---
title: "ChromaQueryTextRetriever"
id: chromaqueryretriever
slug: "/chromaqueryretriever"
description: "This is a a Retriever compatible with the Chroma Document Store."
---

# ChromaQueryTextRetriever

This is a a Retriever compatible with the Chroma Document Store.

<div className="key-value-table">

|  |  |
| --- | --- |
| **Most common position in a pipeline** | 1. After a Text Embedder and before a [`PromptBuilder`](../builders/promptbuilder.mdx)   in a RAG pipeline  2. The last component in the semantic search pipeline  3. After a Text Embedder and before an [`ExtractiveReader`](../readers/extractivereader.mdx)   in an extractive QA pipeline |
| **Mandatory init variables**           | `document_store`: An instance of a [ChromaDocumentStore](../../document-stores/chromadocumentstore.mdx)                                                                                                                                                                                         |
| **Mandatory run variables**            | `query`: A single query in plain-text format to be processed by the [Retriever](../retrievers.mdx)                                                                                                                                                                           |
| **Output variables**                   | `documents`: A list of documents                                                                                                                                                                                                                                            |
| **API reference**                      | [Chroma](/reference/integrations-chroma)                                                                                                                                                                                                                                           |
| **GitHub link**                        | https://github.com/deepset-ai/haystack-core-integrations/tree/main/integrations/chroma                                                                                                                                                                                    |
| **Package name** | `chroma-haystack` |

</div>

## Overview

The `ChromaQueryTextRetriever` is an embedding-based Retriever compatible with the `ChromaDocumentStore` that uses the Chroma [query API](https://docs.trychroma.com/reference/Collection#query).
This component takes a plain-text query string in input and returns the matching documents.
Chroma will create the embedding for the query using its [embedding function](https://docs.trychroma.com/embeddings#default-all-minilm-l6-v2); in case you do not want to use the default embedding function, this must be specified at `ChromaDocumentStore` initialization.

### Usage

#### On its own

This Retriever needs the `ChromaDocumentStore` and indexed documents to run.

```python
from haystack_integrations.document_stores.chroma import ChromaDocumentStore
from haystack_integrations.components.retrievers.chroma import ChromaQueryTextRetriever

document_store = ChromaDocumentStore()

retriever = ChromaQueryTextRetriever(document_store=document_store)

# example run query
retriever.run(query="How does Chroma Retriever work?")
```

#### In a pipeline

Here is how you could use the `ChromaQueryTextRetriever` in a Pipeline. In this example, you would create two pipelines: an indexing one and a querying one.

In the indexing pipeline, the documents are written in the Document Store.

Then, in the querying pipeline, `ChromaQueryTextRetriever` gets the answer from the Document Store based on the provided query.

```python
import os
from pathlib import Path

from haystack import Pipeline
from haystack.dataclasses import Document
from haystack.components.writers import DocumentWriter

from haystack_integrations.document_stores.chroma import ChromaDocumentStore
from haystack_integrations.components.retrievers.chroma import ChromaQueryTextRetriever

# Chroma is used in-memory so we use the same instances in the two pipelines below
document_store = ChromaDocumentStore()

documents = [
    Document(content="This contains variable declarations", meta={"title": "one"}),
    Document(
        content="This contains another sort of variable declarations",
        meta={"title": "two"},
    ),
    Document(
        content="This has nothing to do with variable declarations",
        meta={"title": "three"},
    ),
    Document(content="A random doc", meta={"title": "four"}),
]

indexing = Pipeline()
indexing.add_component("writer", DocumentWriter(document_store))
indexing.run({"writer": {"documents": documents}})

querying = Pipeline()
querying.add_component("retriever", ChromaQueryTextRetriever(document_store))
results = querying.run({"retriever": {"query": "Variable declarations", "top_k": 3}})

for d in results["retriever"]["documents"]:
    print(d.meta, d.score)
```

## Additional References

🧑‍🍳 Cookbook: [Use Chroma for RAG and Indexing](https://haystack.deepset.ai/cookbook/chroma-indexing-and-rag-examples)
