langchain/libs/partners/mongodb
Jib 866d6408af
mongodb[patch]: Remove embedding retrieval from mongodb payload (#19035)
## Description
Returning the embedding is not necessary in the vector search
functionality unless specified as a debugging step. This change defaults
the behavior such that the server _only_ returns the embedding key if
explicitly requested, such as in the case of
`max_marginal_relevance_search`.


- [x] **Add tests and docs**: If you're adding a new integration, please
include
* Added `test_from_documents_no_embedding_return`


- [x] **Lint and test**: Run `make format`, `make lint` and `make test`
from the root of the package(s) you've modified. See contribution
guidelines for more: https://python.langchain.com/docs/contributing/

---------

Co-authored-by: Erick Friis <erick@langchain.dev>
2024-03-18 19:43:50 +00:00
..
langchain_mongodb mongodb[patch]: Remove embedding retrieval from mongodb payload (#19035) 2024-03-18 19:43:50 +00:00
scripts
tests mongodb[patch]: Remove embedding retrieval from mongodb payload (#19035) 2024-03-18 19:43:50 +00:00
.gitignore
LICENSE
Makefile
poetry.lock mongodb[patch]: fix core dep (#18926) 2024-03-11 10:27:29 -07:00
pyproject.toml mongodb[patch]: fix core dep (#18926) 2024-03-11 10:27:29 -07:00
README.md

langchain-mongodb

Installation

pip install -U langchain-mongodb

Usage

Using MongoDBAtlasVectorSearch

from langchain_mongodb import MongoDBAtlasVectorSearch

# Pull MongoDB Atlas URI from environment variables
MONGODB_ATLAS_CLUSTER_URI = os.environ.get("MONGODB_ATLAS_CLUSTER_URI")

DB_NAME = "langchain_db"
COLLECTION_NAME = "test"
ATLAS_VECTOR_SEARCH_INDEX_NAME = "index_name"
MONGODB_COLLECTION = client[DB_NAME][COLLECITON_NAME]

# Create the vector search via `from_connection_string`
vector_search = MongoDBAtlasVectorSearch.from_connection_string(
    MONGODB_ATLAS_CLUSTER_URI,
    DB_NAME + "." + COLLECTION_NAME,
    OpenAIEmbeddings(disallowed_special=()),
    index_name=ATLAS_VECTOR_SEARCH_INDEX_NAME,
)

# Initialize MongoDB python client
client = MongoClient(MONGODB_ATLAS_CLUSTER_URI)
# Create the vector search via instantiation
vector_search_2 = MongoDBAtlasVectorSearch(
    collection=MONGODB_COLLECTION,
    embeddings=OpenAIEmbeddings(disallowed_special=()),
    index_name=ATLAS_VECTOR_SEARCH_INDEX_NAME,
)