(fix) unable to pass input_type parameter to Voyage AI embedding mode (#7276)

* VoyageEmbeddingConfig

* fix voyage logic to get params

* add voyage embedding transformation

* add get_provider_embedding_config

* use BaseEmbeddingConfig

* voyage clean up

* use llm http handler for embedding transformations

* test_voyage_ai_embedding_extra_params

* add voyage async

* test_voyage_ai_embedding_extra_params

* add async for llm http handler

* update BaseLLMEmbeddingTest

* test_voyage_ai_embedding_extra_params

* fix linting

* fix get_provider_embedding_config

* fix anthropic text test

* update location of base/chat/transformation

* fix import path

* fix IBMWatsonXAIConfig

litellm/__init__.py

@@ -1083,6 +1083,7 @@ from .llms.openai.openai import OpenAIConfig, MistralEmbeddingConfig
 from .llms.deepinfra.chat.transformation import DeepInfraConfig
 from litellm.llms.openai.completion.transformation import OpenAITextCompletionConfig
 from .llms.groq.chat.transformation import GroqChatConfig
+from .llms.voyage.embedding.transformation import VoyageEmbeddingConfig
 from .llms.azure_ai.chat.transformation import AzureAIStudioConfig
 from .llms.mistral.mistral_chat_transformation import MistralConfig
 from .llms.openai.chat.o1_transformation import (

litellm/litellm_core_utils/get_llm_provider_logic.py

@@ -536,14 +536,6 @@ def _get_openai_compatible_provider_info(  # noqa: PLR0915
         ) = litellm.XAIChatConfig()._get_openai_compatible_provider_info(
             api_base, api_key
         )
-    elif custom_llm_provider == "voyage":
-        # voyage is openai compatible, we just need to set this to custom_openai and have the api_base be https://api.voyageai.com/v1
-        api_base = (
-            api_base
-            or get_secret_str("VOYAGE_API_BASE")
-            or "https://api.voyageai.com/v1"
-        )  # type: ignore
-        dynamic_api_key = api_key or get_secret_str("VOYAGE_API_KEY")
     elif custom_llm_provider == "together_ai":
         api_base = (
             api_base

litellm/litellm_core_utils/get_supported_openai_params.py

@@ -34,6 +34,8 @@ def get_supported_openai_params(  # noqa: PLR0915
         return litellm.OllamaChatConfig().get_supported_openai_params(model=model)
     elif custom_llm_provider == "anthropic":
         return litellm.AnthropicConfig().get_supported_openai_params(model=model)
+    elif custom_llm_provider == "anthropic_text":
+        return litellm.AnthropicTextConfig().get_supported_openai_params(model=model)
     elif custom_llm_provider == "fireworks_ai":
         if request_type == "embeddings":
             return litellm.FireworksAIEmbeddingConfig().get_supported_openai_params(
@@ -168,10 +170,17 @@ 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":
+    elif custom_llm_provider == "watsonx_text":
+        return litellm.IBMWatsonXAIConfig().get_supported_openai_params(model=model)
+    elif (
+        custom_llm_provider == "custom_openai"
+        or custom_llm_provider == "text-completion-openai"
+    ):
         return litellm.OpenAITextCompletionConfig().get_supported_openai_params(
             model=model
         )
     elif custom_llm_provider == "predibase":
         return litellm.PredibaseConfig().get_supported_openai_params(model=model)
+    elif custom_llm_provider == "voyage":
+        return litellm.VoyageEmbeddingConfig().get_supported_openai_params(model=model)
     return None

litellm/llms/anthropic/chat/transformation.py

@@ -21,7 +21,7 @@ import litellm
 from litellm.constants import RESPONSE_FORMAT_TOOL_NAME
 from litellm.litellm_core_utils.core_helpers import map_finish_reason
 from litellm.litellm_core_utils.prompt_templates.factory import anthropic_messages_pt
-from litellm.llms.base_llm.transformation import BaseConfig, BaseLLMException
+from litellm.llms.base_llm.chat.transformation import BaseConfig, BaseLLMException
 from litellm.types.llms.anthropic import (
     AllAnthropicToolsValues,
     AnthropicComputerTool,

litellm/llms/anthropic/common_utils.py

@@ -6,7 +6,7 @@ from typing import Optional, Union
 
 import httpx
 
-from litellm.llms.base_llm.transformation import BaseLLMException
+from litellm.llms.base_llm.chat.transformation import BaseLLMException
 
 
 class AnthropicError(BaseLLMException):

litellm/llms/anthropic/completion/transformation.py

@@ -11,13 +11,16 @@ from typing import Any, AsyncIterator, Dict, Iterator, List, Optional, Union
 import httpx
 
 import litellm
+from litellm.litellm_core_utils.prompt_templates.factory import (
+    custom_prompt,
+    prompt_factory,
+)
 from litellm.llms.base_llm.base_model_iterator import BaseModelResponseIterator
-from litellm.llms.base_llm.transformation import (
+from litellm.llms.base_llm.chat.transformation import (
     BaseConfig,
     BaseLLMException,
     LiteLLMLoggingObj,
 )
-from litellm.litellm_core_utils.prompt_templates.factory import custom_prompt, prompt_factory
 from litellm.types.llms.openai import AllMessageValues
 from litellm.types.utils import (
     ChatCompletionToolCallChunk,

litellm/llms/azure/chat/gpt_transformation.py

@@ -7,7 +7,7 @@ import litellm
 from litellm.litellm_core_utils.prompt_templates.factory import (
     convert_to_azure_openai_messages,
 )
-from litellm.llms.base_llm.transformation import BaseLLMException
+from litellm.llms.base_llm.chat.transformation import BaseLLMException
 from litellm.types.utils import ModelResponse
 
 from ....exceptions import UnsupportedParamsError
@@ -18,7 +18,7 @@ from ....types.llms.openai import (
     ChatCompletionToolParam,
     ChatCompletionToolParamFunctionChunk,
 )
-from ...base_llm.transformation import BaseConfig
+from ...base_llm.chat.transformation import BaseConfig
 from ..common_utils import AzureOpenAIError
 
 if TYPE_CHECKING:

litellm/llms/azure/common_utils.py

@@ -3,7 +3,7 @@ from typing import Callable, Optional, Union
 import httpx
 
 from litellm._logging import verbose_logger
-from litellm.llms.base_llm.transformation import BaseLLMException
+from litellm.llms.base_llm.chat.transformation import BaseLLMException
 from litellm.secret_managers.main import get_secret_str
 
 

litellm/llms/base_llm/embedding/transformation.py

@@ -0,0 +1,94 @@
+import types
+from abc import ABC, abstractmethod
+from typing import (
+    TYPE_CHECKING,
+    Any,
+    AsyncIterator,
+    Callable,
+    Dict,
+    Iterator,
+    List,
+    Optional,
+    TypedDict,
+    Union,
+)
+
+import httpx
+
+from litellm.llms.base_llm.chat.transformation import BaseConfig
+from litellm.types.llms.openai import AllMessageValues
+from litellm.types.utils import EmbeddingResponse, ModelResponse
+
+if TYPE_CHECKING:
+    from litellm.litellm_core_utils.litellm_logging import Logging as _LiteLLMLoggingObj
+
+    LiteLLMLoggingObj = _LiteLLMLoggingObj
+else:
+    LiteLLMLoggingObj = Any
+
+
+class BaseEmbeddingConfig(BaseConfig, ABC):
+
+    @abstractmethod
+    def transform_embedding_request(
+        self,
+        model: str,
+        input: Union[str, List[str], List[float], List[List[float]]],
+        optional_params: dict,
+        headers: dict,
+    ) -> dict:
+        return {}
+
+    @abstractmethod
+    def transform_embedding_response(
+        self,
+        model: str,
+        raw_response: httpx.Response,
+        model_response: EmbeddingResponse,
+        logging_obj: LiteLLMLoggingObj,
+        api_key: Optional[str] = None,
+        request_data: dict = {},
+        optional_params: dict = {},
+        litellm_params: dict = {},
+    ) -> EmbeddingResponse:
+        return model_response
+
+    def get_complete_url(self, api_base: Optional[str], model: str) -> str:
+        """
+        OPTIONAL
+
+        Get the complete url for the request
+
+        Some providers need `model` in `api_base`
+        """
+        return api_base or ""
+
+    def transform_request(
+        self,
+        model: str,
+        messages: List[AllMessageValues],
+        optional_params: dict,
+        litellm_params: dict,
+        headers: dict,
+    ) -> dict:
+        raise NotImplementedError(
+            "EmbeddingConfig does not need a request transformation for chat models"
+        )
+
+    def transform_response(
+        self,
+        model: str,
+        raw_response: httpx.Response,
+        model_response: ModelResponse,
+        logging_obj: LiteLLMLoggingObj,
+        request_data: dict,
+        messages: List[AllMessageValues],
+        optional_params: dict,
+        litellm_params: dict,
+        encoding: Any,
+        api_key: Optional[str] = None,
+        json_mode: Optional[bool] = None,
+    ) -> ModelResponse:
+        raise NotImplementedError(
+            "EmbeddingConfig does not need a response transformation for chat models"
+        )

litellm/llms/clarifai/chat/transformation.py

@@ -9,7 +9,7 @@ from litellm.litellm_core_utils.prompt_templates.common_utils import (
     convert_content_list_to_str,
 )
 from litellm.llms.base_llm.base_model_iterator import FakeStreamResponseIterator
-from litellm.llms.base_llm.transformation import BaseConfig, BaseLLMException
+from litellm.llms.base_llm.chat.transformation import BaseConfig, BaseLLMException
 from litellm.types.llms.openai import AllMessageValues
 from litellm.types.utils import (
     ChatCompletionToolCallChunk,

litellm/llms/clarifai/common_utils.py

@@ -1,6 +1,6 @@
 import httpx
 
-from litellm.llms.base_llm.transformation import BaseLLMException
+from litellm.llms.base_llm.chat.transformation import BaseLLMException
 
 
 class ClarifaiError(BaseLLMException):

litellm/llms/cloudflare/chat/transformation.py

@@ -6,7 +6,7 @@ import httpx
 
 import litellm
 from litellm.llms.base_llm.base_model_iterator import BaseModelResponseIterator
-from litellm.llms.base_llm.transformation import (
+from litellm.llms.base_llm.chat.transformation import (
     BaseConfig,
     BaseLLMException,
     LiteLLMLoggingObj,

litellm/llms/cohere/chat/transformation.py

@@ -5,8 +5,8 @@ from typing import TYPE_CHECKING, Any, AsyncIterator, Iterator, List, Optional,
 import httpx
 
 import litellm
-from litellm.llms.base_llm.transformation import BaseConfig, BaseLLMException
 from litellm.litellm_core_utils.prompt_templates.factory import cohere_messages_pt_v2
+from litellm.llms.base_llm.chat.transformation import BaseConfig, BaseLLMException
 from litellm.types.llms.openai import AllMessageValues
 from litellm.types.utils import ModelResponse, Usage
 

litellm/llms/cohere/common_utils.py

@@ -1,7 +1,7 @@
 import json
 from typing import List, Optional
 
-from litellm.llms.base_llm.transformation import BaseLLMException
+from litellm.llms.base_llm.chat.transformation import BaseLLMException
 from litellm.types.llms.openai import AllMessageValues
 from litellm.types.utils import (
     ChatCompletionToolCallChunk,

litellm/llms/cohere/completion/transformation.py

@@ -6,8 +6,10 @@ from typing import TYPE_CHECKING, Any, AsyncIterator, Iterator, List, Optional,
 import httpx
 
 import litellm
-from litellm.llms.base_llm.transformation import BaseConfig, BaseLLMException
-from litellm.litellm_core_utils.prompt_templates.common_utils import convert_content_list_to_str
+from litellm.litellm_core_utils.prompt_templates.common_utils import (
+    convert_content_list_to_str,
+)
+from litellm.llms.base_llm.chat.transformation import BaseConfig, BaseLLMException
 from litellm.types.llms.openai import AllMessageValues
 from litellm.types.utils import (
     ChatCompletionToolCallChunk,

litellm/llms/custom_httpx/llm_http_handler.py

@@ -21,13 +21,15 @@ import litellm.types
 import litellm.types.utils
 from litellm import verbose_logger
 from litellm.litellm_core_utils.core_helpers import map_finish_reason
-from litellm.llms.base_llm.transformation import BaseConfig, BaseLLMException
+from litellm.llms.base_llm.chat.transformation import BaseConfig, BaseLLMException
+from litellm.llms.base_llm.embedding.transformation import BaseEmbeddingConfig
 from litellm.llms.custom_httpx.http_handler import (
     AsyncHTTPHandler,
     HTTPHandler,
     _get_httpx_client,
     get_async_httpx_client,
 )
+from litellm.types.utils import EmbeddingResponse
 from litellm.utils import CustomStreamWrapper, ModelResponse, ProviderConfigManager
 
 if TYPE_CHECKING:
@@ -403,6 +405,139 @@ class BaseLLMHTTPHandler:
 
         return completion_stream, response.headers
 
+    def embedding(
+        self,
+        model: str,
+        input: list,
+        timeout: float,
+        custom_llm_provider: str,
+        logging_obj: LiteLLMLoggingObj,
+        api_base: Optional[str],
+        optional_params: dict,
+        model_response: EmbeddingResponse,
+        api_key: Optional[str] = None,
+        client: Optional[Union[HTTPHandler, AsyncHTTPHandler]] = None,
+        aembedding: bool = False,
+        headers={},
+    ) -> EmbeddingResponse:
+
+        provider_config = ProviderConfigManager.get_provider_embedding_config(
+            model=model, provider=litellm.LlmProviders(custom_llm_provider)
+        )
+        # get config from model, custom llm provider
+        headers = provider_config.validate_environment(
+            api_key=api_key,
+            headers=headers,
+            model=model,
+            messages=[],
+            optional_params=optional_params,
+        )
+
+        api_base = provider_config.get_complete_url(
+            api_base=api_base,
+            model=model,
+        )
+
+        data = provider_config.transform_embedding_request(
+            model=model,
+            input=input,
+            optional_params=optional_params,
+            headers=headers,
+        )
+
+        ## LOGGING
+        logging_obj.pre_call(
+            input=input,
+            api_key=api_key,
+            additional_args={
+                "complete_input_dict": data,
+                "api_base": api_base,
+                "headers": headers,
+            },
+        )
+
+        if aembedding is True:
+            return self.aembedding(  # type: ignore
+                request_data=data,
+                api_base=api_base,
+                headers=headers,
+                model=model,
+                custom_llm_provider=custom_llm_provider,
+                provider_config=provider_config,
+                model_response=model_response,
+                logging_obj=logging_obj,
+                api_key=api_key,
+                timeout=timeout,
+                client=client,
+            )
+
+        if client is None or not isinstance(client, HTTPHandler):
+            sync_httpx_client = _get_httpx_client()
+        else:
+            sync_httpx_client = client
+
+        try:
+            response = sync_httpx_client.post(
+                url=api_base,
+                headers=headers,
+                data=json.dumps(data),
+                timeout=timeout,
+            )
+        except Exception as e:
+            raise self._handle_error(
+                e=e,
+                provider_config=provider_config,
+            )
+
+        return provider_config.transform_embedding_response(
+            model=model,
+            raw_response=response,
+            model_response=model_response,
+            logging_obj=logging_obj,
+            api_key=api_key,
+            request_data=data,
+        )
+
+    async def aembedding(
+        self,
+        request_data: dict,
+        api_base: str,
+        headers: dict,
+        model: str,
+        custom_llm_provider: str,
+        provider_config: BaseEmbeddingConfig,
+        model_response: EmbeddingResponse,
+        logging_obj: LiteLLMLoggingObj,
+        api_key: Optional[str] = None,
+        timeout: Optional[Union[float, httpx.Timeout]] = None,
+        client: Optional[Union[HTTPHandler, AsyncHTTPHandler]] = None,
+    ) -> EmbeddingResponse:
+        if client is None or not isinstance(client, AsyncHTTPHandler):
+            async_httpx_client = get_async_httpx_client(
+                llm_provider=litellm.LlmProviders(custom_llm_provider)
+            )
+        else:
+            async_httpx_client = client
+
+        try:
+            response = await async_httpx_client.post(
+                url=api_base,
+                headers=headers,
+                data=json.dumps(request_data),
+                timeout=timeout,
+            )
+        except Exception as e:
+            raise self._handle_error(e=e, provider_config=provider_config)
+
+        return provider_config.transform_embedding_response(
+            model=model,
+            raw_response=response,
+            model_response=model_response,
+            logging_obj=logging_obj,
+            api_key=api_key,
+            request_data=request_data,
+        )
+
     def _handle_error(self, e: Exception, provider_config: BaseConfig):
         status_code = getattr(e, "status_code", 500)
         error_headers = getattr(e, "headers", None)
@@ -421,6 +556,3 @@ class BaseLLMHTTPHandler:
             status_code=status_code,
             headers=error_headers,
         )
-
-    def embedding(self):
-        pass

litellm/llms/huggingface/chat/transformation.py

@@ -16,7 +16,7 @@ from litellm.litellm_core_utils.prompt_templates.factory import (
     prompt_factory,
 )
 from litellm.litellm_core_utils.streaming_handler import CustomStreamWrapper
-from litellm.llms.base_llm.transformation import BaseConfig, BaseLLMException
+from litellm.llms.base_llm.chat.transformation import BaseConfig, BaseLLMException
 from litellm.secret_managers.main import get_secret_str
 from litellm.types.llms.openai import AllMessageValues
 from litellm.types.utils import Choices, Message, ModelResponse, Usage

litellm/llms/huggingface/common_utils.py

@@ -2,7 +2,7 @@ from typing import Literal, Optional, Union
 
 import httpx
 
-from litellm.llms.base_llm.transformation import BaseLLMException
+from litellm.llms.base_llm.chat.transformation import BaseLLMException
 
 
 class HuggingfaceError(BaseLLMException):

litellm/llms/maritalk.py

@@ -9,7 +9,7 @@ from typing import Any, Callable, List, Optional, Union
 from httpx._models import Headers
 
 import litellm
-from litellm.llms.base_llm.transformation import BaseLLMException
+from litellm.llms.base_llm.chat.transformation import BaseLLMException
 from litellm.llms.openai.chat.gpt_transformation import OpenAIGPTConfig
 from litellm.utils import Choices, Message, ModelResponse, Usage
 

litellm/llms/nlp_cloud/chat/handler.py

@@ -8,7 +8,7 @@ from typing import Any, Callable, List, Optional, Union
 import httpx
 
 import litellm
-from litellm.llms.base_llm.transformation import BaseConfig, BaseLLMException
+from litellm.llms.base_llm.chat.transformation import BaseConfig, BaseLLMException
 from litellm.llms.custom_httpx.http_handler import (
     AsyncHTTPHandler,
     HTTPHandler,

litellm/llms/nlp_cloud/chat/transformation.py

@@ -4,8 +4,10 @@ from typing import TYPE_CHECKING, Any, List, Optional, Union
 
 import httpx
 
-from litellm.llms.base_llm.transformation import BaseConfig, BaseLLMException
-from litellm.litellm_core_utils.prompt_templates.common_utils import convert_content_list_to_str
+from litellm.litellm_core_utils.prompt_templates.common_utils import (
+    convert_content_list_to_str,
+)
+from litellm.llms.base_llm.chat.transformation import BaseConfig, BaseLLMException
 from litellm.types.llms.openai import AllMessageValues
 from litellm.utils import ModelResponse, Usage
 

litellm/llms/nlp_cloud/common_utils.py

@@ -2,7 +2,7 @@ from typing import Optional, Union
 
 import httpx
 
-from litellm.llms.base_llm.transformation import BaseLLMException
+from litellm.llms.base_llm.chat.transformation import BaseLLMException
 
 
 class NLPCloudError(BaseLLMException):

litellm/llms/ollama/common_utils.py

@@ -2,7 +2,7 @@ from typing import Union
 
 import httpx
 
-from litellm.llms.base_llm.transformation import BaseLLMException
+from litellm.llms.base_llm.chat.transformation import BaseLLMException
 
 
 class OllamaError(BaseLLMException):

litellm/llms/ollama/completion/transformation.py

@@ -13,7 +13,7 @@ from litellm.litellm_core_utils.prompt_templates.factory import (
     ollama_pt,
 )
 from litellm.llms.base_llm.base_model_iterator import BaseModelResponseIterator
-from litellm.llms.base_llm.transformation import BaseConfig, BaseLLMException
+from litellm.llms.base_llm.chat.transformation import BaseConfig, BaseLLMException
 from litellm.secret_managers.main import get_secret_str
 from litellm.types.llms.openai import (
     AllMessageValues,

litellm/llms/oobabooga/chat/transformation.py

@@ -6,7 +6,7 @@ from typing import TYPE_CHECKING, Any, List, Optional, Union
 import httpx
 
 import litellm
-from litellm.llms.base_llm.transformation import BaseConfig, BaseLLMException
+from litellm.llms.base_llm.chat.transformation import BaseConfig, BaseLLMException
 from litellm.llms.openai.chat.gpt_transformation import OpenAIGPTConfig
 from litellm.types.llms.openai import AllMessageValues
 from litellm.types.utils import Choices, Message, ModelResponse, Usage

litellm/llms/oobabooga/common_utils.py

@@ -2,7 +2,7 @@ from typing import Optional, Union
 
 import httpx
 
-from litellm.llms.base_llm.transformation import BaseLLMException
+from litellm.llms.base_llm.chat.transformation import BaseLLMException
 
 
 class OobaboogaError(BaseLLMException):

litellm/llms/openai/chat/gpt_transformation.py

@@ -8,7 +8,7 @@ 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.llms.base_llm.chat.transformation import BaseConfig, BaseLLMException
 from litellm.types.llms.openai import AllMessageValues, ChatCompletionUserMessage
 from litellm.types.utils import ModelResponse
 

litellm/llms/openai/common_utils.py

@@ -8,7 +8,7 @@ from typing import Any, Dict, List, Optional, Union
 import httpx
 import openai
 
-from litellm.llms.base_llm.transformation import BaseLLMException
+from litellm.llms.base_llm.chat.transformation import BaseLLMException
 
 
 class OpenAIError(BaseLLMException):

litellm/llms/openai/completion/transformation.py

@@ -6,7 +6,10 @@ import types
 from typing import List, Optional, Union, cast
 
 import litellm
-from litellm.llms.base_llm.transformation import BaseConfig
+from litellm.litellm_core_utils.prompt_templates.common_utils import (
+    convert_content_list_to_str,
+)
+from litellm.llms.base_llm.chat.transformation import BaseConfig
 from litellm.types.llms.openai import (
     AllMessageValues,
     AllPromptValues,
@@ -14,7 +17,6 @@ from litellm.types.llms.openai import (
 )
 from litellm.types.utils import Choices, Message, ModelResponse, TextCompletionResponse
 
-from litellm.litellm_core_utils.prompt_templates.common_utils import convert_content_list_to_str
 from ..chat.gpt_transformation import OpenAIGPTConfig
 from ..common_utils import OpenAIError
 from .utils import is_tokens_or_list_of_tokens

litellm/llms/openai/openai.py

@@ -32,7 +32,7 @@ from litellm.litellm_core_utils.prompt_templates.factory import (
     custom_prompt,
     prompt_factory,
 )
-from litellm.llms.base_llm.transformation import BaseConfig, BaseLLMException
+from litellm.llms.base_llm.chat.transformation import BaseConfig, BaseLLMException
 from litellm.llms.custom_httpx.http_handler import _DEFAULT_TTL_FOR_HTTPX_CLIENTS
 from litellm.secret_managers.main import get_secret_str
 from litellm.types.utils import (

litellm/llms/petals/common_utils.py

@@ -2,7 +2,7 @@ from typing import Union
 
 from httpx import Headers
 
-from litellm.llms.base_llm.transformation import BaseLLMException
+from litellm.llms.base_llm.chat.transformation import BaseLLMException
 
 
 class PetalsError(BaseLLMException):

litellm/llms/petals/completion/transformation.py

@@ -4,7 +4,7 @@ from typing import Any, List, Optional, Union
 from httpx import Headers, Response
 
 import litellm
-from litellm.llms.base_llm.transformation import (
+from litellm.llms.base_llm.chat.transformation import (
     BaseConfig,
     BaseLLMException,
     LiteLLMLoggingObj,

litellm/llms/predibase/chat/transformation.py

@@ -3,7 +3,7 @@ from typing import TYPE_CHECKING, Any, List, Literal, Optional, Union
 
 from httpx import Headers, Response
 
-from litellm.llms.base_llm.transformation import BaseConfig, BaseLLMException
+from litellm.llms.base_llm.chat.transformation import BaseConfig, BaseLLMException
 from litellm.types.llms.openai import AllMessageValues
 from litellm.types.utils import ModelResponse
 

litellm/llms/predibase/common_utils.py

@@ -2,7 +2,7 @@ from typing import Optional, Union
 
 import httpx
 
-from litellm.llms.base_llm.transformation import BaseLLMException
+from litellm.llms.base_llm.chat.transformation import BaseLLMException
 
 
 class PredibaseError(BaseLLMException):

litellm/llms/replicate/chat/transformation.py

@@ -4,9 +4,14 @@ from typing import TYPE_CHECKING, Any, List, Optional, Union
 import httpx
 
 import litellm
-from litellm.llms.base_llm.transformation import BaseConfig, BaseLLMException
-from litellm.litellm_core_utils.prompt_templates.common_utils import convert_content_list_to_str
-from litellm.litellm_core_utils.prompt_templates.factory import custom_prompt, prompt_factory
+from litellm.litellm_core_utils.prompt_templates.common_utils import (
+    convert_content_list_to_str,
+)
+from litellm.litellm_core_utils.prompt_templates.factory import (
+    custom_prompt,
+    prompt_factory,
+)
+from litellm.llms.base_llm.chat.transformation import BaseConfig, BaseLLMException
 from litellm.types.llms.openai import AllMessageValues
 from litellm.types.utils import Choices, Message, ModelResponse, Usage
 from litellm.utils import token_counter

litellm/llms/replicate/common_utils.py

@@ -2,7 +2,7 @@ from typing import Optional, Union
 
 import httpx
 
-from litellm.llms.base_llm.transformation import BaseLLMException
+from litellm.llms.base_llm.chat.transformation import BaseLLMException
 
 
 class ReplicateError(BaseLLMException):

litellm/llms/sagemaker/chat/transformation.py

@@ -11,7 +11,7 @@ from typing import Union
 
 from httpx._models import Headers
 
-from litellm.llms.base_llm.transformation import BaseLLMException
+from litellm.llms.base_llm.chat.transformation import BaseLLMException
 
 from ...openai.chat.gpt_transformation import OpenAIGPTConfig
 from ..common_utils import SagemakerError

litellm/llms/sagemaker/common_utils.py

@@ -4,7 +4,7 @@ from typing import AsyncIterator, Iterator, List, Optional, Union
 import httpx
 
 from litellm import verbose_logger
-from litellm.llms.base_llm.transformation import BaseLLMException
+from litellm.llms.base_llm.chat.transformation import BaseLLMException
 from litellm.types.utils import GenericStreamingChunk as GChunk
 from litellm.types.utils import StreamingChatCompletionChunk
 

litellm/llms/sagemaker/completion/transformation.py

@@ -17,7 +17,7 @@ from litellm.litellm_core_utils.prompt_templates.factory import (
     custom_prompt,
     prompt_factory,
 )
-from litellm.llms.base_llm.transformation import BaseConfig, BaseLLMException
+from litellm.llms.base_llm.chat.transformation import BaseConfig, BaseLLMException
 from litellm.types.llms.openai import AllMessageValues
 from litellm.types.utils import ModelResponse, Usage
 

litellm/llms/triton/common_utils.py

@@ -2,7 +2,7 @@ from typing import Optional, Union
 
 import httpx
 
-from litellm.llms.base_llm.transformation import BaseLLMException
+from litellm.llms.base_llm.chat.transformation import BaseLLMException
 
 
 class TritonError(BaseLLMException):

litellm/llms/triton/completion/transformation.py

@@ -7,7 +7,7 @@ from typing import Any, Dict, List, Optional, Union
 from httpx import Headers, Response
 
 from litellm.litellm_core_utils.prompt_templates.factory import prompt_factory
-from litellm.llms.base_llm.transformation import (
+from litellm.llms.base_llm.chat.transformation import (
     BaseConfig,
     BaseLLMException,
     LiteLLMLoggingObj,

litellm/llms/vertex_ai/common_utils.py

@@ -3,7 +3,7 @@ from typing import Dict, List, Literal, Optional, Tuple, Union
 import httpx
 
 from litellm import supports_response_schema, supports_system_messages, verbose_logger
-from litellm.llms.base_llm.transformation import BaseLLMException
+from litellm.llms.base_llm.chat.transformation import BaseLLMException
 from litellm.types.llms.vertex_ai import PartType
 
 

litellm/llms/vertex_ai/gemini/vertex_and_google_ai_studio_gemini.py

@@ -34,7 +34,7 @@ from litellm.litellm_core_utils.prompt_templates.factory import (
     convert_generic_image_chunk_to_openai_image_obj,
     convert_to_anthropic_image_obj,
 )
-from litellm.llms.base_llm.transformation import BaseConfig, BaseLLMException
+from litellm.llms.base_llm.chat.transformation import BaseConfig, BaseLLMException
 from litellm.llms.custom_httpx.http_handler import (
     AsyncHTTPHandler,
     HTTPHandler,

litellm/llms/voyage/embedding/transformation.py

@@ -0,0 +1,141 @@
+import json
+from typing import Any, List, Optional, Tuple, Union
+
+import httpx
+
+import litellm
+from litellm._logging import verbose_logger
+from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
+from litellm.llms.base_llm.chat.transformation import BaseLLMException
+from litellm.llms.base_llm.embedding.transformation import BaseEmbeddingConfig
+from litellm.secret_managers.main import get_secret_str
+from litellm.types.llms.openai import AllMessageValues
+from litellm.types.utils import EmbeddingResponse, ModelResponse, Usage
+
+
+class VoyageError(BaseLLMException):
+    def __init__(
+        self,
+        status_code: int,
+        message: str,
+        headers: Union[dict, httpx.Headers] = {},
+    ):
+        self.status_code = status_code
+        self.message = message
+        self.request = httpx.Request(
+            method="POST", url="https://api.voyageai.com/v1/embeddings"
+        )
+        self.response = httpx.Response(status_code=status_code, request=self.request)
+        super().__init__(
+            status_code=status_code,
+            message=message,
+            headers=headers,
+        )
+
+
+class VoyageEmbeddingConfig(BaseEmbeddingConfig):
+    """
+    Reference: https://docs.voyageai.com/reference/embeddings-api
+    """
+
+    def __init__(self) -> None:
+        pass
+
+    def get_complete_url(self, api_base: Optional[str], model: str) -> str:
+        if api_base:
+            if not api_base.endswith("/embeddings"):
+                api_base = f"{api_base}/embeddings"
+            return api_base
+        return "https://api.voyageai.com/v1/embeddings"
+
+    def get_supported_openai_params(self, model: str) -> list:
+        return [
+            "encoding_format",
+            "dimensions",
+        ]
+
+    def map_openai_params(
+        self,
+        non_default_params: dict,
+        optional_params: dict,
+        model: str,
+        drop_params: bool,
+    ) -> dict:
+        """
+        Map OpenAI params to Voyage params
+
+        Reference: https://docs.voyageai.com/reference/embeddings-api
+        """
+        if "encoding_format" in non_default_params:
+            optional_params["encoding_format"] = non_default_params["encoding_format"]
+        if "dimensions" in non_default_params:
+            optional_params["output_dimension"] = non_default_params["dimensions"]
+        return optional_params
+
+    def validate_environment(
+        self,
+        headers: dict,
+        model: str,
+        messages: List[AllMessageValues],
+        optional_params: dict,
+        api_key: Optional[str] = None,
+    ) -> dict:
+        if api_key is None:
+            api_key = (
+                get_secret_str("VOYAGE_API_KEY")
+                or get_secret_str("VOYAGE_AI_API_KEY")
+                or get_secret_str("VOYAGE_AI_TOKEN")
+            )
+        return {
+            "Authorization": f"Bearer {api_key}",
+        }
+
+    def transform_embedding_request(
+        self,
+        model: str,
+        input: Union[str, List[str], List[float], List[List[float]]],
+        optional_params: dict,
+        headers: dict,
+    ) -> dict:
+        return {
+            "input": input,
+            "model": model,
+            **optional_params,
+        }
+
+    def transform_embedding_response(
+        self,
+        model: str,
+        raw_response: httpx.Response,
+        model_response: EmbeddingResponse,
+        logging_obj: LiteLLMLoggingObj,
+        api_key: Optional[str] = None,
+        request_data: dict = {},
+        optional_params: dict = {},
+        litellm_params: dict = {},
+    ) -> EmbeddingResponse:
+        try:
+            raw_response_json = raw_response.json()
+        except Exception:
+            raise VoyageError(
+                message=raw_response.text, status_code=raw_response.status_code
+            )
+
+        # model_response.usage
+        model_response.model = raw_response_json.get("model")
+        model_response.data = raw_response_json.get("data")
+        model_response.object = raw_response_json.get("object")
+
+        usage = Usage(
+            prompt_tokens=raw_response_json.get("usage", {}).get("prompt_tokens", 0),
+            total_tokens=raw_response_json.get("usage", {}).get("total_tokens", 0),
+        )
+        model_response.usage = usage
+        return model_response
+
+    def get_error_class(
+        self, error_message: str, status_code: int, headers: Union[dict, httpx.Headers]
+    ) -> BaseLLMException:
+        return VoyageError(
+            message=error_message, status_code=status_code, headers=headers
+        )

litellm/llms/watsonx/common_utils.py

@@ -5,7 +5,7 @@ import httpx
 import litellm
 from litellm import verbose_logger
 from litellm.caching import InMemoryCache
-from litellm.llms.base_llm.transformation import BaseLLMException
+from litellm.llms.base_llm.chat.transformation import BaseLLMException
 from litellm.secret_managers.main import get_secret_str
 from litellm.types.llms.watsonx import WatsonXAPIParams
 

litellm/llms/watsonx/completion/transformation.py

@@ -24,7 +24,8 @@ from typing import (
 import httpx
 
 import litellm
-from litellm.llms.base_llm.transformation import BaseLLMException
+from litellm.litellm_core_utils.prompt_templates import factory as ptf
+from litellm.llms.base_llm.chat.transformation import BaseLLMException
 from litellm.llms.custom_httpx.http_handler import (
     AsyncHTTPHandler,
     get_async_httpx_client,
@@ -35,8 +36,7 @@ from litellm.types.llms.watsonx import WatsonXAIEndpoint
 from litellm.utils import EmbeddingResponse, ModelResponse, Usage, map_finish_reason
 
 from ...base import BaseLLM
-from ...base_llm.transformation import BaseConfig
-from litellm.litellm_core_utils.prompt_templates import factory as ptf
+from ...base_llm.chat.transformation import BaseConfig
 from ..common_utils import WatsonXAIError, _get_api_params, generate_iam_token
 
 if TYPE_CHECKING:

litellm/main.py

@@ -3058,6 +3058,7 @@ async def aembedding(*args, **kwargs) -> EmbeddingResponse:
             or custom_llm_provider == "together_ai"
             or custom_llm_provider == "openai_like"
             or custom_llm_provider == "jina_ai"
+            or custom_llm_provider == "voyage"
         ):  # currently implemented aiohttp calls for just azure and openai, soon all.
             # Await normally
             init_response = await loop.run_in_executor(None, func_with_context)
@@ -3632,10 +3633,10 @@ def embedding(  # noqa: PLR0915
                 aembedding=aembedding,
             )
         elif custom_llm_provider == "voyage":
-            api_key = api_key or litellm.api_key or get_secret_str("VOYAGE_API_KEY")
-            response = openai_chat_completions.embedding(
+            response = base_llm_http_handler.embedding(
                 model=model,
                 input=input,
+                custom_llm_provider=custom_llm_provider,
                 api_base=api_base,
                 api_key=api_key,
                 logging_obj=logging,

litellm/utils.py

@@ -168,7 +168,8 @@ from typing import (
 
 from openai import OpenAIError as OriginalError
 
-from litellm.llms.base_llm.transformation import BaseConfig
+from litellm.llms.base_llm.chat.transformation import BaseConfig
+from litellm.llms.base_llm.embedding.transformation import BaseEmbeddingConfig
 
 from ._logging import verbose_logger
 from .caching.caching import (
@@ -2377,6 +2378,21 @@ def get_optional_params_embeddings(  # noqa: PLR0915
         )
         final_params = {**optional_params, **kwargs}
         return final_params
+    elif custom_llm_provider == "voyage":
+        supported_params = get_supported_openai_params(
+            model=model,
+            custom_llm_provider="voyage",
+            request_type="embeddings",
+        )
+        _check_valid_arg(supported_params=supported_params)
+        optional_params = litellm.VoyageEmbeddingConfig().map_openai_params(
+            non_default_params=non_default_params,
+            optional_params={},
+            model=model,
+            drop_params=drop_params if drop_params is not None else False,
+        )
+        final_params = {**optional_params, **kwargs}
+        return final_params
     elif custom_llm_provider == "fireworks_ai":
         supported_params = get_supported_openai_params(
             model=model,
@@ -6200,6 +6216,15 @@ class ProviderConfigManager:
             return litellm.PetalsConfig()
         return litellm.OpenAIGPTConfig()
 
+    @staticmethod
+    def get_provider_embedding_config(
+        model: str,
+        provider: LlmProviders,
+    ) -> BaseEmbeddingConfig:
+        if litellm.LlmProviders.VOYAGE == provider:
+            return litellm.VoyageEmbeddingConfig()
+        raise ValueError(f"Provider {provider} does not support embedding config")
+
 
 def get_end_user_id_for_cost_tracking(
     litellm_params: dict,

tests/llm_translation/base_embedding_unit_tests.py

@@ -59,6 +59,10 @@ class BaseLLMEmbeddingTest(ABC):
 
             print("async embedding response: ", response)
 
+        from openai.types.create_embedding_response import CreateEmbeddingResponse
+
+        CreateEmbeddingResponse.model_validate(response.model_dump())
+
     def test_embedding_optional_params_max_retries(self):
         embedding_call_args = self.get_base_embedding_call_args()
         optional_params = get_optional_params_embeddings(

tests/llm_translation/test_voyage_ai.py

@@ -0,0 +1,56 @@
+import json
+import os
+import sys
+from datetime import datetime
+from unittest.mock import AsyncMock
+import pytest
+
+sys.path.insert(
+    0, os.path.abspath("../..")
+)  # Adds the parent directory to the system path
+
+
+from base_embedding_unit_tests import BaseLLMEmbeddingTest
+import litellm
+from litellm.llms.custom_httpx.http_handler import HTTPHandler
+from unittest.mock import patch, MagicMock
+
+
+class TestVoyageAI(BaseLLMEmbeddingTest):
+    def get_custom_llm_provider(self) -> litellm.LlmProviders:
+        return litellm.LlmProviders.VOYAGE
+
+    def get_base_embedding_call_args(self) -> dict:
+        return {
+            "model": "voyage/voyage-3-lite",
+        }
+
+
+def test_voyage_ai_embedding_extra_params():
+    try:
+
+        client = HTTPHandler()
+        litellm.set_verbose = True
+
+        with patch.object(client, "post") as mock_client:
+            response = litellm.embedding(
+                model="voyage/voyage-3-lite",
+                input=["a"],
+                dimensions=512,
+                input_type="document",
+                client=client,
+            )
+
+            mock_client.assert_called_once()
+            json_data = json.loads(mock_client.call_args.kwargs["data"])
+
+            print("request data to voyage ai", json.dumps(json_data, indent=4))
+
+            # Assert the request parameters
+            assert json_data["input"] == ["a"]
+            assert json_data["model"] == "voyage-3-lite"
+            assert json_data["output_dimension"] == 512
+            assert json_data["input_type"] == "document"
+
+    except Exception as e:
+        pytest.fail(f"Error occurred: {e}")

tests/local_testing/test_config.py

@@ -348,7 +348,7 @@ async def test_add_and_delete_deployments(llm_router, model_list_flag_value):
 
 from litellm import LITELLM_CHAT_PROVIDERS, LlmProviders
 from litellm.utils import ProviderConfigManager
-from litellm.llms.base_llm.transformation import BaseConfig
+from litellm.llms.base_llm.chat.transformation import BaseConfig
 
 
 def _check_provider_config(config: BaseConfig, provider: LlmProviders):