向量模型

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://tokenhub.tencentmaas.com/v1"
)

response = client.embeddings.create(
    model="kinfra-text-embedding-0.6b",
    input="腾讯云 TokenHub 是一站式 AI 大模型服务平台。",
    encoding_format="float"
)

print(response.data[0].embedding)

import OpenAI from 'openai';

const client = new OpenAI({
  apiKey: 'YOUR_API_KEY',
  baseURL: 'https://tokenhub.tencentmaas.com/v1'
});

async function main() {
  const response = await client.embeddings.create({
    model: 'kinfra-text-embedding-0.6b',
    input: '腾讯云 TokenHub 是一站式 AI 大模型服务平台。',
    encoding_format: 'float'
  });

  console.log(response.data[0].embedding);
}

main();

package main

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

func main() {
    body, err := json.Marshal(map[string]interface{}{
        "model":           "kinfra-text-embedding-0.6b",
        "input":           "腾讯云 TokenHub 是一站式 AI 大模型服务平台。",
        "encoding_format": "float",
    })
    if err != nil {
        panic(err)
    }

    req, err := http.NewRequest("POST",
        "https://tokenhub.tencentmaas.com/v1/embeddings",
        bytes.NewBuffer(body))
    if err != nil {
        panic(err)
    }
    req.Header.Set("Authorization", "Bearer YOUR_API_KEY")
    req.Header.Set("Content-Type", "application/json")

    resp, err := http.DefaultClient.Do(req)
    if err != nil {
        panic(err)
    }
    defer resp.Body.Close()

    data, err := io.ReadAll(resp.Body)
    if err != nil {
        panic(err)
    }
    fmt.Println(string(data))
}

import okhttp3.*;
import com.google.gson.Gson;
import java.util.*;

public class TextEmbeddingQuickStart {
    public static void main(String[] args) throws Exception {
        Map<String, Object> body = new HashMap<>();
        body.put("model", "kinfra-text-embedding-0.6b");
        body.put("input", "腾讯云 TokenHub 是一站式 AI 大模型服务平台。");
        body.put("encoding_format", "float");

        Request request = new Request.Builder()
            .url("https://tokenhub.tencentmaas.com/v1/embeddings")
            .header("Authorization", "Bearer YOUR_API_KEY")
            .header("Content-Type", "application/json")
            .post(RequestBody.create(new Gson().toJson(body), MediaType.parse("application/json")))
            .build();

        try (Response response = new OkHttpClient().newCall(request).execute()) {
            System.out.println(response.body().string());
        }
    }
}

response = client.embeddings.create(
    model="kinfra-text-embedding-0.6b",
    input=["什么是 RAG？", "向量模型用于语义检索", "TokenHub 是一站式 AI 大模型服务平台"]
)

for item in response.data:
    print(f"index={item.index}, dim={len(item.embedding)}")

import requests

url = "https://tokenhub.tencentmaas.com/v1/embeddings/multimodal"
headers = {
    "Authorization": "Bearer YOUR_API_KEY",
    "Content-Type": "application/json"
}
payload = {
    "model": "kinfra-vl-embedding-2b",
    "input": [
        {"type": "text", "text": "一只白色猫坐在窗边"},
        {"type": "image_url", "image_url": {"url": "https://example.com/cat.png"}},
        {"type": "video_url", "video_url": {"url": "https://media.w3.org/2010/05/sintel/trailer.mp4"}}
    ],
    "instructions": "生成适合图文检索的向量",
    "encoding_format": "float"
}

response = requests.post(url, headers=headers, json=payload)
print(response.json())

async function main() {
  const response = await fetch('https://tokenhub.tencentmaas.com/v1/embeddings/multimodal', {
    method: 'POST',
    headers: {
      Authorization: 'Bearer YOUR_API_KEY',
      'Content-Type': 'application/json'
    },
    body: JSON.stringify({
      model: 'kinfra-vl-embedding-2b',
      input: [
        { type: 'text', text: '一只白色猫坐在窗边' },
        { type: 'image_url', image_url: { url: 'https://example.com/cat.png' } },
        { type: 'video_url', video_url: { url: 'https://media.w3.org/2010/05/sintel/trailer.mp4' } }
      ],
      instructions: '生成适合图文检索的向量',
      encoding_format: 'float'
    })
  });

  console.log(await response.json());
}

main();

package main

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

func main() {
    body, err := json.Marshal(map[string]interface{}{
        "model": "kinfra-vl-embedding-2b",
        "input": []map[string]interface{}{
            {"type": "text", "text": "一只白色猫坐在窗边"},
            {"type": "image_url", "image_url": map[string]string{"url": "https://example.com/cat.png"}},
            {"type": "video_url", "video_url": map[string]string{"url": "https://media.w3.org/2010/05/sintel/trailer.mp4"}},
        },
        "instructions":    "生成适合图文检索的向量",
        "encoding_format": "float",
    })
    if err != nil {
        panic(err)
    }

    req, err := http.NewRequest("POST",
        "https://tokenhub.tencentmaas.com/v1/embeddings/multimodal",
        bytes.NewBuffer(body))
    if err != nil {
        panic(err)
    }
    req.Header.Set("Authorization", "Bearer YOUR_API_KEY")
    req.Header.Set("Content-Type", "application/json")

    resp, err := http.DefaultClient.Do(req)
    if err != nil {
        panic(err)
    }
    defer resp.Body.Close()

    data, err := io.ReadAll(resp.Body)
    if err != nil {
        panic(err)
    }
    fmt.Println(string(data))
}

import okhttp3.*;
import com.google.gson.Gson;
import java.util.*;

public class MultimodalEmbeddingQuickStart {
    public static void main(String[] args) throws Exception {
        Map<String, Object> body = new HashMap<>();
        body.put("model", "kinfra-vl-embedding-2b");

        List<Map<String, Object>> inputList = new ArrayList<>();
        inputList.add(Map.of("type", "text", "text", "一只白色猫坐在窗边"));
        inputList.add(Map.of("type", "image_url", "image_url", Map.of("url", "https://example.com/cat.png")));
        inputList.add(Map.of("type", "video_url", "video_url", Map.of("url", "https://media.w3.org/2010/05/sintel/trailer.mp4")));
        body.put("input", inputList);
        body.put("instructions", "生成适合图文检索的向量");
        body.put("encoding_format", "float");

        Request request = new Request.Builder()
            .url("https://tokenhub.tencentmaas.com/v1/embeddings/multimodal")
            .header("Authorization", "Bearer YOUR_API_KEY")
            .header("Content-Type", "application/json")
            .post(RequestBody.create(new Gson().toJson(body), MediaType.parse("application/json")))
            .build();

        try (Response response = new OkHttpClient().newCall(request).execute()) {
            System.out.println(response.body().string());
        }
    }
}