6 months ago
research-and-dataEnterprise-ready vector database toolkit for building searchable knowledge bases from multiple data sources. Supports multi-project management, automatic ingestion from Confluence/JIRA/Git, intelligent file conversion (PDF/Office/images), and semantic search. Includes MCP server for seamless AI assistant integration in development environments.
Overview
What is QDrant Loader?
QDrant Loader is an enterprise-ready vector database toolkit designed for building searchable knowledge bases from various data sources, including Confluence, JIRA, and Git.
How to use QDrant Loader?
To use QDrant Loader, clone the repository, set up a virtual environment, install the necessary packages, and configure your environment variables. You can then initialize the QDrant collection and load data from your configured sources using the command line interface.
Key features of QDrant Loader?
- Supports multiple data source connectors (Git, Confluence, JIRA, etc.)
- Automatic file conversion from PDF, Office documents, and images to markdown
- Intelligent document processing and chunking
- Vector embeddings with OpenAI integration
- Real-time query processing and semantic search capabilities
Use cases of QDrant Loader?
- Building a searchable knowledge base for technical documentation.
- Integrating with AI assistants for enhanced data retrieval.
- Automating the ingestion of data from various project management tools.
FAQ from QDrant Loader?
- Is QDrant Loader suitable for enterprise use?
Yes, it is designed to be enterprise-ready with support for multiple projects and data sources.
- Can I integrate it with existing tools?
Yes, it supports integration with tools like Confluence, JIRA, and Git.
- What types of files can be processed?
It can process PDF, Office documents, images, and more.