Ai Agents on ayyzenn

Agentic RAG: My Multi-Agent Setup with Gemini and ChromaDB

Wed, 29 Oct 2025 00:00:00 +0000

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.

LlamaIndex + Text-to-SQL: What I Learned

Mon, 27 Oct 2025 00:00:00 +0000

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.