from openai import OpenAI

client = OpenAI(
    base_url="https://api.infercom.ai/v1",
    api_key="your-infercom-api-key",
)

response = client.embeddings.create(
    input=["text to embed"],
    model="E5-Mistral-7B-Instruct",
)

print(response.data[0].embedding)

curl -X POST https://api.infercom.ai/v1/embeddings \
  -H "Authorization: Bearer $INFERCOM_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "input": ["text to embed"],
    "model": "E5-Mistral-7B-Instruct"
  }'

const options = {
  method: 'POST',
  headers: {Authorization: 'Bearer <token>', 'Content-Type': 'application/json'},
  body: JSON.stringify({
    input: ['text to embed number 1', 'text to embed number 2'],
    model: 'E5-Mistral-7B-Instruct'
  })
};

fetch('https://api.infercom.ai/v1/embeddings', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://api.infercom.ai/v1/embeddings",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "POST",
  CURLOPT_POSTFIELDS => json_encode([
    'input' => [
        'text to embed number 1',
        'text to embed number 2'
    ],
    'model' => 'E5-Mistral-7B-Instruct'
  ]),
  CURLOPT_HTTPHEADER => [
    "Authorization: Bearer <token>",
    "Content-Type: application/json"
  ],
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}

package main

import (
	"fmt"
	"strings"
	"net/http"
	"io"
)

func main() {

	url := "https://api.infercom.ai/v1/embeddings"

	payload := strings.NewReader("{\n  \"input\": [\n    \"text to embed number 1\",\n    \"text to embed number 2\"\n  ],\n  \"model\": \"E5-Mistral-7B-Instruct\"\n}")

	req, _ := http.NewRequest("POST", url, payload)

	req.Header.Add("Authorization", "Bearer <token>")
	req.Header.Add("Content-Type", "application/json")

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}

HttpResponse<String> response = Unirest.post("https://api.infercom.ai/v1/embeddings")
  .header("Authorization", "Bearer <token>")
  .header("Content-Type", "application/json")
  .body("{\n  \"input\": [\n    \"text to embed number 1\",\n    \"text to embed number 2\"\n  ],\n  \"model\": \"E5-Mistral-7B-Instruct\"\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.infercom.ai/v1/embeddings")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Post.new(url)
request["Authorization"] = 'Bearer <token>'
request["Content-Type"] = 'application/json'
request.body = "{\n  \"input\": [\n    \"text to embed number 1\",\n    \"text to embed number 2\"\n  ],\n  \"model\": \"E5-Mistral-7B-Instruct\"\n}"

response = http.request(request)
puts response.read_body

{
  "data": [
    {
      "index": 0,
      "object": "embedding",
      "embedding": [
        0.024864232167601585,
        -0.01452154759317636,
        0.008880083449184895
      ]
    },
    {
      "index": 1,
      "object": "embedding",
      "embedding": [
        0.010919672437012196,
        0.0016351072117686272,
        0.008019134402275085
      ]
    }
  ],
  "model": "E5-Mistral-7B-Instruct",
  "object": "list",
  "usage": {
    "prompt_tokens": 716,
    "total_tokens": 716
  }
}

"Invalid request body:  - missing property 'model'\""

"unauthorized"

{
  "error": "<string>"
}

{
  "error": "<string>"
}

{
  "error": "<string>"
}

{
  "error": {
    "code": "<string>",
    "message": "<string>",
    "param": "<string>",
    "type": "<string>"
  }
}

"<string>"

"Service Temporarily Unavailable"