document_transformers.doctran_text_qa.DoctranQATransformer([...])
Extract QA from text documents using doctran.
document_transformers.doctran_text_translate.DoctranTextTranslator([...])
Translate text documents using doctran.
document_transformers.embeddings_redundant_filter.EmbeddingsClusteringFilter
Perform K-means clustering on document vectors.
document_transformers.embeddings_redundant_filter.EmbeddingsRedundantFilter
Filter that drops redundant documents by comparing their embeddings.
document_transformers.google_translate.GoogleTranslateTransformer(...)
Translate text documents using Google Cloud Translation.
document_transformers.html2text.Html2TextTransformer([...])
Replace occurrences of a particular search pattern with a replacement string
document_transformers.long_context_reorder.LongContextReorder
Lost in the middle: Performance degrades when models must access relevant information in the middle of long contexts.
document_transformers.nuclia_text_transform.NucliaTextTransformer(nua)
The Nuclia Understanding API splits into paragraphs and sentences, identifies entities, provides a summary of the text and generates embeddings for all sentences.
document_transformers.openai_functions.OpenAIMetadataTagger
Extract metadata tags from document contents using OpenAI functions.
Functions¶
document_transformers.beautiful_soup_transformer.get_navigable_strings(element)
document_transformers.embeddings_redundant_filter.get_stateful_documents(...)
Convert a list of documents to a list of documents with state.
document_transformers.openai_functions.create_metadata_tagger(...)
Create a DocumentTransformer that uses an OpenAI function chain to automatically
langchain_community.embeddings¶
Embedding models  are wrappers around embedding models
from different APIs and services.
Embedding models can be LLMs or not.
Class hierarchy:
Embeddings --> <name>Embeddings  # Examples: OpenAIEmbeddings, HuggingFaceEmbeddings
Classes¶