mmfiRan

mmfiRan / ran-feed

Public

面向内容型产品的后端业务系统，围绕“发布-互动-关系-信息流”闭环构建：支持文章/视频发布与详情，点赞/收藏/评论/回复等互动能力，关注/取关与粉丝关系，以及推荐流、关注流、个人发布列表、个人收藏列表等信息流场景，并提供相关计数统计能力

19
1
100% credibility
Found Mar 23, 2026 at 19 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
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AI Summary

RAN·FEED is a backend system for social content platforms supporting user accounts, publishing articles/videos, interactions like likes/comments/follows, personalized feeds, and usage stats.

How It Works

1
👀 Discover RAN·FEED

You find this open project that powers social feeds like sharing posts and seeing recommendations.

2
🚀 Start with one click

Run a simple script to launch everything on your computer, no hassle needed.

3
👤 Create your profile

Sign up with your details and upload a photo to join the community.

4
Share your creation
📝
Write an article

Type your thoughts, add a cover image, and hit publish.

🎥
Upload a video

Share a clip with a title, cover, and description.

5
❤️ Interact and connect

Like posts, comment, favorite, or follow friends to build your network.

6
📱 Browse your feeds

Swipe through recommendations, friends' posts, or your own collection.

🎉 Your social hub thrives

Watch your community grow with lively shares and conversations.

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Star Growth

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AI-Generated Review

What is ran-feed?

ran-feed is a Go backend for content platforms, delivering the full publish-interact-relate-feed loop: users post articles/videos with OSS uploads, engage via likes/comments/follows, and pull personalized streams like recommendations, following feeds, personal posts, or favorites lists, complete with interaction counts. Powered by go-zero with MySQL/Redis/Kafka for data flows and Docker Compose for one-click deploys, it solves the pain of stitching social features from zero. If you're ran out of feed boilerplate, this hands you ready APIs for ran feed scenarios.

Why is it gaining traction?

It packs enterprise-grade feeds—recommend/follow/user lists—into a lean HTTP gateway calling gRPC services, with built-in tracing (Jaeger), metrics (Prometheus/Grafana), and logging (ELK), skipping weeks of infra setup. The hook? Bilingual READMEs with UI demos, XXL-Job for crons, and MIT license for quick forks. Devs try it to prototype kill feed ran online without custom rec engines.

Who should use this?

Go backend devs at content startups prototyping TikTok-style apps, or teams needing fast social feeds with auth/uploads/interactions. Perfect for indie hackers building ran feed MVPs, or evals of microservices before scaling.

Verdict

Solid bootstrap for feed-heavy Go services—deployable in minutes, feature-complete for core loops. With 19 stars and 1.0% credibility, it's immature (light tests, early rec algos) but actively polished; spin it up locally, extend for prod.

(198 words)

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