🤖 Execute invoice analytics workflow

Introduction

This API allows users to send an invoice via a POST request, and n8n will automatically evaluate and rate the invoice. The API processes the content and returns an analysis based on the provided model.

Execute an invoice analytics

Endpoint

Use the following endpoint to submit the invoice for analytic:

POST https://n8n.japanyosan.com/execute/invoice-analytics

Headers

The API requires the following headers:

• X-N8N-API-KEY - Your n8n API key for authentication
• Content-Type: application/json

Request Parameters

• The API expects the following parameters as a JSON payload:
• model (string) - The AI model to use. Accepted values:
  • ollama
  • gpt-4o
  • gpt-4o-mini
  • gpt-4-turbo
  • gpt-3.5-turbo
  • gemini-1.5-pro
  • gemini-1.5-flash
  • claude-3-5-sonnet-latest
  • claude-3-5-haiku-latest
  • claude-3-opus-latest
• prompt (string) - The specific prompt to provide for the invoice evaluation.
• content (string) - The invoice text to be analyzed.
• llmKey (string) - Your API key for the selected model. Not required when using the ollama model.

Example Request

Bash

curl --location 'https://n8n.japanyosan.com/execute/invoice-analytics' \
  --header 'X-N8N-API-KEY: ey*********' \
  --header 'Content-Type: application/json' \
  --data '{
      "model": "gpt-4o-mini",
      "content": "...",
      "llmKey": "sk-proj-ERa23*******",
      "prompt": "..."
  }'

Javascript

fetch('https://n8n.japanyosan.com/execute/invoice-analytics', {
  method: 'POST',
  headers: {
    'X-N8N-API-KEY': 'ey*********',
    'Content-Type': 'application/json'
  },
  body: JSON.stringify({
    model: 'gpt-4o-mini',
    content: '...',
    llmKey: 'sk-proj-ERa23*******',
    prompt: '...'
  })
})
  .then(response => response.json())
  .then(data => console.log(data));

Python

import requests
import json

url = "https://n8n.japanyosan.com/execute/invoice-analytics"
headers = {
    "X-N8N-API-KEY": "ey*********",
    "Content-Type": "application/json"
}
data = {
    "model": "gpt-4o-mini",
    "content": "...",
    "llmKey": "sk-proj-ERa23*******",
    "prompt": "..."
}

response = requests.post(url, headers=headers, data=json.dumps(data))
print(response.json())

Php

<?php
$url = "https://n8n.japanyosan.com/execute/invoice-analytics";
$headers = [
    "X-N8N-API-KEY: ey*********",
    "Content-Type: application/json"
];
$data = [
    "model" => "gpt-4o-mini",
    "content" => "...",
    "llmKey" => "sk-proj-ERa23*******",
    "prompt" => "..."
];

$options = [
    "http" => [
        "header" => implode("
", $headers),
        "method" => "POST",
        "content" => json_encode($data)
    ]
];
$context = stream_context_create($options);
$response = file_get_contents($url, false, $context);
echo $response;
?>

For Ollama model requests, you can omit the llmKey:

Bash

curl --location 'https://n8n.japanyosan.com/execute/invoice-analytics' \
  --header 'X-N8N-API-KEY: ey*********' \
  --header 'Content-Type: application/json' \
  --data '{
      "model": "gpt-4o-mini",
      "content": "...",
      "prompt": "..."
  }'

Javascript

fetch('https://n8n.japanyosan.com/execute/invoice-analytics', {
  method: 'POST',
  headers: {
    'X-N8N-API-KEY': 'ey*********',
    'Content-Type': 'application/json'
  },
  body: JSON.stringify({
    model: 'gpt-4o-mini',
    content: '...',
    prompt: '...'
  })
})
  .then(response => response.json())
  .then(data => console.log(data));

Python

import requests
import json

url = "https://n8n.japanyosan.com/execute/invoice-analytics"
headers = {
    "X-N8N-API-KEY": "ey*********",
    "Content-Type": "application/json"
}
data = {
    "model": "gpt-4o-mini",
    "content": "...",
    "prompt": "..."
}

response = requests.post(url, headers=headers, data=json.dumps(data))
print(response.json())

Php

<?php
$url = "https://n8n.japanyosan.com/execute/invoice-analytics";
$headers = [
    "X-N8N-API-KEY: ey*********",
    "Content-Type: application/json"
];
$data = [
    "model" => "gpt-4o-mini",
    "content" => "...",
    "prompt" => "..."
];

$options = [
    "http" => [
        "header" => implode("
", $headers),
        "method" => "POST",
        "content" => json_encode($data)
    ]
];
$context = stream_context_create($options);
$response = file_get_contents($url, false, $context);
echo $response;
?>

Response

The response body contains the following two keys:

• response (string): The result of the invoice analysis, which provides the evaluation and rating of the submitted invoice.
• execution_id (integer): A unique identifier for the specific execution of the invoice analytics workflow.

{
    "response": ".....",
    "execution_id": 778
}