yangjian102621/geekai

AI 助手全套开源解决方案,自带运营管理后台,开箱即用。集成了 ChatGPT, Azure, ChatGLM,讯飞星火,文心一言等多个平台的大语言模型。支持 MJ AI 绘画,Stable Diffusion AI 绘画,微博热搜等插件工具。采用 Go + Vue3 + element-plus 实现。

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yangjian102621/geekai has 4.5k+ stars and 1k+ forks on GitHub, is written in Vue, and was last pushed on Sep 13, 2026. Data as of . Signed-in members get hourly updates — create a free account.

Summary Information

Updated 1 minute ago
Added to GitGenius on September 14th, 2026
Created on May 6th, 2023
Open Issues & Pull Requests: 32 (+0)
GitHub issues: Enabled
Number of forks: 1,068
Total Stargazers: 4,715 (+0)
Total Subscribers: 48 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 42.0 hours
Mean response time: 11.4 days
90th percentile: 42.9 days
Tracked items: 13

Charts & Analytics

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Issue Activity (beta)

Open issues: 16
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 356 days
Stale 30+ days: 14
Stale 90+ days: 14

Recent activity

Opened in 7 days: 0
Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 0

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  • feature (11)

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Detailed Description

GeekAI is an open-source AI content creation platform that integrates multiple large language models and generative AI capabilities into a single deployable system.

The platform addresses the need for a complete, ready-to-use AI creative suite by combining conversation, image generation, audio creation, video production, and mind mapping tools in one application. It integrates models from ChatGPT, Claude, Azure, ChatGLM, and others alongside image generation engines like Midjourney, DALL-E, and Stable Diffusion. The backend uses Go with Gin, MySQL, and Redis for performance, while the frontend is built with Vue3 and Element Plus to support both desktop and mobile interfaces. The system includes built-in user management, flexible billing models, and an administrative dashboard for operations and analytics.

GeekAI suits teams and individuals who want to deploy a multi-modal AI platform without building from scratch. It works well for content creators, marketing teams, educators, and enterprises needing a private, self-hosted solution. The platform supports multiple cloud storage backends including Qiniu, Aliyun OSS, Tencent Cloud OSS, and Minio. Docker containerization enables straightforward deployment and scaling. The README emphasizes that this is a complete commercial solution rather than a component library, positioning it for organizations ready to launch a full-featured AI service.

Development activity shows consistent feature expansion across multiple AI modalities and integrations. The project maintains comprehensive documentation covering deployment and API development. The codebase demonstrates modular architecture designed to support customization and extension. Updates track emerging AI capabilities and new model integrations, indicating active alignment with the evolving AI landscape.