Ai Agents

What I Built Basic RAG retrieves docs and generates an answer. I wanted something smarter — a system that picks the right strategy and retries with heavier techniques when the first answer isn’t good enough. This project uses three agents: Router Agent — reads the question and checks answer quality Basic Generator Agent — fast retrieval for simple questions Advanced Generator Agent — uses heavier techniques for hard questions The system tries the fast path first. If the answer is weak, it automatically switches to advanced methods like query decomposition, HyDE, and multi-query retrieval. ...

What I Was Trying to Do I had structured data in SQLite and didn’t want to write SQL for every question. LlamaIndex let me ask things like “which city has the most people?” in plain English — it figures out the query, runs it, and returns the answer. Key capabilities include: Translating natural language into SQL queries. Converting unstructured context into structured insights. Dynamically retrieving relevant schemas or tables for complex databases. Note: Never expose full write-access databases to LLMs. Always use read-only credentials or sandboxed environments for safety. ...