mirror of
https://github.com/BerriAI/litellm.git
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test GCS BUCKET
This commit is contained in:
Ishaan Jaffer
parent
ee4ded4c44
commit
7844571d36
1 changed files with 182 additions and 184 deletions
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@ -21,177 +21,68 @@ from litellm.integrations.gcs_bucket.gcs_bucket import (
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StandardLoggingPayload,
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)
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from litellm.types.utils import StandardCallbackDynamicParams
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from unittest.mock import patch
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from litellm.types.integrations.gcs_bucket import GCSLoggingConfig
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from unittest.mock import patch, AsyncMock, MagicMock
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verbose_logger.setLevel(logging.DEBUG)
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def load_vertex_ai_credentials():
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# Define the path to the vertex_key.json file
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print("loading vertex ai credentials")
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os.environ["GCS_FLUSH_INTERVAL"] = "1"
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os.environ["GCS_USE_BATCHED_LOGGING"] = "false"
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filepath = os.path.dirname(os.path.abspath(__file__))
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vertex_key_path = filepath + "/vertex_key.json"
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# Read the existing content of the file or create an empty dictionary
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try:
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with open(vertex_key_path, "r") as file:
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# Read the file content
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print("Read vertexai file path")
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content = file.read()
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# If the file is empty or not valid JSON, create an empty dictionary
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if not content or not content.strip():
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service_account_key_data = {}
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else:
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# Attempt to load the existing JSON content
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file.seek(0)
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service_account_key_data = json.load(file)
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except FileNotFoundError:
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# If the file doesn't exist, create an empty dictionary
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service_account_key_data = {}
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# Update the service_account_key_data with environment variables
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private_key_id = os.environ.get("VERTEX_AI_PRIVATE_KEY_ID", "")
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private_key = os.environ.get("VERTEX_AI_PRIVATE_KEY", "")
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private_key = private_key.replace("\\n", "\n")
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service_account_key_data["private_key_id"] = private_key_id
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service_account_key_data["private_key"] = private_key
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# Create a temporary file
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with tempfile.NamedTemporaryFile(mode="w+", delete=False) as temp_file:
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# Write the updated content to the temporary files
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json.dump(service_account_key_data, temp_file, indent=2)
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# Export the temporary file as GOOGLE_APPLICATION_CREDENTIALS
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os.environ["GCS_PATH_SERVICE_ACCOUNT"] = os.path.abspath(temp_file.name)
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print("created gcs path service account=", os.environ["GCS_PATH_SERVICE_ACCOUNT"])
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def _make_mock_gcs_logging_config():
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return GCSLoggingConfig(
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bucket_name="test-bucket",
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vertex_instance=MagicMock(),
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path_service_account=None,
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)
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@pytest.mark.asyncio
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async def test_aaabasic_gcs_logger():
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load_vertex_ai_credentials()
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gcs_logger = GCSBucketLogger()
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print("GCSBucketLogger", gcs_logger)
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os.environ["GCS_FLUSH_INTERVAL"] = "1"
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os.environ["GCS_USE_BATCHED_LOGGING"] = "false"
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os.environ["GCS_BUCKET_NAME"] = "test-bucket"
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litellm.callbacks = [gcs_logger]
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response = await litellm.acompletion(
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model="gpt-3.5-turbo",
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temperature=0.7,
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messages=[{"role": "user", "content": "This is a test"}],
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max_tokens=10,
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user="ishaan-2",
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mock_response="Hi!",
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metadata={
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"tags": ["model-anthropic-claude-v2.1", "app-ishaan-prod"],
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"user_api_key": "a1b2c3d4e5f6789012345678901234567890abcdef1234567890abcdef123456",
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"user_api_key_alias": None,
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"user_api_end_user_max_budget": None,
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"litellm_api_version": "0.0.0",
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"global_max_parallel_requests": None,
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"user_api_key_user_id": "116544810872468347480",
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"user_api_key_org_id": None,
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"user_api_key_team_id": None,
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"user_api_key_team_alias": None,
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"user_api_key_metadata": {},
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"requester_ip_address": "127.0.0.1",
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"requester_metadata": {"foo": "bar"},
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"spend_logs_metadata": {"hello": "world"},
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"headers": {
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"content-type": "application/json",
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"user-agent": "PostmanRuntime/7.32.3",
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"accept": "*/*",
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"postman-token": "92300061-eeaa-423b-a420-0b44896ecdc4",
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"host": "localhost:4000",
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"accept-encoding": "gzip, deflate, br",
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"connection": "keep-alive",
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"content-length": "163",
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},
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"endpoint": "http://localhost:4000/chat/completions",
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"model_group": "gpt-3.5-turbo",
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"model_info": {
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"id": "4bad40a1eb6bebd1682800f16f44b9f06c52a6703444c99c7f9f32e9de3693b4",
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"db_model": False,
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},
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"api_base": "https://openai-gpt-4-test-v-1.openai.azure.com/",
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"caching_groups": None,
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"raw_request": "\n\nPOST Request Sent from LiteLLM:\ncurl -X POST \\\nhttps://openai-gpt-4-test-v-1.openai.azure.com//openai/ \\\n-H 'Authorization: *****' \\\n-d '{'model': 'chatgpt-v-3', 'messages': [{'role': 'system', 'content': 'you are a helpful assistant.\\n'}, {'role': 'user', 'content': 'bom dia'}], 'stream': False, 'max_tokens': 10, 'user': '116544810872468347480', 'extra_body': {}}'\n",
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},
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)
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captured_payloads = []
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print("response", response)
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async def mock_log_json_data_on_gcs(
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self, headers, bucket_name, object_name, logging_payload
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):
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captured_payloads.append(
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{
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"bucket_name": bucket_name,
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"object_name": object_name,
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"logging_payload": logging_payload,
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}
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)
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return {"kind": "storage#object", "name": object_name}
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await asyncio.sleep(5)
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with patch(
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"litellm.proxy.proxy_server.premium_user", True
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), patch.object(
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GCSBucketLogger,
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"construct_request_headers",
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new_callable=AsyncMock,
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return_value={"Authorization": "Bearer mock_token"},
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), patch.object(
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GCSBucketLogger,
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"get_gcs_logging_config",
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new_callable=AsyncMock,
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return_value=_make_mock_gcs_logging_config(),
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), patch.object(
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GCSBucketLogger,
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"_log_json_data_on_gcs",
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mock_log_json_data_on_gcs,
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):
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gcs_logger = GCSBucketLogger()
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# Get the current date
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# Get the current date
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current_date = datetime.now().strftime("%Y-%m-%d")
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# Modify the object_name to include the date-based folder
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object_name = f"{current_date}%2F{response.id}"
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print("object_name", object_name)
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# Check if object landed on GCS
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object_from_gcs = await gcs_logger.download_gcs_object(object_name=object_name)
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print("object from gcs=", object_from_gcs)
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# convert object_from_gcs from bytes to DICT
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parsed_data = json.loads(object_from_gcs)
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print("object_from_gcs as dict", parsed_data)
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print("type of object_from_gcs", type(parsed_data))
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gcs_payload = StandardLoggingPayload(**parsed_data)
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print("gcs_payload", gcs_payload)
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assert gcs_payload["model"] == "gpt-3.5-turbo"
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assert gcs_payload["messages"] == [{"role": "user", "content": "This is a test"}]
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assert gcs_payload["response"]["choices"][0]["message"]["content"] == "Hi!"
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assert gcs_payload["response_cost"] > 0.0
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assert gcs_payload["status"] == "success"
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assert (
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gcs_payload["metadata"]["user_api_key_hash"]
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== "a1b2c3d4e5f6789012345678901234567890abcdef1234567890abcdef123456"
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)
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assert gcs_payload["metadata"]["user_api_key_user_id"] == "116544810872468347480"
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assert gcs_payload["metadata"]["requester_metadata"] == {"foo": "bar"}
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# Delete Object from GCS
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print("deleting object from GCS")
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await gcs_logger.delete_gcs_object(object_name=object_name)
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@pytest.mark.asyncio
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async def test_basic_gcs_logger_failure():
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load_vertex_ai_credentials()
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gcs_logger = GCSBucketLogger()
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print("GCSBucketLogger", gcs_logger)
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gcs_log_id = f"failure-test-{uuid.uuid4().hex}"
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litellm.callbacks = [gcs_logger]
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try:
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litellm.callbacks = [gcs_logger]
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response = await litellm.acompletion(
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model="gpt-3.5-turbo",
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temperature=0.7,
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messages=[{"role": "user", "content": "This is a test"}],
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max_tokens=10,
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user="ishaan-2",
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mock_response=litellm.BadRequestError(
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model="gpt-3.5-turbo",
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message="Error: 400: Bad Request: Invalid API key, please check your API key and try again.",
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llm_provider="openai",
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),
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mock_response="Hi!",
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metadata={
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"gcs_log_id": gcs_log_id,
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"tags": ["model-anthropic-claude-v2.1", "app-ishaan-prod"],
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"user_api_key": "a1b2c3d4e5f6789012345678901234567890abcdef1234567890abcdef123456",
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"user_api_key_alias": None,
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@ -204,6 +95,7 @@ async def test_basic_gcs_logger_failure():
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"user_api_key_team_alias": None,
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"user_api_key_metadata": {},
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"requester_ip_address": "127.0.0.1",
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"requester_metadata": {"foo": "bar"},
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"spend_logs_metadata": {"hello": "world"},
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"headers": {
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"content-type": "application/json",
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@ -226,47 +118,153 @@ async def test_basic_gcs_logger_failure():
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"raw_request": "\n\nPOST Request Sent from LiteLLM:\ncurl -X POST \\\nhttps://openai-gpt-4-test-v-1.openai.azure.com//openai/ \\\n-H 'Authorization: *****' \\\n-d '{'model': 'chatgpt-v-3', 'messages': [{'role': 'system', 'content': 'you are a helpful assistant.\\n'}, {'role': 'user', 'content': 'bom dia'}], 'stream': False, 'max_tokens': 10, 'user': '116544810872468347480', 'extra_body': {}}'\n",
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},
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)
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except Exception:
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pass
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await asyncio.sleep(5)
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print("response", response)
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# Get the current date
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# Get the current date
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current_date = datetime.now().strftime("%Y-%m-%d")
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await asyncio.sleep(3)
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# Modify the object_name to include the date-based folder
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object_name = gcs_log_id
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assert len(captured_payloads) == 1, (
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f"Expected 1 GCS upload, got {len(captured_payloads)}"
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)
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print("object_name", object_name)
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gcs_payload = captured_payloads[0]["logging_payload"]
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# Check if object landed on GCS
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object_from_gcs = await gcs_logger.download_gcs_object(object_name=object_name)
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print("object from gcs=", object_from_gcs)
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# convert object_from_gcs from bytes to DICT
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parsed_data = json.loads(object_from_gcs)
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print("object_from_gcs as dict", parsed_data)
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assert gcs_payload["model"] == "gpt-3.5-turbo"
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assert gcs_payload["messages"] == [
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{"role": "user", "content": "This is a test"}
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]
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print("type of object_from_gcs", type(parsed_data))
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assert gcs_payload["response"]["choices"][0]["message"]["content"] == "Hi!"
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gcs_payload = StandardLoggingPayload(**parsed_data)
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assert gcs_payload["response_cost"] > 0.0
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print("gcs_payload", gcs_payload)
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assert gcs_payload["status"] == "success"
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assert gcs_payload["model"] == "gpt-3.5-turbo"
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assert gcs_payload["messages"] == [{"role": "user", "content": "This is a test"}]
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assert (
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gcs_payload["metadata"]["user_api_key_hash"]
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== "a1b2c3d4e5f6789012345678901234567890abcdef1234567890abcdef123456"
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)
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assert (
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gcs_payload["metadata"]["user_api_key_user_id"] == "116544810872468347480"
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)
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assert gcs_payload["response_cost"] == 0
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assert gcs_payload["status"] == "failure"
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assert (
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gcs_payload["metadata"]["user_api_key_hash"]
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== "a1b2c3d4e5f6789012345678901234567890abcdef1234567890abcdef123456"
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)
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assert gcs_payload["metadata"]["user_api_key_user_id"] == "116544810872468347480"
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# Delete Object from GCS
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print("deleting object from GCS")
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await gcs_logger.delete_gcs_object(object_name=object_name)
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assert gcs_payload["metadata"]["requester_metadata"] == {"foo": "bar"}
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@pytest.mark.asyncio
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async def test_basic_gcs_logger_failure():
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os.environ["GCS_FLUSH_INTERVAL"] = "1"
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os.environ["GCS_USE_BATCHED_LOGGING"] = "false"
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os.environ["GCS_BUCKET_NAME"] = "test-bucket"
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captured_payloads = []
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async def mock_log_json_data_on_gcs(
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self, headers, bucket_name, object_name, logging_payload
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):
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captured_payloads.append(
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{
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"bucket_name": bucket_name,
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"object_name": object_name,
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"logging_payload": logging_payload,
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}
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)
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return {"kind": "storage#object", "name": object_name}
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gcs_log_id = f"failure-test-{uuid.uuid4().hex}"
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with patch(
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"litellm.proxy.proxy_server.premium_user", True
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), patch.object(
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GCSBucketLogger,
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"construct_request_headers",
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new_callable=AsyncMock,
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return_value={"Authorization": "Bearer mock_token"},
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), patch.object(
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GCSBucketLogger,
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"get_gcs_logging_config",
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new_callable=AsyncMock,
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return_value=_make_mock_gcs_logging_config(),
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), patch.object(
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GCSBucketLogger,
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"_log_json_data_on_gcs",
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mock_log_json_data_on_gcs,
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):
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gcs_logger = GCSBucketLogger()
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litellm.callbacks = [gcs_logger]
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try:
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response = await litellm.acompletion(
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model="gpt-3.5-turbo",
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temperature=0.7,
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messages=[{"role": "user", "content": "This is a test"}],
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max_tokens=10,
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user="ishaan-2",
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mock_response=litellm.BadRequestError(
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model="gpt-3.5-turbo",
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message="Error: 400: Bad Request: Invalid API key, please check your API key and try again.",
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llm_provider="openai",
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),
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metadata={
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"gcs_log_id": gcs_log_id,
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"tags": ["model-anthropic-claude-v2.1", "app-ishaan-prod"],
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"user_api_key": "a1b2c3d4e5f6789012345678901234567890abcdef1234567890abcdef123456",
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"user_api_key_alias": None,
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"user_api_end_user_max_budget": None,
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"litellm_api_version": "0.0.0",
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"global_max_parallel_requests": None,
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"user_api_key_user_id": "116544810872468347480",
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"user_api_key_org_id": None,
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"user_api_key_team_id": None,
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"user_api_key_team_alias": None,
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"user_api_key_metadata": {},
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"requester_ip_address": "127.0.0.1",
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"spend_logs_metadata": {"hello": "world"},
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"headers": {
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"content-type": "application/json",
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"user-agent": "PostmanRuntime/7.32.3",
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"accept": "*/*",
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"postman-token": "92300061-eeaa-423b-a420-0b44896ecdc4",
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"host": "localhost:4000",
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"accept-encoding": "gzip, deflate, br",
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"connection": "keep-alive",
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"content-length": "163",
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},
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"endpoint": "http://localhost:4000/chat/completions",
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"model_group": "gpt-3.5-turbo",
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"model_info": {
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"id": "4bad40a1eb6bebd1682800f16f44b9f06c52a6703444c99c7f9f32e9de3693b4",
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"db_model": False,
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},
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"api_base": "https://openai-gpt-4-test-v-1.openai.azure.com/",
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"caching_groups": None,
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"raw_request": "\n\nPOST Request Sent from LiteLLM:\ncurl -X POST \\\nhttps://openai-gpt-4-test-v-1.openai.azure.com//openai/ \\\n-H 'Authorization: *****' \\\n-d '{'model': 'chatgpt-v-3', 'messages': [{'role': 'system', 'content': 'you are a helpful assistant.\\n'}, {'role': 'user', 'content': 'bom dia'}], 'stream': False, 'max_tokens': 10, 'user': '116544810872468347480', 'extra_body': {}}'\n",
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},
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)
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except Exception:
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pass
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await asyncio.sleep(3)
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assert len(captured_payloads) == 1, (
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f"Expected 1 GCS upload, got {len(captured_payloads)}"
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)
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|
||||
gcs_payload = captured_payloads[0]["logging_payload"]
|
||||
|
||||
assert gcs_payload["model"] == "gpt-3.5-turbo"
|
||||
assert gcs_payload["messages"] == [
|
||||
{"role": "user", "content": "This is a test"}
|
||||
]
|
||||
|
||||
assert gcs_payload["response_cost"] == 0
|
||||
assert gcs_payload["status"] == "failure"
|
||||
|
||||
assert (
|
||||
gcs_payload["metadata"]["user_api_key_hash"]
|
||||
== "a1b2c3d4e5f6789012345678901234567890abcdef1234567890abcdef123456"
|
||||
)
|
||||
assert (
|
||||
gcs_payload["metadata"]["user_api_key_user_id"] == "116544810872468347480"
|
||||
)
|
||||
|
|
|
|||
Loading…
Add table
Reference in a new issue