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test(test_amazing_vertex_completion.py): reduce vertex tests - quota exhaustion

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This commit is contained in:
Krrish Dholakia 2024-06-29 19:14:19 -07:00
parent 7670c5bd13
commit b78043f904
1 changed files with 0 additions and 42 deletions
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42
litellm/tests/test_amazing_vertex_completion.py
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@ -1111,48 +1111,6 @@ async def test_gemini_pro_httpx_custom_api_base(provider):
assert "hello" in mock_call.call_args.kwargs["headers"] assert "hello" in mock_call.call_args.kwargs["headers"]
@pytest.mark.parametrize("sync_mode", [True, False])
@pytest.mark.parametrize("provider", ["vertex_ai_beta"]) # "vertex_ai",
@pytest.mark.asyncio
async def test_gemini_pro_httpx_custom_api_base_streaming_real_call(
provider, sync_mode
):
load_vertex_ai_credentials()
import random
litellm.set_verbose = True
messages = [
{
"role": "user",
"content": "Hey, how's it going?",
}
]
vertex_region = random.sample(["asia-southeast1", "us-central1"], k=1)[0]
if sync_mode is True:
response = completion(
model="vertex_ai_beta/gemini-1.5-flash",
messages=messages,
api_base="https://gateway.ai.cloudflare.com/v1/fa4cdcab1f32b95ca3b53fd36043d691/test/google-vertex-ai/v1/projects/adroit-crow-413218/locations/us-central1/publishers/google/models/gemini-1.5-flash",
stream=True,
vertex_region=vertex_region,
)
for chunk in response:
print(chunk)
else:
response = await litellm.acompletion(
model="vertex_ai_beta/gemini-1.5-flash",
messages=messages,
api_base="https://gateway.ai.cloudflare.com/v1/fa4cdcab1f32b95ca3b53fd36043d691/test/google-vertex-ai/v1/projects/adroit-crow-413218/locations/us-central1/publishers/google/models/gemini-1.5-flash",
stream=True,
vertex_region=vertex_region,
)
async for chunk in response:
print(chunk)
@pytest.mark.skip(reason="exhausted vertex quota. need to refactor to mock the call") @pytest.mark.skip(reason="exhausted vertex quota. need to refactor to mock the call")
@pytest.mark.parametrize("sync_mode", [True]) @pytest.mark.parametrize("sync_mode", [True])
@pytest.mark.parametrize("provider", ["vertex_ai"]) @pytest.mark.parametrize("provider", ["vertex_ai"])