diff --git a/openai/embeddings_utils.py b/openai/embeddings_utils.py
index 08fa94c2ea..f711d3e42a 100644
--- a/openai/embeddings_utils.py
+++ b/openai/embeddings_utils.py
@@ -15,22 +15,16 @@
 
 
 @retry(wait=wait_random_exponential(min=1, max=20), stop=stop_after_attempt(6))
-def get_embedding(text: str, engine="text-similarity-davinci-001") -> List[float]:
-
-    # replace newlines, which can negatively affect performance.
-    text = text.replace("\n", " ")
+def get_embedding(text: str, engine="text-embedding-ada-002") -> List[float]:
 
     return openai.Embedding.create(input=[text], engine=engine)["data"][0]["embedding"]
 
 
 @retry(wait=wait_random_exponential(min=1, max=20), stop=stop_after_attempt(6))
 async def aget_embedding(
-    text: str, engine="text-similarity-davinci-001"
+    text: str, engine="text-embedding-ada-002"
 ) -> List[float]:
 
-    # replace newlines, which can negatively affect performance.
-    text = text.replace("\n", " ")
-
     return (await openai.Embedding.acreate(input=[text], engine=engine))["data"][0][
         "embedding"
     ]
@@ -38,12 +32,9 @@ async def aget_embedding(
 
 @retry(wait=wait_random_exponential(min=1, max=20), stop=stop_after_attempt(6))
 def get_embeddings(
-    list_of_text: List[str], engine="text-similarity-babbage-001"
+    list_of_text: List[str], engine="text-embedding-ada-002"
 ) -> List[List[float]]:
-    assert len(list_of_text) <= 2048, "The batch size should not be larger than 2048."
-
-    # replace newlines, which can negatively affect performance.
-    list_of_text = [text.replace("\n", " ") for text in list_of_text]
+    assert len(list_of_text) <= 8191, "The batch size should not be larger than 8191."
 
     data = openai.Embedding.create(input=list_of_text, engine=engine).data
     data = sorted(data, key=lambda x: x["index"])  # maintain the same order as input.
@@ -52,12 +43,9 @@ def get_embeddings(
 
 @retry(wait=wait_random_exponential(min=1, max=20), stop=stop_after_attempt(6))
 async def aget_embeddings(
-    list_of_text: List[str], engine="text-similarity-babbage-001"
+    list_of_text: List[str], engine="text-embedding-ada-002"
 ) -> List[List[float]]:
-    assert len(list_of_text) <= 2048, "The batch size should not be larger than 2048."
-
-    # replace newlines, which can negatively affect performance.
-    list_of_text = [text.replace("\n", " ") for text in list_of_text]
+    assert len(list_of_text) <= 8191, "The batch size should not be larger than 8191."
 
     data = (await openai.Embedding.acreate(input=list_of_text, engine=engine)).data
     data = sorted(data, key=lambda x: x["index"])  # maintain the same order as input.