fix(vertex_ai.py): correctly parse optional params and pass vertex ai project

litellm/llms/vertex_ai.py

@@ -1047,6 +1047,7 @@ def embedding(
     vertex_project=None,
     vertex_location=None,
     aembedding=False,
+    print_verbose=None,
 ):
     # logic for parsing in - calling - parsing out model embedding calls
     try:
@@ -1062,7 +1063,13 @@ def embedding(
 
     ## Load credentials with the correct quota project ref: https://github.com/googleapis/python-aiplatform/issues/2557#issuecomment-1709284744
     try:
+        print_verbose(
+            f"VERTEX AI: vertex_project={vertex_project}; vertex_location={vertex_location}"
+        )
         creds, _ = google.auth.default(quota_project_id=vertex_project)
+        print_verbose(
+            f"VERTEX AI: creds={creds}; google application credentials: {os.getenv('GOOGLE_APPLICATION_CREDENTIALS')}"
+        )
         vertexai.init(
             project=vertex_project, location=vertex_location, credentials=creds
         )

litellm/main.py

@@ -2617,6 +2617,7 @@ def embedding(
                 vertex_project=vertex_ai_project,
                 vertex_location=vertex_ai_location,
                 aembedding=aembedding,
+                print_verbose=print_verbose,
             )
         elif custom_llm_provider == "oobabooga":
             response = oobabooga.embedding(

litellm/tests/test_amazing_vertex_completion.py

@@ -451,6 +451,34 @@ async def test_gemini_pro_async_function_calling():
 
 # asyncio.run(gemini_pro_async_function_calling())
 
+
+def test_vertexai_embedding():
+    try:
+        load_vertex_ai_credentials()
+        # litellm.set_verbose=True
+        response = embedding(
+            model="textembedding-gecko@001",
+            input=["good morning from litellm", "this is another item"],
+        )
+        print(f"response:", response)
+    except Exception as e:
+        pytest.fail(f"Error occurred: {e}")
+
+
+@pytest.mark.asyncio
+async def test_vertexai_aembedding():
+    try:
+        load_vertex_ai_credentials()
+        # litellm.set_verbose=True
+        response = await litellm.aembedding(
+            model="textembedding-gecko@001",
+            input=["good morning from litellm", "this is another item"],
+        )
+        print(f"response: {response}")
+    except Exception as e:
+        pytest.fail(f"Error occurred: {e}")
+
+
 # Extra gemini Vision tests for completion + stream, async, async + stream
 # if we run into issues with gemini, we will also add these to our ci/cd pipeline
 # def test_gemini_pro_vision_stream():

litellm/tests/test_embedding.py

@@ -231,31 +231,6 @@ def test_cohere_embedding3():
 # test_cohere_embedding3()
 
 
-def test_vertexai_embedding():
-    try:
-        # litellm.set_verbose=True
-        response = embedding(
-            model="textembedding-gecko@001",
-            input=["good morning from litellm", "this is another item"],
-        )
-        print(f"response:", response)
-    except Exception as e:
-        pytest.fail(f"Error occurred: {e}")
-
-
-@pytest.mark.asyncio
-async def test_vertexai_aembedding():
-    try:
-        # litellm.set_verbose=True
-        response = await litellm.aembedding(
-            model="textembedding-gecko@001",
-            input=["good morning from litellm", "this is another item"],
-        )
-        print(f"response: {response}")
-    except Exception as e:
-        pytest.fail(f"Error occurred: {e}")
-
-
 def test_bedrock_embedding_titan():
     try:
         # this tests if we support str input for bedrock embedding

litellm/tests/test_get_optional_params_embeddings.py

@@ -0,0 +1,42 @@
+# What is this?
+## This tests the `get_optional_params_embeddings` function
+import sys, os
+import traceback
+from dotenv import load_dotenv
+
+load_dotenv()
+import os, io
+
+sys.path.insert(
+    0, os.path.abspath("../..")
+)  # Adds the parent directory to the system path
+import pytest
+import litellm
+from litellm import embedding
+from litellm.utils import get_optional_params_embeddings, get_llm_provider
+
+
+def test_vertex_projects():
+    litellm.drop_params = True
+    model, custom_llm_provider, _, _ = get_llm_provider(
+        model="vertex_ai/textembedding-gecko"
+    )
+    optional_params = get_optional_params_embeddings(
+        model=model,
+        user="test-litellm-user-5",
+        dimensions=None,
+        encoding_format="base64",
+        custom_llm_provider=custom_llm_provider,
+        **{
+            "vertex_ai_project": "my-test-project",
+            "vertex_ai_location": "us-east-1",
+        },
+    )
+
+    print(f"received optional_params: {optional_params}")
+
+    assert "vertex_ai_project" in optional_params
+    assert "vertex_ai_location" in optional_params
+
+
+# test_vertex_projects()