xyh4ck

xyh4ck / SmartSafe

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SmartSafe LLM Evaluation System

47
0
89% credibility
Found Feb 17, 2026 at 47 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Vue
AI Summary

SmartSafe is a platform for testing AI language models on safety risks using test cases, analyzers, and generating evaluation reports.

How It Works

1
🔍 Discover SmartSafe

You hear about SmartSafe, a friendly tool that helps check if your AI assistant gives safe, helpful answers without risks like bias or bad advice.

2
📝 Gather test questions

You collect simple questions that might trick the AI into unsafe responses, like tricky topics on fairness or danger.

3
🏗️ Build a test plan

You organize the questions into categories of risks and pick your AI model to test against them.

4
🚀 Launch the safety check

With one click, you start the evaluation and watch it run tests automatically on your AI.

5
📊 Review the safety scores

You see clear results showing risk levels for each test, like low danger or needs fixing.

6
📈 Create reports

You generate easy-to-read summaries and charts to share how safe your AI really is.

✅ AI is safer now

Your AI passes most tests, giving you confidence it's ready for real users without surprises.

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Star Growth

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AI-Generated Review

What is SmartSafe?

SmartSafe is a Vue-based web system for evaluating LLM outputs on smart safety risks like bias, toxicity, illegal content, and prompt leakage. Developers upload test prompts, run batch evaluations asynchronously, and get risk scores, summaries, and PDF reports highlighting high-risk cases. Built with a FastAPI backend, Celery for task queuing, and Docker Compose for easy MySQL/Redis setup, it delivers a full LLM evaluation workflow without manual scripting.

Why is it gaining traction?

It stands out by integrating DeepTeam analyzers for precise vulnerability detection across 20+ categories, plus keyword matching and scheduled re-runs—saving hours on custom eval pipelines. The real hook is one-click exports (Excel/PDF) with progress tracking and detailed logs, making it dead simple to audit LLM safety before deployment. At 47 stars, it's niche but practical for teams needing quick smartsafe access beyond basic playground tests.

Who should use this?

AI safety engineers red-teaming production LLMs for compliance audits, or backend devs building chatbots who need to batch-test prompts against toxicity and jailbreak risks. Perfect for research teams tracking model improvements over versions, or startups validating fine-tuned models without spinning up complex infra.

Verdict

Grab it if you're doing LLM evaluation—solid foundation with async tasks and reports, despite low 0.9% credibility score and early maturity (47 stars, basic docs). Polish the UI and add more analyzers to scale; it's a smart starter for smartsafe system needs today.

(198 words)

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