An integration package connecting Qdrant and LangChain
Project description
langchain-qdrant
This package contains the LangChain integration with Qdrant.
Installation
pip install -U langchain-qdrant
Usage
The Qdrant
class exposes the connection to the Qdrant vector store.
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",
)
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
langchain_qdrant-0.1.0.tar.gz
(13.7 kB
view details)
Built Distribution
File details
Details for the file langchain_qdrant-0.1.0.tar.gz
.
File metadata
- Download URL: langchain_qdrant-0.1.0.tar.gz
- Upload date:
- Size: 13.7 kB
- Tags: Source
- Uploaded using Trusted Publishing? Yes
- Uploaded via: twine/5.0.0 CPython/3.12.3
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 8f49c08b0e5e648ba3bb685914d50a2805ba2bff96922b2f3e6c51311284d3b0 |
|
MD5 | 45b48e09eaf4b2f5b310ffae4a032891 |
|
BLAKE2b-256 | 4a841e038b354deeebd5a0f7df7376db86842264d85e1913954fec134f2c4aa1 |
File details
Details for the file langchain_qdrant-0.1.0-py3-none-any.whl
.
File metadata
- Download URL: langchain_qdrant-0.1.0-py3-none-any.whl
- Upload date:
- Size: 14.0 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? Yes
- Uploaded via: twine/5.0.0 CPython/3.12.3
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 3e4213425a806745409ad6705841fde948024699b44ff584ad58f95e82858116 |
|
MD5 | 3bde48216e64c3d3f3b91332321360e3 |
|
BLAKE2b-256 | 2c9f48eb8025dac49410c34d29b7727803098e3415568965fa26e64db74e29b7 |