"""**Embedding models** are wrappers around embedding models from different APIs and services. **Embedding models** can be LLMs or not. **Class hierarchy:** .. code-block:: Embeddings --> Embeddings # Examples: OpenAIEmbeddings, HuggingFaceEmbeddings """ import logging from typing import Any from langchain_community.embeddings.aleph_alpha import ( AlephAlphaAsymmetricSemanticEmbedding, AlephAlphaSymmetricSemanticEmbedding, ) from langchain_community.embeddings.awa import AwaEmbeddings from langchain_community.embeddings.azure_openai import AzureOpenAIEmbeddings from langchain_community.embeddings.baichuan import BaichuanTextEmbeddings from langchain_community.embeddings.baidu_qianfan_endpoint import ( QianfanEmbeddingsEndpoint, ) from langchain_community.embeddings.bedrock import BedrockEmbeddings from langchain_community.embeddings.bookend import BookendEmbeddings from langchain_community.embeddings.clarifai import ClarifaiEmbeddings from langchain_community.embeddings.cohere import CohereEmbeddings from langchain_community.embeddings.dashscope import DashScopeEmbeddings from langchain_community.embeddings.databricks import DatabricksEmbeddings from langchain_community.embeddings.deepinfra import DeepInfraEmbeddings from langchain_community.embeddings.edenai import EdenAiEmbeddings from langchain_community.embeddings.elasticsearch import ElasticsearchEmbeddings from langchain_community.embeddings.embaas import EmbaasEmbeddings from langchain_community.embeddings.ernie import ErnieEmbeddings from langchain_community.embeddings.fake import ( DeterministicFakeEmbedding, FakeEmbeddings, ) from langchain_community.embeddings.fastembed import FastEmbedEmbeddings from langchain_community.embeddings.google_palm import GooglePalmEmbeddings from langchain_community.embeddings.gpt4all import GPT4AllEmbeddings from langchain_community.embeddings.gradient_ai import GradientEmbeddings from langchain_community.embeddings.huggingface import ( HuggingFaceBgeEmbeddings, HuggingFaceEmbeddings, HuggingFaceInferenceAPIEmbeddings, HuggingFaceInstructEmbeddings, ) from langchain_community.embeddings.huggingface_hub import HuggingFaceHubEmbeddings from langchain_community.embeddings.infinity import InfinityEmbeddings from langchain_community.embeddings.javelin_ai_gateway import JavelinAIGatewayEmbeddings from langchain_community.embeddings.jina import JinaEmbeddings from langchain_community.embeddings.johnsnowlabs import JohnSnowLabsEmbeddings from langchain_community.embeddings.llamacpp import LlamaCppEmbeddings from langchain_community.embeddings.llm_rails import LLMRailsEmbeddings from langchain_community.embeddings.localai import LocalAIEmbeddings from langchain_community.embeddings.minimax import MiniMaxEmbeddings from langchain_community.embeddings.mlflow import ( MlflowCohereEmbeddings, MlflowEmbeddings, ) from langchain_community.embeddings.mlflow_gateway import MlflowAIGatewayEmbeddings from langchain_community.embeddings.modelscope_hub import ModelScopeEmbeddings from langchain_community.embeddings.mosaicml import MosaicMLInstructorEmbeddings from langchain_community.embeddings.nlpcloud import NLPCloudEmbeddings from langchain_community.embeddings.oci_generative_ai import OCIGenAIEmbeddings from langchain_community.embeddings.octoai_embeddings import OctoAIEmbeddings from langchain_community.embeddings.ollama import OllamaEmbeddings from langchain_community.embeddings.openai import OpenAIEmbeddings from langchain_community.embeddings.sagemaker_endpoint import ( SagemakerEndpointEmbeddings, ) from langchain_community.embeddings.self_hosted import SelfHostedEmbeddings from langchain_community.embeddings.self_hosted_hugging_face import ( SelfHostedHuggingFaceEmbeddings, SelfHostedHuggingFaceInstructEmbeddings, ) from langchain_community.embeddings.sentence_transformer import ( SentenceTransformerEmbeddings, ) from langchain_community.embeddings.spacy_embeddings import SpacyEmbeddings from langchain_community.embeddings.tensorflow_hub import TensorflowHubEmbeddings from langchain_community.embeddings.vertexai import VertexAIEmbeddings from langchain_community.embeddings.volcengine import VolcanoEmbeddings from langchain_community.embeddings.voyageai import VoyageEmbeddings from langchain_community.embeddings.xinference import XinferenceEmbeddings logger = logging.getLogger(__name__) __all__ = [ "OpenAIEmbeddings", "AzureOpenAIEmbeddings", "BaichuanTextEmbeddings", "ClarifaiEmbeddings", "CohereEmbeddings", "DatabricksEmbeddings", "ElasticsearchEmbeddings", "FastEmbedEmbeddings", "HuggingFaceEmbeddings", "HuggingFaceInferenceAPIEmbeddings", "InfinityEmbeddings", "GradientEmbeddings", "JinaEmbeddings", "LlamaCppEmbeddings", "LLMRailsEmbeddings", "HuggingFaceHubEmbeddings", "MlflowEmbeddings", "MlflowCohereEmbeddings", "MlflowAIGatewayEmbeddings", "ModelScopeEmbeddings", "TensorflowHubEmbeddings", "SagemakerEndpointEmbeddings", "HuggingFaceInstructEmbeddings", "MosaicMLInstructorEmbeddings", "SelfHostedEmbeddings", "SelfHostedHuggingFaceEmbeddings", "SelfHostedHuggingFaceInstructEmbeddings", "FakeEmbeddings", "DeterministicFakeEmbedding", "AlephAlphaAsymmetricSemanticEmbedding", "AlephAlphaSymmetricSemanticEmbedding", "SentenceTransformerEmbeddings", "GooglePalmEmbeddings", "MiniMaxEmbeddings", "VertexAIEmbeddings", "BedrockEmbeddings", "DeepInfraEmbeddings", "EdenAiEmbeddings", "DashScopeEmbeddings", "EmbaasEmbeddings", "OctoAIEmbeddings", "SpacyEmbeddings", "NLPCloudEmbeddings", "GPT4AllEmbeddings", "XinferenceEmbeddings", "LocalAIEmbeddings", "AwaEmbeddings", "HuggingFaceBgeEmbeddings", "ErnieEmbeddings", "JavelinAIGatewayEmbeddings", "OllamaEmbeddings", "QianfanEmbeddingsEndpoint", "JohnSnowLabsEmbeddings", "VoyageEmbeddings", "BookendEmbeddings", "VolcanoEmbeddings", "OCIGenAIEmbeddings", ] # TODO: this is in here to maintain backwards compatibility class HypotheticalDocumentEmbedder: def __init__(self, *args: Any, **kwargs: Any): logger.warning( "Using a deprecated class. Please use " "`from langchain.chains import HypotheticalDocumentEmbedder` instead" ) from langchain.chains.hyde.base import HypotheticalDocumentEmbedder as H return H(*args, **kwargs) # type: ignore @classmethod def from_llm(cls, *args: Any, **kwargs: Any) -> Any: logger.warning( "Using a deprecated class. Please use " "`from langchain.chains import HypotheticalDocumentEmbedder` instead" ) from langchain.chains.hyde.base import HypotheticalDocumentEmbedder as H return H.from_llm(*args, **kwargs)