kmjs1915/CeTaPet-AI-DeskTopPet-DeepSeek

这是一款基于Python开发的桌面AI桌宠,对接DeepSeek模型,支持角色聊天,以及轻量化RAG知识库

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kmjs1915/CeTaPet-AI-DeskTopPet-DeepSeek has 10+ stars on GitHub, is written in Python, and was last pushed on Sep 10, 2026. Data as of . Signed-in members get hourly updates — create a free account.

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Updated 34 minutes ago
Added to GitGenius on October 12th, 2026
Created on September 10th, 2026
Open Issues & Pull Requests: 0 (+0)
GitHub issues: Enabled
Number of forks: 0
Total Stargazers: 10 (+0)
Total Subscribers: 1 (+0)

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Detailed Description

CeTaPet is a Windows desktop AI pet application that integrates the DeepSeek language model to enable interactive character conversations and lightweight local document retrieval.

The tool addresses the desire for an engaging desktop companion that combines conversational AI with practical knowledge management. It works by running as a persistent window application where users interact with an animated character through left-click interactions that trigger dialogue bubbles. The application supports character-driven conversations powered by DeepSeek's API and includes a lightweight retrieval-augmented generation system that reads local text and document files. Users can drag files onto the character to add them to the knowledge base, allowing the pet to reference and discuss their contents in subsequent conversations.

Adoption suits developers or users interested in exploring AI desktop applications, learning PySide6 GUI development, or experimenting with DeepSeek API integration in a playful context. The project explicitly positions itself as a personal learning demonstration rather than production software. All character assets, animations, and dialogue scripts are customizable through the asset_library folder, making it suitable for those wanting to personalize the pet's appearance and behavior. The tool requires users to provide their own DeepSeek API key to function.

The project is maintained with responsiveness to user feedback through GitHub Issues for bug reports and feature suggestions. Development activity shows engagement with the codebase through issue tracking and appears oriented toward addressing reported problems and incorporating user requests.