mirror of
https://github.com/hwchase17/langchain
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b7c71e2e07
* **Description:** adds `LlamafileEmbeddings` class implementation for generating embeddings using [llamafile](https://github.com/Mozilla-Ocho/llamafile)-based models. Includes related unit tests and notebook showing example usage. * **Issue:** N/A * **Dependencies:** N/A
186 lines
7.3 KiB
Python
186 lines
7.3 KiB
Python
"""**Embedding models** are wrappers around embedding models
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from different APIs and services.
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**Embedding models** can be LLMs or not.
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**Class hierarchy:**
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.. code-block::
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Embeddings --> <name>Embeddings # Examples: OpenAIEmbeddings, HuggingFaceEmbeddings
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"""
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import logging
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from typing import Any
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from langchain_community.embeddings.aleph_alpha import (
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AlephAlphaAsymmetricSemanticEmbedding,
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AlephAlphaSymmetricSemanticEmbedding,
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)
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from langchain_community.embeddings.awa import AwaEmbeddings
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from langchain_community.embeddings.azure_openai import AzureOpenAIEmbeddings
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from langchain_community.embeddings.baichuan import BaichuanTextEmbeddings
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from langchain_community.embeddings.baidu_qianfan_endpoint import (
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QianfanEmbeddingsEndpoint,
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)
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from langchain_community.embeddings.bedrock import BedrockEmbeddings
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from langchain_community.embeddings.bookend import BookendEmbeddings
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from langchain_community.embeddings.clarifai import ClarifaiEmbeddings
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from langchain_community.embeddings.cohere import CohereEmbeddings
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from langchain_community.embeddings.dashscope import DashScopeEmbeddings
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from langchain_community.embeddings.databricks import DatabricksEmbeddings
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from langchain_community.embeddings.deepinfra import DeepInfraEmbeddings
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from langchain_community.embeddings.edenai import EdenAiEmbeddings
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from langchain_community.embeddings.elasticsearch import ElasticsearchEmbeddings
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from langchain_community.embeddings.embaas import EmbaasEmbeddings
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from langchain_community.embeddings.ernie import ErnieEmbeddings
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from langchain_community.embeddings.fake import (
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DeterministicFakeEmbedding,
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FakeEmbeddings,
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)
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from langchain_community.embeddings.fastembed import FastEmbedEmbeddings
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from langchain_community.embeddings.google_palm import GooglePalmEmbeddings
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from langchain_community.embeddings.gpt4all import GPT4AllEmbeddings
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from langchain_community.embeddings.gradient_ai import GradientEmbeddings
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from langchain_community.embeddings.huggingface import (
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HuggingFaceBgeEmbeddings,
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HuggingFaceEmbeddings,
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HuggingFaceInferenceAPIEmbeddings,
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HuggingFaceInstructEmbeddings,
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)
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from langchain_community.embeddings.huggingface_hub import HuggingFaceHubEmbeddings
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from langchain_community.embeddings.infinity import InfinityEmbeddings
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from langchain_community.embeddings.infinity_local import InfinityEmbeddingsLocal
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from langchain_community.embeddings.javelin_ai_gateway import JavelinAIGatewayEmbeddings
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from langchain_community.embeddings.jina import JinaEmbeddings
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from langchain_community.embeddings.johnsnowlabs import JohnSnowLabsEmbeddings
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from langchain_community.embeddings.laser import LaserEmbeddings
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from langchain_community.embeddings.llamacpp import LlamaCppEmbeddings
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from langchain_community.embeddings.llamafile import LlamafileEmbeddings
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from langchain_community.embeddings.llm_rails import LLMRailsEmbeddings
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from langchain_community.embeddings.localai import LocalAIEmbeddings
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from langchain_community.embeddings.minimax import MiniMaxEmbeddings
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from langchain_community.embeddings.mlflow import (
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MlflowCohereEmbeddings,
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MlflowEmbeddings,
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)
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from langchain_community.embeddings.mlflow_gateway import MlflowAIGatewayEmbeddings
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from langchain_community.embeddings.modelscope_hub import ModelScopeEmbeddings
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from langchain_community.embeddings.mosaicml import MosaicMLInstructorEmbeddings
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from langchain_community.embeddings.nemo import NeMoEmbeddings
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from langchain_community.embeddings.nlpcloud import NLPCloudEmbeddings
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from langchain_community.embeddings.oci_generative_ai import OCIGenAIEmbeddings
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from langchain_community.embeddings.octoai_embeddings import OctoAIEmbeddings
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from langchain_community.embeddings.ollama import OllamaEmbeddings
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from langchain_community.embeddings.openai import OpenAIEmbeddings
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from langchain_community.embeddings.optimum_intel import QuantizedBiEncoderEmbeddings
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from langchain_community.embeddings.sagemaker_endpoint import (
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SagemakerEndpointEmbeddings,
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)
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from langchain_community.embeddings.self_hosted import SelfHostedEmbeddings
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from langchain_community.embeddings.self_hosted_hugging_face import (
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SelfHostedHuggingFaceEmbeddings,
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SelfHostedHuggingFaceInstructEmbeddings,
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)
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from langchain_community.embeddings.sentence_transformer import (
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SentenceTransformerEmbeddings,
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)
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from langchain_community.embeddings.spacy_embeddings import SpacyEmbeddings
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from langchain_community.embeddings.sparkllm import SparkLLMTextEmbeddings
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from langchain_community.embeddings.tensorflow_hub import TensorflowHubEmbeddings
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from langchain_community.embeddings.vertexai import VertexAIEmbeddings
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from langchain_community.embeddings.volcengine import VolcanoEmbeddings
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from langchain_community.embeddings.voyageai import VoyageEmbeddings
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from langchain_community.embeddings.xinference import XinferenceEmbeddings
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logger = logging.getLogger(__name__)
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__all__ = [
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"OpenAIEmbeddings",
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"AzureOpenAIEmbeddings",
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"BaichuanTextEmbeddings",
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"ClarifaiEmbeddings",
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"CohereEmbeddings",
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"DatabricksEmbeddings",
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"ElasticsearchEmbeddings",
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"FastEmbedEmbeddings",
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"HuggingFaceEmbeddings",
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"HuggingFaceInferenceAPIEmbeddings",
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"InfinityEmbeddings",
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"InfinityEmbeddingsLocal",
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"GradientEmbeddings",
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"JinaEmbeddings",
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"LaserEmbeddings",
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"LlamaCppEmbeddings",
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"LlamafileEmbeddings",
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"LLMRailsEmbeddings",
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"HuggingFaceHubEmbeddings",
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"MlflowEmbeddings",
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"MlflowCohereEmbeddings",
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"MlflowAIGatewayEmbeddings",
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"ModelScopeEmbeddings",
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"TensorflowHubEmbeddings",
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"SagemakerEndpointEmbeddings",
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"HuggingFaceInstructEmbeddings",
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"MosaicMLInstructorEmbeddings",
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"SelfHostedEmbeddings",
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"SelfHostedHuggingFaceEmbeddings",
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"SelfHostedHuggingFaceInstructEmbeddings",
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"FakeEmbeddings",
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"DeterministicFakeEmbedding",
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"AlephAlphaAsymmetricSemanticEmbedding",
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"AlephAlphaSymmetricSemanticEmbedding",
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"SentenceTransformerEmbeddings",
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"GooglePalmEmbeddings",
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"MiniMaxEmbeddings",
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"VertexAIEmbeddings",
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"BedrockEmbeddings",
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"DeepInfraEmbeddings",
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"EdenAiEmbeddings",
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"DashScopeEmbeddings",
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"EmbaasEmbeddings",
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"OctoAIEmbeddings",
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"SpacyEmbeddings",
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"NLPCloudEmbeddings",
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"GPT4AllEmbeddings",
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"XinferenceEmbeddings",
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"LocalAIEmbeddings",
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"AwaEmbeddings",
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"HuggingFaceBgeEmbeddings",
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"ErnieEmbeddings",
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"JavelinAIGatewayEmbeddings",
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"OllamaEmbeddings",
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"QianfanEmbeddingsEndpoint",
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"JohnSnowLabsEmbeddings",
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"VoyageEmbeddings",
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"BookendEmbeddings",
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"VolcanoEmbeddings",
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"OCIGenAIEmbeddings",
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"QuantizedBiEncoderEmbeddings",
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"NeMoEmbeddings",
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"SparkLLMTextEmbeddings",
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]
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# TODO: this is in here to maintain backwards compatibility
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class HypotheticalDocumentEmbedder:
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def __init__(self, *args: Any, **kwargs: Any):
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logger.warning(
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"Using a deprecated class. Please use "
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"`from langchain.chains import HypotheticalDocumentEmbedder` instead"
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)
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from langchain.chains.hyde.base import HypotheticalDocumentEmbedder as H
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return H(*args, **kwargs) # type: ignore
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@classmethod
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def from_llm(cls, *args: Any, **kwargs: Any) -> Any:
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logger.warning(
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"Using a deprecated class. Please use "
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"`from langchain.chains import HypotheticalDocumentEmbedder` instead"
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)
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from langchain.chains.hyde.base import HypotheticalDocumentEmbedder as H
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return H.from_llm(*args, **kwargs)
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