OCR.chat API
Eine HTTP-Anfrage verwandelt ein Bild oder PDF in sauberen Text, Markdown, Tabellen und JSON, in 100+ Sprachen. Pro Seite gemessen, keine Überraschungen.
Überblick
The OCR.chat API is a small REST interface. You POST a file and get back a job with the recognized text and a per-page breakdown (text, bounding boxes, confidence). Jobs of 5 pages or fewer return inline; larger jobs return immediately with a pending status that you poll until done.
- Base URL:
https://ocr.chat - Formats in: PNG, JPG, WEBP, GIF, BMP, TIFF, and multi-page PDF
- Formats out:
txt,md,docx,pdf,csv,json - Engines:
cpu(fast, printed docs) andvlm(premium AI, handwriting, complex layout, math)
Authentifizierung
Authenticate with your API token (find it on your account page) as a Bearer header:
Authorization: Bearer YOUR_API_TOKEN
You can also pass ?api_token=… as a query parameter. Usage is metered against your account's page balance.
Ein Dokument übermitteln
POST /api/v1/ocr/, multipart form upload.
curl -X POST https://ocr.chat/api/v1/ocr/ \
-H "Authorization: Bearer YOUR_API_TOKEN" \
-F "file=@invoice.pdf" \
-F "tier=vlm" \
-F "language=auto"
Returns the job. For ≤5-page files it is already done with the text; larger files come back pending/processing, poll the status endpoint.
{
"uuid": "9f2c1b7e4a...",
"status": "done",
"tier": "vlm",
"language": "auto",
"page_count": 1,
"mean_confidence": 0.98,
"text": "INVOICE\nAcme Corp\nTotal: 215.00 USD",
"markdown": "# INVOICE\n\n**Acme Corp** ...",
"pages": [ { "index": 0, "text": "...", "blocks": [ { "text": "...", "bbox": [x0,y0,x1,y1], "confidence": 0.98 } ] } ]
}
Ergebnis erzielen
GET /api/v1/ocr/<uuid>/, poll until status is done or failed.
curl https://ocr.chat/api/v1/ocr/9f2c1b7e4a.../ \
-H "Authorization: Bearer YOUR_API_TOKEN"
Format herunterladen
GET /api/v1/ocr/<uuid>/download/?format=md, export the result. format is one of txt, md, docx, pdf, csv, json.
curl -L "https://ocr.chat/api/v1/ocr/9f2c1b7e4a.../download/?format=docx" \
-H "Authorization: Bearer YOUR_API_TOKEN" -o result.docx
Chatten Sie mit einem Dokument
Stellen Sie Fragen zu einem fertigen Auftrag. Antworten werden nur in den extrahierten Text geerdet und zitieren Sie die Quellseite. Erfordert ein Konto Token, die Chat-Funktion ist account-gated.
POST /api/v1/chat/<uuid>/, JSON body {"message": "your question"}.
curl -X POST https://ocr.chat/api/v1/chat/9f2c1b7e4a.../ \
-H "Authorization: Bearer YOUR_API_TOKEN" \
-H "Content-Type: application/json" \
-d '{"message": "What is the invoice total and due date?"}'
Gibt die Assistentennachricht mit ihrer Antwort und einer Liste der zitierten Seiten zurück:
{"conversation": "a1b2…", "message": {
"role": "assistant",
"content": "The total is $42, due on March 3 (p. 1).",
"citations": [{"page": 1, "snippet": "The invoice total is $42…"}]
}}
GET /api/v1/chat/<uuid>/history/, die vollständige Transkript für einen Job zu holen.
Beispiele für den Code
import requests, time
API = "https://ocr.chat/api/v1/ocr/"
H = {"Authorization": "Bearer YOUR_API_TOKEN"}
# Submit
with open("invoice.pdf", "rb") as f:
job = requests.post(API, headers=H,
files={"file": f}, data={"tier": "vlm"}).json()
# Poll until done
while job["status"] in ("pending", "processing"):
time.sleep(2)
job = requests.get(API + job["uuid"] + "/", headers=H).json()
print(job["markdown"])
# Download as DOCX
r = requests.get(API + job["uuid"] + "/download/",
headers=H, params={"format": "docx"})
open("result.docx", "wb").write(r.content)
import fs from "fs";
const API = "https://ocr.chat/api/v1/ocr/";
const H = { Authorization: "Bearer YOUR_API_TOKEN" };
const form = new FormData();
form.append("file", new Blob([fs.readFileSync("invoice.pdf")]), "invoice.pdf");
form.append("tier", "vlm");
let job = await (await fetch(API, { method: "POST", headers: H, body: form })).json();
while (["pending", "processing"].includes(job.status)) {
await new Promise(r => setTimeout(r, 2000));
job = await (await fetch(API + job.uuid + "/", { headers: H })).json();
}
console.log(job.markdown);
# 1. Submit
curl -X POST https://ocr.chat/api/v1/ocr/ \
-H "Authorization: Bearer YOUR_API_TOKEN" \
-F "file=@invoice.pdf" -F "tier=vlm"
# 2. Poll (use the uuid from step 1)
curl https://ocr.chat/api/v1/ocr/UUID/ \
-H "Authorization: Bearer YOUR_API_TOKEN"
# 3. Download
curl -L "https://ocr.chat/api/v1/ocr/UUID/download/?format=md" \
-H "Authorization: Bearer YOUR_API_TOKEN" -o result.md
Parameter
| Field | Type | Description |
|---|---|---|
file | file | Required. The image or PDF to process. |
tier | string | cpu (default, fast/printed) or vlm (premium AI: handwriting, layout, math). |
language | string | auto (default) or a language code (en, ch, ja, ar, …). |
tool | string | Optional tool slug (e.g. extract-tables, handwriting-to-text) to apply that tool's preset. |
translate_to | string | For the translate tool, target language code. |
Fehler & Grenzen
| Code | Meaning |
|---|---|
400 | No file, unsupported type, or file too large. |
401 | Missing or invalid API token. |
402 | Out of pages, daily/monthly free limit reached, or no credits. The body includes used/cap. |
404 | Job UUID not found. |
409 | Download requested before the job finished. |
Each page processed costs credits (1/page on the fast tier, more on premium). Paid plans raise per-file page caps and add priority. See pricing.
Häufig gestellte Fragen
language=auto to detect, or pass a specific code.