Enables creation and querying of knowledge bases using Google's Gemini API File Search feature, allowing AI applications to upload documents and retrieve information through RAG (Retrieval-Augmented Generation).
Enables intelligent ingestion and querying of PDF, Markdown, and text files using hybrid search that combines keyword matching and semantic embeddings with citations.
Enables semantic search and question-answering over uploaded documents using vector embeddings and Google AI. Supports document organization with tags, section-aware queries, and hierarchical markdown structure preservation.
Provides advanced document search and processing capabilities through vector stores, including PDF processing, semantic search, web search integration, and file operations. Enables users to create searchable document collections and retrieve relevant information using natural language queries.