Complete course on vector databases, embeddings, and RAG pipelines.
Last Updated: April 2026 - All code updated and tested with the latest APIs including ChromaDB 1.5+, LangChain 1.2+, Pinecone 7.x, and OpenAI's newest models.
git clone https://github.com/pdichone/vector-databases-course.git
cd vector-databases-course# Install uv if you don't have it
curl -LsSf https://astral.sh/uv/install.sh | sh
# Create venv and install dependencies
uv venv
source .venv/bin/activate # On Windows: .venv\Scripts\activate
uv pip install -r requirements.txtpython -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
pip install -r requirements.txtcp .env.example .env
# Edit .env with your API keys- OpenAI: https://platform.openai.com/api-keys
- Pinecone: https://app.pinecone.io/
| File | Section | Description |
|---|---|---|
chroma_emb.py |
ChromaDB | Basic embedding functions |
chroma_persist.py |
ChromaDB | Persisting data to disk |
chroma_openai_emb.py |
ChromaDB | OpenAI embeddings with Chroma |
vector_db_llm.py |
RAG | Complete RAG pipeline (no LangChain) |
vector_db_llm_lang_chain.py |
LangChain | RAG with LangChain + Chroma |
pinecone_intro.py |
Pinecone | Pinecone basics |
pinecone_db_llm_lang_chain.py |
Pinecone | RAG with LangChain + Pinecone |
raw_emb.py |
Embeddings | Raw OpenAI embeddings |
- Updated all ChromaDB code to v1.5+ API
- Updated LangChain imports to use
langchain-chromapackage - Fixed all deprecated OpenAI model references (
gpt-4o-mini) - Added
requirements.txtwith pinned dependencies - Added
pyproject.tomlfor uv/modern Python tooling - All code tested and working with Python 3.13
The data/new_articles/ directory contains sample text files for the RAG examples.
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