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Source channel @githubtrending · Post #15263 · Nov 2

#python#deep_learning#inference#llm#nlp#pytorch#transformer Nano-vLLM is a small, fast, and easy-to-understand tool for running large language models offline. It matches the speed of bigger systems like vLLM but uses only about 1,200 lines of clean Python code, making it simple to read and modify. It includes smart features like prefix caching and tensor parallelism to boost performance. You can install it easily and run models like Qwen3-0.6B on your own GPU. This tool is great if you want fast, efficient AI inference without complex setups, ideal for learning, research, or small deployments on limited hardware. https://github.com/GeeeekExplorer/nano-vllm

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@githubtrending · Post #14996 · 07/25/2025, 12:00 PM

#ocaml#c#go#java#javascript#python#r2c#ruby#sast#semgrep#static_analysis#static_code_analysis#typescript Semgrep is a fast, open-source tool that scans your code to find bugs and security issues in over 30 programming languages. It works locally on your computer or in your build system, so your code stays private. Semgrep’s rules are easy to write and understand, helping you catch problems early in development, whether in your IDE, pre-commit checks, or CI/CD pipelines. For stronger security, the Semgrep AppSec Platform offers advanced analysis, AI-powered triage, and detailed fix guidance, reducing false alarms and helping developers fix issues quickly without slowing down. This improves code quality and security efficiently. https://github.com/semgrep/semgrep

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@githubtrending · Post #15349 · 12/20/2025, 12:30 PM

#python#ai#bug_detection#code_audit#code_quality#code_review#developer_tools#devsecops#google_gemini#llm#react#sast#security_scanner#supabase#typescript#vite#vulnerability_scanner#xai **DeepAudit** is an AI-powered code audit tool using multi-agent collaboration to deeply scan projects for vulnerabilities like SQL injection, XSS, and path traversal. Import code from GitHub/GitLab or paste snippets; agents plan, analyze with RAG knowledge, and verify issues via secure Docker sandbox PoCs, generating PDF reports with fix suggestions. Deploy easily with one Docker command, supports local Ollama models for privacy, and cuts traditional tools' high false positives. **You benefit** by automating secure audits like a pro hacker—saving time, reducing errors, ensuring real exploits are caught, and speeding safe releases without manual hassle. https://github.com/lintsinghua/DeepAudit