| title | batch_get_chunks |
|---|---|
| description | Retrieve specific chunks by their document ID and chunk number |
sources(List[Union[ChunkSource, Dict[str, Any]]]): List of ChunkSource objects or dictionaries with document_id and chunk_numberfolder_name(str | List[str], optional): Optional folder scope. Accepts canonical paths or a list of paths/names.use_colpali(bool, optional): Whether to request multimodal chunks when available. Defaults to True.output_format(str, optional): Controls how image chunks are returned. Set to"url"to receive presigned URLs; omit or set to"base64"(default) to receive base64 content.
List[FinalChunkResult]: List of chunk results
db = Morphik()
# Using dictionaries
sources = [
{"document_id": "doc_123", "chunk_number": 0},
{"document_id": "doc_456", "chunk_number": 2}
]
# Or using ChunkSource objects
sources = [
ChunkSource(document_id="doc_123", chunk_number=0),
ChunkSource(document_id="doc_456", chunk_number=2)
]
chunks = db.batch_get_chunks(sources)
for chunk in chunks:
print(f"Chunk from {chunk.document_id}, number {chunk.chunk_number}: {chunk.content[:50]}...")
```
async with AsyncMorphik() as db:
# Using dictionaries
sources = [
{"document_id": "doc_123", "chunk_number": 0},
{"document_id": "doc_456", "chunk_number": 2}
]
# Or using ChunkSource objects
sources = [
ChunkSource(document_id="doc_123", chunk_number=0),
ChunkSource(document_id="doc_456", chunk_number=2)
]
chunks = await db.batch_get_chunks(sources)
for chunk in chunks:
print(f"Chunk from {chunk.document_id}, number {chunk.chunk_number}: {chunk.content[:50]}...")
```
Each FinalChunkResult object in the returned list has the following properties:
content(str | PILImage): Chunk content (text or image)score(float): Relevance scoredocument_id(str): Parent document IDchunk_number(int): Chunk sequence numbermetadata(Dict[str, Any]): Document metadatacontent_type(str): Content typefilename(Optional[str]): Original filenamedownload_url(Optional[str]): URL to download full document