Anonymous75.8分人上人，Dify核心佬瑞思拜

Anonymous75.8 score, 'upper class' tier? Dify core work slaps.

Anonymous插件缝合怪这tag也太精准了哈哈

AnonymousPlugin Stitcher tag is so accurate lmao

Anonymousbio空成白板？全靠贡献说话啊

AnonymousNull bio, empty contribs? Pure OSS grind.

AnonymousLLM工具搭子，开源打工人实锤了

AnonymousLLM tool builder + OSS worker, solid combo.

Anonymous75.8分人上人，Dify核心佬瑞思拜

Anonymous75.8 score, 'upper class' tier? Dify core work slaps.

Anonymous插件缝合怪这tag也太精准了哈哈

AnonymousPlugin Stitcher tag is so accurate lmao

Anonymousbio空成白板？全靠贡献说话啊

AnonymousNull bio, empty contribs? Pure OSS grind.

AnonymousLLM工具搭子，开源打工人实锤了

AnonymousLLM tool builder + OSS worker, solid combo.

← Back to Hall of Fame

@zhouhaojiang

Joe

81.30/100

🥇 ELITE

Elite · Top-tier dev

🏢 LangGenius

Your standing

#1692/ of 17712

Beat 90.4% of developers

8.70 pts to “GOD”

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🏆 Notable contributions

Popular open-source repos they've shipped to (commits + PRs)

langgenius/dify⭐ 147.1K50 commits · 54 PRs svcvit/Awesome-Dify-Workflow⭐ 10.6K1 commits · 1 PRs langgenius/dify-official-plugins⭐ 5964 commits · 6 PRs langgenius/dify-docs-archived⭐ 5291 commits · 1 PRs langgenius/dify-plugins⭐ 5263 commits · 1 PRs

Score breakdown

Account maturity9.2 / 10

Original project quality9.6 / 18

Contribution quality23.0 / 27

Ecosystem / maintenance impact19.2 / 20

Community influence4.4 / 8

Activity authenticity15.9 / 17

🛠 Featured work

Their own popular and pinned repositories

PdfReader-LangChian-LLM⭐ 55

ChatPDF Implement PDF parsing based on LangChain and LLM language model(ChatGLM,GPT...) | ChatPDF 基于LangChain和LLM语言模型实现PDF解析阅读

Python

fastapi-with-fatmcp-agent⭐ 10

A modular application API interface based on FastMCP, integrating a demo of the MCP server, FastAPI interface and LLM Agent processing capabilities | 一个基于FastMCP的模块化应用，集成了MCP服务器、FastAPI接口和LLM Agent 处理能力的 demo

Python

crawler_utils⭐ 8

爬虫工具练习，目前支持小红书指定关键词爬取

Python

dify-dsl-batch-migration⭐ 5

批量迁移 Dify DSL 至不同环境

Shell

mood-esp⭐ 3

image-classification⭐ 3

身份证，隐私，证件票据图片分类|The project is based on Pytorch and through MobileNetV2 network structure, it realizes four classification tasks of chat screenshots, identity tickets and private pictures, realizes model training, testing, model saving, model loading and conversion, and visualization of training process.

Python