Directory Indexer

Example Use Cases

• 1

  Semantically search and retrieve information from local files and directories.

• 2

  Integrate with AI assistants to provide contextual knowledge base search.

• 3

  Organize searchable content into workspaces for focused queries.

Description

Directory Indexer allows you to index and semantically search your local files and directories by creating vector embeddings stored in a Qdrant database. It integrates with AI assistants to provide meaningful search results from your actual knowledge base, supporting various file types and workspace organization. The system supports multiple embedding providers including Ollama (free, local) and OpenAI (paid API). It is designed for easy setup with Docker or native installations and offers advanced configuration and performance optimization options.