xiaoyaosearch — What is it?

XiaoyaoSearch is a cross-platform desktop application that utilizes AI to perform deep local file searches, making search as intuitive as chatting.

⭐ 1,018 Stars 🍴 88 Forks Python NOASSERTION Author: dtsola
Source: README View on GitHub →

Why it matters

XiaoyaoSearch is gaining attention due to its innovative multi-modal search capabilities, integration of advanced AI models, and privacy-focused design. It addresses the pain point of complex and inefficient local file searches, filling the gap in user-friendly AI-powered search solutions. The unique technical choices include a hybrid search architecture and support for various AI models.

Source: Synthesis of README and project traits

Core Features

Multi-modal Input

Supports voice input, text input, and image upload, converting user queries into semantic searches for deep local file retrieval.

Source: README
Deep Retrieval

Supports searching within video, audio, and document files, including content and filenames, leveraging AI models for enhanced search capabilities.

Source: README
AI Enhancement

Integrates advanced AI models like BGE-M3, FasterWhisper, CN-CLIP, and OLLAMA, with support for cloud-based models and APIs for improved search quality.

Source: README
High Performance

Utilizes a hybrid retrieval architecture based on Faiss vector search and Whoosh full-text search for efficient and fast searches.

Source: README
Privacy-Focused

Runs locally by default without uploading data, with options for cloud-based API usage for a balance between performance and privacy.

Source: README
Modern Interface

Built with Electron, Vue 3, and TypeScript, providing a modern and user-friendly desktop application interface.

Source: README
AI Ecosystem Integration

Supports Model Context Protocol and Agent Skills for integration with other AI tools and platforms.

Source: README

Architecture

The architecture is a hybrid of a desktop application and a server-side service. The frontend is built with Electron, Vue 3, and TypeScript, while the backend uses Python 3.10 with FastAPI and Uvicorn. AI models and search engines are integrated for processing and indexing data, with a focus on efficient and secure local file search.

Source: Code tree + README

Tech Stack

infra: Local desktop application, potentially serverless for cloud-based API support  |  key_deps: Faiss, Whoosh, BGE-M3, FasterWhisper, CN-CLIP, OLLAMA  |  language: Python  |  framework: Electron, Vue 3, TypeScript, FastAPI, Uvicorn

Source: Dependency files + code tree

Quick Start

1. Clone the project repository. 2. Install dependencies for the backend. 3. Install AI models and dependencies. 4. Start the backend service. 5. Start the frontend service. 6. Run the application.
Source: README Installation/Quick Start

Use Cases

XiaoyaoSearch is suitable for knowledge workers, content creators, and technical developers who need an efficient and intuitive way to search local files. It is useful in scenarios where quick access to specific files is critical, such as in professional environments or for personal organization of digital assets.

Source: README

Strengths & Limitations

Strengths

  • Strengths: Advanced AI integration, multi-modal input, privacy-focused design, modern interface, and support for various file types.

Limitations

  • Limitations: Requires a relatively powerful system to run efficiently, and the lack of detailed performance metrics makes it difficult to assess its efficiency in real-world scenarios.
Source: Synthesis of README, code structure and dependencies

Latest Release

v1.9.0 (2026-04-12): Release focused on optimizing the search logic of the professional terminology library system and concurrent control optimization.

Source: GitHub Releases

Verdict

XiaoyaoSearch is a promising project for teams or individuals seeking an advanced and user-friendly AI-powered local file search solution. Its innovative features and privacy considerations make it a project worth watching, particularly for those who require efficient and intuitive access to their digital assets.

Transparency Notice
This page is auto-generated by AI (a large language model) from the following public materials: GitHub README, code tree, dependency files and release notes. Analyzed at: 2026-04-19 18:33. Quality score: 85/100.

Data sources: README, GitHub API, dependency files