Litellm dev 11 08 2024 (#6658)

* fix(deepseek/chat): convert content list to str

Fixes https://github.com/BerriAI/litellm/issues/6642

* test(test_deepseek_completion.py): implement base llm unit tests

increase robustness across providers

* fix(router.py): support content policy violation fallbacks with default fallbacks

* fix(opentelemetry.py): refactor to move otel imports behing flag

Fixes https://github.com/BerriAI/litellm/issues/6636

* fix(opentelemtry.py): close span on success completion

* fix(user_api_key_auth.py): allow user_role to default to none

* fix: mark flaky test

* fix(opentelemetry.py): move otelconfig.from_env to inside the init

prevent otel errors raised just by importing the litellm class

* fix(user_api_key_auth.py): fix auth error

litellm/__init__.py

@@ -1045,6 +1045,7 @@ from .llms.AzureOpenAI.azure import (
 
 from .llms.AzureOpenAI.chat.gpt_transformation import AzureOpenAIConfig
 from .llms.hosted_vllm.chat.transformation import HostedVLLMChatConfig
+from .llms.deepseek.chat.transformation import DeepSeekChatConfig
 from .llms.lm_studio.chat.transformation import LMStudioChatConfig
 from .llms.perplexity.chat.transformation import PerplexityChatConfig
 from .llms.AzureOpenAI.chat.o1_transformation import AzureOpenAIO1Config

litellm/integrations/opentelemetry.py

@@ -16,6 +16,7 @@ from litellm.types.utils import (
 )
 
 if TYPE_CHECKING:
+    from opentelemetry.sdk.trace.export import SpanExporter as _SpanExporter
     from opentelemetry.trace import Span as _Span
 
     from litellm.proxy._types import (
@@ -24,10 +25,12 @@ if TYPE_CHECKING:
     from litellm.proxy.proxy_server import UserAPIKeyAuth as _UserAPIKeyAuth
 
     Span = _Span
+    SpanExporter = _SpanExporter
     UserAPIKeyAuth = _UserAPIKeyAuth
     ManagementEndpointLoggingPayload = _ManagementEndpointLoggingPayload
 else:
     Span = Any
+    SpanExporter = Any
     UserAPIKeyAuth = Any
     ManagementEndpointLoggingPayload = Any
 
@@ -44,7 +47,6 @@ LITELLM_REQUEST_SPAN_NAME = "litellm_request"
 
 @dataclass
 class OpenTelemetryConfig:
-    from opentelemetry.sdk.trace.export import SpanExporter
 
     exporter: Union[str, SpanExporter] = "console"
     endpoint: Optional[str] = None
@@ -77,7 +79,7 @@ class OpenTelemetryConfig:
 class OpenTelemetry(CustomLogger):
     def __init__(
         self,
-        config: OpenTelemetryConfig = OpenTelemetryConfig.from_env(),
+        config: Optional[OpenTelemetryConfig] = None,
         callback_name: Optional[str] = None,
         **kwargs,
     ):
@@ -85,6 +87,9 @@ class OpenTelemetry(CustomLogger):
         from opentelemetry.sdk.resources import Resource
         from opentelemetry.sdk.trace import TracerProvider
 
+        if config is None:
+            config = OpenTelemetryConfig.from_env()
+
         self.config = config
         self.OTEL_EXPORTER = self.config.exporter
         self.OTEL_ENDPOINT = self.config.endpoint
@@ -319,8 +324,8 @@ class OpenTelemetry(CustomLogger):
 
         span.end(end_time=self._to_ns(end_time))
 
-        # if parent_otel_span is not None:
-        #     parent_otel_span.end(end_time=self._to_ns(datetime.now()))
+        if parent_otel_span is not None:
+            parent_otel_span.end(end_time=self._to_ns(datetime.now()))
 
     def _handle_failure(self, kwargs, response_obj, start_time, end_time):
         from opentelemetry.trace import Status, StatusCode
@@ -700,10 +705,10 @@ class OpenTelemetry(CustomLogger):
             TraceContextTextMapPropagator,
         )
 
-        verbose_logger.debug("OpenTelemetry: GOT A TRACEPARENT {}".format(_traceparent))
         propagator = TraceContextTextMapPropagator()
-        _parent_context = propagator.extract(carrier={"traceparent": _traceparent})
-        verbose_logger.debug("OpenTelemetry: PARENT CONTEXT {}".format(_parent_context))
+        carrier = {"traceparent": _traceparent}
+        _parent_context = propagator.extract(carrier=carrier)
+
         return _parent_context
 
     def _get_span_context(self, kwargs):

litellm/llms/OpenAI/chat/gpt_transformation.py

@@ -3,7 +3,7 @@ Support for gpt model family
 """
 
 import types
-from typing import Optional, Union
+from typing import List, Optional, Union
 
 import litellm
 from litellm.types.llms.openai import AllMessageValues, ChatCompletionUserMessage
@@ -163,3 +163,8 @@ class OpenAIGPTConfig:
             model=model,
             drop_params=drop_params,
         )
+
+    def _transform_messages(
+        self, messages: List[AllMessageValues]
+    ) -> List[AllMessageValues]:
+        return messages

litellm/llms/OpenAI/chat/o1_transformation.py

@@ -108,7 +108,9 @@ class OpenAIO1Config(OpenAIGPTConfig):
             return True
         return False
 
-    def o1_prompt_factory(self, messages: List[AllMessageValues]):
+    def _transform_messages(
+        self, messages: List[AllMessageValues]
+    ) -> List[AllMessageValues]:
         """
         Handles limitations of O-1 model family.
         - modalities: image => drop param (if user opts in to dropping param)

litellm/llms/OpenAI/openai.py

@@ -15,6 +15,7 @@ from pydantic import BaseModel
 from typing_extensions import overload, override
 
 import litellm
+from litellm import LlmProviders
 from litellm._logging import verbose_logger
 from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
 from litellm.secret_managers.main import get_secret_str
@@ -24,6 +25,7 @@ from litellm.utils import (
     CustomStreamWrapper,
     Message,
     ModelResponse,
+    ProviderConfigManager,
     TextCompletionResponse,
     Usage,
     convert_to_model_response_object,
@@ -701,13 +703,11 @@ class OpenAIChatCompletion(BaseLLM):
                         messages=messages,
                         custom_llm_provider=custom_llm_provider,
                     )
-            if (
-                litellm.openAIO1Config.is_model_o1_reasoning_model(model=model)
-                and messages is not None
-            ):
-                messages = litellm.openAIO1Config.o1_prompt_factory(
-                    messages=messages,
+            if messages is not None and custom_llm_provider is not None:
+                provider_config = ProviderConfigManager.get_provider_config(
+                    model=model, provider=LlmProviders(custom_llm_provider)
                 )
+                messages = provider_config._transform_messages(messages)
 
             for _ in range(
                 2

litellm/llms/deepseek/chat/transformation.py

@@ -0,0 +1,41 @@
+"""
+Translates from OpenAI's `/v1/chat/completions` to DeepSeek's `/v1/chat/completions`
+"""
+
+import types
+from typing import List, Optional, Tuple, Union
+
+from pydantic import BaseModel
+
+import litellm
+from litellm.secret_managers.main import get_secret_str
+from litellm.types.llms.openai import AllMessageValues, ChatCompletionAssistantMessage
+
+from ....utils import _remove_additional_properties, _remove_strict_from_schema
+from ...OpenAI.chat.gpt_transformation import OpenAIGPTConfig
+from ...prompt_templates.common_utils import (
+    handle_messages_with_content_list_to_str_conversion,
+)
+
+
+class DeepSeekChatConfig(OpenAIGPTConfig):
+
+    def _transform_messages(
+        self, messages: List[AllMessageValues]
+    ) -> List[AllMessageValues]:
+        """
+        DeepSeek does not support content in list format.
+        """
+        messages = handle_messages_with_content_list_to_str_conversion(messages)
+        return super()._transform_messages(messages)
+
+    def _get_openai_compatible_provider_info(
+        self, api_base: Optional[str], api_key: Optional[str]
+    ) -> Tuple[Optional[str], Optional[str]]:
+        api_base = (
+            api_base
+            or get_secret_str("DEEPSEEK_API_BASE")
+            or "https://api.deepseek.com/beta"
+        )  # type: ignore
+        dynamic_api_key = api_key or get_secret_str("DEEPSEEK_API_KEY")
+        return api_base, dynamic_api_key

litellm/llms/prompt_templates/common_utils.py

@@ -24,6 +24,19 @@ DEFAULT_ASSISTANT_CONTINUE_MESSAGE = ChatCompletionAssistantMessage(
 )
 
 
+def handle_messages_with_content_list_to_str_conversion(
+    messages: List[AllMessageValues],
+) -> List[AllMessageValues]:
+    """
+    Handles messages with content list conversion
+    """
+    for message in messages:
+        texts = convert_content_list_to_str(message=message)
+        if texts:
+            message["content"] = texts
+    return messages
+
+
 def convert_content_list_to_str(message: AllMessageValues) -> str:
     """
     - handles scenario where content is list and not string

litellm/proxy/_new_secret_config.yaml

@@ -59,10 +59,10 @@ model_list:
       timeout: 300
       stream_timeout: 60
 
-# litellm_settings:
-#   fallbacks: [{ "claude-3-5-sonnet-20240620": ["claude-3-5-sonnet-aihubmix"] }]
-#   callbacks: ["otel", "prometheus"]
-#   default_redis_batch_cache_expiry: 10
+litellm_settings:
+  fallbacks: [{ "claude-3-5-sonnet-20240620": ["claude-3-5-sonnet-aihubmix"] }]
+  callbacks: ["otel", "prometheus"]
+  default_redis_batch_cache_expiry: 10
 
 # litellm_settings:
 #   cache: True

litellm/proxy/auth/user_api_key_auth.py

@@ -703,12 +703,17 @@ async def user_api_key_auth(  # noqa: PLR0915
             )
 
         if is_master_key_valid:
-            _user_api_key_obj = UserAPIKeyAuth(
-                api_key=master_key,
+            _user_api_key_obj = _return_user_api_key_auth_obj(
+                user_obj=None,
                 user_role=LitellmUserRoles.PROXY_ADMIN,
-                user_id=litellm_proxy_admin_name,
+                api_key=master_key,
                 parent_otel_span=parent_otel_span,
+                valid_token_dict={
                     **end_user_params,
+                    "user_id": litellm_proxy_admin_name,
+                },
+                route=route,
+                start_time=start_time,
             )
             await _cache_key_object(
                 hashed_token=hash_token(master_key),
@@ -1229,7 +1234,9 @@ def _return_user_api_key_auth_obj(
     valid_token_dict: dict,
     route: str,
     start_time: datetime,
+    user_role: Optional[LitellmUserRoles] = None,
 ) -> UserAPIKeyAuth:
+    traceback.print_stack()
     end_time = datetime.now()
     user_api_key_service_logger_obj.service_success_hook(
         service=ServiceTypes.AUTH,
@@ -1240,7 +1247,7 @@ def _return_user_api_key_auth_obj(
         parent_otel_span=parent_otel_span,
     )
     retrieved_user_role = (
-        _get_user_role(user_obj=user_obj) or LitellmUserRoles.INTERNAL_USER
+        user_role or _get_user_role(user_obj=user_obj) or LitellmUserRoles.INTERNAL_USER
     )
 
     user_api_key_kwargs = {

litellm/router.py

@@ -3558,6 +3558,15 @@ class Router:
             # Catch all - if any exceptions default to cooling down
             return True
 
+    def _has_default_fallbacks(self) -> bool:
+        if self.fallbacks is None:
+            return False
+        for fallback in self.fallbacks:
+            if isinstance(fallback, dict):
+                if "*" in fallback:
+                    return True
+        return False
+
     def _should_raise_content_policy_error(
         self, model: str, response: ModelResponse, kwargs: dict
     ) -> bool:
@@ -3574,6 +3583,7 @@ class Router:
         content_policy_fallbacks = kwargs.get(
             "content_policy_fallbacks", self.content_policy_fallbacks
         )
+
         ### ONLY RAISE ERROR IF CP FALLBACK AVAILABLE ###
         if content_policy_fallbacks is not None:
             fallback_model_group = None
@@ -3584,6 +3594,8 @@ class Router:
 
             if fallback_model_group is not None:
                 return True
+        elif self._has_default_fallbacks():  # default fallbacks set
+            return True
 
         verbose_router_logger.info(
             "Content Policy Error occurred. No available fallbacks. Returning original response. model={}, content_policy_fallbacks={}".format(

litellm/utils.py

@@ -8252,3 +8252,22 @@ def validate_chat_completion_user_messages(messages: List[AllMessageValues]):
             )
 
     return messages
+
+
+from litellm.llms.OpenAI.chat.gpt_transformation import OpenAIGPTConfig
+
+
+class ProviderConfigManager:
+    @staticmethod
+    def get_provider_config(
+        model: str, provider: litellm.LlmProviders
+    ) -> OpenAIGPTConfig:
+        """
+        Returns the provider config for a given provider.
+        """
+        if litellm.openAIO1Config.is_model_o1_reasoning_model(model=model):
+            return litellm.OpenAIO1Config()
+        elif litellm.LlmProviders.DEEPSEEK == provider:
+            return litellm.DeepSeekChatConfig()
+
+        return OpenAIGPTConfig()

tests/llm_translation/base_llm_unit_tests.py

@@ -0,0 +1,46 @@
+import asyncio
+import httpx
+import json
+import pytest
+import sys
+from typing import Any, Dict, List
+from unittest.mock import MagicMock, Mock, patch
+import os
+
+sys.path.insert(
+    0, os.path.abspath("../..")
+)  # Adds the parent directory to the system path
+import litellm
+from litellm.exceptions import BadRequestError
+from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler, HTTPHandler
+from litellm.utils import CustomStreamWrapper
+
+
+# test_example.py
+from abc import ABC, abstractmethod
+
+
+class BaseLLMChatTest(ABC):
+    """
+    Abstract base test class that enforces a common test across all test classes.
+    """
+
+    @abstractmethod
+    def get_base_completion_call_args(self) -> dict:
+        """Must return the base completion call args"""
+        pass
+
+    def test_content_list_handling(self):
+        """Check if content list is supported by LLM API"""
+        base_completion_call_args = self.get_base_completion_call_args()
+        messages = [
+            {
+                "role": "user",
+                "content": [{"type": "text", "text": "Hello, how are you?"}],
+            }
+        ]
+        response = litellm.completion(
+            **base_completion_call_args,
+            messages=messages,
+        )
+        assert response is not None

tests/llm_translation/test_deepseek_completion.py

@@ -0,0 +1,9 @@
+from base_llm_unit_tests import BaseLLMChatTest
+
+
+# Test implementation
+class TestDeepSeekChatCompletion(BaseLLMChatTest):
+    def get_base_completion_call_args(self) -> dict:
+        return {
+            "model": "deepseek/deepseek-chat",
+        }

tests/local_testing/test_completion.py

@@ -4526,6 +4526,7 @@ async def test_completion_ai21_chat():
     "stream",
     [False, True],
 )
+@pytest.mark.flaky(retries=3, delay=1)
 def test_completion_response_ratelimit_headers(model, stream):
     response = completion(
         model=model,

tests/local_testing/test_opentelemetry_unit_tests.py

@@ -0,0 +1,41 @@
+# What is this?
+## Unit tests for opentelemetry integration
+
+# What is this?
+## Unit test for presidio pii masking
+import sys, os, asyncio, time, random
+from datetime import datetime
+import traceback
+from dotenv import load_dotenv
+
+load_dotenv()
+import os
+import asyncio
+
+sys.path.insert(
+    0, os.path.abspath("../..")
+)  # Adds the parent directory to the system path
+import pytest
+import litellm
+from unittest.mock import patch, MagicMock, AsyncMock
+
+
+@pytest.mark.asyncio
+async def test_opentelemetry_integration():
+    """
+    Unit test to confirm the parent otel span is ended
+    """
+
+    parent_otel_span = MagicMock()
+    litellm.callbacks = ["otel"]
+
+    await litellm.acompletion(
+        model="gpt-3.5-turbo",
+        messages=[{"role": "user", "content": "Hello, world!"}],
+        mock_response="Hey!",
+        metadata={"litellm_parent_otel_span": parent_otel_span},
+    )
+
+    await asyncio.sleep(1)
+
+    parent_otel_span.end.assert_called_once()

tests/local_testing/test_python_38.py

@@ -72,6 +72,19 @@ def test_litellm_proxy_server_config_no_general_settings():
         # Check if the response is successful
         assert response.status_code == 200
         assert response.json() == "I'm alive!"
+
+        # Test /chat/completions
+        response = requests.post(
+            "http://localhost:4000/chat/completions",
+            headers={"Authorization": "Bearer 1234567890"},
+            json={
+                "model": "test_openai_models",
+                "messages": [{"role": "user", "content": "Hello, how are you?"}],
+            },
+        )
+
+        assert response.status_code == 200
+
     except ImportError:
         pytest.fail("Failed to import litellm.proxy_server")
     except requests.ConnectionError:

tests/local_testing/test_router_fallbacks.py

@@ -1120,9 +1120,10 @@ async def test_client_side_fallbacks_list(sync_mode):
 
 @pytest.mark.parametrize("sync_mode", [True, False])
 @pytest.mark.parametrize("content_filter_response_exception", [True, False])
+@pytest.mark.parametrize("fallback_type", ["model-specific", "default"])
 @pytest.mark.asyncio
 async def test_router_content_policy_fallbacks(
-    sync_mode, content_filter_response_exception
+    sync_mode, content_filter_response_exception, fallback_type
 ):
     os.environ["LITELLM_LOG"] = "DEBUG"
 
@@ -1152,6 +1153,14 @@ async def test_router_content_policy_fallbacks(
                     "mock_response": "This works!",
                 },
             },
+            {
+                "model_name": "my-default-fallback-model",
+                "litellm_params": {
+                    "model": "openai/my-fake-model",
+                    "api_key": "",
+                    "mock_response": "This works 2!",
+                },
+            },
             {
                 "model_name": "my-general-model",
                 "litellm_params": {
@@ -1169,9 +1178,14 @@ async def test_router_content_policy_fallbacks(
                 },
             },
         ],
-        content_policy_fallbacks=[{"claude-2": ["my-fallback-model"]}],
-        fallbacks=[{"claude-2": ["my-general-model"]}],
-        context_window_fallbacks=[{"claude-2": ["my-context-window-model"]}],
+        content_policy_fallbacks=(
+            [{"claude-2": ["my-fallback-model"]}]
+            if fallback_type == "model-specific"
+            else None
+        ),
+        default_fallbacks=(
+            ["my-default-fallback-model"] if fallback_type == "default" else None
+        ),
     )
 
     if sync_mode is True:

tests/router_unit_tests/test_router_helper_utils.py

@@ -452,11 +452,17 @@ def test_update_usage(model_list):
 
 
 @pytest.mark.parametrize(
-    "finish_reason, expected_error", [("content_filter", True), ("stop", False)]
+    "finish_reason, expected_fallback", [("content_filter", True), ("stop", False)]
 )
-def test_should_raise_content_policy_error(model_list, finish_reason, expected_error):
+@pytest.mark.parametrize("fallback_type", ["model-specific", "default"])
+def test_should_raise_content_policy_error(
+    model_list, finish_reason, expected_fallback, fallback_type
+):
     """Test if the '_should_raise_content_policy_error' function is working correctly"""
-    router = Router(model_list=model_list)
+    router = Router(
+        model_list=model_list,
+        default_fallbacks=["gpt-4o"] if fallback_type == "default" else None,
+    )
 
     assert (
         router._should_raise_content_policy_error(
@@ -472,10 +478,14 @@ def test_should_raise_content_policy_error(model_list, finish_reason, expected_e
                 usage={"total_tokens": 100},
             ),
             kwargs={
-                "content_policy_fallbacks": [{"gpt-3.5-turbo": "gpt-4o"}],
+                "content_policy_fallbacks": (
+                    [{"gpt-3.5-turbo": "gpt-4o"}]
+                    if fallback_type == "model-specific"
+                    else None
+                )
             },
         )
-        is expected_error
+        is expected_fallback
     )
 
 
@@ -1019,3 +1029,17 @@ async def test_pass_through_moderation_endpoint_factory(model_list):
     response = await router._pass_through_moderation_endpoint_factory(
         original_function=litellm.amoderation, input="this is valid good text"
     )
+
+
+@pytest.mark.parametrize(
+    "has_default_fallbacks, expected_result",
+    [(True, True), (False, False)],
+)
+def test_has_default_fallbacks(model_list, has_default_fallbacks, expected_result):
+    router = Router(
+        model_list=model_list,
+        default_fallbacks=(
+            ["my-default-fallback-model"] if has_default_fallbacks else None
+        ),
+    )
+    assert router._has_default_fallbacks() is expected_result

tests/test_team.py

@@ -362,7 +362,7 @@ async def test_team_info():
 
         try:
             await get_team_info(session=session, get_team=team_id, call_key=key)
-            pytest.fail(f"Expected call to fail")
+            pytest.fail("Expected call to fail")
         except Exception as e:
             pass