Pagination & Field Selection ↗

Summary: Control how many results to return and which fields to include in your search results.

Original Documentation

Documentation Index#
Fetch the complete documentation index at: https://docs.trychroma.com/llms.txt Use this file to discover all available pages before exploring further.

Control how many results to return and which fields to include in your search results.

export const Callout = ({title, children}) =>

{title && <p className="block mb-2"><strong>{title}</strong></p>}
{children}

;

Pagination with Limit#

Use limit() to control how many results to return and offset to skip results for pagination.

from chromadb import Search

# Limit results
search = Search().limit(10)  # Return top 10 results

# Pagination with offset
search = Search().limit(10, offset=20)  # Skip first 20, return next 10

# No limit - returns all matching results
search = Search()  # Be careful with large collections!

import { Search } from 'chromadb';

// Limit results
const search1 = new Search().limit(10);  // Return top 10 results

// Pagination with offset
const search2 = new Search().limit(10, 20);  // Skip first 20, return next 10

// No limit - returns all matching results
const search3 = new Search();  // Be careful with large collections!

use chroma::types::SearchPayload;

let search = SearchPayload::default().limit(Some(10), 0);
let search = SearchPayload::default().limit(Some(10), 20);
let search = SearchPayload::default();

Limit Parameters#

Parameter	Type	Default	Description
`limit`	int or None	`None`	Maximum results to return (`None` = no limit)
`offset`	int	`0`	Number of results to skip (for pagination)

For Chroma Cloud users: The actual number of results returned will be capped by your quota limits, regardless of the limit value specified. This applies even when no limit is set.

Pagination Patterns#

# Page through results (0-indexed)
page_size = 10

# Page 0: Results 1-10
page_0 = Search().limit(page_size, offset=0)

# Page 1: Results 11-20
page_1 = Search().limit(page_size, offset=10)

# Page 2: Results 21-30
page_2 = Search().limit(page_size, offset=20)

# General formula
def get_page(page_number, page_size=10):
    return Search().limit(page_size, offset=page_number * page_size)

// Page through results (0-indexed)
const pageSize = 10;

// Page 0: Results 1-10
const page0 = new Search().limit(pageSize, 0);

// Page 1: Results 11-20
const page1 = new Search().limit(pageSize, 10);

// Page 2: Results 21-30
const page2 = new Search().limit(pageSize, 20);

// General formula
function getPage(pageNumber: number, pageSize = 10) {
  return new Search().limit(pageSize, pageNumber * pageSize);
}

use chroma::types::SearchPayload;

let page_size = 10;

// Page 0: Results 1-10
let page_0 = SearchPayload::default().limit(Some(page_size), 0);

// Page 1: Results 11-20
let page_1 = SearchPayload::default().limit(Some(page_size), 10);

// Page 2: Results 21-30
let page_2 = SearchPayload::default().limit(Some(page_size), 20);

// General Formula
fn get_page(page_number: usize, page_size: usize) -> SearchPayload {
    SearchPayload::default().limit(Some(page_size), page_number * page_size)
}

Pagination uses 0-based indexing. The first page is page 0, not page 1.

Field Selection with Select#

Control which fields are returned in your results to optimize data transfer and processing.

from chromadb import Search, K

# Default - returns IDs only
search = Search()

# Select specific fields
search = Search().select(K.DOCUMENT, K.SCORE)

# Select metadata fields
search = Search().select("title", "author", "date")

# Mix predefined and metadata fields
search = Search().select(K.DOCUMENT, K.SCORE, "title", "author")

# Select all available fields
search = Search().select_all()
# Returns: IDs, documents, embeddings, metadata, scores

import { Search, K } from 'chromadb';

// Default - returns IDs only
const search1 = new Search();

// Select specific fields
const search2 = new Search().select(K.DOCUMENT, K.SCORE);

// Select metadata fields
const search3 = new Search().select("title", "author", "date");

// Mix predefined and metadata fields
const search4 = new Search().select(K.DOCUMENT, K.SCORE, "title", "author");

// Select all available fields
const search5 = new Search().selectAll();
// Returns: IDs, documents, embeddings, metadata, scores

// Default - returns IDs only
use chroma::types::{Key, SearchPayload};

let search = SearchPayload::default(); // IDs only

// Select specific fields
let search = SearchPayload::default().select([Key::Document, Key::Score]);

// Select metadata fields
let search = SearchPayload::default().select([Key::field("title"), Key::field("author")]);

// Mix predefined and metadata fields
let search = SearchPayload::default().select([
    Key::Document,
    Key::Score,
    Key::field("title"),
    Key::field("author"),
]);

Selectable Fields#

Field	Internal Key	Usage	Description
IDs	`#id`	Always included	Document IDs are always returned
`K.DOCUMENT`	`#document`	`.select(K.DOCUMENT)`	Full document text
`K.EMBEDDING`	`#embedding`	`.select(K.EMBEDDING)`	Vector embeddings
`K.METADATA`	`#metadata`	`.select(K.METADATA)`	All metadata fields as a dict
`K.SCORE`	`#score`	`.select(K.SCORE)`	Search scores (when ranking is used)
`"field_name"`	(user-defined)	`.select("title", "author")`	Specific metadata fields

Field constants: K.* constants (e.g., K.DOCUMENT, K.EMBEDDING, K.ID) correspond to internal keys with # prefix (e.g., #document, #embedding, #id). Use the K.* constants in queries. Internal keys like #document and #embedding are used in schema configuration, while #metadata and #score are query-only fields not used in schema.

When selecting specific metadata fields (e.g., “title”), they appear directly in the metadata dict. Using K.METADATA returns ALL metadata fields at once.

Performance Considerations#

Selecting fewer fields improves performance by reducing data transfer:

Minimal: IDs only (default) - fastest queries
Moderate: Add scores and specific metadata fields
Heavy: Including documents and embeddings - larger payloads

Maximum: select_all() - returns everything

# Fast - minimal data
search = Search().limit(100)  # IDs only

# Moderate - just what you need
search = Search().limit(100).select(K.SCORE, "title", "date")

# Slower - large fields
search = Search().limit(100).select(K.DOCUMENT, K.EMBEDDING)

# Slowest - everything
search = Search().limit(100).select_all()

// Fast - minimal data
const search1 = new Search().limit(100);  // IDs only

// Moderate - just what you need
const search2 = new Search().limit(100).select(K.SCORE, "title", "date");

// Slower - large fields
const search3 = new Search().limit(100).select(K.DOCUMENT, K.EMBEDDING);

// Slowest - everything
const search4 = new Search().limit(100).selectAll();

Edge Cases#

No Limit Specified#

Without a limit, the search attempts to return all matching results, but will be capped by quota limits in Chroma Cloud.

# Attempts to return ALL matching documents
search = Search().where(K("status") == "active")  # No limit()
# Chroma Cloud: Results capped by quota

// Attempts to return ALL matching documents
const search = new Search().where(K("status").eq("active"));  // No limit()
// Chroma Cloud: Results capped by quota

Empty Results#

When no documents match, results will have empty lists/arrays.

Non-existent Fields#

Selecting non-existent metadata fields simply omits them from the results - they won’t appear in the metadata dict.

# If "non_existent_field" doesn't exist
search = Search().select("title", "non_existent_field")

# Result metadata will only contain "title" if it exists
# "non_existent_field" will not appear in the metadata dict at all

// If "non_existent_field" doesn't exist
const search = new Search().select("title", "non_existent_field");

// Result metadata will only contain "title" if it exists
// "non_existent_field" will not appear in the metadata object at all

Complete Example#

Here’s a practical example combining pagination with field selection:

from chromadb import Search, K, Knn

# Paginated search with field selection
def search_with_pagination(collection, query_text, page_size=20):
    current_page = 0

    while True:
        search = (Search()
            .where(K("status") == "published")
            .rank(Knn(query=query_text))
            .limit(page_size, offset=current_page * page_size)
            .select(K.DOCUMENT, K.SCORE, "title", "author", "date")
        )

        results = collection.search(search)
        rows = results.rows()[0]  # Get first (and only) search results

        if not rows:  # No more results
            break

        print(f"\n--- Page {current_page + 1} ---")
        for i, row in enumerate(rows, 1):
            print(f"{i}. {row['metadata']['title']} by {row['metadata']['author']}")
            print(f"   Score: {row['score']:.3f}, Date: {row['metadata']['date']}")
            print(f"   Preview: {row['document'][:100]}...")

        # Check if we want to continue
        user_input = input("\nPress Enter for next page, or 'q' to quit: ")
        if user_input.lower() == 'q':
            break

        current_page += 1

import { Search, K, Knn, type Collection } from 'chromadb';
import * as readline from 'readline';

// Paginated search with field selection
async function searchWithPagination(
  collection: Collection,
  queryText: string,
  pageSize = 20
) {
  let currentPage = 0;
  const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout
  });

  while (true) {
    const search = new Search()
      .where(K("status").eq("published"))
      .rank(Knn({ query: queryText }))
      .limit(pageSize, currentPage * pageSize)
      .select(K.DOCUMENT, K.SCORE, "title", "author", "date");

    const results = await collection.search(search);
    const rows = results.rows()[0];  // Get first (and only) search results

    if (!rows || rows.length === 0) {  // No more results
      break;
    }

    console.log(`\n--- Page ${currentPage + 1} ---`);
    for (const [i, row] of rows.entries()) {
      console.log(`${i+1}. ${row.metadata?.title} by ${row.metadata?.author}`);
      console.log(`   Score: ${row.score?.toFixed(3)}, Date: ${row.metadata?.date}`);
      console.log(`   Preview: ${row.document?.substring(0, 100)}...`);
    }

    // Check if we want to continue
    const userInput = await new Promise<string>(resolve => {
      rl.question("\nPress Enter for next page, or 'q' to quit: ", resolve);
    });

    if (userInput.toLowerCase() === 'q') {
      break;
    }

    currentPage += 1;
  }

  rl.close();
}

Tips and Best Practices#

Select only what you need - Reduces network transfer and memory usage
Use appropriate page sizes - 10-50 for UI, 100-500 for batch processing
Consider bandwidth - Avoid selecting embeddings unless necessary
IDs are always included - No need to explicitly select them
Use select_all() sparingly - Only when you truly need all fields

Next Steps#

Learn about Group By & Aggregation to diversify search results by category
Learn about batch operations for running multiple searches
See practical examples of pagination in production
Explore search basics for building complete queries

Link last verified June 7, 2026. View original ↗

Source: Chroma Docs

Link last verified: 2026-03-04