Créer une prédiction
curl --request POST \
--url https://api.example.com/v2/{entity}/{project}/predictions \
--header 'Authorization: Basic <encoded-value>' \
--header 'Content-Type: application/json' \
--data '
{
"inputs": {},
"model": "<string>",
"output": "<unknown>",
"evaluation_run_id": "<string>",
"genai_span_ref": [
{
"span_id": "<string>",
"trace_id": "<string>"
}
]
}
'import requests
url = "https://api.example.com/v2/{entity}/{project}/predictions"
payload = {
"inputs": {},
"model": "<string>",
"output": "<unknown>",
"evaluation_run_id": "<string>",
"genai_span_ref": [
{
"span_id": "<string>",
"trace_id": "<string>"
}
]
}
headers = {
"Authorization": "Basic <encoded-value>",
"Content-Type": "application/json"
}
response = requests.post(url, json=payload, headers=headers)
print(response.text)const options = {
method: 'POST',
headers: {Authorization: 'Basic <encoded-value>', 'Content-Type': 'application/json'},
body: JSON.stringify({
inputs: {},
model: '<string>',
output: '<unknown>',
evaluation_run_id: '<string>',
genai_span_ref: [{span_id: '<string>', trace_id: '<string>'}]
})
};
fetch('https://api.example.com/v2/{entity}/{project}/predictions', 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.example.com/v2/{entity}/{project}/predictions",
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([
'inputs' => [
],
'model' => '<string>',
'output' => '<unknown>',
'evaluation_run_id' => '<string>',
'genai_span_ref' => [
[
'span_id' => '<string>',
'trace_id' => '<string>'
]
]
]),
CURLOPT_HTTPHEADER => [
"Authorization: Basic <encoded-value>",
"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.example.com/v2/{entity}/{project}/predictions"
payload := strings.NewReader("{\n \"inputs\": {},\n \"model\": \"<string>\",\n \"output\": \"<unknown>\",\n \"evaluation_run_id\": \"<string>\",\n \"genai_span_ref\": [\n {\n \"span_id\": \"<string>\",\n \"trace_id\": \"<string>\"\n }\n ]\n}")
req, _ := http.NewRequest("POST", url, payload)
req.Header.Add("Authorization", "Basic <encoded-value>")
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.example.com/v2/{entity}/{project}/predictions")
.header("Authorization", "Basic <encoded-value>")
.header("Content-Type", "application/json")
.body("{\n \"inputs\": {},\n \"model\": \"<string>\",\n \"output\": \"<unknown>\",\n \"evaluation_run_id\": \"<string>\",\n \"genai_span_ref\": [\n {\n \"span_id\": \"<string>\",\n \"trace_id\": \"<string>\"\n }\n ]\n}")
.asString();require 'uri'
require 'net/http'
url = URI("https://api.example.com/v2/{entity}/{project}/predictions")
http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true
request = Net::HTTP::Post.new(url)
request["Authorization"] = 'Basic <encoded-value>'
request["Content-Type"] = 'application/json'
request.body = "{\n \"inputs\": {},\n \"model\": \"<string>\",\n \"output\": \"<unknown>\",\n \"evaluation_run_id\": \"<string>\",\n \"genai_span_ref\": [\n {\n \"span_id\": \"<string>\",\n \"trace_id\": \"<string>\"\n }\n ]\n}"
response = http.request(request)
puts response.read_body{
"prediction_id": "<string>"
}{
"detail": [
{
"loc": [
"<string>"
],
"msg": "<string>",
"type": "<string>"
}
]
}Créer une prédiction
Créer une prédiction.
POST
/
v2
/
{entity}
/
{project}
/
predictions
Créer une prédiction
curl --request POST \
--url https://api.example.com/v2/{entity}/{project}/predictions \
--header 'Authorization: Basic <encoded-value>' \
--header 'Content-Type: application/json' \
--data '
{
"inputs": {},
"model": "<string>",
"output": "<unknown>",
"evaluation_run_id": "<string>",
"genai_span_ref": [
{
"span_id": "<string>",
"trace_id": "<string>"
}
]
}
'import requests
url = "https://api.example.com/v2/{entity}/{project}/predictions"
payload = {
"inputs": {},
"model": "<string>",
"output": "<unknown>",
"evaluation_run_id": "<string>",
"genai_span_ref": [
{
"span_id": "<string>",
"trace_id": "<string>"
}
]
}
headers = {
"Authorization": "Basic <encoded-value>",
"Content-Type": "application/json"
}
response = requests.post(url, json=payload, headers=headers)
print(response.text)const options = {
method: 'POST',
headers: {Authorization: 'Basic <encoded-value>', 'Content-Type': 'application/json'},
body: JSON.stringify({
inputs: {},
model: '<string>',
output: '<unknown>',
evaluation_run_id: '<string>',
genai_span_ref: [{span_id: '<string>', trace_id: '<string>'}]
})
};
fetch('https://api.example.com/v2/{entity}/{project}/predictions', 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.example.com/v2/{entity}/{project}/predictions",
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([
'inputs' => [
],
'model' => '<string>',
'output' => '<unknown>',
'evaluation_run_id' => '<string>',
'genai_span_ref' => [
[
'span_id' => '<string>',
'trace_id' => '<string>'
]
]
]),
CURLOPT_HTTPHEADER => [
"Authorization: Basic <encoded-value>",
"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.example.com/v2/{entity}/{project}/predictions"
payload := strings.NewReader("{\n \"inputs\": {},\n \"model\": \"<string>\",\n \"output\": \"<unknown>\",\n \"evaluation_run_id\": \"<string>\",\n \"genai_span_ref\": [\n {\n \"span_id\": \"<string>\",\n \"trace_id\": \"<string>\"\n }\n ]\n}")
req, _ := http.NewRequest("POST", url, payload)
req.Header.Add("Authorization", "Basic <encoded-value>")
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.example.com/v2/{entity}/{project}/predictions")
.header("Authorization", "Basic <encoded-value>")
.header("Content-Type", "application/json")
.body("{\n \"inputs\": {},\n \"model\": \"<string>\",\n \"output\": \"<unknown>\",\n \"evaluation_run_id\": \"<string>\",\n \"genai_span_ref\": [\n {\n \"span_id\": \"<string>\",\n \"trace_id\": \"<string>\"\n }\n ]\n}")
.asString();require 'uri'
require 'net/http'
url = URI("https://api.example.com/v2/{entity}/{project}/predictions")
http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true
request = Net::HTTP::Post.new(url)
request["Authorization"] = 'Basic <encoded-value>'
request["Content-Type"] = 'application/json'
request.body = "{\n \"inputs\": {},\n \"model\": \"<string>\",\n \"output\": \"<unknown>\",\n \"evaluation_run_id\": \"<string>\",\n \"genai_span_ref\": [\n {\n \"span_id\": \"<string>\",\n \"trace_id\": \"<string>\"\n }\n ]\n}"
response = http.request(request)
puts response.read_body{
"prediction_id": "<string>"
}{
"detail": [
{
"loc": [
"<string>"
],
"msg": "<string>",
"type": "<string>"
}
]
}Autorisations
HTTPBasicHTTPBearer
Basic authentication header of the form Basic <encoded-value>, where <encoded-value> is the base64-encoded string username:password.
Corps
application/json
Corps de la requête pour créer une prédiction via l’API REST.
Ce modèle exclut project_id, car il provient du chemin d’URL dans les endpoints REST.
Les entrées de la prédiction
La référence du modèle (URI weave://)
La sortie de la prédiction
ID de run d’évaluation facultatif permettant de lier cette prédiction en tant qu’appel enfant
Références facultatives aux spans GenAI générées par cette prédiction.
Show child attributes
Show child attributes
Réponse
Réponse réussie
L’ID de la prédiction
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