Skip to main content

2 posts tagged with "Pinecone"

Using Pinecone as a vector database for AI-powered search and retrieval. Covers vector storage, similarity search, hybrid retrieval, and integrating with LlamaIndex for efficient AI search systems.

View All Tags

How to build a custom embedder in LlamaIndex: AWS Titan Multimodal example

· 14 min read
Norah Sakal
AI Consultant & Developer

How to build a custom embedder in LlamaIndex: AWS Titan Multimodal example

LlamaIndex makes it easy to build AI-powered search, but if you're working with multimodal embeddings (text + images), like the AWS Titan multimodal model, you'll notice it's not natively supported.

For e-commerce search, I need embeddings that capture both product descriptions and images to generate more accurate search results.

This guide will show you how to override LlamaIndex's default embedder to use AWS Titan Multimodal.

How to build an AI agent with LlamaIndex that can handle multiple color requirements

· 49 min read
Norah Sakal
AI Consultant & Developer

How to build an AI agent with LlamaIndex that can handle multiple color requirements

When an e-commerce customer asks for something like women's black shoes with red details, naive chatbots often struggle to apply multiple color filters simultaneously.

In this post, learn how to build a more advanced AI agent using Python, Pinecone and LlamaIndex, complete with metadata filtering and real-world code examples to handle multi-color product queries seamlessly.