MongoDB is a NoSQL , document-oriented database that supports JSON-like documents with a dynamic schema.

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Overview

The MongoDB Document Loader returns a list of Langchain Documents from a MongoDB database. The Loader requires the following parameters:
  • MongoDB connection string
  • MongoDB database name
  • MongoDB collection name
  • (Optional) Content Filter dictionary
  • (Optional) List of field names to include in the output
The output takes the following format:
  • pageContent= Mongo Document
  • metadata={‘database’: ‘[database_name]’, ‘collection’: ‘[collection_name]‘}

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Load the Document Loader

# add this import for running in jupyter notebook
import nest_asyncio

nest_asyncio.apply()

from langchain_community.document_loaders.mongodb import MongodbLoader

loader = MongodbLoader(
    connection_string="mongodb://localhost:27017/",
    db_name="sample_restaurants",
    collection_name="restaurants",
    filter_criteria={"borough": "Bronx", "cuisine": "Bakery"},
    field_names=["name", "address"],
)

docs = loader.load()

len(docs)

71

docs[0]

Document(page_content="Morris Park Bake Shop {'building': '1007', 'coord': [-73.856077, 40.848447], 'street': 'Morris Park Ave', 'zipcode': '10462'}", metadata={'database': 'sample_restaurants', 'collection': 'restaurants'})