List Pipeline Document Chunks

client.pipelines.documents.getChunks(, , ?): DocumentGetChunksResponse { class_name, embedding, end_char_idx, 11 more }

GET/api/v1/pipelines/{pipeline_id}/documents/{document_id}/chunks

Return a list of chunks for a pipeline document.

ParametersExpand Collapse

documentID: string

params: DocumentGetChunksParams { pipeline_id }

pipeline_id: string

ReturnsExpand Collapse

DocumentGetChunksResponse = Array<TextNode { class_name, embedding, end_char_idx, 11 more } >

class_name?: string

embedding?: Array<number> | null

Embedding of the node.

end_char_idx?: number | null

End char index of the node.

excluded_embed_metadata_keys?: Array<string>

Metadata keys that are excluded from text for the embed model.

excluded_llm_metadata_keys?: Array<string>

Metadata keys that are excluded from text for the LLM.

extra_info?: Record<string, unknown>

A flat dictionary of metadata fields

id_?: string

Unique ID of the node.

metadata_seperator?: string

Separator between metadata fields when converting to string.

metadata_template?: string

Template for how metadata is formatted, with {key} and {value} placeholders.

mimetype?: string

MIME type of the node content.

relationships?: Record<string, RelatedNodeInfo { node_id, class_name, hash, 2 more } | Array<UnionMember1>>

A mapping of relationships to other node information.

One of the following:

RelatedNodeInfo { node_id, class_name, hash, 2 more }

node_id: string

class_name?: string

hash?: string | null

metadata?: Record<string, unknown>

node_type?: "1" | "2" | "3" | 2 more | (string & {}) | null

One of the following:

"1" | "2" | "3" | 2 more

"1"

"2"

"3"

"4"

"5"

(string & {})

Array<UnionMember1>

node_id: string

class_name?: string

hash?: string | null

metadata?: Record<string, unknown>

node_type?: "1" | "2" | "3" | 2 more | (string & {}) | null

One of the following:

"1" | "2" | "3" | 2 more

"1"

"2"

"3"

"4"

"5"

(string & {})

start_char_idx?: number | null

Start char index of the node.

text?: string

Text content of the node.

text_template?: string

Template for how text is formatted, with {content} and {metadata_str} placeholders.

List Pipeline Document Chunks

import LlamaCloud from '@llamaindex/llama-cloud';

const client = new LlamaCloud({
  apiKey: process.env['LLAMA_CLOUD_API_KEY'], // This is the default and can be omitted
});

const textNodes = await client.pipelines.documents.getChunks('document_id', {
  pipeline_id: '182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e',
});

console.log(textNodes);

[
  {
    "class_name": "class_name",
    "embedding": [
      0
    ],
    "end_char_idx": 0,
    "excluded_embed_metadata_keys": [
      "string"
    ],
    "excluded_llm_metadata_keys": [
      "string"
    ],
    "extra_info": {
      "foo": "bar"
    },
    "id_": "id_",
    "metadata_seperator": "metadata_seperator",
    "metadata_template": "metadata_template",
    "mimetype": "mimetype",
    "relationships": {
      "foo": {
        "node_id": "node_id",
        "class_name": "class_name",
        "hash": "hash",
        "metadata": {
          "foo": "bar"
        },
        "node_type": "1"
      }
    },
    "start_char_idx": 0,
    "text": "text",
    "text_template": "text_template"
  }
]

Returns Examples

[
  {
    "class_name": "class_name",
    "embedding": [
      0
    ],
    "end_char_idx": 0,
    "excluded_embed_metadata_keys": [
      "string"
    ],
    "excluded_llm_metadata_keys": [
      "string"
    ],
    "extra_info": {
      "foo": "bar"
    },
    "id_": "id_",
    "metadata_seperator": "metadata_seperator",
    "metadata_template": "metadata_template",
    "mimetype": "mimetype",
    "relationships": {
      "foo": {
        "node_id": "node_id",
        "class_name": "class_name",
        "hash": "hash",
        "metadata": {
          "foo": "bar"
        },
        "node_type": "1"
      }
    },
    "start_char_idx": 0,
    "text": "text",
    "text_template": "text_template"
  }
]