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Zeus’s knowledge base system implements Agentic RAG (Retrieval-Augmented Generation), enabling the Agent to proactively retrieve relevant information from user-uploaded documents. Unlike traditional RAG, Zeus’s knowledge base is a specialized tool for the Agent — the Agent autonomously decides when to invoke retrieval, supports multi-turn queries and result verification, and works in concert with other tools (code execution, web search, etc.).

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Core Architecture

The system uses a dual-path recall strategy combining vector semantic search + BM25 keyword matching, with results merged and ranked via RRF (Reciprocal Rank Fusion) for optimal results.

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Technology Stack

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Data Flow Overview

Document Processing

Multi-format upload, SmartChunker intelligent chunking, processing pipeline

Vector Store

pgvector storage, user-level embedding configuration

Retrieval Strategy

Dual-path recall, RRF fusion, BM25 3-tier cache

API Reference

Knowledge base / document management APIs, Agent tools