ї іЛNgБЦС|≈UddlmZmZmZmZddlZddlmZddl m Z ddlmZm Z dZeed<Gd└d eeі╚ZdS) И)зAnyзDictзListзOptionalN)з Embeddings)зpre_init)з BaseModelз ConfigDictзlaser2зLASER_MULTILINGUAL_MODELcСф≈eZdZUdZdZeeed< dZe ed<e d╛і╚Zede de fd └і╚Zd eedeeefd└Zdedeefd └ZdS)зLaserEmbeddingsaпLASER Language-Agnostic SEntence Representations. LASER is a Python library developed by the Meta AI Research team and used for creating multilingual sentence embeddings for over 147 languages as of 2/25/2024 See more documentation at: * https://github.com/facebookresearch/LASER/ * https://github.com/facebookresearch/LASER/tree/main/laser_encoders * https://arxiv.org/abs/2205.12654 To use this class, you must install the `laser_encoders` Python package. `pip install laser_encoders` Example: from laser_encoders import LaserEncoderPipeline encoder = LaserEncoderPipeline(lang="eng_Latn") embeddings = encoder.encode_sentences(["Hello", "World"]) Nзlangз_encoder_pipelineзforbid)зextraзvaluesзreturncСн≈ ddlm}|═dі╚}|r ||╛і╚}n|t╛і╚}||d<n"#t$r}t dі╚|┌d}~wwxYw|S) z0Validate that laser_encoders has been installed.r)зLaserEncoderPipeliner)r)зlaserrzfCould not import 'laser_encoders' Python package. Please install it with `pip install laser_encoders`.N)зlaser_encodersrзgetrзImportError)зclsrrrзencoder_pipelineзes З`/var/www/html/ai-engine/env/lib/python3.11/site-packages/langchain_community/embeddings/laser.pyзvalidate_environmentz$LaserEmbeddings.validate_environment,s╟─П ь;п;п;п;п;п;Ю≈:▓:≤fя%т%┬DьП Xь#7п#7╦Tп#Bя#Bт#Bп п Ю#7п#7у>Vп#Wя#Wт#Wп ь*:┬Fп&я'п'ЬЕП П П щПGЯТПП ЬЬЬЬП ЬЬЬП ┬ s┌AAа A"а AаA"зtextscС^≈|j═|і╚}|═і╚S)z╨Generate embeddings for documents using LASER. Args: texts: The list of texts to embed. Returns: List of embeddings, one for each text. ╘rзencode_sentencesзtolist)зselfr з embeddingss rзembed_documentszLaserEmbeddings.embed_documents@s,─Пт+в<р<╦UяCтC┬ Юв р я"т"п"СзtextcСl≈|j═|gі╚}|═і╚dS)zіGenerate single query text embeddings using LASER. Args: text: The text to embed. Returns: Embeddings for the text. rr")r%r)зquery_embeddingss rзembed_queryzLaserEmbeddings.embed_queryNs4─П т1вBрBюDю6яJтJпьв&р&я(т(╗т+п+r()з__name__з __module__з__qualname__з__doc__rrзstrз__annotations__rrr зmodel_configrrrrзfloatr'r,╘r(rrrsЙ──────ППП$─D┬(░3▄-ппяПП"п░sп!п!я!Ю░:ьПЯТ─LПП╗$П╟4ПППЯ└XПП&#═T╗#єYП#╟4╦╦U╪т3DП#П#П#П#П,═П,╗╗U╛П,П,П,П,П,П,r(r)зtypingrrrrзnumpyзnpзlangchain_core.embeddingsrзlangchain_core.utilsrзpydanticr r rr1r2rr5r(rЗr<sеПь,п,п,п,п,п,п,п,п,п,п,п,п,Юпппь0п0п0п0п0п0ь)п)п)п)п)п)ь*п*п*п*п*п*п*п*Ю (п≤#п(п(я(ПN,ПN,ПN,ПN,ПN,░i═ЯN,ТN,ПN,ПN,ПN,r(