Tool Calling

Prerequisite: Familiarity with the concepts introduced in Part 3 — Qdrant Hybrid Search. Review it first if the terminology in this part is unfamiliar. In Part 3: Qdrant Hybrid Search - Solving Semantic and Hard Filters, we successfully built a powerful Hybrid search engine combining Dense Semantic and Sparse Lexical Search. However, a practical e-commerce search system goes far beyond merely retrieving static documents from a vector database. For example, a user asks: “I want to buy a 400L Samsung Inverter refrigerator available at the District 1 branch that has an active promotion.” If we rely solely on a Vector Database, we face two critical errors: ...

Prerequisite: Familiarity with the concepts introduced in Part 5 — Enterprise Security Data Poisoning. Review it first if the terminology in this part is unfamiliar. Part 6 — From Passive RAG to Autonomous Agents: ReAct, Router & Tool Use Answer-first: Passive RAG systems are constrained to single-shot document retrieval, leaving complex multi-step reasoning unaddressed. Autonomous AI Agents leverage the Reasoning + Acting (ReAct) paradigm, dynamic query routers, and schema-validated tool invocation to decompose complex enterprise goals into iterative execution loops with 89% task completion accuracy. ...