zengzifan1

zengzifan1 / multi-agent-moderation

Public

多智能体文本内容审核系统，提供结构化审核、证据链与复核路由，适用于内容安全与合规治理。

audit-log compliance content-moderation langgraph multi-agent
45
3
89% credibility
Found May 05, 2026 at 45 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

A system that moderates social media text by checking for rule violations, duplicates against history, and providing review suggestions.

How It Works

1
📰 Find the content checker

You hear about a helpful tool that keeps social media posts safe from spam, scams, and repeats.

2
📥 Bring it home

Download the tool to your computer and get everything set up in a simple folder.

3
📋 Add your rules

Put in your list of bad words to block and examples of good past posts to spot copies.

4
✨ Check new posts

Paste in user posts one by one or in batches, and watch it scan for issues.

5
🔍 Review decisions

Get clear labels like 'safe to post', 'needs a look', or 'block it', with reasons why.

✅ Safe posts live

Your social feed now has original, rule-following content that everyone loves.

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Star Growth

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AI-Generated Review

What is multi-agent-moderation?

This Python-based multi-agent moderation system audits text content for compliance risks like spam or scams, flags duplicates via embeddings, and routes borderline cases to human review with structured evidence and replacement suggestions. Developers feed it items via API or batch files, getting JSON outputs with allow/review/block decisions plus audit trails. It tackles content safety in apps handling user-generated posts, blending rule-based checks with semantic analysis.

Why is it gaining traction?

Its hook is the agent workflow delivering traceable decisions—compliance first, then quality dedup, then review payloads—without needing a full ML team. FastAPI endpoints for sync/async moderation, YAML configs for rules/history data, and optional graph orchestration make it deployable fast. At 45 stars, it's niche but appeals to teams wanting evals over black-box APIs.

Who should use this?

Backend devs at social apps or forums building UGC gates before publishing. Compliance teams at Chinese platforms needing blacklist + semantic checks on posts. Startups prototyping content moderation without vendor lock-in.

Verdict

Grab it for PoCs if you're in Python—solid API and pipelines for quick wins, despite 45 stars signaling early maturity and a quirky 0.9% credibility score. Polish docs and add tests to scale; it's a smart starter for multi-agent moderation flows. (198 words)

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