153 lines
6.0 KiB
Python
153 lines
6.0 KiB
Python
"""
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Tests for Lambda AI provider integration
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"""
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import os
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from unittest import mock
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import pytest
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import litellm
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from litellm import completion
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from litellm.llms.lambda_ai.chat.transformation import LambdaAIChatConfig
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def test_lambda_ai_config_initialization():
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"""Test LambdaAIChatConfig initializes correctly"""
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config = LambdaAIChatConfig()
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assert config.custom_llm_provider == "lambda_ai"
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def test_lambda_ai_get_openai_compatible_provider_info():
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"""Test Lambda AI provider info retrieval"""
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config = LambdaAIChatConfig()
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# Test with default values (no env vars set)
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with mock.patch.dict(os.environ, {}, clear=True):
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api_base, api_key = config._get_openai_compatible_provider_info(None, None)
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assert api_base == "https://api.lambda.ai/v1"
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assert api_key is None
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# Test with environment variables
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with mock.patch.dict(os.environ, {"LAMBDA_API_KEY": "test-key", "LAMBDA_API_BASE": "https://custom.lambda.ai/v1"}):
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api_base, api_key = config._get_openai_compatible_provider_info(None, None)
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assert api_base == "https://custom.lambda.ai/v1"
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assert api_key == "test-key"
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# Test with explicit parameters (should override env vars)
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with mock.patch.dict(os.environ, {"LAMBDA_API_KEY": "env-key", "LAMBDA_API_BASE": "https://env.lambda.ai/v1"}):
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api_base, api_key = config._get_openai_compatible_provider_info(
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"https://param.lambda.ai/v1", "param-key"
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)
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assert api_base == "https://param.lambda.ai/v1"
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assert api_key == "param-key"
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def test_get_llm_provider_lambda_ai():
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"""Test that get_llm_provider correctly identifies Lambda AI"""
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from litellm.litellm_core_utils.get_llm_provider_logic import get_llm_provider
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# Test with lambda_ai/model-name format
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model, provider, api_key, api_base = get_llm_provider("lambda_ai/llama3.1-8b-instruct")
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assert model == "llama3.1-8b-instruct"
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assert provider == "lambda_ai"
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# Test with api_base containing Lambda AI endpoint
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model, provider, api_key, api_base = get_llm_provider(
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"llama3.1-8b-instruct", api_base="https://api.lambda.ai/v1"
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)
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assert model == "llama3.1-8b-instruct"
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assert provider == "lambda_ai"
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assert api_base == "https://api.lambda.ai/v1"
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def test_lambda_ai_in_provider_lists():
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"""Test that Lambda AI is registered in all necessary provider lists"""
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assert "lambda_ai" in litellm.openai_compatible_providers
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assert "lambda_ai" in litellm.provider_list
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assert "https://api.lambda.ai/v1" in litellm.openai_compatible_endpoints
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@pytest.mark.asyncio
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async def test_lambda_ai_completion_call():
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"""Test completion call with Lambda AI provider (requires LAMBDA_API_KEY)"""
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# Skip if no API key is available
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if not os.getenv("LAMBDA_API_KEY"):
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pytest.skip("LAMBDA_API_KEY not set")
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try:
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response = await litellm.acompletion(
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model="lambda_ai/llama3.1-8b-instruct",
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messages=[{"role": "user", "content": "Hello, this is a test"}],
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max_tokens=10,
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)
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assert response.choices[0].message.content
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assert response.model
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assert response.usage
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except Exception as e:
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# If the API key is invalid or there's a network issue, that's okay
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# The important thing is that the provider was recognized
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if "lambda_ai" not in str(e) and "provider" not in str(e).lower():
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# Re-raise if it's not a provider-related error
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raise
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def test_lambda_ai_models_configuration():
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"""Test that Lambda AI models are configured correctly"""
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from litellm import get_model_info
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# Reload model cost map to pick up local changes
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os.environ["LITELLM_LOCAL_MODEL_COST_MAP"] = "True"
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litellm.model_cost = litellm.get_model_cost_map(url="")
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# Clear and repopulate lambda_ai_models list after reloading model_cost
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litellm.lambda_ai_models = []
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litellm.add_known_models()
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# Some Lambda AI models to test
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lambda_ai_models = [
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"lambda_ai/deepseek-llama3.3-70b",
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"lambda_ai/hermes3-8b",
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"lambda_ai/llama3.1-8b-instruct",
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"lambda_ai/llama3.2-11b-vision-instruct",
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"lambda_ai/qwen25-coder-32b-instruct",
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]
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for model in lambda_ai_models:
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model_info = get_model_info(model)
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assert model_info is not None, f"Model info not found for {model}"
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assert model_info.get("litellm_provider") == "lambda_ai", f"{model} should have lambda_ai as provider"
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assert model_info.get("mode") == "chat", f"{model} should be in chat mode"
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assert model_info.get("supports_function_calling") is True, f"{model} should support function calling"
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assert model_info.get("supports_system_messages") is True, f"{model} should support system messages"
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# Check vision support for vision models
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if "vision" in model:
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assert model_info.get("supports_vision") is True, f"{model} should support vision"
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def test_lambda_ai_model_list_populated():
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"""Test that lambda_ai_models list is populated correctly"""
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# Ensure we're using local model cost map and repopulate models
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os.environ["LITELLM_LOCAL_MODEL_COST_MAP"] = "True"
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litellm.model_cost = litellm.get_model_cost_map(url="")
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# Clear and repopulate all model lists after reloading model_cost
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litellm.lambda_ai_models = []
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litellm.add_known_models()
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# This should be populated by the add_known_models function
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assert len(litellm.lambda_ai_models) > 0, "lambda_ai_models list should not be empty"
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# Check that all models in the list are Lambda AI models
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for model in litellm.lambda_ai_models:
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assert model.startswith("lambda_ai/"), f"Model {model} should start with 'lambda_ai/'"
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# Check some expected models are in the list
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expected_models = [
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"lambda_ai/llama3.1-8b-instruct",
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"lambda_ai/hermes3-405b",
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"lambda_ai/deepseek-v3-0324",
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]
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for model in expected_models:
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assert model in litellm.lambda_ai_models, f"{model} should be in lambda_ai_models list" |