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Split large text documents into smaller, manageable chunks using different chunking strategies optimized for RAG (Retrieval-Augmented Generation) workflows. This endpoint supports multiple chunking algorithms including token-based, sentence-based, recursive, semantic, and specialized strategies.
curl --request POST \
--url https://api.orq.ai/v2/chunking \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '
{
"text": "The quick brown fox jumps over the lazy dog. This is a sample text that will be chunked into smaller pieces. Each chunk will maintain context while respecting the maximum chunk size.",
"strategy": "semantic",
"chunk_size": 256,
"threshold": 0.8,
"embedding_model": "openai/text-embedding-3-small",
"dimensions": 512,
"mode": "window",
"similarity_window": 1,
"metadata": true
}
'{
"chunks": [
{
"id": "01HQ3K4M5N6P7Q8R9SATBVCWDX",
"text": "The quick brown fox jumps over the lazy dog.",
"index": 0,
"metadata": {
"start_index": 0,
"end_index": 44,
"token_count": 10
}
},
{
"id": "01HQ3K4M5N6P7Q8R9SATBVCWDY",
"text": "This is a sample text that will be chunked into smaller pieces.",
"index": 1,
"metadata": {
"start_index": 45,
"end_index": 108,
"token_count": 12
}
}
]
}Documentation Index
Fetch the complete documentation index at: https://docs.orq.ai/llms.txt
Use this file to discover all available pages before exploring further.
Authorizations
Bearer authentication header of the form Bearer <token>, where <token> is your auth token.
Body
- Token Chunker Strategy
- Sentence Chunker Strategy
- Recursive Chunker Strategy
- Semantic Chunker Strategy
- Agentic Chunker Strategy
- Fast Chunker Strategy
Splits text based on token count. Best for ensuring chunks fit within LLM context windows and maintaining consistent chunk sizes for embedding models.
The text content to be chunked
token Whether to include metadata for each chunk
Return format: chunks (with metadata) or texts (plain strings)
chunks, texts Maximum tokens per chunk
Number of tokens to overlap between chunks
x >= 0Response
Text successfully chunked
Show child attributes
Show child attributes
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curl --request POST \
--url https://api.orq.ai/v2/chunking \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '
{
"text": "The quick brown fox jumps over the lazy dog. This is a sample text that will be chunked into smaller pieces. Each chunk will maintain context while respecting the maximum chunk size.",
"strategy": "semantic",
"chunk_size": 256,
"threshold": 0.8,
"embedding_model": "openai/text-embedding-3-small",
"dimensions": 512,
"mode": "window",
"similarity_window": 1,
"metadata": true
}
'{
"chunks": [
{
"id": "01HQ3K4M5N6P7Q8R9SATBVCWDX",
"text": "The quick brown fox jumps over the lazy dog.",
"index": 0,
"metadata": {
"start_index": 0,
"end_index": 44,
"token_count": 10
}
},
{
"id": "01HQ3K4M5N6P7Q8R9SATBVCWDY",
"text": "This is a sample text that will be chunked into smaller pieces.",
"index": 1,
"metadata": {
"start_index": 45,
"end_index": 108,
"token_count": 12
}
}
]
}