Metadata-Version: 2.1
Name: langchain-qdrant
Version: 0.2.0
Summary: An integration package connecting Qdrant and LangChain
Home-page: https://github.com/langchain-ai/langchain
License: MIT
Requires-Python: >=3.9,<4
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
Provides-Extra: fastembed
Requires-Dist: fastembed (>=0.3.3,<0.4.0) ; (python_version >= "3.9" and python_version < "3.13") and (extra == "fastembed")
Requires-Dist: langchain-core (>=0.2.43,<0.4.0,!=0.3.0,!=0.3.1,!=0.3.2,!=0.3.3,!=0.3.4,!=0.3.5,!=0.3.6,!=0.3.7,!=0.3.8,!=0.3.9,!=0.3.10,!=0.3.11,!=0.3.12,!=0.3.13,!=0.3.14)
Requires-Dist: pydantic (>=2.7.4,<3.0.0)
Requires-Dist: qdrant-client (>=1.10.1,<2.0.0)
Project-URL: Repository, https://github.com/langchain-ai/langchain
Project-URL: Release Notes, https://github.com/langchain-ai/langchain/releases?q=tag%3A%22langchain-qdrant%3D%3D0%22&expanded=true
Project-URL: Source Code, https://github.com/langchain-ai/langchain/tree/master/libs/partners/qdrant
Description-Content-Type: text/markdown

# langchain-qdrant

This package contains the LangChain integration with [Qdrant](https://qdrant.tech/).

## Installation

```bash
pip install -U langchain-qdrant
```

## Usage

The `Qdrant` class exposes the connection to the Qdrant vector store.

```python
from langchain_qdrant import Qdrant

embeddings = ... # use a LangChain Embeddings class

vectorstore = Qdrant.from_existing_collection(
    embeddings=embeddings,
    collection_name="<COLLECTION_NAME>",
    url="http://localhost:6333",
)
```

