diff --git a/document_stores/chroma/pyproject.toml b/document_stores/chroma/pyproject.toml
index d19461895..c1ab121a1 100644
--- a/document_stores/chroma/pyproject.toml
+++ b/document_stores/chroma/pyproject.toml
@@ -23,7 +23,7 @@ classifiers = [
   "Programming Language :: Python :: Implementation :: PyPy",
 ]
 dependencies = [
-  "haystack-ai",
+  "haystack-ai<0.144.0",
   "chromadb",
 ]
 
diff --git a/document_stores/chroma/src/chroma_haystack/document_store.py b/document_stores/chroma/src/chroma_haystack/document_store.py
index 30517ca5f..d67a2a36a 100644
--- a/document_stores/chroma/src/chroma_haystack/document_store.py
+++ b/document_stores/chroma/src/chroma_haystack/document_store.py
@@ -281,7 +281,8 @@ def _get_result_to_documents(self, result: GetResult) -> List[Document]:
                 document_dict["content"] = result_documents[i]
 
             result_metadata = result.get("metadatas")
-            if result_metadata:
+            # Ensure metadata[i] is not None or don't add it to the document dict
+            if result_metadata and result_metadata[i]:
                 document_dict["meta"] = result_metadata[i]
 
             result_embeddings = result.get("embeddings")
@@ -296,26 +297,29 @@ def _query_result_to_documents(self, result: QueryResult) -> List[List[Document]
         """
         Helper function to convert Chroma results into Haystack Documents
         """
-        retval = []
-        for i, answers in enumerate(result["documents"]):
+        retval: List[List[Document]] = []
+        documents = result.get("documents")
+        if documents is None:
+            return retval
+
+        for i, answers in enumerate(documents):
             converted_answers = []
             for j in range(len(answers)):
-                # prepare metadata
-                metadata = result["metadatas"][i][j]
-                mime_type = metadata.pop("_mime_type")
-
-                document_dict = {
+                document_dict: Dict[str, Any] = {
                     "id": result["ids"][i][j],
-                    "text": result["documents"][i][j].text,
-                    "metadata": metadata,
-                    "mime_type": mime_type,
+                    "content": documents[i][j],
                 }
 
-                if result["embeddings"][i][j]:
-                    document_dict["embedding"] = np.array(result["embeddings"][i][j])
+                # prepare metadata
+                if metadatas := result.get("metadatas"):
+                    document_dict["metadata"] = dict(metadatas[i][j])
+                    document_dict["mime_type"] = document_dict["metadata"].pop("_mime_type")
+
+                if embeddings := result.get("embeddings"):
+                    document_dict["embedding"] = np.array(embeddings[i][j])
 
-                if result["distances"][i][j]:
-                    document_dict["score"] = result["distances"][i][j]
+                if distances := result.get("distances"):
+                    document_dict["score"] = distances[i][j]
 
                 converted_answers.append(Document.from_dict(document_dict))
             retval.append(converted_answers)
diff --git a/document_stores/chroma/tests/test_document_store.py b/document_stores/chroma/tests/test_document_store.py
index 8d420be1a..ea204f6f6 100644
--- a/document_stores/chroma/tests/test_document_store.py
+++ b/document_stores/chroma/tests/test_document_store.py
@@ -64,7 +64,7 @@ def test_delete_not_empty_nonexisting(self, docstore: ChromaDocumentStore):
         """
         Deleting a non-existing document should not raise with Chroma
         """
-        doc = Document(text="test doc")
+        doc = Document(content="test doc")
         docstore.write_documents([doc])
         docstore.delete_documents(["non_existing"])