mirror of
https://github.com/BerriAI/litellm.git
synced 2025-04-25 10:44:24 +00:00
7b27cfb0ae
* fix(gpt_transformation.py): fix response_format translation check for 4o models Fixes https://github.com/BerriAI/litellm/issues/7616 * feat(key_management_endpoints.py): support 'temp_budget_increase' and 'temp_budget_expiry' fields Allow proxy admin to grant temporary budget increases to keys * fix(proxy/_types.py): enforce temp_budget_increase and temp_budget_expiry are always passed together * feat(user_api_key_auth.py): initial working temp budget increase logic ensures key budget exceeded error checks for temp budget in key metadata * feat(proxy_server.py): return the key max budget and key spend in the response headers Allows clientside user to know their remaining limits * test: add unit testing for new proxy utils Ensures new key budget is correctly handled * docs(temporary_budget_increase.md): add doc on temporary budget increase * fix(utils.py): remove 3.5 from response_format check for now not all azure 3.5 models support response_format * fix(user_api_key_auth.py): return valid user api key auth object on all paths
285 lines
9.2 KiB
Python
285 lines
9.2 KiB
Python
import sys
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import os
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sys.path.insert(
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0, os.path.abspath("../../")
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) # Adds the parent directory to the system path
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import pytest
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from litellm.llms.azure.common_utils import process_azure_headers
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from httpx import Headers
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from base_embedding_unit_tests import BaseLLMEmbeddingTest
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def test_process_azure_headers_empty():
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result = process_azure_headers({})
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assert result == {}, "Expected empty dictionary for no input"
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def test_process_azure_headers_with_all_headers():
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input_headers = Headers(
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{
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"x-ratelimit-limit-requests": "100",
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"x-ratelimit-remaining-requests": "90",
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"x-ratelimit-limit-tokens": "10000",
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"x-ratelimit-remaining-tokens": "9000",
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"other-header": "value",
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}
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)
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expected_output = {
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"x-ratelimit-limit-requests": "100",
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"x-ratelimit-remaining-requests": "90",
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"x-ratelimit-limit-tokens": "10000",
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"x-ratelimit-remaining-tokens": "9000",
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"llm_provider-x-ratelimit-limit-requests": "100",
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"llm_provider-x-ratelimit-remaining-requests": "90",
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"llm_provider-x-ratelimit-limit-tokens": "10000",
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"llm_provider-x-ratelimit-remaining-tokens": "9000",
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"llm_provider-other-header": "value",
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}
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result = process_azure_headers(input_headers)
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assert result == expected_output, "Unexpected output for all Azure headers"
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def test_process_azure_headers_with_partial_headers():
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input_headers = Headers(
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{
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"x-ratelimit-limit-requests": "100",
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"x-ratelimit-remaining-tokens": "9000",
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"other-header": "value",
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}
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)
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expected_output = {
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"x-ratelimit-limit-requests": "100",
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"x-ratelimit-remaining-tokens": "9000",
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"llm_provider-x-ratelimit-limit-requests": "100",
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"llm_provider-x-ratelimit-remaining-tokens": "9000",
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"llm_provider-other-header": "value",
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}
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result = process_azure_headers(input_headers)
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assert result == expected_output, "Unexpected output for partial Azure headers"
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def test_process_azure_headers_with_no_matching_headers():
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input_headers = Headers(
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{"unrelated-header-1": "value1", "unrelated-header-2": "value2"}
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)
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expected_output = {
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"llm_provider-unrelated-header-1": "value1",
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"llm_provider-unrelated-header-2": "value2",
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}
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result = process_azure_headers(input_headers)
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assert result == expected_output, "Unexpected output for non-matching headers"
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def test_process_azure_headers_with_dict_input():
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input_headers = {
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"x-ratelimit-limit-requests": "100",
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"x-ratelimit-remaining-requests": "90",
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"other-header": "value",
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}
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expected_output = {
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"x-ratelimit-limit-requests": "100",
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"x-ratelimit-remaining-requests": "90",
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"llm_provider-x-ratelimit-limit-requests": "100",
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"llm_provider-x-ratelimit-remaining-requests": "90",
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"llm_provider-other-header": "value",
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}
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result = process_azure_headers(input_headers)
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assert result == expected_output, "Unexpected output for dict input"
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from httpx import Client
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from unittest.mock import MagicMock, patch
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from openai import AzureOpenAI
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import litellm
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from litellm import completion
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import os
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@pytest.mark.parametrize(
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"input, call_type",
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[
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({"messages": [{"role": "user", "content": "Hello world"}]}, "completion"),
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({"input": "Hello world"}, "embedding"),
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({"prompt": "Hello world"}, "image_generation"),
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],
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)
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@pytest.mark.parametrize(
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"header_value",
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[
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"headers",
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"extra_headers",
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],
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)
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def test_azure_extra_headers(input, call_type, header_value):
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from litellm import embedding, image_generation
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http_client = Client()
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messages = [{"role": "user", "content": "Hello world"}]
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with patch.object(http_client, "send", new=MagicMock()) as mock_client:
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litellm.client_session = http_client
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try:
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if call_type == "completion":
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func = completion
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elif call_type == "embedding":
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func = embedding
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elif call_type == "image_generation":
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func = image_generation
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data = {
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"model": "azure/chatgpt-v-2",
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"api_base": "https://openai-gpt-4-test-v-1.openai.azure.com",
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"api_version": "2023-07-01-preview",
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"api_key": "my-azure-api-key",
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header_value: {
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"Authorization": "my-bad-key",
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"Ocp-Apim-Subscription-Key": "hello-world-testing",
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},
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**input,
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}
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response = func(**data)
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print(response)
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except Exception as e:
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print(e)
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mock_client.assert_called()
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print(f"mock_client.call_args: {mock_client.call_args}")
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request = mock_client.call_args[0][0]
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print(request.method) # This will print 'POST'
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print(request.url) # This will print the full URL
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print(request.headers) # This will print the full URL
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auth_header = request.headers.get("Authorization")
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apim_key = request.headers.get("Ocp-Apim-Subscription-Key")
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print(auth_header)
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assert auth_header == "my-bad-key"
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assert apim_key == "hello-world-testing"
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@pytest.mark.parametrize(
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"api_base, model, expected_endpoint",
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[
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(
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"https://my-endpoint-sweden-berri992.openai.azure.com",
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"dall-e-3-test",
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"https://my-endpoint-sweden-berri992.openai.azure.com/openai/deployments/dall-e-3-test/images/generations?api-version=2023-12-01-preview",
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),
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(
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"https://my-endpoint-sweden-berri992.openai.azure.com/openai/deployments/my-custom-deployment",
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"dall-e-3",
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"https://my-endpoint-sweden-berri992.openai.azure.com/openai/deployments/my-custom-deployment/images/generations?api-version=2023-12-01-preview",
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),
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],
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)
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def test_process_azure_endpoint_url(api_base, model, expected_endpoint):
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from litellm.llms.azure.azure import AzureChatCompletion
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azure_chat_completion = AzureChatCompletion()
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input_args = {
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"azure_client_params": {
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"api_version": "2023-12-01-preview",
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"azure_endpoint": api_base,
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"azure_deployment": model,
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"max_retries": 2,
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"timeout": 600,
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"api_key": "f28ab7b695af4154bc53498e5bdccb07",
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},
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"model": model,
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}
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result = azure_chat_completion.create_azure_base_url(**input_args)
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assert result == expected_endpoint, "Unexpected endpoint"
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class TestAzureEmbedding(BaseLLMEmbeddingTest):
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def get_base_embedding_call_args(self) -> dict:
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return {
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"model": "azure/azure-embedding-model",
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"api_key": os.getenv("AZURE_API_KEY"),
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"api_base": os.getenv("AZURE_API_BASE"),
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}
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def get_custom_llm_provider(self) -> litellm.LlmProviders:
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return litellm.LlmProviders.AZURE
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@patch("azure.identity.UsernamePasswordCredential")
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@patch("azure.identity.get_bearer_token_provider")
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def test_get_azure_ad_token_from_username_password(
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mock_get_bearer_token_provider, mock_credential
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):
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from litellm.llms.azure.common_utils import (
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get_azure_ad_token_from_username_password,
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)
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# Test inputs
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client_id = "test-client-id"
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username = "test-username"
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password = "test-password"
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# Mock the token provider function
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mock_token_provider = lambda: "mock-token"
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mock_get_bearer_token_provider.return_value = mock_token_provider
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# Call the function
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result = get_azure_ad_token_from_username_password(
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client_id=client_id, azure_username=username, azure_password=password
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)
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# Verify UsernamePasswordCredential was called with correct arguments
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mock_credential.assert_called_once_with(
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client_id=client_id, username=username, password=password
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)
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# Verify get_bearer_token_provider was called
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mock_get_bearer_token_provider.assert_called_once_with(
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mock_credential.return_value, "https://cognitiveservices.azure.com/.default"
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)
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# Verify the result is the mock token provider
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assert result == mock_token_provider
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def test_azure_openai_gpt_4o_naming(monkeypatch):
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from openai import AzureOpenAI
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from pydantic import BaseModel, Field
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monkeypatch.setenv("AZURE_API_VERSION", "2024-10-21")
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client = AzureOpenAI(
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api_key="test-api-key",
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base_url="https://my-endpoint-sweden-berri992.openai.azure.com",
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api_version="2023-12-01-preview",
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)
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class ResponseFormat(BaseModel):
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number: str = Field(description="total number of days in a week")
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days: list[str] = Field(description="name of days in a week")
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with patch.object(client.chat.completions.with_raw_response, "create") as mock_post:
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try:
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completion(
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model="azure/gpt4o",
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messages=[{"role": "user", "content": "Hello world"}],
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response_format=ResponseFormat,
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client=client,
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)
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except Exception as e:
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print(e)
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mock_post.assert_called_once()
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print(mock_post.call_args.kwargs)
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assert "tool_calls" not in mock_post.call_args.kwargs
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