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Gradient Inference

Community skill (unofficial) for DigitalOcean Gradient AI Serverless Inference. Discover available models and pricing, run chat completions or the Responses...

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Community skill (unofficial) for DigitalOcean Gradient AI Serverless Inference. Discover available models and pricing, run chat completions or the Responses...

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Download the package from Yavira.
Extract the archive and review SKILL.md first.
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Requirements

Target platform: OpenClaw
Install method: Manual import
Extraction: Extract archive
Prerequisites: OpenClaw
Primary doc: SKILL.md

Package facts

Download mode: Yavira redirect
Package format: ZIP package
Source platform: Tencent SkillHub
What's included: SKILL.md, scripts/gradient_chat.py, scripts/gradient_image.py, scripts/gradient_models.py, scripts/gradient_pricing.py, scripts/pricing_snapshot.json

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Trust & source

Release facts

Source: Tencent SkillHub
Verification: Indexed source record
Version: 0.1.3

Provenance

Publisher: simondelorean
Source page: View original listing
Canonical URL: Open canonical page

Documentation

ClawHub primary doc Primary doc: SKILL.md 13 sections Open source page

🦞 Gradient AI — Serverless Inference

⚠️ This is an unofficial community skill, not maintained by DigitalOcean. Use at your own risk. "Why manage GPUs when the ocean provides?" — ancient lobster proverb Use DigitalOcean's Gradient Serverless Inference to call large language models without managing infrastructure. The API is OpenAI-compatible, so standard SDKs and patterns work — just point at https://inference.do-ai.run/v1 and swim.

Authentication

All requests need a Model Access Key in the Authorization: Bearer header. export GRADIENT_API_KEY="your-model-access-key" Where to get one: DigitalOcean Console → Gradient AI → Model Access Keys → Create Key. 📖 Full auth docs

🔍 List Available Models

Window-shop for LLMs before you swipe the card. python3 gradient_models.py # Pretty table python3 gradient_models.py --json # Machine-readable python3 gradient_models.py --filter "llama" # Search by name Use this before hardcoding model IDs — models are added and deprecated over time. Direct API call: curl -s https://inference.do-ai.run/v1/models \ -H "Authorization: Bearer $GRADIENT_API_KEY" | python3 -m json.tool 📖 Models reference

💬 Chat Completions

The classic. Send structured messages (system/user/assistant roles), get a response. OpenAI-compatible, so you probably already know how this works. python3 gradient_chat.py \ --model "openai-gpt-oss-120b" \ --system "You are a helpful assistant." \ --prompt "Explain serverless inference in one paragraph." # Different model python3 gradient_chat.py \ --model "llama3.3-70b-instruct" \ --prompt "Write a haiku about cloud computing." Direct API call: curl -s https://inference.do-ai.run/v1/chat/completions \ -H "Authorization: Bearer $GRADIENT_API_KEY" \ -H "Content-Type: application/json" \ -d '{ "model": "openai-gpt-oss-120b", "messages": [ {"role": "system", "content": "You are a helpful assistant."}, {"role": "user", "content": "Hello!"} ], "temperature": 0.7, "max_tokens": 1000 }' 📖 Chat Completions docs

⚡ Responses API (Recommended)

DigitalOcean's recommended endpoint for new integrations. Simpler request format and supports prompt caching — a.k.a. "stop paying twice for the same context." # Basic usage python3 gradient_chat.py \ --model "openai-gpt-oss-120b" \ --prompt "Summarize this earnings report." \ --responses-api # With prompt caching (saves cost on follow-up queries) python3 gradient_chat.py \ --model "openai-gpt-oss-120b" \ --prompt "Now compare it to last quarter." \ --responses-api --cache Direct API call: curl -s https://inference.do-ai.run/v1/responses \ -H "Authorization: Bearer $GRADIENT_API_KEY" \ -H "Content-Type: application/json" \ -d '{ "model": "openai-gpt-oss-120b", "input": "Explain prompt caching.", "store": true }' When to use which: Chat CompletionsResponses APIRequest formatArray of messages with rolesSingle input stringPrompt caching❌✅ via store: trueMulti-step tool useManualBuilt-inBest forStructured conversationsSimple queries, cost savings 📖 Responses API docs

🖼️ Generate Images

Turn text prompts into images. Because sometimes a chart isn't enough. python3 gradient_image.py --prompt "A lobster trading stocks on Wall Street" python3 gradient_image.py --prompt "Sunset over the NYSE" --output sunset.png python3 gradient_image.py --prompt "Fintech logo" --json Direct API call: curl -s https://inference.do-ai.run/v1/images/generations \ -H "Authorization: Bearer $GRADIENT_API_KEY" \ -H "Content-Type: application/json" \ -d '{ "model": "dall-e-3", "prompt": "A lobster analyzing candlestick charts", "n": 1 }' 📖 Image generation docs

🧠 Model Selection Guide

Not all models are created equal. Choose wisely, young crustacean: ModelBest ForSpeedQualityContextopenai-gpt-oss-120bComplex reasoning, analysis, writingMedium★★★★★128Kllama3.3-70b-instructGeneral tasks, instruction followingFast★★★★128Kdeepseek-r1-distill-llama-70bMath, code, step-by-step reasoningSlow★★★★★128Kqwen3-32bQuick triage, short tasksFastest★★★32K 🦞 Pro tip: Cost-aware routing. Use a fast model (e.g., qwen3-32b) to score or triage, then only escalate to a strong model (e.g., openai-gpt-oss-120b) when depth is needed. Enable prompt caching for repeated context. Always run python3 gradient_models.py to check what's currently available — the menu changes. 📖 Available models

💰 Model Pricing Lookup

Check what models cost before you rack up a bill. Scrapes the official DigitalOcean pricing page — no API key needed. python3 gradient_pricing.py # Pretty table python3 gradient_pricing.py --json # Machine-readable python3 gradient_pricing.py --model "llama" # Filter by model name python3 gradient_pricing.py --no-cache # Skip cache, fetch live How it works: Fetches live pricing from DigitalOcean's docs (public page, no auth) Caches results for 24 hours in /tmp/gradient_pricing_cache.json Falls back to a bundled snapshot if the live fetch fails 🦞 Pro tip: Run python3 gradient_pricing.py --model "gpt-oss" before choosing a model to see the cost difference between gpt-oss-120b ($0.10/$0.70) and gpt-oss-20b ($0.05/$0.45) per 1M tokens. 📖 Pricing docs

CLI Reference

All scripts accept --json for machine-readable output. gradient_models.py [--json] [--filter QUERY] gradient_chat.py --prompt TEXT [--model ID] [--system TEXT] [--responses-api] [--cache] [--temperature F] [--max-tokens N] [--json] gradient_image.py --prompt TEXT [--model ID] [--output PATH] [--size WxH] [--json] gradient_pricing.py [--json] [--model QUERY] [--no-cache]

External Endpoints

EndpointPurposehttps://inference.do-ai.run/v1/modelsList available modelshttps://inference.do-ai.run/v1/chat/completionsChat Completions APIhttps://inference.do-ai.run/v1/responsesResponses API (recommended)https://inference.do-ai.run/v1/images/generationsImage generationhttps://docs.digitalocean.com/.../pricing/Pricing page (scraped, public)

Security & Privacy

All requests go to inference.do-ai.run — DigitalOcean's own endpoint Your GRADIENT_API_KEY is sent as a Bearer token in the Authorization header No other credentials or local data leave the machine Model Access Keys are scoped to inference only — they can't manage your DO account Prompt caching entries are scoped to your account and automatically expire

Trust Statement

By using this skill, prompts and data are sent to DigitalOcean's Gradient Inference API. Only install if you trust DigitalOcean with the content you send to their LLMs.

Important Notes

Run python3 gradient_models.py before assuming a model exists — they rotate All scripts exit with code 1 and print errors to stderr on failure

Category context

Code helpers, APIs, CLIs, browser automation, testing, and developer operations.

Source: Tencent SkillHub

Largest current source with strong distribution and engagement signals.

Package contents

Included in package

4 Scripts1 Docs1 Config

SKILL.md Primary doc
scripts/gradient_chat.py Scripts
scripts/gradient_image.py Scripts
scripts/gradient_models.py Scripts
scripts/gradient_pricing.py Scripts
scripts/pricing_snapshot.json Config