docker POSIX $(pwd) bind-mounts, explicit 'linux-only' /
'macos-only' text). 3 skills flagged as having hard signals on review:
docker-management and qdrant only had POSIX $(pwd) docker examples and
the tools themselves (Docker Desktop, Qdrant) run fine on Windows —
declared ALL. whisper had an apt/brew ffmpeg install path and nothing
else but the openai-whisper Windows install story is rough enough to
warrant gating.
Strict-over-lenient policy: when in doubt, gate. Easier to un-gate after
verified Windows support lands than to leak partial support that
manifests as mid-task failures for Windows users.
156 lines
4.6 KiB
Markdown
156 lines
4.6 KiB
Markdown
---
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name: inference-sh-cli
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description: "Run 150+ AI apps via inference.sh CLI (infsh) — image generation, video creation, LLMs, search, 3D, social automation. Uses the terminal tool. Triggers: inference.sh, infsh, ai apps, flux, veo, image generation, video generation, seedream, seedance, tavily"
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version: 1.0.0
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author: okaris
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license: MIT
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platforms: [linux, macos, windows]
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metadata:
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hermes:
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tags: [AI, image-generation, video, LLM, search, inference, FLUX, Veo, Claude]
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related_skills: []
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---
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# inference.sh CLI
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Run 150+ AI apps in the cloud with a simple CLI. No GPU required.
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All commands use the **terminal tool** to run `infsh` commands.
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## When to Use
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- User asks to generate images (FLUX, Reve, Seedream, Grok, Gemini image)
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- User asks to generate video (Veo, Wan, Seedance, OmniHuman)
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- User asks about inference.sh or infsh
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- User wants to run AI apps without managing individual provider APIs
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- User asks for AI-powered search (Tavily, Exa)
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- User needs avatar/lipsync generation
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## Prerequisites
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The `infsh` CLI must be installed and authenticated. Check with:
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```bash
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infsh me
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```
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If not installed:
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```bash
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curl -fsSL https://cli.inference.sh | sh
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infsh login
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```
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See `references/authentication.md` for full setup details.
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## Workflow
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### 1. Always Search First
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Never guess app names — always search to find the correct app ID:
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```bash
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infsh app list --search flux
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infsh app list --search video
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infsh app list --search image
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```
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### 2. Run an App
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Use the exact app ID from the search results. Always use `--json` for machine-readable output:
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```bash
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infsh app run <app-id> --input '{"prompt": "your prompt here"}' --json
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```
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### 3. Parse the Output
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The JSON output contains URLs to generated media. Present these to the user with `MEDIA:<url>` for inline display.
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## Common Commands
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### Image Generation
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```bash
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# Search for image apps
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infsh app list --search image
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# FLUX Dev with LoRA
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infsh app run falai/flux-dev-lora --input '{"prompt": "sunset over mountains", "num_images": 1}' --json
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# Gemini image generation
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infsh app run google/gemini-2-5-flash-image --input '{"prompt": "futuristic city", "num_images": 1}' --json
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# Seedream (ByteDance)
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infsh app run bytedance/seedream-5-lite --input '{"prompt": "nature scene"}' --json
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# Grok Imagine (xAI)
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infsh app run xai/grok-imagine-image --input '{"prompt": "abstract art"}' --json
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```
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### Video Generation
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```bash
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# Search for video apps
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infsh app list --search video
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# Veo 3.1 (Google)
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infsh app run google/veo-3-1-fast --input '{"prompt": "drone shot of coastline"}' --json
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# Seedance (ByteDance)
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infsh app run bytedance/seedance-1-5-pro --input '{"prompt": "dancing figure", "resolution": "1080p"}' --json
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# Wan 2.5
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infsh app run falai/wan-2-5 --input '{"prompt": "person walking through city"}' --json
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```
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### Local File Uploads
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The CLI automatically uploads local files when you provide a path:
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```bash
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# Upscale a local image
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infsh app run falai/topaz-image-upscaler --input '{"image": "/path/to/photo.jpg", "upscale_factor": 2}' --json
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# Image-to-video from local file
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infsh app run falai/wan-2-5-i2v --input '{"image": "/path/to/image.png", "prompt": "make it move"}' --json
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# Avatar with audio
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infsh app run bytedance/omnihuman-1-5 --input '{"audio": "/path/to/audio.mp3", "image": "/path/to/face.jpg"}' --json
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```
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### Search & Research
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```bash
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infsh app list --search search
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infsh app run tavily/tavily-search --input '{"query": "latest AI news"}' --json
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infsh app run exa/exa-search --input '{"query": "machine learning papers"}' --json
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```
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### Other Categories
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```bash
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# 3D generation
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infsh app list --search 3d
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# Audio / TTS
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infsh app list --search tts
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# Twitter/X automation
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infsh app list --search twitter
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```
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## Pitfalls
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1. **Never guess app IDs** — always run `infsh app list --search <term>` first. App IDs change and new apps are added frequently.
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2. **Always use `--json`** — raw output is hard to parse. The `--json` flag gives structured output with URLs.
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3. **Check authentication** — if commands fail with auth errors, run `infsh login` or verify `INFSH_API_KEY` is set.
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4. **Long-running apps** — video generation can take 30-120 seconds. The terminal tool timeout should be sufficient, but warn the user it may take a moment.
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5. **Input format** — the `--input` flag takes a JSON string. Make sure to properly escape quotes.
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## Reference Docs
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- `references/authentication.md` — Setup, login, API keys
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- `references/app-discovery.md` — Searching and browsing the app catalog
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- `references/running-apps.md` — Running apps, input formats, output handling
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- `references/cli-reference.md` — Complete CLI command reference
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