2025-05-12 Calibrate Conference
Agentic workflows and RAG with LlamaIndex
What are we talking about?
- What is LlamaIndex
- What is an agent?
- Why build agents?
- What is RAG?
- Why agents need RAG
- Agent Patterns in LlamaIndex
- Chaining
- Routing
- Parallelization
- Orchestrator-Workers
- Evaluator-Optimizer
- Demo!
What is LlamaIndex?
Python: docs.llamaindex.ai
TypeScript: ts.llamaindex.ai
LlamaParse
World's best parser of complex documents
Free for 10000 pages/month!
cloud.llamaindex.ai
LlamaCloud
Turn-key RAG API for Enterprises
Available as SaaS or private cloud deployment
Sign up at cloud.llamaindex.ai
LlamaHub
Why LlamaIndex?
- Build faster
- Skip the boilerplate
- Avoid early pitfalls
- Get best practices for free
- Go from prototype to production
What can you build in LlamaIndex?
- Lots of stuff! Especially...
- AI agents
- RAG
What is an agent?
Semi-autonomous software
that uses tools to accomplish a goal
Agentic programming is a new paradigm
When does an agent make sense?
When your data is messy, which is most of the time
LLMs are good at turning lots of text into less text
LLMs work well under the hood
You don't have to build a chatbot
LLMs need data
The solution is RAG
RAG = infinite context
Agents need RAG
and RAG needs agents
Building Effective Agents
- Chaining
- Routing
- Parallelization
- Orchestrator-Workers
- Evaluator-Optimizer
Chaining
Routing
Parallelization
Sectioning
Parallelization: flavor 1
Voting
Parallelization: flavor 2
Orchestrator-Workers
Evaluator-Optimizer
aka Self-reflection
Arbitrary complexity
Workbook time!
What's next?
Thanks!
Follow me on BlueSky:
🦋 @seldo.com
