langchain/libs/partners/mongodb
2024-07-29 09:54:01 -07:00
..
langchain_mongodb mongodb: bson optional import (#24685) 2024-07-29 09:54:01 -07:00
scripts
tests partners/mongodb : Significant MongoDBVectorSearch ID enhancements (#23535) 2024-07-17 13:26:20 -07:00
.gitignore mongodb[minor]: MongoDB Partner Package -- Porting MongoDBAtlasVectorSearch (#17652) 2024-02-29 23:09:48 +00:00
LICENSE mongodb[minor]: MongoDB Partner Package -- Porting MongoDBAtlasVectorSearch (#17652) 2024-02-29 23:09:48 +00:00
Makefile infra: update mypy 1.10, ruff 0.5 (#23721) 2024-07-03 10:33:27 -07:00
poetry.lock mongodb: release 0.1.7 (#24409) 2024-07-18 18:13:27 +00:00
pyproject.toml all: add release notes to pypi (#24519) 2024-07-22 13:59:13 -07:00
README.md docs: Update mongodb README.md (#24412) 2024-07-18 14:02:34 -07:00

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,
)