Litellm code qa common config (#7116)

* feat(base_llm): initial commit for common base config class

Addresses code qa critique andrewyng/aisuite#113 (comment)

* feat(base_llm/): add transform request/response abstract methods to base config class

---------

Co-authored-by: Krrish Dholakia <[email protected]>

litellm/__init__.py

@@ -22,6 +22,7 @@
     DEFAULT_FLUSH_INTERVAL_SECONDS,
     ROUTER_MAX_FALLBACKS,
     DEFAULT_MAX_RETRIES,
+    LITELLM_CHAT_PROVIDERS,
 )
 from litellm.types.guardrails import GuardrailItem
 from litellm.proxy._types import (
@@ -1128,10 +1129,10 @@ class LlmProviders(str, Enum):
 from .llms.bedrock.embed.cohere_transformation import BedrockCohereEmbeddingConfig
 from .llms.OpenAI.openai import (
     OpenAIConfig,
-    OpenAITextCompletionConfig,
     MistralEmbeddingConfig,
     DeepInfraConfig,
 )
+from litellm.llms.OpenAI.completion.transformation import OpenAITextCompletionConfig
 from .llms.groq.chat.transformation import GroqChatConfig
 from .llms.azure_ai.chat.transformation import AzureAIStudioConfig
 from .llms.mistral.mistral_chat_transformation import MistralConfig
@@ -1165,7 +1166,7 @@ class LlmProviders(str, Enum):
     FireworksAIEmbeddingConfig,
 )
 from .llms.jina_ai.embedding.transformation import JinaAIEmbeddingConfig
-from .llms.xai.chat.xai_transformation import XAIChatConfig
+from .llms.xai.chat.transformation import XAIChatConfig
 from .llms.volcengine import VolcEngineConfig
 from .llms.text_completion_codestral import MistralTextCompletionConfig
 from .llms.azure.azure import (

litellm/constants.py

@@ -2,3 +2,67 @@
 DEFAULT_BATCH_SIZE = 512
 DEFAULT_FLUSH_INTERVAL_SECONDS = 5
 DEFAULT_MAX_RETRIES = 2
+LITELLM_CHAT_PROVIDERS = [
+    "openai",
+    "openai_like",
+    "xai",
+    "custom_openai",
+    "text-completion-openai",
+    "cohere",
+    "cohere_chat",
+    "clarifai",
+    "anthropic",
+    "replicate",
+    "huggingface",
+    "together_ai",
+    "openrouter",
+    "vertex_ai",
+    "vertex_ai_beta",
+    "palm",
+    "gemini",
+    "ai21",
+    "baseten",
+    "azure",
+    "azure_text",
+    "azure_ai",
+    "sagemaker",
+    "sagemaker_chat",
+    "bedrock",
+    "vllm",
+    "nlp_cloud",
+    "petals",
+    "oobabooga",
+    "ollama",
+    "ollama_chat",
+    "deepinfra",
+    "perplexity",
+    "anyscale",
+    "mistral",
+    "groq",
+    "nvidia_nim",
+    "cerebras",
+    "ai21_chat",
+    "volcengine",
+    "codestral",
+    "text-completion-codestral",
+    "deepseek",
+    "sambanova",
+    "maritalk",
+    "voyage",
+    "cloudflare",
+    "xinference",
+    "fireworks_ai",
+    "friendliai",
+    "watsonx",
+    "watsonx_text",
+    "triton",
+    "predibase",
+    "databricks",
+    "empower",
+    "github",
+    "custom",
+    "litellm_proxy",
+    "hosted_vllm",
+    "lm_studio",
+    "galadriel",
+]

litellm/litellm_core_utils/get_supported_openai_params.py

@@ -255,27 +255,7 @@ def get_supported_openai_params(  # noqa: PLR0915
     elif custom_llm_provider == "watsonx":
         return litellm.IBMWatsonXChatConfig().get_supported_openai_params(model=model)
     elif custom_llm_provider == "custom_openai" or "text-completion-openai":
-        return [
-            "functions",
-            "function_call",
-            "temperature",
-            "top_p",
-            "n",
-            "stream",
-            "stream_options",
-            "stop",
-            "max_tokens",
-            "presence_penalty",
-            "frequency_penalty",
-            "logit_bias",
-            "user",
-            "response_format",
-            "seed",
-            "tools",
-            "tool_choice",
-            "max_retries",
-            "logprobs",
-            "top_logprobs",
-            "extra_headers",
-        ]
+        return litellm.OpenAITextCompletionConfig().get_supported_openai_params(
+            model=model
+        )
     return None

litellm/llms/OpenAI/chat/gpt_transformation.py

@@ -3,13 +3,26 @@
 """
 
 import types
-from typing import List, Optional, Union
+from typing import TYPE_CHECKING, Any, List, Optional, Union, cast
+
+import httpx
 
 import litellm
+from litellm.llms.base_llm.transformation import BaseConfig, BaseLLMException
 from litellm.types.llms.openai import AllMessageValues, ChatCompletionUserMessage
+from litellm.types.utils import ModelResponse
+
+from ..common_utils import OpenAIError
+
+if TYPE_CHECKING:
+    from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
+
+    LoggingClass = LiteLLMLoggingObj
+else:
+    LoggingClass = Any
 
 
-class OpenAIGPTConfig:
+class OpenAIGPTConfig(BaseConfig):
     """
     Reference: https://platform.openai.com/docs/api-reference/chat/create
 
@@ -168,3 +181,57 @@ def _transform_messages(
         self, messages: List[AllMessageValues]
     ) -> List[AllMessageValues]:
         return messages
+
+    def transform_request(
+        self,
+        model: str,
+        messages: List[AllMessageValues],
+        optional_params: dict,
+        litellm_params: dict,
+        headers: dict,
+    ) -> dict:
+        """
+        Transform the overall request to be sent to the API.
+
+        Returns:
+            dict: The transformed request. Sent as the body of the API call.
+        """
+        raise NotImplementedError
+
+    def transform_response(
+        self,
+        model: str,
+        raw_response: dict,
+        model_response: ModelResponse,
+        logging_obj: LoggingClass,
+        api_key: str,
+        request_data: dict,
+        messages: List[AllMessageValues],
+        optional_params: dict,
+        encoding: str,
+    ) -> ModelResponse:
+        """
+        Transform the response from the API.
+
+        Returns:
+            dict: The transformed response.
+        """
+        raise NotImplementedError
+
+    def get_error_class(
+        self, error_message: str, status_code: int, headers: Union[dict, httpx.Headers]
+    ) -> BaseLLMException:
+        return OpenAIError(
+            status_code=status_code,
+            message=error_message,
+            headers=cast(httpx.Headers, headers),
+        )
+
+    def validate_environment(
+        self,
+        api_key: str,
+        headers: dict,
+        model: str,
+        messages: List[AllMessageValues],
+    ) -> dict:
+        raise NotImplementedError

litellm/llms/OpenAI/common_utils.py

@@ -3,10 +3,44 @@
 """
 
 import json
-from typing import Any, Dict, List
+from typing import Any, Dict, List, Optional
 
+import httpx
 import openai
 
+from litellm.llms.base_llm.transformation import BaseLLMException
+
+
+class OpenAIError(BaseLLMException):
+    def __init__(
+        self,
+        status_code: int,
+        message: str,
+        request: Optional[httpx.Request] = None,
+        response: Optional[httpx.Response] = None,
+        headers: Optional[httpx.Headers] = None,
+    ):
+        self.status_code = status_code
+        self.message = message
+        self.headers = headers
+        if request:
+            self.request = request
+        else:
+            self.request = httpx.Request(method="POST", url="https://api.openai.com/v1")
+        if response:
+            self.response = response
+        else:
+            self.response = httpx.Response(
+                status_code=status_code, request=self.request
+            )
+        super().__init__(
+            status_code=status_code,
+            message=self.message,
+            headers=self.headers,
+            request=self.request,
+            response=self.response,
+        )
+
 
 ####### Error Handling Utils for OpenAI API #######################
 ###################################################################