Infer (File Upload)

Upload a CSV file and get results back immediately.

POST /models/{model_id}/infer

Infer (File Upload)

cURL

curl --request POST \
  --url https://api.woodwide.ai/models/{model_id}/infer \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: multipart/form-data' \
  --form file=test.csv \
  --form output_type=json

import requests

url = "https://api.woodwide.ai/models/{model_id}/infer"

payload = "-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"file\"\r\n\r\ntest.csv\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"output_type\"\r\n\r\njson\r\n-----011000010111000001101001--"
headers = {
    "Authorization": "Bearer <token>",
    "Content-Type": "multipart/form-data"
}

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

print(response.text)

const form = new FormData();
form.append('file', 'test.csv');
form.append('output_type', 'json');

const options = {method: 'POST', headers: {Authorization: 'Bearer <token>'}};

options.body = form;

fetch('https://api.woodwide.ai/models/{model_id}/infer', 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.woodwide.ai/models/{model_id}/infer",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "POST",
  CURLOPT_POSTFIELDS => "-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"file\"\r\n\r\ntest.csv\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"output_type\"\r\n\r\njson\r\n-----011000010111000001101001--",
  CURLOPT_HTTPHEADER => [
    "Authorization: Bearer <token>",
    "Content-Type: multipart/form-data"
  ],
]);

$response = curl_exec($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.woodwide.ai/models/{model_id}/infer"

	payload := strings.NewReader("-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"file\"\r\n\r\ntest.csv\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"output_type\"\r\n\r\njson\r\n-----011000010111000001101001--")

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

	req.Header.Add("Authorization", "Bearer <token>")

	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.woodwide.ai/models/{model_id}/infer")
  .header("Authorization", "Bearer <token>")
  .body("-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"file\"\r\n\r\ntest.csv\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"output_type\"\r\n\r\njson\r\n-----011000010111000001101001--")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.woodwide.ai/models/{model_id}/infer")

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

request = Net::HTTP::Post.new(url)
request["Authorization"] = 'Bearer <token>'
request.body = "-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"file\"\r\n\r\ntest.csv\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"output_type\"\r\n\r\njson\r\n-----011000010111000001101001--"

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

200

{
  "job_id": "c3d4e5f6-0000-0000-0000-000000000001",
  "status": "succeeded",
  "latency_ms": 29567,
  "model_id": "b2c3d4e5-0000-0000-0000-000000000001",
  "model_version_id": "b2c3d4e5-0000-0000-0000-000000000002",
  "model_type": "prediction",
  "data": {
    "id": [
      0
    ],
    "prediction": [
      "competitor"
    ],
    "prediction_probs": [
      0.9999940395355225
    ]
  },
  "prediction_descriptions": {
    "competitor": {
      "summary": "Service Recovery and Support Volume",
      "description": "These active accounts are flagged for retention efforts due to elevated support volumes."
    }
  }
}

{
  "detail": "Not authenticated"
}

{
  "detail": "Forbidden"
}

{
  "detail": "Not found"
}

{
  "detail": [
    {
      "loc": [
        "<string>"
      ],
      "msg": "<string>",
      "type": "<string>"
    }
  ]
}

{
  "detail": "Rate limit exceeded. Retry after a short delay."
}

Uses the latest ready model version unless model_version_id is specified. Maximum file size is 30 MB.

Set output_type to control the response format (json, csv, or parquet). For anomaly models, set anomaly_format to ids_only (default) or per_row.

See Output Formats for output columns by model type.

Authorizations

Authorization · string · header · required

Bearer authentication header of the form Bearer <token>, where <token> is your auth token.

Path Parameters

model_id · string<uuid> · required

Body

multipart/form-data

file · string · required

The file to upload. Maximum file size: 30 MB.

model_version_id · string<uuid>

output_type · enum<string> · default: csv

Supported inference output formats.

Available options: json, csv, parquet

Example:

"json"

anomaly_format · enum<string> · default: ids_only

Controls anomaly detection output shape. 'ids_only' returns a list of anomalous row indices. 'per_row' returns id, is_anomaly, and anomaly_score for every input row. Ignored for non-anomaly model types.

Available options: ids_only, per_row

Response

200

application/json

Successful Response Output format depends on the output_type parameter (json, csv, or parquet). See Output Formats for output columns by model type.

When output_type is json, the response is a JSON object. When output_type is csv or parquet, the response is a file download.

job_id · string<uuid>

Unique ID for the inference job.

status · string

Job status (e.g. succeeded).

latency_ms · integer

Inference latency in milliseconds.

model_id · string<uuid>

ID of the model used.

model_version_id · string<uuid>

ID of the model version used.

model_type · string

Type of the model (e.g. prediction, clustering).

data · object

Inference results. Structure varies by model type.

prediction_descriptions · object

Human-readable descriptions keyed by prediction value (prediction models only).