Video course · 12 chapters · 39 min · certificate
Agentic RAG and Knowledge Graphs: Build Smarter AI Retrieval Systems (Free Template)
Build an agentic RAG agent that combines vector search with a knowledge graph: a live demo, the tech stack (Pydantic AI, Graphiti, Postgres, Neo4j), why agentic RAG helps, setup with Neon and Neo4j, configuration, ingesting a knowledge base, search behaviour, testing and building it with Claude Code.
What you'll learn
- Explain agentic RAG and knowledge graphs
- Set up Postgres (Neon) and Neo4j
- Configure LLMs and databases
- Ingest documents into vectors and a graph
- Define when the agent uses each search
- Run and test the agent
Chapters
12 chapters · 38:48-
1:05
01Intro Members
Agentic RAG plus knowledge graphs
The best RAG strategy.
-
4:16
02Demo Members
Live demo
CLI talking to an API agent.
-
1:10
03Stack Members
Tech stack
Libraries used.
-
4:05
04Concepts Members
What is agentic RAG
Why it's useful.
-
2:17
05Setup Members
Set it up yourself
Cloning and installing.
-
1:07
06Postgres Members
Database setup in Neon
Hosted Postgres.
-
1:07
07Graph Members
Installing Neo4j
Local graph database.
-
3:10
08Config Members
Environment configuration
LLMs, DB, Neo4j.
-
4:18
09Ingestion Members
Setting up the knowledge base
Documents into vectors and graph.
-
2:12
10Prompting Members
Defining how the agent searches
Tool choice rules.
-
3:24
11Testing Members
Running and testing
API and CLI.
-
10:37
12Process Members
Built with Claude Code
AI-assisted build.
Jobs this course suits
Our AI checked this course against 500 jobs; these get the most out of it. Each job links to its learning path.