> Source: https://txtfetch.com/solutions/resume-and-cv-parsing
> Plain-text twin — every page on txtfetch.com has one. https://txtfetch.com/text

---

# Turn any résumé format into text your ATS can search.

Candidates upload whatever they have: .docx, .pdf, .doc, .odt, .rtf, and sometimes a design-tool PDF with no text layer. txtfetch turns every one of them into plain text.

the-problem

Applicant tracking systems accept whatever a candidate uploads. Most resumes arrive as .docx or .pdf, but some come as .doc, .odt, or .rtf. A design-tool export sometimes has no text layer at all, just an image of the page. A parser tuned for one format silently drops every candidate who used another.

how-txtfetch-solves-it

txtfetch returns the résumé as plain text, whatever the source format. It does not return a typed name, skill, or date field. Feed that text to your own parser or an LLM to pull structured fields out. A design-tool PDF with no text layer still works, because OCR runs automatically.

-   One endpoint reads .docx, .pdf, .doc, .odt, and .rtf.
-   OCR runs automatically on a design-tool PDF with no text layer.
-   The response is plain text, ready for your own parser or LLM to structure.
-   Async job and webhook mode covers bulk résumé imports.
-   Idempotency-Key support stops a retried upload from reprocessing the same résumé.
-   A batch of mixed .docx, .pdf, and scanned résumés needs no branching logic on your side.

curl

```curl
curl -X POST https://api.txtfetch.com/v1/extract \
  -H "Authorization: Bearer $TXTFETCH_KEY" \
  -F file=@resume.docx
```

Python

```python
import os
import requests

with open("resume.docx", "rb") as f:
    r = requests.post(
        "https://api.txtfetch.com/v1/extract",
        headers={"Authorization": f"Bearer {os.environ['TXTFETCH_KEY']}"},
        files={"file": f},
    )

print(r.json()["extracted_text"])
```

JavaScript

```javascript
import { readFile } from "node:fs/promises";

const file = new Blob([await readFile("resume.docx")]);
const form = new FormData();
form.append("file", file, "resume.docx");

const res = await fetch("https://api.txtfetch.com/v1/extract", {
  method: "POST",
  headers: { Authorization: `Bearer ${process.env.TXTFETCH_KEY}` },
  body: form,
});

const { extracted_text } = await res.json();
console.log(extracted_text);
```

Go

```go
package main

import (
	"bytes"
	"encoding/json"
	"fmt"
	"io"
	"mime/multipart"
	"net/http"
	"os"
)

type extractResponse struct {
	Status        string `json:"status"`
	ExtractedText string `json:"extracted_text"`
}

func main() {
	f, err := os.Open("resume.docx")
	if err != nil {
		panic(err)
	}
	defer f.Close()

	var body bytes.Buffer
	writer := multipart.NewWriter(&body)
	part, err := writer.CreateFormFile("file", "resume.docx")
	if err != nil {
		panic(err)
	}
	if _, err := io.Copy(part, f); err != nil {
		panic(err)
	}
	writer.Close()

	req, err := http.NewRequest("POST", "https://api.txtfetch.com/v1/extract", &body)
	if err != nil {
		panic(err)
	}
	req.Header.Set("Authorization", "Bearer "+os.Getenv("TXTFETCH_KEY"))
	req.Header.Set("Content-Type", writer.FormDataContentType())

	resp, err := http.DefaultClient.Do(req)
	if err != nil {
		panic(err)
	}
	defer resp.Body.Close()

	var result extractResponse
	if err := json.NewDecoder(resp.Body).Decode(&result); err != nil {
		panic(err)
	}
	fmt.Println(result.ExtractedText)
}
```

```
{
  "status": "success",
  "extracted_text": "..."
}
```

faq

**Does txtfetch extract structured fields like name or skills from a résumé?**: No. It returns the résumé as plain text. Pull structured fields with your own parser or an LLM.

**What happens with a résumé exported from a design tool with no text layer?**: OCR runs automatically, the same as any scanned page, so you still get text back.

**Which resume file formats does txtfetch read?**: docx, pdf, doc, odt, and rtf, all through the same endpoint.

related-reading

-   [Extract text from Word & Office →](https://txtfetch.com/extract/docx)
-   [Extract text from legacy .doc →](https://txtfetch.com/extract/legacy-office)
-   [Extract text from RTF →](https://txtfetch.com/extract/rtf)
-   [Extract text from OpenDocument (.odt) →](https://txtfetch.com/extract/odf)
-   [Any file to text, in the browser →](https://txtfetch.com/tools/file-to-text)
-   [Fix: Office text missing →](https://txtfetch.com/fixes/office-text-missing)
-   [Get an API key →](https://app.txtfetch.com/signup)

other-solutions

-   [RAG & LLM ingestion →](https://txtfetch.com/solutions/rag-ingestion)
-   [Search indexing →](https://txtfetch.com/solutions/search-indexing)
-   [Document workflows & automation →](https://txtfetch.com/solutions/document-workflows)
-   [Invoice & receipt processing →](https://txtfetch.com/solutions/invoice-and-receipt-processing)
-   [Contract & legal review →](https://txtfetch.com/solutions/contract-and-legal-review)
-   [Research & academic papers →](https://txtfetch.com/solutions/research-and-academic-papers)

## Start on the free plan.

Run your own documents through it before you commit. The Hobby plan needs no card.

[Get started →](https://app.txtfetch.com/signup)

[See the pricing →](https://txtfetch.com/pricing)