Metadata-Version: 2.1
Name: gega-promptflow-vectordb
Version: 0.0.1
Summary: Prompt flow tools for accessing popular vector databases
Author: Microsoft Corporation
Author-email: aethercn@microsoft.com
Classifier: Programming Language :: Python :: 3
Classifier: License :: Other/Proprietary License
Description-Content-Type: text/markdown
Requires-Dist: psutil
Requires-Dist: faiss.cpu >=1.7.3
Requires-Dist: numpy >=1.24.1
Requires-Dist: pandas >=1.5.3
Requires-Dist: langchain >=0.0.123
Requires-Dist: openai >=0.27.0
Requires-Dist: flask >=2.2.3
Requires-Dist: requests >=2.28.1
Provides-Extra: azure
Requires-Dist: azure.identity >=1.12.0 ; extra == 'azure'
Requires-Dist: azure.keyvault >=4.2.0 ; extra == 'azure'
Requires-Dist: azure.storage.blob >=12.13.0 ; extra == 'azure'
Requires-Dist: azure.core >=1.26.3 ; extra == 'azure'
Requires-Dist: azure.ai.ml >=1.5.0 ; extra == 'azure'
Requires-Dist: azureml.rag >=0.2.18 ; extra == 'azure'
Requires-Dist: opencensus.ext.azure >=1.1.9 ; extra == 'azure'

# Introduction

To store and search over unstructured data, a widely adopted approach is embedding data into vectors, stored and indexed in vector databases. The promptflow-vectordb SDK is designed for PromptFlow, provides essential tools for vector similarity search within popular vector databases, including  FAISS, Qdrant, Azure Congnitive Search, and more.
