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[
{
"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,
"droppedSpanCount": 2,
"conversationSimulatorVersion": "1.0.0",
"traceId": "a1b2c3d4e5f6a1b2c3d4e5f6a1b2c3d4",
"createdAt": "2023-11-07T05:31:56Z",
"deletedAt": "2023-11-07T05:31:56Z",
"comments": [
{
"id": "comment_123",
"inferenceResultId": "inferenceResult_123",
"text": "Agent hallucinated the price.",
"tags": [
"hallucination",
"tone"
],
"userId": "user_123",
"userName": "John Doe",
"userEmail": "user@example.com",
"createdAt": "2023-11-07T05:31:56Z"
}
]
}
]{
"error": "Error type",
"message": "Error message description"
}Create traces batch
Create multiple traces from conversation turns. Identify the session with exactly one of sessionId or sessionCustomId (same find-existing semantics as POST /inferenceResults). See Traces. The REST path /inferenceResults and the inferenceResult* JSON fields keep the old name of this entity.
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[
{
"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,
"droppedSpanCount": 2,
"conversationSimulatorVersion": "1.0.0",
"traceId": "a1b2c3d4e5f6a1b2c3d4e5f6a1b2c3d4",
"createdAt": "2023-11-07T05:31:56Z",
"deletedAt": "2023-11-07T05:31:56Z",
"comments": [
{
"id": "comment_123",
"inferenceResultId": "inferenceResult_123",
"text": "Agent hallucinated the price.",
"tags": [
"hallucination",
"tone"
],
"userId": "user_123",
"userName": "John Doe",
"userEmail": "user@example.com",
"createdAt": "2023-11-07T05:31:56Z"
}
]
}
]{
"error": "Error type",
"message": "Error message description"
}Authorizations
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
ID of the session. Provide this or sessionCustomId.
"session_123"
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.
"my-conversation-42"
Version anchor for the sessionCustomId lookup. Provide this or productId; if both are given, versionId wins.
"ver_123"
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.
"prod_123"
Response
Traces created successfully
"ir_123"
"session_123"
"user_123"
Order index within the session
0
PENDING, GENERATED, FAILED, SKIPPED "PENDING"
Error message explaining why this trace failed or was skipped
null
Structured input data. For plain text input, format is { user_message: "..." }
{ "user_message": "User input text" }
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.
"Model response"
150
100
50
20
Total tokens
150
0.00001
0.00003
0.000005
0.001
1
How many spans sent with this trace were refused, for example a span with an empty name or a negative latency. Null means none were refused.
2
"1.0.0"
W3C trace ID for the root span created during direct inference. This is the OpenTelemetry trace id, not the id of this Galtea trace, which is id. The same trace ID is propagated to the user endpoint via the traceparent header.
"a1b2c3d4e5f6a1b2c3d4e5f6a1b2c3d4"
Free-form reviewer annotations on this turn, oldest first.
Show child attributes
Show child attributes