---
id: SEARCH-003
title: Unified Vector Repositories
status: To Do
assignee: jamiepine
parent: SEARCH-000
priority: High
tags: [search, vector-search, ai, repositories]
whitepaper: Section 4.7
---

## Description

Implement the Unified Vector Repositories, a system for storing and querying vector embeddings of file content and metadata. This is the foundation of the semantic search capabilities.

## Implementation Steps

1.  Choose a vector database or library for storing and querying vector embeddings.
2.  Implement the logic to generate vector embeddings for files and metadata.
3.  Create a `VectorRepository` service that provides an API for adding, updating, and searching for vectors.
4.  Integrate the `VectorRepository` with the `SearchJob` and the semantic re-ranking logic.

## Acceptance Criteria

- [ ] The system can generate and store vector embeddings for files.
- [ ] The `VectorRepository` can perform efficient vector similarity searches.
- [ ] The semantic search capabilities are integrated into the overall search system.
