Integrate Azure AI Search for Enhanced Vector and Hybrid Search Capabilities

[Zochory]

Problem Statement
Currently, our system lacks a robust, scalable search infrastructure to handle vector embeddings, semantic search, and hybrid search scenarios. As we build out agentic systems and AI-driven features, we need a production-ready search solution that can:

Efficiently index and query large volumes of vector embeddings

Support hybrid search combining keyword and semantic search

Scale with our growing data and query demands

Integrate seamlessly with our existing Azure infrastructure

Motivation
Azure AI Search (formerly Azure Cognitive Search) provides:

Vector search capabilities with built-in support for embeddings from OpenAI, Azure OpenAI, and other models

Hybrid search combining vector similarity with traditional full-text search

Semantic ranking for improved relevance

Native Azure integration aligning with our existing cloud infrastructure

Scalability and performance with managed indexing and query optimization

This is critical for features like:

RAG (Retrieval-Augmented Generation) implementations

Semantic document search across knowledge bases

Agent memory and context retrieval

Real-time search in multi-agent systems

Proposed Solution
Implementation Plan:

Service Setup

Provision Azure AI Search service in appropriate region

Configure pricing tier based on expected load (consider Standard S1 for production)

Set up authentication using Azure managed identity or API keys

Index Schema Design

Define index schema with vector fields for embeddings

Configure hybrid search fields (text + vector)

Set up semantic configuration for ranking

Define filtering and faceting fields

Integration Points

FastAPI Backend: Create service layer for search operations

Vector Embeddings: Integrate with Azure OpenAI or OpenAI API for generating embeddings

Data Ingestion: Build indexing pipeline for documents/content

Query Interface: Implement search endpoints with hybrid query support

Key Features to Implement

Vector search with configurable similarity metrics

Hybrid search combining keyword + semantic

Filtering and faceting capabilities

Batch indexing operations

Real-time document updates

Search result ranking and scoring

[linear]

QRE-247