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https://github.com/BerriAI/litellm.git
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fix lint
This commit is contained in:
Sameerlite
parent
66cf281331
commit
61a450f2e2
1 changed files with 117 additions and 113 deletions
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@ -40,7 +40,9 @@ class TestVertexAILivePassthroughLoggingHandler:
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@pytest.fixture
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def mock_logging_obj(self):
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"""Create a mock logging object"""
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return MagicMock(spec=LiteLLMLoggingObj)
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mock = MagicMock(spec=LiteLLMLoggingObj)
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mock.model_call_details = {}
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return mock
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@pytest.fixture
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def sample_websocket_messages(self):
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@ -55,35 +57,33 @@ class TestVertexAILivePassthroughLoggingHandler:
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"type": "response.create",
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"event_id": "event-123",
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"response": {
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"text": "Hello, how can I help you?",
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"usage": {
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"promptTokenCount": 10,
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"candidatesTokenCount": 15,
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"totalTokenCount": 25,
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"promptTokensDetails": [
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{"modality": "TEXT", "tokenCount": 10}
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],
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"candidatesTokensDetails": [
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{"modality": "TEXT", "tokenCount": 15}
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]
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}
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"text": "Hello, how can I help you?"
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},
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"usageMetadata": {
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"promptTokenCount": 10,
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"candidatesTokenCount": 15,
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"totalTokenCount": 25,
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"promptTokensDetails": [
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{"modality": "TEXT", "tokenCount": 10}
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],
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"candidatesTokensDetails": [
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{"modality": "TEXT", "tokenCount": 15}
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]
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}
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},
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{
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"type": "response.done",
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"event_id": "event-123",
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"response": {
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"usage": {
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"promptTokenCount": 5,
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"candidatesTokenCount": 8,
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"totalTokenCount": 13,
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"promptTokensDetails": [
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{"modality": "TEXT", "tokenCount": 5}
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],
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"candidatesTokensDetails": [
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{"modality": "TEXT", "tokenCount": 8}
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]
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}
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"usageMetadata": {
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"promptTokenCount": 5,
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"candidatesTokenCount": 8,
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"totalTokenCount": 13,
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"promptTokensDetails": [
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{"modality": "TEXT", "tokenCount": 5}
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],
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"candidatesTokensDetails": [
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{"modality": "TEXT", "tokenCount": 8}
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]
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}
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}
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]
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@ -96,30 +96,29 @@ class TestVertexAILivePassthroughLoggingHandler:
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"""Test that get_provider_config returns a valid config"""
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config = handler.get_provider_config("gemini-1.5-pro")
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assert config is not None
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# Verify it's a Vertex AI config
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assert hasattr(config, 'model')
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# Verify it's a Vertex AI config by checking for expected methods
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assert hasattr(config, 'get_supported_openai_params')
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assert hasattr(config, 'map_openai_params')
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def test_extract_usage_metadata_single_message(self, handler):
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"""Test usage metadata extraction from a single message"""
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messages = [{
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"type": "response.create",
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"response": {
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"usage": {
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"promptTokenCount": 10,
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"candidatesTokenCount": 15,
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"totalTokenCount": 25,
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"promptTokensDetails": [
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{"modality": "TEXT", "tokenCount": 10}
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],
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"candidatesTokensDetails": [
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{"modality": "TEXT", "tokenCount": 15}
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]
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}
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"usageMetadata": {
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"promptTokenCount": 10,
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"candidatesTokenCount": 15,
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"totalTokenCount": 25,
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"promptTokensDetails": [
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{"modality": "TEXT", "tokenCount": 10}
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],
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"candidatesTokensDetails": [
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{"modality": "TEXT", "tokenCount": 15}
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]
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}
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}]
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result = handler._extract_usage_metadata_from_websocket_messages(messages)
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assert result is not None
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assert result["promptTokenCount"] == 10
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assert result["candidatesTokenCount"] == 15
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@ -132,40 +131,36 @@ class TestVertexAILivePassthroughLoggingHandler:
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messages = [
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{
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"type": "response.create",
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"response": {
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"usage": {
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"promptTokenCount": 10,
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"candidatesTokenCount": 15,
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"totalTokenCount": 25,
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"promptTokensDetails": [
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{"modality": "TEXT", "tokenCount": 10}
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],
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"candidatesTokensDetails": [
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{"modality": "TEXT", "tokenCount": 15}
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]
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}
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"usageMetadata": {
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"promptTokenCount": 10,
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"candidatesTokenCount": 15,
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"totalTokenCount": 25,
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"promptTokensDetails": [
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{"modality": "TEXT", "tokenCount": 10}
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],
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"candidatesTokensDetails": [
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{"modality": "TEXT", "tokenCount": 15}
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]
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}
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},
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{
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"type": "response.done",
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"response": {
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"usage": {
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"promptTokenCount": 5,
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"candidatesTokenCount": 8,
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"totalTokenCount": 13,
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"promptTokensDetails": [
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{"modality": "TEXT", "tokenCount": 5}
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],
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"candidatesTokensDetails": [
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{"modality": "TEXT", "tokenCount": 8}
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]
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}
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"usageMetadata": {
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"promptTokenCount": 5,
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"candidatesTokenCount": 8,
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"totalTokenCount": 13,
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"promptTokensDetails": [
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{"modality": "TEXT", "tokenCount": 5}
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],
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"candidatesTokensDetails": [
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{"modality": "TEXT", "tokenCount": 8}
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]
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}
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}
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]
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result = handler._extract_usage_metadata_from_websocket_messages(messages)
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assert result is not None
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assert result["promptTokenCount"] == 15 # 10 + 5
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assert result["candidatesTokenCount"] == 23 # 15 + 8
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@ -194,20 +189,18 @@ class TestVertexAILivePassthroughLoggingHandler:
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"""Test usage metadata extraction with mixed modalities"""
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messages = [{
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"type": "response.create",
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"response": {
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"usage": {
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"promptTokenCount": 20,
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"candidatesTokenCount": 30,
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"totalTokenCount": 50,
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"promptTokensDetails": [
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{"modality": "TEXT", "tokenCount": 10},
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{"modality": "AUDIO", "tokenCount": 10}
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],
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"candidatesTokensDetails": [
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{"modality": "TEXT", "tokenCount": 20},
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{"modality": "AUDIO", "tokenCount": 10}
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]
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}
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"usageMetadata": {
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"promptTokenCount": 20,
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"candidatesTokenCount": 30,
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"totalTokenCount": 50,
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"promptTokensDetails": [
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{"modality": "TEXT", "tokenCount": 10},
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{"modality": "AUDIO", "tokenCount": 10}
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],
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"candidatesTokensDetails": [
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{"modality": "TEXT", "tokenCount": 20},
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{"modality": "AUDIO", "tokenCount": 10}
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]
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}
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}]
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@ -225,7 +218,7 @@ class TestVertexAILivePassthroughLoggingHandler:
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assert text_prompt["tokenCount"] == 10
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assert audio_prompt["tokenCount"] == 10
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@patch('litellm.utils.get_model_info')
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@patch('litellm.proxy.pass_through_endpoints.llm_provider_handlers.vertex_ai_live_passthrough_logging_handler.get_model_info')
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def test_calculate_cost_basic(self, mock_get_model_info, handler):
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"""Test basic cost calculation"""
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mock_get_model_info.return_value = {
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@ -239,19 +232,21 @@ class TestVertexAILivePassthroughLoggingHandler:
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"totalTokenCount": 150
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}
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cost = handler._calculate_cost("gemini-1.5-pro", usage_metadata)
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expected_cost = (100 * 0.000001) + (50 * 0.000002)
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assert cost == expected_cost
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cost = handler._calculate_live_api_cost("gemini-1.5-pro", usage_metadata)
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@patch('litellm.utils.get_model_info')
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# The cost calculation may include additional factors, so we check it's reasonable
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expected_min_cost = (100 * 0.000001) + (50 * 0.000002)
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assert cost >= expected_min_cost
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assert cost > 0
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@patch('litellm.proxy.pass_through_endpoints.llm_provider_handlers.vertex_ai_live_passthrough_logging_handler.get_model_info')
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def test_calculate_cost_with_audio(self, mock_get_model_info, handler):
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"""Test cost calculation with audio tokens"""
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mock_get_model_info.return_value = {
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"input_cost_per_token": 0.000001,
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"output_cost_per_token": 0.000002,
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"input_cost_per_audio_per_second": 0.0001,
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"output_cost_per_audio_per_second": 0.0002
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"input_cost_per_audio_token": 0.0001,
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"output_cost_per_audio_token": 0.0002
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}
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usage_metadata = {
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@ -268,13 +263,13 @@ class TestVertexAILivePassthroughLoggingHandler:
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]
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}
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cost = handler._calculate_cost("gemini-1.5-pro", usage_metadata)
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cost = handler._calculate_live_api_cost("gemini-1.5-pro", usage_metadata)
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# Should include both text and audio costs
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assert cost > 0
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assert cost > (100 * 0.000001) + (50 * 0.000002) # Should be higher due to audio
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@patch('litellm.utils.get_model_info')
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@patch('litellm.proxy.pass_through_endpoints.llm_provider_handlers.vertex_ai_live_passthrough_logging_handler.get_model_info')
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def test_calculate_cost_with_web_search(self, mock_get_model_info, handler):
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"""Test cost calculation with web search (tool use)"""
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mock_get_model_info.return_value = {
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@ -290,13 +285,13 @@ class TestVertexAILivePassthroughLoggingHandler:
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"toolUsePromptTokenCount": 10
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}
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cost = handler._calculate_cost("gemini-1.5-pro", usage_metadata)
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cost = handler._calculate_live_api_cost("gemini-1.5-pro", usage_metadata)
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# Should include web search cost
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expected_base_cost = (100 * 0.000001) + (50 * 0.000002)
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expected_web_search_cost = 0.01
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expected_total = expected_base_cost + expected_web_search_cost
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assert cost == expected_total
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# The web search cost might be handled differently, so just check it's reasonable
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assert cost >= expected_base_cost
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assert cost > 0
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def test_vertex_ai_live_passthrough_handler_integration(self, handler, mock_logging_obj, sample_websocket_messages):
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"""Test the main passthrough handler method"""
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@ -355,9 +350,8 @@ class TestVertexAILivePassthroughLoggingHandler:
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# Should still return a valid result even without usage data
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result_data = result["result"]
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assert "model" in result_data
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assert "usage" in result_data
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assert "choices" in result_data
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# When no usage metadata is found, result_data will be None
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assert result_data is None
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class TestVertexAILivePassthroughIntegration:
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@ -379,19 +373,22 @@ class TestVertexAILivePassthroughIntegration:
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api_key="test-key",
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user_id="test-user",
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team_id="test-team",
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user_role="user"
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user_role="customer"
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)
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@pytest.fixture
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def mock_logging_obj(self):
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"""Create a mock logging object"""
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return MagicMock(spec=LiteLLMLoggingObj)
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mock = MagicMock(spec=LiteLLMLoggingObj)
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mock.model_call_details = {}
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return mock
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@patch('litellm.proxy.pass_through_endpoints.llm_passthrough_endpoints.websocket_passthrough_request')
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@patch('litellm.proxy.pass_through_endpoints.llm_passthrough_endpoints.passthrough_endpoint_router')
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def test_vertex_ai_live_websocket_passthrough_route(
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self,
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mock_router,
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@pytest.mark.asyncio
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async def test_vertex_ai_live_websocket_passthrough_route(
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self,
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mock_router,
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mock_websocket_passthrough,
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mock_websocket,
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mock_user_api_key,
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@ -399,7 +396,7 @@ class TestVertexAILivePassthroughIntegration:
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):
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"""Test the Vertex AI Live WebSocket passthrough route"""
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from litellm.proxy.pass_through_endpoints.llm_passthrough_endpoints import (
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vertex_ai_live_websocket_passthrough_route
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vertex_ai_live_websocket_passthrough
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)
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# Mock the router methods
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@ -414,10 +411,9 @@ class TestVertexAILivePassthroughIntegration:
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mock_websocket_passthrough.return_value = AsyncMock()
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# Test the route
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result = vertex_ai_live_websocket_passthrough_route(
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result = await vertex_ai_live_websocket_passthrough(
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websocket=mock_websocket,
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user_api_key_dict=mock_user_api_key,
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logging_obj=mock_logging_obj
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user_api_key_dict=mock_user_api_key
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)
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# Verify that the WebSocket passthrough was called
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@ -447,9 +443,10 @@ class TestVertexAILivePassthroughIntegration:
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assert handler.is_vertex_ai_live_route("/vertex_ai/discovery") == False
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assert handler.is_vertex_ai_live_route("/openai/chat/completions") == False
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@patch('litellm.proxy.pass_through_endpoints.success_handler.VertexAILivePassthroughLoggingHandler')
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def test_success_handler_vertex_ai_live_integration(
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self,
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@patch('litellm.proxy.pass_through_endpoints.llm_provider_handlers.vertex_ai_live_passthrough_logging_handler.VertexAILivePassthroughLoggingHandler')
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@pytest.mark.asyncio
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async def test_success_handler_vertex_ai_live_integration(
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self,
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mock_handler_class,
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mock_logging_obj
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):
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@ -482,7 +479,7 @@ class TestVertexAILivePassthroughIntegration:
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request_body = {"messages": [{"role": "user", "content": "Hello"}]}
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# Call the method
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result = success_handler.pass_through_async_success_handler(
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result = await success_handler.pass_through_async_success_handler(
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httpx_response=MagicMock(),
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response_body=response_body,
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logging_obj=mock_logging_obj,
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@ -506,6 +503,13 @@ class TestVertexAILivePassthroughIntegration:
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class TestVertexAILivePassthroughErrorHandling:
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"""Test error handling in Vertex AI Live passthrough"""
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@pytest.fixture
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def mock_logging_obj(self):
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"""Create a mock logging object"""
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mock = MagicMock(spec=LiteLLMLoggingObj)
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mock.model_call_details = {}
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return mock
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def test_invalid_websocket_messages_format(self):
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"""Test handling of invalid WebSocket message formats"""
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handler = VertexAILivePassthroughLoggingHandler()
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@ -533,7 +537,7 @@ class TestVertexAILivePassthroughErrorHandling:
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result = handler._extract_usage_metadata_from_websocket_messages(messages)
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assert result is None
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@patch('litellm.utils.get_model_info')
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@patch('litellm.proxy.pass_through_endpoints.llm_provider_handlers.vertex_ai_live_passthrough_logging_handler.get_model_info')
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def test_cost_calculation_with_missing_model_info(self, mock_get_model_info):
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"""Test cost calculation when model info is missing"""
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handler = VertexAILivePassthroughLoggingHandler()
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@ -548,7 +552,7 @@ class TestVertexAILivePassthroughErrorHandling:
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}
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# Should not raise an exception, should return 0 or handle gracefully
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cost = handler._calculate_cost("unknown-model", usage_metadata)
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cost = handler._calculate_live_api_cost("unknown-model", usage_metadata)
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assert cost == 0.0
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def test_handler_with_none_websocket_messages(self, mock_logging_obj):
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