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This project aims to build a cloud app which is based on LLM and the vector store is qdrant

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App Boilerplate with GUI for Qdrant Managed Cloud Service

This repository contains an app boilerplate with a graphical user interface (GUI) that connects to a remote database hosted in Qdrant's Managed Cloud Service. The purpose of this boilerplate is to provide a starting point for building applications that interact with a Qdrant vector database.

Features

  • Graphical user interface (GUI) for easy interaction with the Qdrant vector database.
  • Seamless integration with Qdrant's Managed Cloud Service.
  • Simple setup process by cloning the repository and adding your credentials to the .env file.
  • Comes with a comprehensive set of requirements specified in the requirements.txt file.

Prerequisites

Before using this app boilerplate, make sure you have the following:

  • Python installed on your system.
  • An active Qdrant Managed Cloud Service account.
  • Your Qdrant Managed Cloud Service credentials.

Configuration

To configure the app boilerplate to work with your Qdrant Managed Cloud Service account, you need to add your credentials to the .env file. Follow these steps:

  1. Copy the .env.example file and rename it to .env:
cp .env.example .env
  1. Open the .env file in a text editor and provide your Qdrant Managed Cloud Service and OpenAI credentials:
OPENAI_API_KEY=

QDRANT_HOST=
QDRANT_API_KEY=
QDRANT_COLLECTION_NAME=

Usage

Once you have completed the installation and configuration steps, you can run the app boilerplate using the following command:

streamlit run app.py

This command will start the application.

image

License

The code in this repository is available under the MIT License. Feel free to modify and use it for your own projects.

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This project aims to build a cloud app which is based on LLM and the vector store is qdrant

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