> ## Documentation Index
> Fetch the complete documentation index at: https://www.edenai.co/docs/llms.txt
> Use this file to discover all available pages before exploring further.
# Resume Parser
> Resume Parser enables users to extract various information from resumes (curriculum vitae, CV) that could be in a variety of formats and returns structured data (name, job list, education, skills) to
export const TechArticleSchema = ({title, description, path, articleSection, about, proficiencyLevel = "Beginner", dependencies, keywords = [], datePublished, dateModified, image, inLanguage = "en"}) => {
const baseUrl = "https://www.edenai.co/docs";
const canonicalUrl = `${baseUrl}/${path}`.replace(/\/+$/, "");
const ogParams = new URLSearchParams({
division: articleSection || "",
title: title || "",
description: description || ""
});
const resolvedImage = image || `https://edenai.mintlify.app/_mintlify/api/og?${ogParams.toString()}`;
const data = {
"@context": "https://schema.org",
"@type": "TechArticle",
"@id": `${canonicalUrl}#techarticle`,
mainEntityOfPage: {
"@type": "WebPage",
"@id": canonicalUrl
},
headline: title,
name: title,
description: description,
url: canonicalUrl,
inLanguage: inLanguage,
isPartOf: {
"@type": "WebSite",
name: "Eden AI Documentation",
url: baseUrl
},
author: [{
"@type": "Organization",
name: "Eden AI",
url: "https://www.edenai.co/"
}],
publisher: {
"@type": "Organization",
name: "Eden AI",
url: "https://www.edenai.co/",
logo: {
"@type": "ImageObject",
url: "https://www.edenai.co/assets/logo.png"
}
}
};
if (articleSection) data.articleSection = articleSection;
if (about) data.about = {
"@type": "Thing",
name: about
};
if (proficiencyLevel) data.proficiencyLevel = proficiencyLevel;
if (dependencies) data.dependencies = dependencies;
if (keywords && keywords.length) data.keywords = keywords;
if (datePublished) data.datePublished = datePublished;
if (dateModified) data.dateModified = dateModified;
data.image = Array.isArray(resolvedImage) ? resolvedImage : [resolvedImage];
const json = JSON.stringify(data);
const schemaId = `techarticle-${canonicalUrl}`;
React.useEffect(() => {
if (typeof document === "undefined") return;
document.querySelectorAll(`script[data-schema-id="${schemaId}"]`).forEach(n => n.remove());
const script = document.createElement("script");
script.type = "application/ld+json";
script.dataset.schemaId = schemaId;
script.textContent = json;
document.head.appendChild(script);
return () => script.remove();
}, [json, schemaId]);
return null;
};
## Endpoint
`POST /v3/universal-ai` (sync)
Model string pattern: `ocr/resume_parser/{provider}[/{model}]`
## Input
| Field | Type | Required | Description |
| ----- | ----------- | -------- | ------------------------------------------ |
| file | file\_input | Yes | File ID from /v3/upload or direct file URL |
## Output
| Field | Type | Required | Description |
| ------------------------------------ | -------------- | -------- | ----------- |
| **extracted\_data** | object | Yes | |
| **personal\_infos** | object | Yes | |
| **name** | object | Yes | |
| first\_name | string | Yes | |
| last\_name | string | Yes | |
| raw\_name | string | Yes | |
| middle | string | Yes | |
| title | string | Yes | |
| prefix | string | Yes | |
| sufix | string | Yes | |
| **address** | object | Yes | |
| formatted\_location | string | Yes | |
| postal\_code | string | Yes | |
| region | string | Yes | |
| country | string | Yes | |
| country\_code | string | Yes | |
| raw\_input\_location | string | Yes | |
| street | string | Yes | |
| street\_number | string | Yes | |
| appartment\_number | string | Yes | |
| city | string | Yes | |
| self\_summary | string | Yes | |
| objective | string | Yes | |
| date\_of\_birth | string | Yes | |
| place\_of\_birth | string | Yes | |
| phones | array\[string] | No | |
| mails | array\[string] | No | |
| urls | array\[string] | No | |
| fax | array\[string] | No | |
| current\_profession | string | Yes | |
| gender | string | Yes | |
| nationality | string | Yes | |
| martial\_status | string | Yes | |
| current\_salary | string | Yes | |
| availability | string | No | |
| **education** | object | Yes | |
| total\_years\_education | int | Yes | |
| **entries** | array\[object] | No | |
| title | string | Yes | |
| start\_date | string | Yes | |
| end\_date | string | Yes | |
| **location** | object | Yes | |
| formatted\_location | string | Yes | |
| postal\_code | string | Yes | |
| region | string | Yes | |
| country | string | Yes | |
| country\_code | string | Yes | |
| raw\_input\_location | string | Yes | |
| street | string | Yes | |
| street\_number | string | Yes | |
| appartment\_number | string | Yes | |
| city | string | Yes | |
| establishment | string | Yes | |
| description | string | Yes | |
| gpa | string | Yes | |
| accreditation | string | Yes | |
| **work\_experience** | object | Yes | |
| total\_years\_experience | string | Yes | |
| **entries** | array\[object] | No | |
| title | string | Yes | |
| start\_date | string | Yes | |
| end\_date | string | Yes | |
| company | string | Yes | |
| **location** | object | Yes | |
| formatted\_location | string | Yes | |
| postal\_code | string | Yes | |
| region | string | Yes | |
| country | string | Yes | |
| country\_code | string | Yes | |
| raw\_input\_location | string | Yes | |
| street | string | Yes | |
| street\_number | string | Yes | |
| appartment\_number | string | Yes | |
| city | string | Yes | |
| description | string | Yes | |
| type | string | No | |
| industry | string | Yes | |
| **languages** | array\[object] | No | |
| name | string | Yes | |
| code | string | Yes | |
| **skills** | array\[object] | No | |
| name | string | Yes | |
| type | string | Yes | |
| **certifications** | array\[object] | No | |
| name | string | Yes | |
| type | string | Yes | |
| **courses** | array\[object] | No | |
| name | string | Yes | |
| type | string | Yes | |
| **publications** | array\[object] | No | |
| name | string | Yes | |
| type | string | Yes | |
| **interests** | array\[object] | No | |
| name | string | Yes | |
| type | string | Yes | |
## Available Providers
| Provider | Model String | Price |
| --------------- | --------------------------------- | ---------------- |
| affinda | `ocr/resume_parser/affinda` | \$0.07 per file |
| extracta | `ocr/resume_parser/extracta` | \$0.1 per page |
| klippa | `ocr/resume_parser/klippa` | \$0.1 per file |
| openai | `ocr/resume_parser/openai` | \$0.04 per page |
| openai (gpt-4o) | `ocr/resume_parser/openai/gpt-4o` | \$0.04 per page |
| senseloaf | `ocr/resume_parser/senseloaf` | \$0.045 per file |
## Quick Start
```python Python theme={null}
import requests
url = "https://api.edenai.run/v3/universal-ai"
headers = {
"Authorization": "Bearer YOUR_API_KEY",
"Content-Type": "application/json"
}
payload = {
"model": "ocr/resume_parser/affinda",
"input": {
"file": "YOUR_FILE_UUID_OR_URL"
}
}
response = requests.post(url, headers=headers, json=payload)
print(response.json())
```
```bash cURL theme={null}
curl -X POST https://api.edenai.run/v3/universal-ai \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "ocr/resume_parser/affinda",
"input": {"file": "YOUR_FILE_UUID_OR_URL"}
}'
```