Chat With Your Documents Using Garudust Agent — No Vector Database Required
Garudust Agent allows users to interact with documents without the need for a vector database. It uses SQLite FTS5 for text extraction and indexing, enabling quick question-and-answer capabilities. The setup is straightforward, requiring minimal configuration to start ingesting various document types.
- ▪Garudust Agent simplifies the process of querying documents by eliminating the need for a vector database.
- ▪It supports multiple document formats including PDF, TXT, CSV, Markdown, and JSON.
- ▪The agent automatically indexes and searches documents using a trigram tokenizer for efficient retrieval.
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try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 408531) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } Garudust Posted on May 21 Chat With Your Documents Using Garudust Agent — No Vector Database Required #rust #ai #rag #llm Most RAG tutorials start the same way: "First, install a vector database…" Then come the embedding models, the chunking strategies, the similarity thresholds. By the time you can ask a question about a PDF, you've deployed three services and written 200 lines of boilerplate. Garudust Agent takes a different path.
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