from_texts

This is a user-friendly interface that:

1. Embeds documents.
2. Adds the documents to a provided MongoDB Atlas Vector Search index (Lucene)

This is intended to be a quick way to get started.

See MongoDBAtlasVectorSearch for kwargs and further description.

Example:

.. code-block:: python from pymongo import MongoClient

from langchain_mongodb import MongoDBAtlasVectorSearch from langchain_openai import OpenAIEmbeddings

mongo_client = MongoClient("") collection = mongo_client["<db_name>"]["<collection_name>"] embeddings = OpenAIEmbeddings() vectorstore = MongoDBAtlasVectorSearch.from_texts( texts, embeddings, metadatas=metadatas, collection=collection )