Regolo AI
透過 Mastra 的模型路由器存取 18 個 Regolo AI 模型。系統會自動使用 REGOLO_API_KEY 環境變數進行驗證。
詳情請參閱Regolo AI 文件。
.env
REGOLO_API_KEY=your-api-key
src/mastra/agents/my-agent.ts
import { Agent } from '@mastra/core/agent'
const agent = new Agent({
id: 'my-agent',
name: 'My Agent',
instructions: 'You are a helpful assistant',
model: 'regolo-ai/apertus-70b',
})
// Generate a response
const response = await agent.generate('Hello!')
// Stream a response
const stream = await agent.stream('Tell me a story')
for await (const chunk of stream) {
console.log(chunk)
}
資訊
Mastra 使用與 OpenAI 相容的 /chat/completions 端點。部分 Provider 專屬功能可能無法使用,詳情請參閱Regolo AI 文件。
模型模型 的直接連結
| Model | Context | Tools | Reasoning | Image | Audio | Video | Input $/1M | Output $/1M |
|---|---|---|---|---|---|---|---|---|
regolo-ai/apertus-70b | 30K | $0.46 | $2 | |||||
regolo-ai/brick-complexity-pro | 100K | $0.12 | $0.46 | |||||
regolo-ai/brick-v1-beta | 100K | — | — | |||||
regolo-ai/deepseek-ocr-2 | 4K | — | — | |||||
regolo-ai/faster-whisper-large-v3 | 448 | — | — | |||||
regolo-ai/gemma4-31b | 100K | $0.46 | $2 | |||||
regolo-ai/glm5.2 | 96K | $2 | $6 | |||||
regolo-ai/gpt-oss-120b | 128K | $1 | $4 | |||||
regolo-ai/gpt-oss-20b | 128K | $0.40 | $2 | |||||
regolo-ai/llama-3.3-70b-instruct | 128K | $0.60 | $3 | |||||
regolo-ai/mistral-small-4-119b | 256K | $0.75 | $3 | |||||
regolo-ai/qwen-image | 8K | $0.50 | $2 | |||||
regolo-ai/qwen3-coder-next | 262K | $0.30 | $1 | |||||
regolo-ai/qwen3-embedding-8b | 33K | $0.10 | $0.10 | |||||
regolo-ai/qwen3-reranker-4b | 33K | $0.12 | $0.12 | |||||
regolo-ai/qwen3.5-122b | 262K | $0.90 | $4 | |||||
regolo-ai/qwen3.5-9b | 262K | $0.15 | $0.60 | |||||
regolo-ai/qwen3.6-27b | 120K | $0.58 | $2 |
進階設定進階設定 的直接連結
自訂標頭自訂標頭 的直接連結
src/mastra/agents/my-agent.ts
const agent = new Agent({
id: 'custom-agent',
name: 'custom-agent',
model: {
url: 'https://api.regolo.ai/v1',
id: 'regolo-ai/apertus-70b',
apiKey: process.env.REGOLO_API_KEY,
headers: {
'X-Custom-Header': 'value',
},
},
})
動態選擇模型動態選擇模型 的直接連結
src/mastra/agents/my-agent.ts
const agent = new Agent({
id: 'dynamic-agent',
name: 'Dynamic Agent',
model: ({ requestContext }) => {
const useAdvanced = requestContext.task === 'complex'
return useAdvanced ? 'regolo-ai/qwen3.6-27b' : 'regolo-ai/apertus-70b'
},
})