Python
from chonkie.cloud import LateChunker 

chunker = LateChunker(api_key="{api_key}") 

chunks = chunker(text="YOUR_TEXT")
[
  {
    "text": "<string>",
    "start_index": 123,
    "end_index": 123,
    "token_count": 123,
    "embedding": [
      123
    ]
  }
]

Authorizations

​
Authorization
string
header
required

Your API Key from the Chonkie Cloud dashboard

Body

multipart/form-data
​
file
file

The file to chunk.

​
embedding_model
string
default:all-MiniLM-L6-v2

SentenceTransformer model identifier to use for embedding.

​
chunk_size
integer
default:2048

Maximum number of tokens per chunk.

​
recipe
string
default:default

Pre-defined recursive rules for splitting. Find all recipes on our Hugging Face Hub.

​
lang
string
default:en

Language of the text, used with recipes. Must match the language of the recipe.

​
min_characters_per_chunk
integer
default:24

Minimum number of characters per chunk.

Response

200 - application/json

Successful Response: A list of LateChunk objects.

A list containing LateChunk objects, detailing segments, sentences, and an optional chunk-level embedding derived from the full document.

​
text
string

The actual text content of the chunk.

​
start_index
integer

The starting character index of the chunk within the original input text.

​
end_index
integer

The ending character index (exclusive) of the chunk within the original input text.

​
token_count
integer

The number of tokens in this specific chunk, according to the tokenizer used.

​
embedding
number[]

Embedding vector (list of floats) for the entire chunk, derived from the full document embedding.