docs: start adding integrations API reference - Chroma (#9904)

2025-12-11 14:57:25 +00:00 · 2025-10-20 14:57:17 +02:00 · 2025-10-20 14:57:17 +02:00 · 705b66bbfd
commit 705b66bbfd
parent 3cb03d44fe
6 changed files with 2032 additions and 0 deletions
--- a/docs-website/reference-sidebars.js
+++ b/docs-website/reference-sidebars.js
@ -15,5 +15,11 @@ export default {
      link: { type: 'generated-index', title: 'Haystack API' },
      items: [{ type: 'autogenerated', dirName: 'haystack-api' }],
    },
+    {
+      type: 'category',
+      label: 'Integrations API',
+      link: { type: 'generated-index', title: 'Integrations API' },
+      items: [{ type: 'autogenerated', dirName: 'integrations-api' }],
+    },
  ],
 };
--- a/docs-website/reference/integrations-api/chroma.md
+++ b/docs-website/reference/integrations-api/chroma.md
@ -0,0 +1,666 @@
+---
+title: "Chroma"
+id: integrations-chroma
+description: "Chroma integration for Haystack"
+slug: "/integrations-chroma"
+---
+
+<a id="haystack_integrations.components.retrievers.chroma.retriever"></a>
+
+# Module haystack\_integrations.components.retrievers.chroma.retriever
+
+<a id="haystack_integrations.components.retrievers.chroma.retriever.ChromaQueryTextRetriever"></a>
+
+## ChromaQueryTextRetriever
+
+A component for retrieving documents from a [Chroma database](https://docs.trychroma.com/) using the `query` API.
+
+Example usage:
+```python
+from haystack import Pipeline
+from haystack.components.converters import TextFileToDocument
+from haystack.components.writers import DocumentWriter
+
+from haystack_integrations.document_stores.chroma import ChromaDocumentStore
+from haystack_integrations.components.retrievers.chroma import ChromaQueryTextRetriever
+
+file_paths = ...
+
+# Chroma is used in-memory so we use the same instances in the two pipelines below
+document_store = ChromaDocumentStore()
+
+indexing = Pipeline()
+indexing.add_component("converter", TextFileToDocument())
+indexing.add_component("writer", DocumentWriter(document_store))
+indexing.connect("converter", "writer")
+indexing.run({"converter": {"sources": file_paths}})
+
+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)
+```
+
+<a id="haystack_integrations.components.retrievers.chroma.retriever.ChromaQueryTextRetriever.__init__"></a>
+
+#### ChromaQueryTextRetriever.\_\_init\_\_
+
+```python
+def __init__(document_store: ChromaDocumentStore,
+             filters: Optional[Dict[str, Any]] = None,
+             top_k: int = 10,
+             filter_policy: Union[str, FilterPolicy] = FilterPolicy.REPLACE)
+```
+
+**Arguments**:
+
+- `document_store`: an instance of `ChromaDocumentStore`.
+- `filters`: filters to narrow down the search space.
+- `top_k`: the maximum number of documents to retrieve.
+- `filter_policy`: Policy to determine how filters are applied.
+
+<a id="haystack_integrations.components.retrievers.chroma.retriever.ChromaQueryTextRetriever.run"></a>
+
+#### ChromaQueryTextRetriever.run
+
+```python
+@component.output_types(documents=List[Document])
+def run(query: str,
+        filters: Optional[Dict[str, Any]] = None,
+        top_k: Optional[int] = None) -> Dict[str, Any]
+```
+
+Run the retriever on the given input data.
+
+**Arguments**:
+
+- `query`: The input data for the retriever. In this case, a plain-text query.
+- `filters`: Filters applied to the retrieved Documents. The way runtime filters are applied depends on
+the `filter_policy` chosen at retriever initialization. See init method docstring for more
+details.
+- `top_k`: The maximum number of documents to retrieve.
+If not specified, the default value from the constructor is used.
+
+**Raises**:
+
+- `ValueError`: If the specified document store is not found or is not a MemoryDocumentStore instance.
+
+**Returns**:
+
+A dictionary with the following keys:
+- `documents`: List of documents returned by the search engine.
+
+<a id="haystack_integrations.components.retrievers.chroma.retriever.ChromaQueryTextRetriever.run_async"></a>
+
+#### ChromaQueryTextRetriever.run\_async
+
+```python
+@component.output_types(documents=List[Document])
+async def run_async(query: str,
+                    filters: Optional[Dict[str, Any]] = None,
+                    top_k: Optional[int] = None) -> Dict[str, Any]
+```
+
+Asynchronously run the retriever on the given input data.
+
+Asynchronous methods are only supported for HTTP connections.
+
+**Arguments**:
+
+- `query`: The input data for the retriever. In this case, a plain-text query.
+- `filters`: Filters applied to the retrieved Documents. The way runtime filters are applied depends on
+the `filter_policy` chosen at retriever initialization. See init method docstring for more
+details.
+- `top_k`: The maximum number of documents to retrieve.
+If not specified, the default value from the constructor is used.
+
+**Raises**:
+
+- `ValueError`: If the specified document store is not found or is not a MemoryDocumentStore instance.
+
+**Returns**:
+
+A dictionary with the following keys:
+- `documents`: List of documents returned by the search engine.
+
+<a id="haystack_integrations.components.retrievers.chroma.retriever.ChromaQueryTextRetriever.from_dict"></a>
+
+#### ChromaQueryTextRetriever.from\_dict
+
+```python
+@classmethod
+def from_dict(cls, data: Dict[str, Any]) -> "ChromaQueryTextRetriever"
+```
+
+Deserializes the component from a dictionary.
+
+**Arguments**:
+
+- `data`: Dictionary to deserialize from.
+
+**Returns**:
+
+Deserialized component.
+
+<a id="haystack_integrations.components.retrievers.chroma.retriever.ChromaQueryTextRetriever.to_dict"></a>
+
+#### ChromaQueryTextRetriever.to\_dict
+
+```python
+def to_dict() -> Dict[str, Any]
+```
+
+Serializes the component to a dictionary.
+
+**Returns**:
+
+Dictionary with serialized data.
+
+<a id="haystack_integrations.components.retrievers.chroma.retriever.ChromaEmbeddingRetriever"></a>
+
+## ChromaEmbeddingRetriever
+
+A component for retrieving documents from a [Chroma database](https://docs.trychroma.com/) using embeddings.
+
+<a id="haystack_integrations.components.retrievers.chroma.retriever.ChromaEmbeddingRetriever.__init__"></a>
+
+#### ChromaEmbeddingRetriever.\_\_init\_\_
+
+```python
+def __init__(document_store: ChromaDocumentStore,
+             filters: Optional[Dict[str, Any]] = None,
+             top_k: int = 10,
+             filter_policy: Union[str, FilterPolicy] = FilterPolicy.REPLACE)
+```
+
+**Arguments**:
+
+- `document_store`: an instance of `ChromaDocumentStore`.
+- `filters`: filters to narrow down the search space.
+- `top_k`: the maximum number of documents to retrieve.
+- `filter_policy`: Policy to determine how filters are applied.
+
+<a id="haystack_integrations.components.retrievers.chroma.retriever.ChromaEmbeddingRetriever.run"></a>
+
+#### ChromaEmbeddingRetriever.run
+
+```python
+@component.output_types(documents=List[Document])
+def run(query_embedding: List[float],
+        filters: Optional[Dict[str, Any]] = None,
+        top_k: Optional[int] = None) -> Dict[str, Any]
+```
+
+Run the retriever on the given input data.
+
+**Arguments**:
+
+- `query_embedding`: the query embeddings.
+- `filters`: Filters applied to the retrieved Documents. The way runtime filters are applied depends on
+the `filter_policy` chosen at retriever initialization. See init method docstring for more
+details.
+- `top_k`: the maximum number of documents to retrieve.
+If not specified, the default value from the constructor is used.
+
+**Returns**:
+
+a dictionary with the following keys:
+- `documents`: List of documents returned by the search engine.
+
+<a id="haystack_integrations.components.retrievers.chroma.retriever.ChromaEmbeddingRetriever.run_async"></a>
+
+#### ChromaEmbeddingRetriever.run\_async
+
+```python
+@component.output_types(documents=List[Document])
+async def run_async(query_embedding: List[float],
+                    filters: Optional[Dict[str, Any]] = None,
+                    top_k: Optional[int] = None) -> Dict[str, Any]
+```
+
+Asynchronously run the retriever on the given input data.
+
+Asynchronous methods are only supported for HTTP connections.
+
+**Arguments**:
+
+- `query_embedding`: the query embeddings.
+- `filters`: Filters applied to the retrieved Documents. The way runtime filters are applied depends on
+the `filter_policy` chosen at retriever initialization. See init method docstring for more
+details.
+- `top_k`: the maximum number of documents to retrieve.
+If not specified, the default value from the constructor is used.
+
+**Returns**:
+
+a dictionary with the following keys:
+- `documents`: List of documents returned by the search engine.
+
+<a id="haystack_integrations.components.retrievers.chroma.retriever.ChromaEmbeddingRetriever.from_dict"></a>
+
+#### ChromaEmbeddingRetriever.from\_dict
+
+```python
+@classmethod
+def from_dict(cls, data: Dict[str, Any]) -> "ChromaEmbeddingRetriever"
+```
+
+Deserializes the component from a dictionary.
+
+**Arguments**:
+
+- `data`: Dictionary to deserialize from.
+
+**Returns**:
+
+Deserialized component.
+
+<a id="haystack_integrations.components.retrievers.chroma.retriever.ChromaEmbeddingRetriever.to_dict"></a>
+
+#### ChromaEmbeddingRetriever.to\_dict
+
+```python
+def to_dict() -> Dict[str, Any]
+```
+
+Serializes the component to a dictionary.
+
+**Returns**:
+
+Dictionary with serialized data.
+
+<a id="haystack_integrations.document_stores.chroma.document_store"></a>
+
+# Module haystack\_integrations.document\_stores.chroma.document\_store
+
+<a id="haystack_integrations.document_stores.chroma.document_store.ChromaDocumentStore"></a>
+
+## ChromaDocumentStore
+
+A document store using [Chroma](https://docs.trychroma.com/) as the backend.
+
+We use the `collection.get` API to implement the document store protocol,
+the `collection.search` API will be used in the retriever instead.
+
+<a id="haystack_integrations.document_stores.chroma.document_store.ChromaDocumentStore.__init__"></a>
+
+#### ChromaDocumentStore.\_\_init\_\_
+
+```python
+def __init__(collection_name: str = "documents",
+             embedding_function: str = "default",
+             persist_path: Optional[str] = None,
+             host: Optional[str] = None,
+             port: Optional[int] = None,
+             distance_function: Literal["l2", "cosine", "ip"] = "l2",
+             metadata: Optional[dict] = None,
+             **embedding_function_params: Any)
+```
+
+Creates a new ChromaDocumentStore instance.
+
+It is meant to be connected to a Chroma collection.
+
+Note: for the component to be part of a serializable pipeline, the __init__
+parameters must be serializable, reason why we use a registry to configure the
+embedding function passing a string.
+
+**Arguments**:
+
+- `collection_name`: the name of the collection to use in the database.
+- `embedding_function`: the name of the embedding function to use to embed the query
+- `persist_path`: Path for local persistent storage. Cannot be used in combination with `host` and `port`.
+If none of `persist_path`, `host`, and `port` is specified, the database will be `in-memory`.
+- `host`: The host address for the remote Chroma HTTP client connection. Cannot be used with `persist_path`.
+- `port`: The port number for the remote Chroma HTTP client connection. Cannot be used with `persist_path`.
+- `distance_function`: The distance metric for the embedding space.
+- `"l2"` computes the Euclidean (straight-line) distance between vectors,
+where smaller scores indicate more similarity.
+- `"cosine"` computes the cosine similarity between vectors,
+with higher scores indicating greater similarity.
+- `"ip"` stands for inner product, where higher scores indicate greater similarity between vectors.
+**Note**: `distance_function` can only be set during the creation of a collection.
+To change the distance metric of an existing collection, consider cloning the collection.
+- `metadata`: a dictionary of chromadb collection parameters passed directly to chromadb's client
+method `create_collection`. If it contains the key `"hnsw:space"`, the value will take precedence over the
+`distance_function` parameter above.
+- `embedding_function_params`: additional parameters to pass to the embedding function.
+
+<a id="haystack_integrations.document_stores.chroma.document_store.ChromaDocumentStore.count_documents"></a>
+
+#### ChromaDocumentStore.count\_documents
+
+```python
+def count_documents() -> int
+```
+
+Returns how many documents are present in the document store.
+
+**Returns**:
+
+how many documents are present in the document store.
+
+<a id="haystack_integrations.document_stores.chroma.document_store.ChromaDocumentStore.count_documents_async"></a>
+
+#### ChromaDocumentStore.count\_documents\_async
+
+```python
+async def count_documents_async() -> int
+```
+
+Asynchronously returns how many documents are present in the document store.
+
+Asynchronous methods are only supported for HTTP connections.
+
+**Returns**:
+
+how many documents are present in the document store.
+
+<a id="haystack_integrations.document_stores.chroma.document_store.ChromaDocumentStore.filter_documents"></a>
+
+#### ChromaDocumentStore.filter\_documents
+
+```python
+def filter_documents(
+        filters: Optional[Dict[str, Any]] = None) -> List[Document]
+```
+
+Returns the documents that match the filters provided.
+
+For a detailed specification of the filters,
+refer to the [documentation](https://docs.haystack.deepset.ai/v2.0/docs/metadata-filtering).
+
+**Arguments**:
+
+- `filters`: the filters to apply to the document list.
+
+**Returns**:
+
+a list of Documents that match the given filters.
+
+<a id="haystack_integrations.document_stores.chroma.document_store.ChromaDocumentStore.filter_documents_async"></a>
+
+#### ChromaDocumentStore.filter\_documents\_async
+
+```python
+async def filter_documents_async(
+        filters: Optional[Dict[str, Any]] = None) -> List[Document]
+```
+
+Asynchronously returns the documents that match the filters provided.
+
+Asynchronous methods are only supported for HTTP connections.
+
+For a detailed specification of the filters,
+refer to the [documentation](https://docs.haystack.deepset.ai/v2.0/docs/metadata-filtering).
+
+**Arguments**:
+
+- `filters`: the filters to apply to the document list.
+
+**Returns**:
+
+a list of Documents that match the given filters.
+
+<a id="haystack_integrations.document_stores.chroma.document_store.ChromaDocumentStore.write_documents"></a>
+
+#### ChromaDocumentStore.write\_documents
+
+```python
+def write_documents(documents: List[Document],
+                    policy: DuplicatePolicy = DuplicatePolicy.FAIL) -> int
+```
+
+Writes (or overwrites) documents into the store.
+
+**Arguments**:
+
+- `documents`: A list of documents to write into the document store.
+- `policy`: Not supported at the moment.
+
+**Raises**:
+
+- `ValueError`: When input is not valid.
+
+**Returns**:
+
+The number of documents written
+
+<a id="haystack_integrations.document_stores.chroma.document_store.ChromaDocumentStore.write_documents_async"></a>
+
+#### ChromaDocumentStore.write\_documents\_async
+
+```python
+async def write_documents_async(
+        documents: List[Document],
+        policy: DuplicatePolicy = DuplicatePolicy.FAIL) -> int
+```
+
+Asynchronously writes (or overwrites) documents into the store.
+
+Asynchronous methods are only supported for HTTP connections.
+
+**Arguments**:
+
+- `documents`: A list of documents to write into the document store.
+- `policy`: Not supported at the moment.
+
+**Raises**:
+
+- `ValueError`: When input is not valid.
+
+**Returns**:
+
+The number of documents written
+
+<a id="haystack_integrations.document_stores.chroma.document_store.ChromaDocumentStore.delete_documents"></a>
+
+#### ChromaDocumentStore.delete\_documents
+
+```python
+def delete_documents(document_ids: List[str]) -> None
+```
+
+Deletes all documents with a matching document_ids from the document store.
+
+**Arguments**:
+
+- `document_ids`: the document ids to delete
+
+<a id="haystack_integrations.document_stores.chroma.document_store.ChromaDocumentStore.delete_documents_async"></a>
+
+#### ChromaDocumentStore.delete\_documents\_async
+
+```python
+async def delete_documents_async(document_ids: List[str]) -> None
+```
+
+Asynchronously deletes all documents with a matching document_ids from the document store.
+
+Asynchronous methods are only supported for HTTP connections.
+
+**Arguments**:
+
+- `document_ids`: the document ids to delete
+
+<a id="haystack_integrations.document_stores.chroma.document_store.ChromaDocumentStore.search"></a>
+
+#### ChromaDocumentStore.search
+
+```python
+def search(queries: List[str],
+           top_k: int,
+           filters: Optional[Dict[str, Any]] = None) -> List[List[Document]]
+```
+
+Search the documents in the store using the provided text queries.
+
+**Arguments**:
+
+- `queries`: the list of queries to search for.
+- `top_k`: top_k documents to return for each query.
+- `filters`: a dictionary of filters to apply to the search. Accepts filters in haystack format.
+
+**Returns**:
+
+matching documents for each query.
+
+<a id="haystack_integrations.document_stores.chroma.document_store.ChromaDocumentStore.search_async"></a>
+
+#### ChromaDocumentStore.search\_async
+
+```python
+async def search_async(
+        queries: List[str],
+        top_k: int,
+        filters: Optional[Dict[str, Any]] = None) -> List[List[Document]]
+```
+
+Asynchronously search the documents in the store using the provided text queries.
+
+Asynchronous methods are only supported for HTTP connections.
+
+**Arguments**:
+
+- `queries`: the list of queries to search for.
+- `top_k`: top_k documents to return for each query.
+- `filters`: a dictionary of filters to apply to the search. Accepts filters in haystack format.
+
+**Returns**:
+
+matching documents for each query.
+
+<a id="haystack_integrations.document_stores.chroma.document_store.ChromaDocumentStore.search_embeddings"></a>
+
+#### ChromaDocumentStore.search\_embeddings
+
+```python
+def search_embeddings(
+        query_embeddings: List[List[float]],
+        top_k: int,
+        filters: Optional[Dict[str, Any]] = None) -> List[List[Document]]
+```
+
+Perform vector search on the stored document, pass the embeddings of the queries instead of their text.
+
+**Arguments**:
+
+- `query_embeddings`: a list of embeddings to use as queries.
+- `top_k`: the maximum number of documents to retrieve.
+- `filters`: a dictionary of filters to apply to the search. Accepts filters in haystack format.
+
+**Returns**:
+
+a list of lists of documents that match the given filters.
+
+<a id="haystack_integrations.document_stores.chroma.document_store.ChromaDocumentStore.search_embeddings_async"></a>
+
+#### ChromaDocumentStore.search\_embeddings\_async
+
+```python
+async def search_embeddings_async(
+        query_embeddings: List[List[float]],
+        top_k: int,
+        filters: Optional[Dict[str, Any]] = None) -> List[List[Document]]
+```
+
+Asynchronously perform vector search on the stored document, pass the embeddings of the queries instead of
+
+their text.
+
+Asynchronous methods are only supported for HTTP connections.
+
+**Arguments**:
+
+- `query_embeddings`: a list of embeddings to use as queries.
+- `top_k`: the maximum number of documents to retrieve.
+- `filters`: a dictionary of filters to apply to the search. Accepts filters in haystack format.
+
+**Returns**:
+
+a list of lists of documents that match the given filters.
+
+<a id="haystack_integrations.document_stores.chroma.document_store.ChromaDocumentStore.from_dict"></a>
+
+#### ChromaDocumentStore.from\_dict
+
+```python
+@classmethod
+def from_dict(cls, data: Dict[str, Any]) -> "ChromaDocumentStore"
+```
+
+Deserializes the component from a dictionary.
+
+**Arguments**:
+
+- `data`: Dictionary to deserialize from.
+
+**Returns**:
+
+Deserialized component.
+
+<a id="haystack_integrations.document_stores.chroma.document_store.ChromaDocumentStore.to_dict"></a>
+
+#### ChromaDocumentStore.to\_dict
+
+```python
+def to_dict() -> Dict[str, Any]
+```
+
+Serializes the component to a dictionary.
+
+**Returns**:
+
+Dictionary with serialized data.
+
+<a id="haystack_integrations.document_stores.chroma.errors"></a>
+
+# Module haystack\_integrations.document\_stores.chroma.errors
+
+<a id="haystack_integrations.document_stores.chroma.errors.ChromaDocumentStoreError"></a>
+
+## ChromaDocumentStoreError
+
+Parent class for all ChromaDocumentStore exceptions.
+
+<a id="haystack_integrations.document_stores.chroma.errors.ChromaDocumentStoreFilterError"></a>
+
+## ChromaDocumentStoreFilterError
+
+Raised when a filter is not valid for a ChromaDocumentStore.
+
+<a id="haystack_integrations.document_stores.chroma.errors.ChromaDocumentStoreConfigError"></a>
+
+## ChromaDocumentStoreConfigError
+
+Raised when a configuration is not valid for a ChromaDocumentStore.
+
+<a id="haystack_integrations.document_stores.chroma.utils"></a>
+
+# Module haystack\_integrations.document\_stores.chroma.utils
+
+<a id="haystack_integrations.document_stores.chroma.utils.get_embedding_function"></a>
+
+#### get\_embedding\_function
+
+```python
+def get_embedding_function(function_name: str,
+                           **kwargs: Any) -> EmbeddingFunction
+```
+
+Load an embedding function by name.
+
+**Arguments**:
+
+- `function_name`: the name of the embedding function.
+- `kwargs`: additional arguments to pass to the embedding function.
+
+**Raises**:
+
+- `ChromaDocumentStoreConfigError`: if the function name is invalid.
+
+**Returns**:
+
+the loaded embedding function.
--- a/docs-website/reference_versioned_docs/version-2.17/integrations-api/chroma.md
+++ b/docs-website/reference_versioned_docs/version-2.17/integrations-api/chroma.md
@ -0,0 +1,666 @@
+---
+title: "Chroma"
+id: integrations-chroma
+description: "Chroma integration for Haystack"
+slug: "/integrations-chroma"
+---
+
+<a id="haystack_integrations.components.retrievers.chroma.retriever"></a>
+
+# Module haystack\_integrations.components.retrievers.chroma.retriever
+
+<a id="haystack_integrations.components.retrievers.chroma.retriever.ChromaQueryTextRetriever"></a>
+
+## ChromaQueryTextRetriever
+
+A component for retrieving documents from a [Chroma database](https://docs.trychroma.com/) using the `query` API.
+
+Example usage:
+```python
+from haystack import Pipeline
+from haystack.components.converters import TextFileToDocument
+from haystack.components.writers import DocumentWriter
+
+from haystack_integrations.document_stores.chroma import ChromaDocumentStore
+from haystack_integrations.components.retrievers.chroma import ChromaQueryTextRetriever
+
+file_paths = ...
+
+# Chroma is used in-memory so we use the same instances in the two pipelines below
+document_store = ChromaDocumentStore()
+
+indexing = Pipeline()
+indexing.add_component("converter", TextFileToDocument())
+indexing.add_component("writer", DocumentWriter(document_store))
+indexing.connect("converter", "writer")
+indexing.run({"converter": {"sources": file_paths}})
+
+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)
+```
+
+<a id="haystack_integrations.components.retrievers.chroma.retriever.ChromaQueryTextRetriever.__init__"></a>
+
+#### ChromaQueryTextRetriever.\_\_init\_\_
+
+```python
+def __init__(document_store: ChromaDocumentStore,
+             filters: Optional[Dict[str, Any]] = None,
+             top_k: int = 10,
+             filter_policy: Union[str, FilterPolicy] = FilterPolicy.REPLACE)
+```
+
+**Arguments**:
+
+- `document_store`: an instance of `ChromaDocumentStore`.
+- `filters`: filters to narrow down the search space.
+- `top_k`: the maximum number of documents to retrieve.
+- `filter_policy`: Policy to determine how filters are applied.
+
+<a id="haystack_integrations.components.retrievers.chroma.retriever.ChromaQueryTextRetriever.run"></a>
+
+#### ChromaQueryTextRetriever.run
+
+```python
+@component.output_types(documents=List[Document])
+def run(query: str,
+        filters: Optional[Dict[str, Any]] = None,
+        top_k: Optional[int] = None) -> Dict[str, Any]
+```
+
+Run the retriever on the given input data.
+
+**Arguments**:
+
+- `query`: The input data for the retriever. In this case, a plain-text query.
+- `filters`: Filters applied to the retrieved Documents. The way runtime filters are applied depends on
+the `filter_policy` chosen at retriever initialization. See init method docstring for more
+details.
+- `top_k`: The maximum number of documents to retrieve.
+If not specified, the default value from the constructor is used.
+
+**Raises**:
+
+- `ValueError`: If the specified document store is not found or is not a MemoryDocumentStore instance.
+
+**Returns**:
+
+A dictionary with the following keys:
+- `documents`: List of documents returned by the search engine.
+
+<a id="haystack_integrations.components.retrievers.chroma.retriever.ChromaQueryTextRetriever.run_async"></a>
+
+#### ChromaQueryTextRetriever.run\_async
+
+```python
+@component.output_types(documents=List[Document])
+async def run_async(query: str,
+                    filters: Optional[Dict[str, Any]] = None,
+                    top_k: Optional[int] = None) -> Dict[str, Any]
+```
+
+Asynchronously run the retriever on the given input data.
+
+Asynchronous methods are only supported for HTTP connections.
+
+**Arguments**:
+
+- `query`: The input data for the retriever. In this case, a plain-text query.
+- `filters`: Filters applied to the retrieved Documents. The way runtime filters are applied depends on
+the `filter_policy` chosen at retriever initialization. See init method docstring for more
+details.
+- `top_k`: The maximum number of documents to retrieve.
+If not specified, the default value from the constructor is used.
+
+**Raises**:
+
+- `ValueError`: If the specified document store is not found or is not a MemoryDocumentStore instance.
+
+**Returns**:
+
+A dictionary with the following keys:
+- `documents`: List of documents returned by the search engine.
+
+<a id="haystack_integrations.components.retrievers.chroma.retriever.ChromaQueryTextRetriever.from_dict"></a>
+
+#### ChromaQueryTextRetriever.from\_dict
+
+```python
+@classmethod
+def from_dict(cls, data: Dict[str, Any]) -> "ChromaQueryTextRetriever"
+```
+
+Deserializes the component from a dictionary.
+
+**Arguments**:
+
+- `data`: Dictionary to deserialize from.
+
+**Returns**:
+
+Deserialized component.
+
+<a id="haystack_integrations.components.retrievers.chroma.retriever.ChromaQueryTextRetriever.to_dict"></a>
+
+#### ChromaQueryTextRetriever.to\_dict
+
+```python
+def to_dict() -> Dict[str, Any]
+```
+
+Serializes the component to a dictionary.
+
+**Returns**:
+
+Dictionary with serialized data.
+
+<a id="haystack_integrations.components.retrievers.chroma.retriever.ChromaEmbeddingRetriever"></a>
+
+## ChromaEmbeddingRetriever
+
+A component for retrieving documents from a [Chroma database](https://docs.trychroma.com/) using embeddings.
+
+<a id="haystack_integrations.components.retrievers.chroma.retriever.ChromaEmbeddingRetriever.__init__"></a>
+
+#### ChromaEmbeddingRetriever.\_\_init\_\_
+
+```python
+def __init__(document_store: ChromaDocumentStore,
+             filters: Optional[Dict[str, Any]] = None,
+             top_k: int = 10,
+             filter_policy: Union[str, FilterPolicy] = FilterPolicy.REPLACE)
+```
+
+**Arguments**:
+
+- `document_store`: an instance of `ChromaDocumentStore`.
+- `filters`: filters to narrow down the search space.
+- `top_k`: the maximum number of documents to retrieve.
+- `filter_policy`: Policy to determine how filters are applied.
+
+<a id="haystack_integrations.components.retrievers.chroma.retriever.ChromaEmbeddingRetriever.run"></a>
+
+#### ChromaEmbeddingRetriever.run
+
+```python
+@component.output_types(documents=List[Document])
+def run(query_embedding: List[float],
+        filters: Optional[Dict[str, Any]] = None,
+        top_k: Optional[int] = None) -> Dict[str, Any]
+```
+
+Run the retriever on the given input data.
+
+**Arguments**:
+
+- `query_embedding`: the query embeddings.
+- `filters`: Filters applied to the retrieved Documents. The way runtime filters are applied depends on
+the `filter_policy` chosen at retriever initialization. See init method docstring for more
+details.
+- `top_k`: the maximum number of documents to retrieve.
+If not specified, the default value from the constructor is used.
+
+**Returns**:
+
+a dictionary with the following keys:
+- `documents`: List of documents returned by the search engine.
+
+<a id="haystack_integrations.components.retrievers.chroma.retriever.ChromaEmbeddingRetriever.run_async"></a>
+
+#### ChromaEmbeddingRetriever.run\_async
+
+```python
+@component.output_types(documents=List[Document])
+async def run_async(query_embedding: List[float],
+                    filters: Optional[Dict[str, Any]] = None,
+                    top_k: Optional[int] = None) -> Dict[str, Any]
+```
+
+Asynchronously run the retriever on the given input data.
+
+Asynchronous methods are only supported for HTTP connections.
+
+**Arguments**:
+
+- `query_embedding`: the query embeddings.
+- `filters`: Filters applied to the retrieved Documents. The way runtime filters are applied depends on
+the `filter_policy` chosen at retriever initialization. See init method docstring for more
+details.
+- `top_k`: the maximum number of documents to retrieve.
+If not specified, the default value from the constructor is used.
+
+**Returns**:
+
+a dictionary with the following keys:
+- `documents`: List of documents returned by the search engine.
+
+<a id="haystack_integrations.components.retrievers.chroma.retriever.ChromaEmbeddingRetriever.from_dict"></a>
+
+#### ChromaEmbeddingRetriever.from\_dict
+
+```python
+@classmethod
+def from_dict(cls, data: Dict[str, Any]) -> "ChromaEmbeddingRetriever"
+```
+
+Deserializes the component from a dictionary.
+
+**Arguments**:
+
+- `data`: Dictionary to deserialize from.
+
+**Returns**:
+
+Deserialized component.
+
+<a id="haystack_integrations.components.retrievers.chroma.retriever.ChromaEmbeddingRetriever.to_dict"></a>
+
+#### ChromaEmbeddingRetriever.to\_dict
+
+```python
+def to_dict() -> Dict[str, Any]
+```
+
+Serializes the component to a dictionary.
+
+**Returns**:
+
+Dictionary with serialized data.
+
+<a id="haystack_integrations.document_stores.chroma.document_store"></a>
+
+# Module haystack\_integrations.document\_stores.chroma.document\_store
+
+<a id="haystack_integrations.document_stores.chroma.document_store.ChromaDocumentStore"></a>
+
+## ChromaDocumentStore
+
+A document store using [Chroma](https://docs.trychroma.com/) as the backend.
+
+We use the `collection.get` API to implement the document store protocol,
+the `collection.search` API will be used in the retriever instead.
+
+<a id="haystack_integrations.document_stores.chroma.document_store.ChromaDocumentStore.__init__"></a>
+
+#### ChromaDocumentStore.\_\_init\_\_
+
+```python
+def __init__(collection_name: str = "documents",
+             embedding_function: str = "default",
+             persist_path: Optional[str] = None,
+             host: Optional[str] = None,
+             port: Optional[int] = None,
+             distance_function: Literal["l2", "cosine", "ip"] = "l2",
+             metadata: Optional[dict] = None,
+             **embedding_function_params: Any)
+```
+
+Creates a new ChromaDocumentStore instance.
+
+It is meant to be connected to a Chroma collection.
+
+Note: for the component to be part of a serializable pipeline, the __init__
+parameters must be serializable, reason why we use a registry to configure the
+embedding function passing a string.
+
+**Arguments**:
+
+- `collection_name`: the name of the collection to use in the database.
+- `embedding_function`: the name of the embedding function to use to embed the query
+- `persist_path`: Path for local persistent storage. Cannot be used in combination with `host` and `port`.
+If none of `persist_path`, `host`, and `port` is specified, the database will be `in-memory`.
+- `host`: The host address for the remote Chroma HTTP client connection. Cannot be used with `persist_path`.
+- `port`: The port number for the remote Chroma HTTP client connection. Cannot be used with `persist_path`.
+- `distance_function`: The distance metric for the embedding space.
+- `"l2"` computes the Euclidean (straight-line) distance between vectors,
+where smaller scores indicate more similarity.
+- `"cosine"` computes the cosine similarity between vectors,
+with higher scores indicating greater similarity.
+- `"ip"` stands for inner product, where higher scores indicate greater similarity between vectors.
+**Note**: `distance_function` can only be set during the creation of a collection.
+To change the distance metric of an existing collection, consider cloning the collection.
+- `metadata`: a dictionary of chromadb collection parameters passed directly to chromadb's client
+method `create_collection`. If it contains the key `"hnsw:space"`, the value will take precedence over the
+`distance_function` parameter above.
+- `embedding_function_params`: additional parameters to pass to the embedding function.
+
+<a id="haystack_integrations.document_stores.chroma.document_store.ChromaDocumentStore.count_documents"></a>
+
+#### ChromaDocumentStore.count\_documents
+
+```python
+def count_documents() -> int
+```
+
+Returns how many documents are present in the document store.
+
+**Returns**:
+
+how many documents are present in the document store.
+
+<a id="haystack_integrations.document_stores.chroma.document_store.ChromaDocumentStore.count_documents_async"></a>
+
+#### ChromaDocumentStore.count\_documents\_async
+
+```python
+async def count_documents_async() -> int
+```
+
+Asynchronously returns how many documents are present in the document store.
+
+Asynchronous methods are only supported for HTTP connections.
+
+**Returns**:
+
+how many documents are present in the document store.
+
+<a id="haystack_integrations.document_stores.chroma.document_store.ChromaDocumentStore.filter_documents"></a>
+
+#### ChromaDocumentStore.filter\_documents
+
+```python
+def filter_documents(
+        filters: Optional[Dict[str, Any]] = None) -> List[Document]
+```
+
+Returns the documents that match the filters provided.
+
+For a detailed specification of the filters,
+refer to the [documentation](https://docs.haystack.deepset.ai/v2.0/docs/metadata-filtering).
+
+**Arguments**:
+
+- `filters`: the filters to apply to the document list.
+
+**Returns**:
+
+a list of Documents that match the given filters.
+
+<a id="haystack_integrations.document_stores.chroma.document_store.ChromaDocumentStore.filter_documents_async"></a>
+
+#### ChromaDocumentStore.filter\_documents\_async
+
+```python
+async def filter_documents_async(
+        filters: Optional[Dict[str, Any]] = None) -> List[Document]
+```
+
+Asynchronously returns the documents that match the filters provided.
+
+Asynchronous methods are only supported for HTTP connections.
+
+For a detailed specification of the filters,
+refer to the [documentation](https://docs.haystack.deepset.ai/v2.0/docs/metadata-filtering).
+
+**Arguments**:
+
+- `filters`: the filters to apply to the document list.
+
+**Returns**:
+
+a list of Documents that match the given filters.
+
+<a id="haystack_integrations.document_stores.chroma.document_store.ChromaDocumentStore.write_documents"></a>
+
+#### ChromaDocumentStore.write\_documents
+
+```python
+def write_documents(documents: List[Document],
+                    policy: DuplicatePolicy = DuplicatePolicy.FAIL) -> int
+```
+
+Writes (or overwrites) documents into the store.
+
+**Arguments**:
+
+- `documents`: A list of documents to write into the document store.
+- `policy`: Not supported at the moment.
+
+**Raises**:
+
+- `ValueError`: When input is not valid.
+
+**Returns**:
+
+The number of documents written
+
+<a id="haystack_integrations.document_stores.chroma.document_store.ChromaDocumentStore.write_documents_async"></a>
+
+#### ChromaDocumentStore.write\_documents\_async
+
+```python
+async def write_documents_async(
+        documents: List[Document],
+        policy: DuplicatePolicy = DuplicatePolicy.FAIL) -> int
+```
+
+Asynchronously writes (or overwrites) documents into the store.
+
+Asynchronous methods are only supported for HTTP connections.
+
+**Arguments**:
+
+- `documents`: A list of documents to write into the document store.
+- `policy`: Not supported at the moment.
+
+**Raises**:
+
+- `ValueError`: When input is not valid.
+
+**Returns**:
+
+The number of documents written
+
+<a id="haystack_integrations.document_stores.chroma.document_store.ChromaDocumentStore.delete_documents"></a>
+
+#### ChromaDocumentStore.delete\_documents
+
+```python
+def delete_documents(document_ids: List[str]) -> None
+```
+
+Deletes all documents with a matching document_ids from the document store.
+
+**Arguments**:
+
+- `document_ids`: the document ids to delete
+
+<a id="haystack_integrations.document_stores.chroma.document_store.ChromaDocumentStore.delete_documents_async"></a>
+
+#### ChromaDocumentStore.delete\_documents\_async
+
+```python
+async def delete_documents_async(document_ids: List[str]) -> None
+```
+
+Asynchronously deletes all documents with a matching document_ids from the document store.
+
+Asynchronous methods are only supported for HTTP connections.
+
+**Arguments**:
+
+- `document_ids`: the document ids to delete
+
+<a id="haystack_integrations.document_stores.chroma.document_store.ChromaDocumentStore.search"></a>
+
+#### ChromaDocumentStore.search
+
+```python
+def search(queries: List[str],
+           top_k: int,
+           filters: Optional[Dict[str, Any]] = None) -> List[List[Document]]
+```
+
+Search the documents in the store using the provided text queries.
+
+**Arguments**:
+
+- `queries`: the list of queries to search for.
+- `top_k`: top_k documents to return for each query.
+- `filters`: a dictionary of filters to apply to the search. Accepts filters in haystack format.
+
+**Returns**:
+
+matching documents for each query.
+
+<a id="haystack_integrations.document_stores.chroma.document_store.ChromaDocumentStore.search_async"></a>
+
+#### ChromaDocumentStore.search\_async
+
+```python
+async def search_async(
+        queries: List[str],
+        top_k: int,
+        filters: Optional[Dict[str, Any]] = None) -> List[List[Document]]
+```
+
+Asynchronously search the documents in the store using the provided text queries.
+
+Asynchronous methods are only supported for HTTP connections.
+
+**Arguments**:
+
+- `queries`: the list of queries to search for.
+- `top_k`: top_k documents to return for each query.
+- `filters`: a dictionary of filters to apply to the search. Accepts filters in haystack format.
+
+**Returns**:
+
+matching documents for each query.
+
+<a id="haystack_integrations.document_stores.chroma.document_store.ChromaDocumentStore.search_embeddings"></a>
+
+#### ChromaDocumentStore.search\_embeddings
+
+```python
+def search_embeddings(
+        query_embeddings: List[List[float]],
+        top_k: int,
+        filters: Optional[Dict[str, Any]] = None) -> List[List[Document]]
+```
+
+Perform vector search on the stored document, pass the embeddings of the queries instead of their text.
+
+**Arguments**:
+
+- `query_embeddings`: a list of embeddings to use as queries.
+- `top_k`: the maximum number of documents to retrieve.
+- `filters`: a dictionary of filters to apply to the search. Accepts filters in haystack format.
+
+**Returns**:
+
+a list of lists of documents that match the given filters.
+
+<a id="haystack_integrations.document_stores.chroma.document_store.ChromaDocumentStore.search_embeddings_async"></a>
+
+#### ChromaDocumentStore.search\_embeddings\_async
+
+```python
+async def search_embeddings_async(
+        query_embeddings: List[List[float]],
+        top_k: int,
+        filters: Optional[Dict[str, Any]] = None) -> List[List[Document]]
+```
+
+Asynchronously perform vector search on the stored document, pass the embeddings of the queries instead of
+
+their text.
+
+Asynchronous methods are only supported for HTTP connections.
+
+**Arguments**:
+
+- `query_embeddings`: a list of embeddings to use as queries.
+- `top_k`: the maximum number of documents to retrieve.
+- `filters`: a dictionary of filters to apply to the search. Accepts filters in haystack format.
+
+**Returns**:
+
+a list of lists of documents that match the given filters.
+
+<a id="haystack_integrations.document_stores.chroma.document_store.ChromaDocumentStore.from_dict"></a>
+
+#### ChromaDocumentStore.from\_dict
+
+```python
+@classmethod
+def from_dict(cls, data: Dict[str, Any]) -> "ChromaDocumentStore"
+```
+
+Deserializes the component from a dictionary.
+
+**Arguments**:
+
+- `data`: Dictionary to deserialize from.
+
+**Returns**:
+
+Deserialized component.
+
+<a id="haystack_integrations.document_stores.chroma.document_store.ChromaDocumentStore.to_dict"></a>
+
+#### ChromaDocumentStore.to\_dict
+
+```python
+def to_dict() -> Dict[str, Any]
+```
+
+Serializes the component to a dictionary.
+
+**Returns**:
+
+Dictionary with serialized data.
+
+<a id="haystack_integrations.document_stores.chroma.errors"></a>
+
+# Module haystack\_integrations.document\_stores.chroma.errors
+
+<a id="haystack_integrations.document_stores.chroma.errors.ChromaDocumentStoreError"></a>
+
+## ChromaDocumentStoreError
+
+Parent class for all ChromaDocumentStore exceptions.
+
+<a id="haystack_integrations.document_stores.chroma.errors.ChromaDocumentStoreFilterError"></a>
+
+## ChromaDocumentStoreFilterError
+
+Raised when a filter is not valid for a ChromaDocumentStore.
+
+<a id="haystack_integrations.document_stores.chroma.errors.ChromaDocumentStoreConfigError"></a>
+
+## ChromaDocumentStoreConfigError
+
+Raised when a configuration is not valid for a ChromaDocumentStore.
+
+<a id="haystack_integrations.document_stores.chroma.utils"></a>
+
+# Module haystack\_integrations.document\_stores.chroma.utils
+
+<a id="haystack_integrations.document_stores.chroma.utils.get_embedding_function"></a>
+
+#### get\_embedding\_function
+
+```python
+def get_embedding_function(function_name: str,
+                           **kwargs: Any) -> EmbeddingFunction
+```
+
+Load an embedding function by name.
+
+**Arguments**:
+
+- `function_name`: the name of the embedding function.
+- `kwargs`: additional arguments to pass to the embedding function.
+
+**Raises**:
+
+- `ChromaDocumentStoreConfigError`: if the function name is invalid.
+
+**Returns**:
+
+the loaded embedding function.
--- a/docs-website/reference_versioned_docs/version-2.18/integrations-api/chroma.md
+++ b/docs-website/reference_versioned_docs/version-2.18/integrations-api/chroma.md
@ -0,0 +1,666 @@
+---
+title: "Chroma"
+id: integrations-chroma
+description: "Chroma integration for Haystack"
+slug: "/integrations-chroma"
+---
+
+<a id="haystack_integrations.components.retrievers.chroma.retriever"></a>
+
+# Module haystack\_integrations.components.retrievers.chroma.retriever
+
+<a id="haystack_integrations.components.retrievers.chroma.retriever.ChromaQueryTextRetriever"></a>
+
+## ChromaQueryTextRetriever
+
+A component for retrieving documents from a [Chroma database](https://docs.trychroma.com/) using the `query` API.
+
+Example usage:
+```python
+from haystack import Pipeline
+from haystack.components.converters import TextFileToDocument
+from haystack.components.writers import DocumentWriter
+
+from haystack_integrations.document_stores.chroma import ChromaDocumentStore
+from haystack_integrations.components.retrievers.chroma import ChromaQueryTextRetriever
+
+file_paths = ...
+
+# Chroma is used in-memory so we use the same instances in the two pipelines below
+document_store = ChromaDocumentStore()
+
+indexing = Pipeline()
+indexing.add_component("converter", TextFileToDocument())
+indexing.add_component("writer", DocumentWriter(document_store))
+indexing.connect("converter", "writer")
+indexing.run({"converter": {"sources": file_paths}})
+
+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)
+```
+
+<a id="haystack_integrations.components.retrievers.chroma.retriever.ChromaQueryTextRetriever.__init__"></a>
+
+#### ChromaQueryTextRetriever.\_\_init\_\_
+
+```python
+def __init__(document_store: ChromaDocumentStore,
+             filters: Optional[Dict[str, Any]] = None,
+             top_k: int = 10,
+             filter_policy: Union[str, FilterPolicy] = FilterPolicy.REPLACE)
+```
+
+**Arguments**:
+
+- `document_store`: an instance of `ChromaDocumentStore`.
+- `filters`: filters to narrow down the search space.
+- `top_k`: the maximum number of documents to retrieve.
+- `filter_policy`: Policy to determine how filters are applied.
+
+<a id="haystack_integrations.components.retrievers.chroma.retriever.ChromaQueryTextRetriever.run"></a>
+
+#### ChromaQueryTextRetriever.run
+
+```python
+@component.output_types(documents=List[Document])
+def run(query: str,
+        filters: Optional[Dict[str, Any]] = None,
+        top_k: Optional[int] = None) -> Dict[str, Any]
+```
+
+Run the retriever on the given input data.
+
+**Arguments**:
+
+- `query`: The input data for the retriever. In this case, a plain-text query.
+- `filters`: Filters applied to the retrieved Documents. The way runtime filters are applied depends on
+the `filter_policy` chosen at retriever initialization. See init method docstring for more
+details.
+- `top_k`: The maximum number of documents to retrieve.
+If not specified, the default value from the constructor is used.
+
+**Raises**:
+
+- `ValueError`: If the specified document store is not found or is not a MemoryDocumentStore instance.
+
+**Returns**:
+
+A dictionary with the following keys:
+- `documents`: List of documents returned by the search engine.
+
+<a id="haystack_integrations.components.retrievers.chroma.retriever.ChromaQueryTextRetriever.run_async"></a>
+
+#### ChromaQueryTextRetriever.run\_async
+
+```python
+@component.output_types(documents=List[Document])
+async def run_async(query: str,
+                    filters: Optional[Dict[str, Any]] = None,
+                    top_k: Optional[int] = None) -> Dict[str, Any]
+```
+
+Asynchronously run the retriever on the given input data.
+
+Asynchronous methods are only supported for HTTP connections.
+
+**Arguments**:
+
+- `query`: The input data for the retriever. In this case, a plain-text query.
+- `filters`: Filters applied to the retrieved Documents. The way runtime filters are applied depends on
+the `filter_policy` chosen at retriever initialization. See init method docstring for more
+details.
+- `top_k`: The maximum number of documents to retrieve.
+If not specified, the default value from the constructor is used.
+
+**Raises**:
+
+- `ValueError`: If the specified document store is not found or is not a MemoryDocumentStore instance.
+
+**Returns**:
+
+A dictionary with the following keys:
+- `documents`: List of documents returned by the search engine.
+
+<a id="haystack_integrations.components.retrievers.chroma.retriever.ChromaQueryTextRetriever.from_dict"></a>
+
+#### ChromaQueryTextRetriever.from\_dict
+
+```python
+@classmethod
+def from_dict(cls, data: Dict[str, Any]) -> "ChromaQueryTextRetriever"
+```
+
+Deserializes the component from a dictionary.
+
+**Arguments**:
+
+- `data`: Dictionary to deserialize from.
+
+**Returns**:
+
+Deserialized component.
+
+<a id="haystack_integrations.components.retrievers.chroma.retriever.ChromaQueryTextRetriever.to_dict"></a>
+
+#### ChromaQueryTextRetriever.to\_dict
+
+```python
+def to_dict() -> Dict[str, Any]
+```
+
+Serializes the component to a dictionary.
+
+**Returns**:
+
+Dictionary with serialized data.
+
+<a id="haystack_integrations.components.retrievers.chroma.retriever.ChromaEmbeddingRetriever"></a>
+
+## ChromaEmbeddingRetriever
+
+A component for retrieving documents from a [Chroma database](https://docs.trychroma.com/) using embeddings.
+
+<a id="haystack_integrations.components.retrievers.chroma.retriever.ChromaEmbeddingRetriever.__init__"></a>
+
+#### ChromaEmbeddingRetriever.\_\_init\_\_
+
+```python
+def __init__(document_store: ChromaDocumentStore,
+             filters: Optional[Dict[str, Any]] = None,
+             top_k: int = 10,
+             filter_policy: Union[str, FilterPolicy] = FilterPolicy.REPLACE)
+```
+
+**Arguments**:
+
+- `document_store`: an instance of `ChromaDocumentStore`.
+- `filters`: filters to narrow down the search space.
+- `top_k`: the maximum number of documents to retrieve.
+- `filter_policy`: Policy to determine how filters are applied.
+
+<a id="haystack_integrations.components.retrievers.chroma.retriever.ChromaEmbeddingRetriever.run"></a>
+
+#### ChromaEmbeddingRetriever.run
+
+```python
+@component.output_types(documents=List[Document])
+def run(query_embedding: List[float],
+        filters: Optional[Dict[str, Any]] = None,
+        top_k: Optional[int] = None) -> Dict[str, Any]
+```
+
+Run the retriever on the given input data.
+
+**Arguments**:
+
+- `query_embedding`: the query embeddings.
+- `filters`: Filters applied to the retrieved Documents. The way runtime filters are applied depends on
+the `filter_policy` chosen at retriever initialization. See init method docstring for more
+details.
+- `top_k`: the maximum number of documents to retrieve.
+If not specified, the default value from the constructor is used.
+
+**Returns**:
+
+a dictionary with the following keys:
+- `documents`: List of documents returned by the search engine.
+
+<a id="haystack_integrations.components.retrievers.chroma.retriever.ChromaEmbeddingRetriever.run_async"></a>
+
+#### ChromaEmbeddingRetriever.run\_async
+
+```python
+@component.output_types(documents=List[Document])
+async def run_async(query_embedding: List[float],
+                    filters: Optional[Dict[str, Any]] = None,
+                    top_k: Optional[int] = None) -> Dict[str, Any]
+```
+
+Asynchronously run the retriever on the given input data.
+
+Asynchronous methods are only supported for HTTP connections.
+
+**Arguments**:
+
+- `query_embedding`: the query embeddings.
+- `filters`: Filters applied to the retrieved Documents. The way runtime filters are applied depends on
+the `filter_policy` chosen at retriever initialization. See init method docstring for more
+details.
+- `top_k`: the maximum number of documents to retrieve.
+If not specified, the default value from the constructor is used.
+
+**Returns**:
+
+a dictionary with the following keys:
+- `documents`: List of documents returned by the search engine.
+
+<a id="haystack_integrations.components.retrievers.chroma.retriever.ChromaEmbeddingRetriever.from_dict"></a>
+
+#### ChromaEmbeddingRetriever.from\_dict
+
+```python
+@classmethod
+def from_dict(cls, data: Dict[str, Any]) -> "ChromaEmbeddingRetriever"
+```
+
+Deserializes the component from a dictionary.
+
+**Arguments**:
+
+- `data`: Dictionary to deserialize from.
+
+**Returns**:
+
+Deserialized component.
+
+<a id="haystack_integrations.components.retrievers.chroma.retriever.ChromaEmbeddingRetriever.to_dict"></a>
+
+#### ChromaEmbeddingRetriever.to\_dict
+
+```python
+def to_dict() -> Dict[str, Any]
+```
+
+Serializes the component to a dictionary.
+
+**Returns**:
+
+Dictionary with serialized data.
+
+<a id="haystack_integrations.document_stores.chroma.document_store"></a>
+
+# Module haystack\_integrations.document\_stores.chroma.document\_store
+
+<a id="haystack_integrations.document_stores.chroma.document_store.ChromaDocumentStore"></a>
+
+## ChromaDocumentStore
+
+A document store using [Chroma](https://docs.trychroma.com/) as the backend.
+
+We use the `collection.get` API to implement the document store protocol,
+the `collection.search` API will be used in the retriever instead.
+
+<a id="haystack_integrations.document_stores.chroma.document_store.ChromaDocumentStore.__init__"></a>
+
+#### ChromaDocumentStore.\_\_init\_\_
+
+```python
+def __init__(collection_name: str = "documents",
+             embedding_function: str = "default",
+             persist_path: Optional[str] = None,
+             host: Optional[str] = None,
+             port: Optional[int] = None,
+             distance_function: Literal["l2", "cosine", "ip"] = "l2",
+             metadata: Optional[dict] = None,
+             **embedding_function_params: Any)
+```
+
+Creates a new ChromaDocumentStore instance.
+
+It is meant to be connected to a Chroma collection.
+
+Note: for the component to be part of a serializable pipeline, the __init__
+parameters must be serializable, reason why we use a registry to configure the
+embedding function passing a string.
+
+**Arguments**:
+
+- `collection_name`: the name of the collection to use in the database.
+- `embedding_function`: the name of the embedding function to use to embed the query
+- `persist_path`: Path for local persistent storage. Cannot be used in combination with `host` and `port`.
+If none of `persist_path`, `host`, and `port` is specified, the database will be `in-memory`.
+- `host`: The host address for the remote Chroma HTTP client connection. Cannot be used with `persist_path`.
+- `port`: The port number for the remote Chroma HTTP client connection. Cannot be used with `persist_path`.
+- `distance_function`: The distance metric for the embedding space.
+- `"l2"` computes the Euclidean (straight-line) distance between vectors,
+where smaller scores indicate more similarity.
+- `"cosine"` computes the cosine similarity between vectors,
+with higher scores indicating greater similarity.
+- `"ip"` stands for inner product, where higher scores indicate greater similarity between vectors.
+**Note**: `distance_function` can only be set during the creation of a collection.
+To change the distance metric of an existing collection, consider cloning the collection.
+- `metadata`: a dictionary of chromadb collection parameters passed directly to chromadb's client
+method `create_collection`. If it contains the key `"hnsw:space"`, the value will take precedence over the
+`distance_function` parameter above.
+- `embedding_function_params`: additional parameters to pass to the embedding function.
+
+<a id="haystack_integrations.document_stores.chroma.document_store.ChromaDocumentStore.count_documents"></a>
+
+#### ChromaDocumentStore.count\_documents
+
+```python
+def count_documents() -> int
+```
+
+Returns how many documents are present in the document store.
+
+**Returns**:
+
+how many documents are present in the document store.
+
+<a id="haystack_integrations.document_stores.chroma.document_store.ChromaDocumentStore.count_documents_async"></a>
+
+#### ChromaDocumentStore.count\_documents\_async
+
+```python
+async def count_documents_async() -> int
+```
+
+Asynchronously returns how many documents are present in the document store.
+
+Asynchronous methods are only supported for HTTP connections.
+
+**Returns**:
+
+how many documents are present in the document store.
+
+<a id="haystack_integrations.document_stores.chroma.document_store.ChromaDocumentStore.filter_documents"></a>
+
+#### ChromaDocumentStore.filter\_documents
+
+```python
+def filter_documents(
+        filters: Optional[Dict[str, Any]] = None) -> List[Document]
+```
+
+Returns the documents that match the filters provided.
+
+For a detailed specification of the filters,
+refer to the [documentation](https://docs.haystack.deepset.ai/v2.0/docs/metadata-filtering).
+
+**Arguments**:
+
+- `filters`: the filters to apply to the document list.
+
+**Returns**:
+
+a list of Documents that match the given filters.
+
+<a id="haystack_integrations.document_stores.chroma.document_store.ChromaDocumentStore.filter_documents_async"></a>
+
+#### ChromaDocumentStore.filter\_documents\_async
+
+```python
+async def filter_documents_async(
+        filters: Optional[Dict[str, Any]] = None) -> List[Document]
+```
+
+Asynchronously returns the documents that match the filters provided.
+
+Asynchronous methods are only supported for HTTP connections.
+
+For a detailed specification of the filters,
+refer to the [documentation](https://docs.haystack.deepset.ai/v2.0/docs/metadata-filtering).
+
+**Arguments**:
+
+- `filters`: the filters to apply to the document list.
+
+**Returns**:
+
+a list of Documents that match the given filters.
+
+<a id="haystack_integrations.document_stores.chroma.document_store.ChromaDocumentStore.write_documents"></a>
+
+#### ChromaDocumentStore.write\_documents
+
+```python
+def write_documents(documents: List[Document],
+                    policy: DuplicatePolicy = DuplicatePolicy.FAIL) -> int
+```
+
+Writes (or overwrites) documents into the store.
+
+**Arguments**:
+
+- `documents`: A list of documents to write into the document store.
+- `policy`: Not supported at the moment.
+
+**Raises**:
+
+- `ValueError`: When input is not valid.
+
+**Returns**:
+
+The number of documents written
+
+<a id="haystack_integrations.document_stores.chroma.document_store.ChromaDocumentStore.write_documents_async"></a>
+
+#### ChromaDocumentStore.write\_documents\_async
+
+```python
+async def write_documents_async(
+        documents: List[Document],
+        policy: DuplicatePolicy = DuplicatePolicy.FAIL) -> int
+```
+
+Asynchronously writes (or overwrites) documents into the store.
+
+Asynchronous methods are only supported for HTTP connections.
+
+**Arguments**:
+
+- `documents`: A list of documents to write into the document store.
+- `policy`: Not supported at the moment.
+
+**Raises**:
+
+- `ValueError`: When input is not valid.
+
+**Returns**:
+
+The number of documents written
+
+<a id="haystack_integrations.document_stores.chroma.document_store.ChromaDocumentStore.delete_documents"></a>
+
+#### ChromaDocumentStore.delete\_documents
+
+```python
+def delete_documents(document_ids: List[str]) -> None
+```
+
+Deletes all documents with a matching document_ids from the document store.
+
+**Arguments**:
+
+- `document_ids`: the document ids to delete
+
+<a id="haystack_integrations.document_stores.chroma.document_store.ChromaDocumentStore.delete_documents_async"></a>
+
+#### ChromaDocumentStore.delete\_documents\_async
+
+```python
+async def delete_documents_async(document_ids: List[str]) -> None
+```
+
+Asynchronously deletes all documents with a matching document_ids from the document store.
+
+Asynchronous methods are only supported for HTTP connections.
+
+**Arguments**:
+
+- `document_ids`: the document ids to delete
+
+<a id="haystack_integrations.document_stores.chroma.document_store.ChromaDocumentStore.search"></a>
+
+#### ChromaDocumentStore.search
+
+```python
+def search(queries: List[str],
+           top_k: int,
+           filters: Optional[Dict[str, Any]] = None) -> List[List[Document]]
+```
+
+Search the documents in the store using the provided text queries.
+
+**Arguments**:
+
+- `queries`: the list of queries to search for.
+- `top_k`: top_k documents to return for each query.
+- `filters`: a dictionary of filters to apply to the search. Accepts filters in haystack format.
+
+**Returns**:
+
+matching documents for each query.
+
+<a id="haystack_integrations.document_stores.chroma.document_store.ChromaDocumentStore.search_async"></a>
+
+#### ChromaDocumentStore.search\_async
+
+```python
+async def search_async(
+        queries: List[str],
+        top_k: int,
+        filters: Optional[Dict[str, Any]] = None) -> List[List[Document]]
+```
+
+Asynchronously search the documents in the store using the provided text queries.
+
+Asynchronous methods are only supported for HTTP connections.
+
+**Arguments**:
+
+- `queries`: the list of queries to search for.
+- `top_k`: top_k documents to return for each query.
+- `filters`: a dictionary of filters to apply to the search. Accepts filters in haystack format.
+
+**Returns**:
+
+matching documents for each query.
+
+<a id="haystack_integrations.document_stores.chroma.document_store.ChromaDocumentStore.search_embeddings"></a>
+
+#### ChromaDocumentStore.search\_embeddings
+
+```python
+def search_embeddings(
+        query_embeddings: List[List[float]],
+        top_k: int,
+        filters: Optional[Dict[str, Any]] = None) -> List[List[Document]]
+```
+
+Perform vector search on the stored document, pass the embeddings of the queries instead of their text.
+
+**Arguments**:
+
+- `query_embeddings`: a list of embeddings to use as queries.
+- `top_k`: the maximum number of documents to retrieve.
+- `filters`: a dictionary of filters to apply to the search. Accepts filters in haystack format.
+
+**Returns**:
+
+a list of lists of documents that match the given filters.
+
+<a id="haystack_integrations.document_stores.chroma.document_store.ChromaDocumentStore.search_embeddings_async"></a>
+
+#### ChromaDocumentStore.search\_embeddings\_async
+
+```python
+async def search_embeddings_async(
+        query_embeddings: List[List[float]],
+        top_k: int,
+        filters: Optional[Dict[str, Any]] = None) -> List[List[Document]]
+```
+
+Asynchronously perform vector search on the stored document, pass the embeddings of the queries instead of
+
+their text.
+
+Asynchronous methods are only supported for HTTP connections.
+
+**Arguments**:
+
+- `query_embeddings`: a list of embeddings to use as queries.
+- `top_k`: the maximum number of documents to retrieve.
+- `filters`: a dictionary of filters to apply to the search. Accepts filters in haystack format.
+
+**Returns**:
+
+a list of lists of documents that match the given filters.
+
+<a id="haystack_integrations.document_stores.chroma.document_store.ChromaDocumentStore.from_dict"></a>
+
+#### ChromaDocumentStore.from\_dict
+
+```python
+@classmethod
+def from_dict(cls, data: Dict[str, Any]) -> "ChromaDocumentStore"
+```
+
+Deserializes the component from a dictionary.
+
+**Arguments**:
+
+- `data`: Dictionary to deserialize from.
+
+**Returns**:
+
+Deserialized component.
+
+<a id="haystack_integrations.document_stores.chroma.document_store.ChromaDocumentStore.to_dict"></a>
+
+#### ChromaDocumentStore.to\_dict
+
+```python
+def to_dict() -> Dict[str, Any]
+```
+
+Serializes the component to a dictionary.
+
+**Returns**:
+
+Dictionary with serialized data.
+
+<a id="haystack_integrations.document_stores.chroma.errors"></a>
+
+# Module haystack\_integrations.document\_stores.chroma.errors
+
+<a id="haystack_integrations.document_stores.chroma.errors.ChromaDocumentStoreError"></a>
+
+## ChromaDocumentStoreError
+
+Parent class for all ChromaDocumentStore exceptions.
+
+<a id="haystack_integrations.document_stores.chroma.errors.ChromaDocumentStoreFilterError"></a>
+
+## ChromaDocumentStoreFilterError
+
+Raised when a filter is not valid for a ChromaDocumentStore.
+
+<a id="haystack_integrations.document_stores.chroma.errors.ChromaDocumentStoreConfigError"></a>
+
+## ChromaDocumentStoreConfigError
+
+Raised when a configuration is not valid for a ChromaDocumentStore.
+
+<a id="haystack_integrations.document_stores.chroma.utils"></a>
+
+# Module haystack\_integrations.document\_stores.chroma.utils
+
+<a id="haystack_integrations.document_stores.chroma.utils.get_embedding_function"></a>
+
+#### get\_embedding\_function
+
+```python
+def get_embedding_function(function_name: str,
+                           **kwargs: Any) -> EmbeddingFunction
+```
+
+Load an embedding function by name.
+
+**Arguments**:
+
+- `function_name`: the name of the embedding function.
+- `kwargs`: additional arguments to pass to the embedding function.
+
+**Raises**:
+
+- `ChromaDocumentStoreConfigError`: if the function name is invalid.
+
+**Returns**:
+
+the loaded embedding function.
--- a/docs-website/reference_versioned_sidebars/version-2.17-sidebars.json
+++ b/docs-website/reference_versioned_sidebars/version-2.17-sidebars.json
@ -18,6 +18,20 @@
          "dirName": "haystack-api"
        }
      ]
+    },
+    {
+      "type": "category",
+      "label": "Integrations API",
+      "link": {
+        "type": "generated-index",
+        "title": "Integrations API"
+      },
+      "items": [
+        {
+          "type": "autogenerated",
+          "dirName": "integrations-api"
+        }
+      ]
    }
  ]
 }
--- a/docs-website/reference_versioned_sidebars/version-2.18-sidebars.json
+++ b/docs-website/reference_versioned_sidebars/version-2.18-sidebars.json
@ -18,6 +18,20 @@
          "dirName": "haystack-api"
        }
      ]
+    },
+    {
+      "type": "category",
+      "label": "Integrations API",
+      "link": {
+        "type": "generated-index",
+        "title": "Integrations API"
+      },
+      "items": [
+        {
+          "type": "autogenerated",
+          "dirName": "integrations-api"
+        }
+      ]
    }
  ]
 }