{"library":"langchain-qdrant","type":"library","category":null,"description":"langchain-qdrant is an integration package connecting the LangChain framework with Qdrant, a high-performance vector similarity search engine. It enables developers to easily utilize Qdrant as a vector store for various LLM-based applications, including Retrieval-Augmented Generation (RAG). The current version is 1.1.0, and as a LangChain partner package, it follows semantic versioning, with minor releases adding new features without breaking changes and frequent patch versions for bug fixes.","language":"python","status":"active","version":"1.1.0","tags":["langchain","qdrant","vector store","embeddings","vector database","RAG","AI","search"],"last_verified":"Sat May 23","install":[{"cmd":"pip install langchain-qdrant","imports":["from langchain_qdrant import QdrantVectorStore","from langchain_qdrant import Qdrant","from qdrant_client import QdrantClient"]}],"homepage":"https://docs.langchain.com/oss/python/integrations/providers/qdrant","github":"https://github.com/langchain-ai/langchain","docs":"https://reference.langchain.com/python/integrations/langchain_qdrant/","changelog":"https://github.com/langchain-ai/langchain/releases?q=%22langchain-qdrant%22","pypi":"https://pypi.org/project/langchain-qdrant/","npm":null,"openapi_spec":null,"status_page":null,"smithery":null,"compatibility":{"summary":{"python_range":"3.10–3.9","success_rate":100,"avg_install_s":10.7,"avg_import_s":5.54,"wheel_type":"wheel"},"url":"https://checklist.day/v1/registry/langchain-qdrant/compatibility"}}