diff --git a/examples/langchain-chroma/query.py b/examples/langchain-chroma/query.py
index 33848818..61f4c3ea 100644
--- a/examples/langchain-chroma/query.py
+++ b/examples/langchain-chroma/query.py
@@ -9,7 +9,7 @@ from langchain.vectorstores.base import VectorStoreRetriever
 base_path = os.environ.get('OPENAI_API_BASE', 'http://localhost:8080/v1')
 
 # Load and process the text
-embedding = OpenAIEmbeddings()
+embedding = OpenAIEmbeddings(model="text-embedding-ada-002", openai_api_base=base_path)
 persist_directory = 'db'
 
 # Now we can load the persisted database from disk, and use it as normal. 
diff --git a/examples/langchain-chroma/store.py b/examples/langchain-chroma/store.py
index b9cbad0e..a52cfe04 100755
--- a/examples/langchain-chroma/store.py
+++ b/examples/langchain-chroma/store.py
@@ -18,8 +18,8 @@ texts = text_splitter.split_documents(documents)
 # Supplying a persist_directory will store the embeddings on disk
 persist_directory = 'db'
 
-embedding = OpenAIEmbeddings(model="text-embedding-ada-002")
+embedding = OpenAIEmbeddings(model="text-embedding-ada-002", openai_api_base=base_path)
 vectordb = Chroma.from_documents(documents=texts, embedding=embedding, persist_directory=persist_directory)
 
 vectordb.persist()
-vectordb = None
\ No newline at end of file
+vectordb = None