ax-ai
This skill helps an LLM generate correct AI provider setup and configuration code using @ax-llm/ax. Use when the user asks about ai(), providers, models, presets, embeddings, batch audio with ai.transcribe() or ai.speak(), extended thinking, context caching, or mentions OpenAI/Anthropic/Google/Azure/DeepSeek/Mistral/Cohere/Reka/Grok with @ax-llm/ax.
ソース情報
- リポジトリ
- Tyler-R-Kendrick/ts-autocode
- ソースの最終更新活動
- 2026年7月12日 02:32
- 検出された SKILL.md の言語
- 英語
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SKILL.md
ソースの指示 · 読み取り専用プレビュー- name
- ax-ai
- description
- This skill helps an LLM generate correct AI provider setup and configuration code using @ax-llm/ax. Use when the user asks about ai(), providers, models, presets, embeddings, batch audio with ai.transcribe() or ai.speak(), extended thinking, context caching, or mentions OpenAI/Anthropic/Google/Azure/DeepSeek/Mistral/Cohere/Reka/Grok with @ax-llm/ax.
- version
- 23.0.0
# AI Provider Codegen Rules (@ax-llm/ax)
Use this skill to generate AI provider setup, configuration, and chat code. Prefer short, modern, copyable patterns. Do not write tutorial prose unless the user explicitly asks for explanation.
## Quick Setup
```typescript
import { ai } from '@ax-llm/ax';
const openai = ai({ name: 'openai', apiKey: 'sk-...' });
const claude = ai({ name: 'anthropic', apiKey: 'sk-ant-...' });
const gemini = ai({ name: 'google-gemini', apiKey: 'AIza...' });
const azure = ai({ name: 'azure-openai', apiKey: 'your-key', resourceName: 'your-resource', deploymentName: 'gpt-5-4-mini' });
const deepseek = ai({ name: 'deepseek', apiKey: 'sk-...' });
const mistral = ai({ name: 'mistral', apiKey: 'your-key' });
const cohere = ai({ name: 'cohere', apiKey: 'your-key' });
const custom = ai({
name: 'openai',
apiKey: process.env.PROVIDER_API_KEY,
apiURL: 'https://example.com/v1',
config: { model: 'provider/model-name' },
});
const reka = ai({ name: 'reka', apiKey: 'your-key' });
const grok = ai({ name: 'grok', apiKey: 'your-key' });
const compatible = ai({ name: 'openai', apiKey: 'key', apiURL: 'https://api.example.com/v1', config: { model: 'provider/model' } });
```
<!-- axir-nonportable:start webllm -->
WebLLM is browser-only and requires a host-created WebLLM engine. The host
loads or reloads models with WebLLM APIs such as `CreateMLCEngine(...)`; Ax
only forwards chat requests to that loaded engine. Do not present WebLLM as a
portable AxIR provider or a server-side default.
```typescript
import { ai, AxAIWebLLMModel } from '@ax-llm/ax';
const engine = await CreateMLCEngine(AxAIWebLLMModel.Llama32_3B_Instruct);
const llm = ai({
name: 'webllm',
engine,
config: {
model: AxAIWebLLMModel.Llama32_3B_Instruct,
stream: false,
supportsFunctions: false,
},
});
```
<!-- axir-nonportable:end webllm -->
## Model Presets
```typescript
import { ai, AxAIGoogleGeminiModel } from '@ax-llm/ax';
const gemini = ai({
name: 'google-gemini',
apiKey: process.env.GOOGLE_APIKEY!,
config: { model: 'simple' },
models: [
{ key: 'tiny', model: AxAIGoogleGeminiModel.Gemini31FlashLite, description: 'Fast + cheap', config: { maxTokens: 1024, temperature: 0.3 } },
{ key: 'simple', model: AxAIGoogleGeminiModel.Gemini35Flash, description: 'Balanced', config: { temperature: 0.6 } },
],
});
await gemini.chat({ model: 'tiny', chatPrompt: [{ role: 'user', content: 'Hi' }] });
```
## Model Catalog
```typescript
import { axGetSupportedAIModels } from '@ax-llm/ax';
const providers = axGetSupportedAIModels();
const openai = providers.find((provider) => provider.name === 'openai');
console.log(openai?.models[0]?.promptTokenCostPer1M);
const textProviders = axGetSupportedAIModels({ type: 'text' });
const embeddingProviders = axGetSupportedAIModels({ type: 'embeddings' });
```
Use `axGetSupportedAIModels()` to build provider/model selectors before creating an `ai(...)` instance. It returns bundled static metadata: provider names, display names, default models, raw `AxModelInfo` pricing/details, model type (`'text'`, `'embeddings'`, `'code'`, or `'audio'`), and normalized capability flags for thinking, thoughts, structured outputs, audio, temperature, and top-p support. Provider groups and models are sorted cheapest to most expensive based on bundled input + output token pricing; unpriced models sort last.
Filter with `{ type: 'all' | 'text' | 'embeddings' | 'code' | 'audio' }` or an array of those values. The `'text'` filter includes code-capable models; use `'code'` to show only code-first models.
Dynamic providers such as Azure OpenAI deployments are marked with `isDynamic: true` and may have an empty or static-limited model list.
## Chat
```typescript
const res = await llm.chat({
chatPrompt: [
{ role: 'system', content: 'You are concise.' },
{ role: 'user', content: 'Write a haiku about the ocean.' },
],
});
console.log(res.results[0]?.content);
```
## Batch Audio
Use `ai.transcribe(...)` for batch speech-to-text and `ai.speak(...)` for batch text-to-speech. These are separate from conversational `.chat()` audio config.
```typescript
const transcript = await llm.transcribe({
audio: { data: base64Wav, format: 'wav' },
model: 'gpt-4o-mini-transcribe',
language: 'en',
});
const speech = await llm.speak({
text: transcript.text,
model: 'gpt-4o-mini-tts',
voice: 'alloy',
format: 'mp3',
});
console.log(transcript.text);
console.log(speech.data);
```
Providers without the requested audio endpoint throw `AxMediaNotSupportedError`. Use `speech` forward options for signature audio artifacts and `modelConfig.audio` for conversational chat audio.
## Common Options
- `stream` (boolean): enable SSE; true by default
- `thinkingTokenBudget`: `'minimal'` | `'low'` | `'medium'` | `'high'` | `'highest'` | `'none'`
- `showThoughts`: include thoughts in output
- `functionCallMode`: `'auto'` | `'native'` | `'prompt'`
- `debug`, `logger`, `tracer`, `rateLimiter`, `timeout`
## Global Runtime Defaults
Use `axGlobals` when the app wants one live default for AI requests, generator runs, flows, or metrics:
```typescript
import { ai, axGlobals, axCreateDefaultColorLogger } from '@ax-llm/ax';
import { trace } from '@opentelemetry/api';
axGlobals.tracer = trace.getTracer('my-app');
axGlobals.debug = true;
axGlobals.logger = axCreateDefaultColorLogger();
axGlobals.customLabels = { service: 'api' };
const llm = ai({ name: 'openai', apiKey: process.env.OPENAI_APIKEY! });
```
Rules:
- `axGlobals.tracer`, `meter`, `logger`, `debug`, `abortSignal`, and `customLabels` are live runtime defaults; future calls read the current value even if the AI instance already exists.
- Precedence is: per-call options, then explicit AI/service options, then current `axGlobals`, then built-in defaults.
- `customLabels` merge from globals to service to call options; later sources override earlier keys.
- `abortSignal` values are merged, so either a global shutdown signal or a local request signal can cancel the request.
## DeepSeek Notes
```typescript
import { ai, AxAIDeepSeekModel } from '@ax-llm/ax';
const deepseek = ai({
name: 'deepseek',
apiKey: process.env.DEEPSEEK_APIKEY!,
config: { model: AxAIDeepSeekModel.DeepSeekV4Flash },
});
```
DeepSeek's current API models are `deepseek-v4-flash` and `deepseek-v4-pro`.
The deprecated `deepseek-chat` and `deepseek-reasoner` aliases are retained for
compatibility until DeepSeek removes them on 2026-07-24.
DeepSeek V4 supports thinking mode. Ax sends `thinking: { type: "disabled" }`
by default to preserve non-thinking behavior, and enables it when
`thinkingTokenBudget` is set. Ax maps lower budget levels to DeepSeek's `high`
effort and maps `highest` to `max`. DeepSeek V4 thinking models support tools,
but reject the `tool_choice` request parameter, so Ax omits forced/auto tool
choice for `deepseek-v4-pro`, `deepseek-v4-flash`, and `deepseek-reasoner`
while still sending tool definitions.
## Extended Thinking
```typescript
import { ai, AxAIAnthropicModel } from '@ax-llm/ax';
const claude = ai({
name: 'anthropic',
apiKey: process.env.ANTHROPIC_APIKEY!,
config: { model: AxAIAnthropicModel.Claude48Opus },
});
const res = await claude.chat(
{ chatPrompt: [{ role: 'user', content: 'Solve step by step...' }] },
{ thinkingTokenBudget: 'medium', showThoughts: true },
);
console.log(res.results[0]?.thought);
console.log(res.results[0]?.content);
```
### Budget Levels
| Level | Anthropic (tokens) | Gemini (tokens) |
|---|---|---|
| `'none'` | disabled | minimal |
| `'minimal'` | 1,024 | 200 |
| `'low'` | 5,000 | 800 |
| `'medium'` | 10,000 | 5,000 |
| `'high'` | 20,000 | 10,000 |
| `'highest'` | 32,000 | 24,500 |
### Anthropic Model-Specific Behavior
- Opus 4.8 and 4.7: adaptive thinking, effort levels including `'xhigh'`,
no manual `budget_tokens`, and no `temperature` / `topP` / `topK`.
- Opus 4.6: adaptive thinking, effort levels
- Opus 4.5: budget_tokens + effort levels (capped at `'high'`)
- Other thinking models: budget tokens only
Anthropic `modelConfig.effort` can be set directly on a request. Fast mode and
task budgets are Anthropic-only opt-ins; `taskBudget.total` must be at least
20,000 tokens.
```typescript
const res = await claude.chat({
chatPrompt: [{ role: 'user', content: 'Review this migration plan.' }],
modelConfig: {
effort: 'xhigh',
speed: 'fast',
taskBudget: { type: 'tokens', total: 64_000 },
},
});
```
### Custom Thinking Levels
```typescript
const claude = ai({
name: 'anthropic',
apiKey: '...',
config: {
model: AxAIAnthropicModel.Claude48Opus,
thinkingTokenBudgetLevels: {
minimal: 2048,
low: 8000,
medium: 16000,
high: 25000,
highest: 40000,
},
effortLevelMapping: {
minimal: 'low',
low: 'medium',
medium: 'high',
high: 'high',
highest: 'max',
},
},
});
```
## Embeddings
```typescript
const { embeddings } = await llm.embed({
texts: ['hello', 'world'],
embedModel: 'text-embedding-005',
});
```
## Context Caching
```typescript
const result = await gen.forward(llm, { code, language }, {
mem,
sessionId: 'code-review-session',
contextCache: {
ttlSeconds: 3600,
cacheBreakpoint: 'after-examples',
},
});
```
Breakpoint values: `'system'` | `'after-functions'` | `'after-examples'`
Provider behavior:
- Google Gemini: explicit caching with cache resource ID, auto TTL refresh
- Anthropic: implicit via `cache_control` markers
### External Registry (serverless)
```typescript
const registry: AxContextCacheRegistry = {
get: async (key) => { /* redis.get */ },
set: async (key, entry) => { /* redis.set */ },
};
```
## AWS Bedrock
```typescript
import { AxAIBedrock, AxAIBedrockModel } from '@ax-llm/ax-ai-aws-bedrock';
const bedrock = new AxAIBedrock({
region: 'us-east-2',
fallbackRegions: ['us-west-2'],
config: { model: AxAIBedrockModel.ClaudeOpus45 },
});
```
## Vercel AI SDK Integration
```typescript
import { generateText } from 'ai';
import { ai } from '@ax-llm/ax';
import { AxAIProvider } from '@ax-llm/ax-ai-sdk-provider';
const axAI = ai({
name: 'openai',
apiKey: process.env.OPENAI_APIKEY ?? '',
});
const model = new AxAIProvider(axAI);
const result = await generateText({
model,
prompt: 'Hello!',
});
```
## MCP + AxJSRuntime
```typescript
import { AxMCPClient } from '@ax-llm/ax';
import { axCreateMCPStdioTransport } from '@ax-llm/ax-tools';
const transport = axCreateMCPStdioTransport({
command: 'npx',
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