文本嵌入

curl https://www.qingbo.dev/v1/embeddings \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "text-embedding-3-small",
    "input": "清波 API 是统一的 AI 模型网关"
  }'

from openai import OpenAI

client = OpenAI(
    base_url="https://www.qingbo.dev/v1",
    api_key="YOUR_API_KEY"
)

response = client.embeddings.create(
    model="text-embedding-3-small",
    input="清波 API 是统一的 AI 模型网关"
)

vector = response.data[0].embedding
print(f"向量维度: {len(vector)}")

import OpenAI from 'openai';

const client = new OpenAI({
  baseURL: 'https://www.qingbo.dev/v1',
  apiKey: 'YOUR_API_KEY'
});

const response = await client.embeddings.create({
  model: 'text-embedding-3-small',
  input: '清波 API 是统一的 AI 模型网关'
});

console.log(`向量维度: ${response.data[0].embedding.length}`);

package main

import (
    "bytes"
    "encoding/json"
    "fmt"
    "io"
    "net/http"
)

func main() {
    payload := map[string]string{
        "model": "text-embedding-3-small",
        "input": "清波 API 是统一的 AI 模型网关",
    }

    body, _ := json.Marshal(payload)
    req, _ := http.NewRequest("POST", "https://www.qingbo.dev/v1/embeddings", bytes.NewBuffer(body))
    req.Header.Set("Authorization", "Bearer YOUR_API_KEY")
    req.Header.Set("Content-Type", "application/json")

    resp, _ := http.DefaultClient.Do(req)
    defer resp.Body.Close()
    result, _ := io.ReadAll(resp.Body)
    fmt.Println(string(result))
}

import java.net.http.*;
import java.net.URI;

public class Main {
    public static void main(String[] args) throws Exception {
        String payload = """
        {
          "model": "text-embedding-3-small",
          "input": "清波 API 是统一的 AI 模型网关"
        }
        """;

        HttpClient client = HttpClient.newHttpClient();
        HttpRequest request = HttpRequest.newBuilder()
            .uri(URI.create("https://www.qingbo.dev/v1/embeddings"))
            .header("Authorization", "Bearer YOUR_API_KEY")
            .header("Content-Type", "application/json")
            .POST(HttpRequest.BodyPublishers.ofString(payload))
            .build();

        HttpResponse<String> response = client.send(request,
            HttpResponse.BodyHandlers.ofString());
        System.out.println(response.body());
    }
}

{
  "object": "list",
  "model": "text-embedding-3-small",
  "data": [
    {
      "object": "embedding",
      "index": 0,
      "embedding": [0.0023, -0.0091, 0.0152, ...]
    }
  ],
  "usage": {
    "prompt_tokens": 8,
    "total_tokens": 8
  }
}