mirror of
https://github.com/hwchase17/langchain
synced 2024-11-02 09:40:22 +00:00
117 lines
6.1 KiB
Python
117 lines
6.1 KiB
Python
"""**Embedding models** are wrappers around embedding models
|
|
from different APIs and services.
|
|
|
|
**Embedding models** can be LLMs or not.
|
|
|
|
**Class hierarchy:**
|
|
|
|
.. code-block::
|
|
|
|
Embeddings --> <name>Embeddings # Examples: OpenAIEmbeddings, HuggingFaceEmbeddings
|
|
"""
|
|
|
|
|
|
import importlib
|
|
import logging
|
|
from typing import Any
|
|
|
|
_module_lookup = {
|
|
"AlephAlphaAsymmetricSemanticEmbedding": "langchain_community.embeddings.aleph_alpha", # noqa: E501
|
|
"AlephAlphaSymmetricSemanticEmbedding": "langchain_community.embeddings.aleph_alpha", # noqa: E501
|
|
"AwaEmbeddings": "langchain_community.embeddings.awa",
|
|
"AzureOpenAIEmbeddings": "langchain_community.embeddings.azure_openai",
|
|
"BaichuanTextEmbeddings": "langchain_community.embeddings.baichuan",
|
|
"BedrockEmbeddings": "langchain_community.embeddings.bedrock",
|
|
"BookendEmbeddings": "langchain_community.embeddings.bookend",
|
|
"ClarifaiEmbeddings": "langchain_community.embeddings.clarifai",
|
|
"CohereEmbeddings": "langchain_community.embeddings.cohere",
|
|
"DashScopeEmbeddings": "langchain_community.embeddings.dashscope",
|
|
"DatabricksEmbeddings": "langchain_community.embeddings.databricks",
|
|
"DeepInfraEmbeddings": "langchain_community.embeddings.deepinfra",
|
|
"DeterministicFakeEmbedding": "langchain_community.embeddings.fake",
|
|
"EdenAiEmbeddings": "langchain_community.embeddings.edenai",
|
|
"ElasticsearchEmbeddings": "langchain_community.embeddings.elasticsearch",
|
|
"EmbaasEmbeddings": "langchain_community.embeddings.embaas",
|
|
"ErnieEmbeddings": "langchain_community.embeddings.ernie",
|
|
"FakeEmbeddings": "langchain_community.embeddings.fake",
|
|
"FastEmbedEmbeddings": "langchain_community.embeddings.fastembed",
|
|
"GPT4AllEmbeddings": "langchain_community.embeddings.gpt4all",
|
|
"GooglePalmEmbeddings": "langchain_community.embeddings.google_palm",
|
|
"GradientEmbeddings": "langchain_community.embeddings.gradient_ai",
|
|
"HuggingFaceBgeEmbeddings": "langchain_community.embeddings.huggingface",
|
|
"HuggingFaceEmbeddings": "langchain_community.embeddings.huggingface",
|
|
"HuggingFaceHubEmbeddings": "langchain_community.embeddings.huggingface_hub",
|
|
"HuggingFaceInferenceAPIEmbeddings": "langchain_community.embeddings.huggingface",
|
|
"HuggingFaceInstructEmbeddings": "langchain_community.embeddings.huggingface",
|
|
"InfinityEmbeddings": "langchain_community.embeddings.infinity",
|
|
"InfinityEmbeddingsLocal": "langchain_community.embeddings.infinity_local",
|
|
"JavelinAIGatewayEmbeddings": "langchain_community.embeddings.javelin_ai_gateway",
|
|
"JinaEmbeddings": "langchain_community.embeddings.jina",
|
|
"JohnSnowLabsEmbeddings": "langchain_community.embeddings.johnsnowlabs",
|
|
"LLMRailsEmbeddings": "langchain_community.embeddings.llm_rails",
|
|
"LaserEmbeddings": "langchain_community.embeddings.laser",
|
|
"LlamaCppEmbeddings": "langchain_community.embeddings.llamacpp",
|
|
"LlamafileEmbeddings": "langchain_community.embeddings.llamafile",
|
|
"LocalAIEmbeddings": "langchain_community.embeddings.localai",
|
|
"MiniMaxEmbeddings": "langchain_community.embeddings.minimax",
|
|
"MlflowAIGatewayEmbeddings": "langchain_community.embeddings.mlflow_gateway",
|
|
"MlflowCohereEmbeddings": "langchain_community.embeddings.mlflow",
|
|
"MlflowEmbeddings": "langchain_community.embeddings.mlflow",
|
|
"ModelScopeEmbeddings": "langchain_community.embeddings.modelscope_hub",
|
|
"MosaicMLInstructorEmbeddings": "langchain_community.embeddings.mosaicml",
|
|
"NLPCloudEmbeddings": "langchain_community.embeddings.nlpcloud",
|
|
"NeMoEmbeddings": "langchain_community.embeddings.nemo",
|
|
"OCIGenAIEmbeddings": "langchain_community.embeddings.oci_generative_ai",
|
|
"OctoAIEmbeddings": "langchain_community.embeddings.octoai_embeddings",
|
|
"OllamaEmbeddings": "langchain_community.embeddings.ollama",
|
|
"OpenAIEmbeddings": "langchain_community.embeddings.openai",
|
|
"QianfanEmbeddingsEndpoint": "langchain_community.embeddings.baidu_qianfan_endpoint", # noqa: E501
|
|
"QuantizedBiEncoderEmbeddings": "langchain_community.embeddings.optimum_intel",
|
|
"SagemakerEndpointEmbeddings": "langchain_community.embeddings.sagemaker_endpoint",
|
|
"SelfHostedEmbeddings": "langchain_community.embeddings.self_hosted",
|
|
"SelfHostedHuggingFaceEmbeddings": "langchain_community.embeddings.self_hosted_hugging_face", # noqa: E501
|
|
"SelfHostedHuggingFaceInstructEmbeddings": "langchain_community.embeddings.self_hosted_hugging_face", # noqa: E501
|
|
"SentenceTransformerEmbeddings": "langchain_community.embeddings.sentence_transformer", # noqa: E501
|
|
"SpacyEmbeddings": "langchain_community.embeddings.spacy_embeddings",
|
|
"SparkLLMTextEmbeddings": "langchain_community.embeddings.sparkllm",
|
|
"TensorflowHubEmbeddings": "langchain_community.embeddings.tensorflow_hub",
|
|
"VertexAIEmbeddings": "langchain_community.embeddings.vertexai",
|
|
"VolcanoEmbeddings": "langchain_community.embeddings.volcengine",
|
|
"VoyageEmbeddings": "langchain_community.embeddings.voyageai",
|
|
"XinferenceEmbeddings": "langchain_community.embeddings.xinference",
|
|
}
|
|
|
|
|
|
def __getattr__(name: str) -> Any:
|
|
if name in _module_lookup:
|
|
module = importlib.import_module(_module_lookup[name])
|
|
return getattr(module, name)
|
|
raise AttributeError(f"module {__name__} has no attribute {name}")
|
|
|
|
|
|
__all__ = list(_module_lookup.keys())
|
|
|
|
logger = logging.getLogger(__name__)
|
|
|
|
|
|
# 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)
|