diff --git a/README.md b/README.md
index d76aab84..cf68862f 100644
--- a/README.md
+++ b/README.md
@@ -71,7 +71,7 @@ The following environment variables are required to run the application:
     - azure: "text-embedding-3-small" (will be used as your Azure Deployment)
     - huggingface: "sentence-transformers/all-MiniLM-L6-v2"
     - huggingfacetei: "http://huggingfacetei:3000". Hugging Face TEI uses model defined on TEI service launch.
-    - vertexai: "text-embedding-004"
+    - vertexai: "text-embedding-005"
     - ollama: "nomic-embed-text"
     - bedrock: "amazon.titan-embed-text-v1"
     - google_genai: "gemini-embedding-001"
@@ -91,6 +91,7 @@ The following environment variables are required to run the application:
 - `GOOGLE_API_KEY`, `GOOGLE_KEY`, `RAG_GOOGLE_API_KEY`: (Optional) Google API key for Google GenAI embeddings. Priority order: RAG_GOOGLE_API_KEY > GOOGLE_KEY > GOOGLE_API_KEY
 - `AWS_SESSION_TOKEN`: (Optional) may be needed for bedrock embeddings
 - `GOOGLE_APPLICATION_CREDENTIALS`: (Optional) needed for Google VertexAI embeddings. This should be a path to a service account credential file in JSON format, as accepted by [langchain](https://python.langchain.com/api_reference/google_vertexai/index.html)
+- `VERTEXAI_LOCATION`: (Optional) needed for Google VertexAI embeddings. Defaults to `us-central1`.
 - `RAG_CHECK_EMBEDDING_CTX_LENGTH` (Optional) Default is true, disabling this will send raw input to the embedder, use this for custom embedding models.
 
 Make sure to set these environment variables before running the application. You can set them in a `.env` file or as system environment variables.
diff --git a/app/config.py b/app/config.py
index de2701bb..13515e43 100644
--- a/app/config.py
+++ b/app/config.py
@@ -245,7 +245,7 @@ def init_embeddings(provider, model):
     elif provider == EmbeddingsProvider.GOOGLE_VERTEXAI:
         from langchain_google_vertexai import VertexAIEmbeddings
 
-        return VertexAIEmbeddings(model=model)
+        return VertexAIEmbeddings(model=model, location=VERTEXAI_LOCATION)
     elif provider == EmbeddingsProvider.BEDROCK:
         from langchain_aws import BedrockEmbeddings
 
@@ -289,7 +289,8 @@ def init_embeddings(provider, model):
         "EMBEDDINGS_MODEL", "http://huggingfacetei:3000"
     )
 elif EMBEDDINGS_PROVIDER == EmbeddingsProvider.GOOGLE_VERTEXAI:
-    EMBEDDINGS_MODEL = get_env_variable("EMBEDDINGS_MODEL", "text-embedding-004")
+    EMBEDDINGS_MODEL = get_env_variable("EMBEDDINGS_MODEL", "text-embedding-005")
+    VERTEXAI_LOCATION = get_env_variable("VERTEXAI_LOCATION", "us-central1")
 elif EMBEDDINGS_PROVIDER == EmbeddingsProvider.OLLAMA:
     EMBEDDINGS_MODEL = get_env_variable("EMBEDDINGS_MODEL", "nomic-embed-text")
 elif EMBEDDINGS_PROVIDER == EmbeddingsProvider.GOOGLE_GENAI: