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@radkod/ai

v0.1.1

Published

Lightweight SDK for RadKod AI API — OpenAI-compatible LLM proxy with streaming and tool calling

Readme

@radkod/ai

Lightweight SDK for RadKod AI API — OpenAI-compatible LLM proxy with streaming and tool calling.

Install

npm install @radkod/ai

Quick Start

import { RadKodAI } from '@radkod/ai'

const ai = new RadKodAI({
  baseUrl: 'https://ai.radkod.com',
  apiKey: 'benv-your-key-here'
})

// Simple prompt
const answer = await ai.prompt('What is quantum computing?')
console.log(answer)

Streaming

await ai.promptStream('Count to 10', (token) => {
  process.stdout.write(token)
})

Or with full control:

const result = await ai.chatStream(
  {
    model: 'z-ai/glm4.7',
    messages: [{ role: 'user', content: 'Hello!' }]
  },
  {
    onToken: (token) => process.stdout.write(token),
    onDone: (fullText) => console.log('\n\nDone:', fullText.length, 'chars'),
    onError: (err) => console.error('Error:', err)
  }
)

Tool Calling

Define tools and handlers — the SDK runs the tool loop automatically:

const result = await ai.chatWithTools(
  {
    messages: [{ role: 'user', content: 'What is the weather in Istanbul?' }],
    tools: [
      {
        type: 'function',
        function: {
          name: 'get_weather',
          description: 'Get current weather for a city',
          parameters: {
            type: 'object',
            properties: {
              city: { type: 'string', description: 'City name' }
            },
            required: ['city']
          }
        }
      }
    ]
  },
  {
    get_weather: async ({ city }) => {
      // Your tool implementation
      return { temperature: 22, condition: 'sunny', city }
    }
  }
)

console.log(result.finalText) // "The weather in Istanbul is 22°C and sunny."

Full Chat API

const response = await ai.chat({
  model: 'meta/llama-3.3-70b-instruct',
  messages: [
    { role: 'system', content: 'You are a helpful assistant.' },
    { role: 'user', content: 'Explain REST vs GraphQL' }
  ],
  temperature: 0.7,
  max_tokens: 2000
})

console.log(response.choices[0].message.content)

List Models

const models = await ai.models()
models.forEach(m => console.log(m.id, '—', m.owned_by))

Health Check

const health = await ai.health()
console.log(health.status) // "ok"

Browser Usage

<script type="module">
  import { RadKodAI } from 'https://cdn.jsdelivr.net/npm/@radkod/ai/dist/index.mjs'

  const ai = new RadKodAI({ apiKey: 'benv-xxx' })
  const answer = await ai.prompt('Hello!')
  document.body.textContent = answer
</script>

Configuration

const ai = new RadKodAI({
  baseUrl: 'https://ai.radkod.com', // API server URL
  apiKey: 'benv-xxx',               // API key (optional in open mode)
  defaultModel: 'z-ai/glm4.7',     // Default model for all requests
  timeout: 300000                    // Request timeout in ms (default: 5min)
})

Error Handling

import { RadKodAI, RadKodError } from '@radkod/ai'

try {
  await ai.prompt('Hello')
} catch (err) {
  if (err instanceof RadKodError) {
    console.log(err.status) // 401, 429, 502, etc.
    console.log(err.body)   // API error response body
  }
}

License

MIT