Metadata-Version: 2.4
Name: langchain-mongodb
Version: 0.1.8
Summary: An integration package connecting MongoDB and LangChain
License: MIT
License-File: LICENSE
Requires-Python: >=3.8.1,<4.0
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Programming Language :: Python :: 3.14
Requires-Dist: langchain-core (>=0.2.21,<0.3.0)
Requires-Dist: numpy (>=1,<2) ; python_version < "3.12"
Requires-Dist: numpy (>=1.26.0,<2.0.0) ; python_version >= "3.12"
Requires-Dist: pymongo (>=4.6.1,<5.0)
Project-URL: Repository, https://github.com/langchain-ai/langchain
Project-URL: Release Notes, https://github.com/langchain-ai/langchain/releases?q=tag%3A%22langchain-mongodb%3D%3D0%22&expanded=true
Project-URL: Source Code, https://github.com/langchain-ai/langchain/tree/master/libs/partners/mongodb
Description-Content-Type: text/markdown

# langchain-mongodb

# Installation
```
pip install -U langchain-mongodb
```

# Usage
- See [Getting Started with the LangChain Integration](https://www.mongodb.com/docs/atlas/atlas-vector-search/ai-integrations/langchain/#get-started-with-the-langchain-integration) for a walkthrough on using your first LangChain implementation with MongoDB Atlas.

## Using MongoDBAtlasVectorSearch
```python
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][COLLECTION_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,
)
```

