Create inference results batch

Create multiple inference results from conversation turns. Identify the session with exactly one of sessionId or sessionCustomId (same find-existing semantics as POST /inferenceResults). See Inference Results.

POST /inferenceResults/batch

Create inference results batch

cURL

curl --request POST \
  --url https://api.galtea.ai/inferenceResults/batch \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "conversationTurns": [
    {}
  ],
  "sessionId": "session_123",
  "sessionCustomId": "my-conversation-42",
  "versionId": "ver_123",
  "productId": "prod_123"
}
'

import requests

url = "https://api.galtea.ai/inferenceResults/batch"

payload = {
    "conversationTurns": [{}],
    "sessionId": "session_123",
    "sessionCustomId": "my-conversation-42",
    "versionId": "ver_123",
    "productId": "prod_123"
}
headers = {
    "Authorization": "Bearer <token>",
    "Content-Type": "application/json"
}

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

print(response.text)

const options = {
  method: 'POST',
  headers: {Authorization: 'Bearer <token>', 'Content-Type': 'application/json'},
  body: JSON.stringify({
    conversationTurns: [{}],
    sessionId: 'session_123',
    sessionCustomId: 'my-conversation-42',
    versionId: 'ver_123',
    productId: 'prod_123'
  })
};

fetch('https://api.galtea.ai/inferenceResults/batch', 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.galtea.ai/inferenceResults/batch",
  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([
    'conversationTurns' => [
        [
                
        ]
    ],
    'sessionId' => 'session_123',
    'sessionCustomId' => 'my-conversation-42',
    'versionId' => 'ver_123',
    'productId' => 'prod_123'
  ]),
  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.galtea.ai/inferenceResults/batch"

	payload := strings.NewReader("{\n  \"conversationTurns\": [\n    {}\n  ],\n  \"sessionId\": \"session_123\",\n  \"sessionCustomId\": \"my-conversation-42\",\n  \"versionId\": \"ver_123\",\n  \"productId\": \"prod_123\"\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.galtea.ai/inferenceResults/batch")
  .header("Authorization", "Bearer <token>")
  .header("Content-Type", "application/json")
  .body("{\n  \"conversationTurns\": [\n    {}\n  ],\n  \"sessionId\": \"session_123\",\n  \"sessionCustomId\": \"my-conversation-42\",\n  \"versionId\": \"ver_123\",\n  \"productId\": \"prod_123\"\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.galtea.ai/inferenceResults/batch")

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  \"conversationTurns\": [\n    {}\n  ],\n  \"sessionId\": \"session_123\",\n  \"sessionCustomId\": \"my-conversation-42\",\n  \"versionId\": \"ver_123\",\n  \"productId\": \"prod_123\"\n}"

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

201

[
  {
    "id": "ir_123",
    "sessionId": "session_123",
    "userId": "user_123",
    "index": 0,
    "status": "PENDING",
    "error": null,
    "input": {
      "user_message": "User input text"
    },
    "actualOutput": "Model response",
    "latency": 150,
    "inputTokens": 100,
    "outputTokens": 50,
    "cacheReadInputTokens": 20,
    "tokens": 150,
    "costPerInputToken": 0.00001,
    "costPerOutputToken": 0.00003,
    "costPerCacheReadInputToken": 0.000005,
    "cost": 0.001,
    "creditsUsed": 1,
    "conversationSimulatorVersion": "1.0.0",
    "traceId": "a1b2c3d4e5f6a1b2c3d4e5f6a1b2c3d4",
    "createdAt": "2023-11-07T05:31:56Z",
    "deletedAt": "2023-11-07T05:31:56Z"
  }
]

{
  "error": "Error type",
  "message": "Error message description"
}

Authorizations

Authorization · string · header · required

API key authorization. Pass your API key in the Authorization header as a Bearer token. Both new (gsk_*) and legacy (gsk-) API keys are accepted, e.g. Authorization: Bearer gsk_... or Authorization: Bearer gsk-....

Body

application/json

conversationTurns · object[] · required

sessionId · string

ID of the session. Provide this or sessionCustomId.

Example:

"session_123"

sessionCustomId · string

Your own conversation id. An existing session with this custom id is found and appended to; if none matches the call returns a 400, so create the session first through the sessions API. Requires versionId or productId. Provide this or sessionId.

Example:

"my-conversation-42"

versionId · string

Version anchor for the sessionCustomId lookup. Provide this or productId; if both are given, versionId wins.

Example:

"ver_123"

productId · string

Product anchor for the sessionCustomId lookup when no versionId is given: the existing session with that custom id is found across the product's versions.

Example:

"prod_123"

Response

201

application/json

Inference results created successfully

id · string

Example:

"ir_123"

sessionId · string

Example:

"session_123"

userId · string | null

Example:

"user_123"

index · integer

Order index within the session

Example:

0

status · enum<string>

Available options: PENDING, GENERATED, FAILED, SKIPPED

Example:

"PENDING"

error · string | null

Error message explaining why this inference result failed or was skipped

Example:

null

input · object | null

Structured input data. For plain text input, format is { user_message: "..." }

Example:

{ "user_message": "User input text" }

actualOutput · string object

The agent turn output. Plain text by default (the scored scalar). For voice turns, an envelope { assistant_message, content: [{ type, uri, transcript }] } carrying audio parts — the scored scalar stays the canonical transcript.

Example:

"Model response"

latency · integer | null

Example:

150

inputTokens · integer | null

Example:

100

outputTokens · integer | null

Example:

50

cacheReadInputTokens · integer | null

Example:

20

tokens · integer | null

Total tokens

Example:

150

costPerInputToken · number | null

Example:

0.00001

costPerOutputToken · number | null

Example:

0.00003

costPerCacheReadInputToken · number | null

Example:

0.000005

cost · number | null

Example:

0.001

creditsUsed · integer | null

Example:

1

conversationSimulatorVersion · string | null

Example:

"1.0.0"

traceId · string | null

W3C trace ID for the root span created during direct inference. The same trace ID is propagated to the user endpoint via the traceparent header.

Example:

"a1b2c3d4e5f6a1b2c3d4e5f6a1b2c3d4"

createdAt · string<date-time>

deletedAt · string<date-time> | null