OCR that's just another curl request.

Scanned receipts, faxed contracts, photographed whiteboards — Tesseract OCR runs automatically, no separate OCR pipeline to stand up.

the-problem

Scans and photos aren't 'documents' to most extraction stacks — they're a special case requiring a separate OCR service, its own SDK, its own error handling, and a branch in your ingestion code to detect when a file needs OCR instead of ordinary parsing. Standing that up and keeping it patched is its own project.

one-request-solution

In txtfetch, OCR isn't a separate code path — it's just what happens when pixels arrive. POST a PNG, JPG, or TIFF (or a scanned PDF) and Tesseract OCR runs automatically behind the same /v1/extract endpoint, returning the same { status, extracted_text } shape as any other format.

curl
curl -X POST https://api.txtfetch.com/v1/extract \
  -H "Authorization: Bearer $TXTFETCH_KEY" \
  -F file=@scanned-invoice.png
Python
import os
import requests

with open("scanned-invoice.png", "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
import { readFile } from "node:fs/promises";

const file = new Blob([await readFile("scanned-invoice.png")]);
const form = new FormData();
form.append("file", file, "scanned-invoice.png");

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
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("scanned-invoice.png")
	if err != nil {
		panic(err)
	}
	defer f.Close()

	var body bytes.Buffer
	writer := multipart.NewWriter(&body)
	part, err := writer.CreateFormFile("file", "scanned-invoice.png")
	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)
}

Or skip the download — pass a url parameter and txtfetch fetches the document server-side:

curl
curl -X POST "https://api.txtfetch.com/v1/extract?url=https://example.com/uploads/receipt-photo.jpg" \
  -H "Authorization: Bearer $TXTFETCH_KEY"
Python
import os
import requests

r = requests.post(
    "https://api.txtfetch.com/v1/extract",
    headers={"Authorization": f"Bearer {os.environ['TXTFETCH_KEY']}"},
    params={"url": "https://example.com/uploads/receipt-photo.jpg"},
)

print(r.json()["extracted_text"])
JavaScript
const endpoint = new URL("https://api.txtfetch.com/v1/extract");
endpoint.searchParams.set("url", "https://example.com/uploads/receipt-photo.jpg");

const res = await fetch(endpoint, {
  method: "POST",
  headers: { Authorization: `Bearer ${process.env.TXTFETCH_KEY}` },
});

const { extracted_text } = await res.json();
console.log(extracted_text);
Go
package main

import (
	"encoding/json"
	"fmt"
	"net/http"
	"net/url"
	"os"
)

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

func main() {
	endpoint, err := url.Parse("https://api.txtfetch.com/v1/extract")
	if err != nil {
		panic(err)
	}
	q := endpoint.Query()
	q.Set("url", "https://example.com/uploads/receipt-photo.jpg")
	endpoint.RawQuery = q.Encode()

	req, err := http.NewRequest("POST", endpoint.String(), nil)
	if err != nil {
		panic(err)
	}
	req.Header.Set("Authorization", "Bearer "+os.Getenv("TXTFETCH_KEY"))

	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": "..."
}

formats-covered

  • .png
  • .jpg
  • .jpeg
  • .tiff
  • .tif
  • .bmp
  • .gif

faq

How do I OCR a scanned document via API?
POST the image as multipart form data to https://api.txtfetch.com/v1/extract — Tesseract OCR runs automatically and the response is { "status": "success", "extracted_text": "..." }, no OCR-specific parameters needed.
Which image formats are supported for OCR?
PNG, JPG/JPEG, TIFF, BMP, and GIF are all routed through Tesseract OCR automatically, the same as scanned PDF pages with no text layer.
Do I need to tell txtfetch that a file needs OCR?
No — format detection is automatic. Any file with no extractable text layer, image or PDF, is OCR'd without any extra flag or parameter.

go-further

Images & OCR

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