#typescript
GitNexus indexes your codebase into a knowledge graph tracking dependencies, call chains, clusters, and flows, then connects AI agents like Cursor and Claude Code via CLI tools for reliable analysis. Run `npx gitnexus analyze` from your repo root to start—it auto-generates context files and MCP setup. Use tools like `impact` for change risks or `rename` for safe refactors. This boosts your productivity by preventing AI blind edits, cutting debugging time, and enabling smaller models to grasp full architecture fast.
https://github.com/abhigyanpatwari/GitNexus
Совсем лайтовая статья для новичков "10 главных конструкций языка R".
Содержание:
- Комментарии
- Переменные и векторы
- Внешние модули
- Ввод и вывод
- Присваивание и сравнение
- Условный оператор if
- Цикл for
- Функции
- Классы, методы и объекты
#статьи
#easy
#Easy#Credit#T#i#ch#nh#s
Join the Easy Credit - Tài chính số beta on ✈️#TestFlight
🔗 Link: https://testflight.apple.com/join/B8XYxOWV
Shared by Dimitri
#python#deepseek#demo#easy#embedding#flask#gpt#huggingface_transformers#llm#mcp#multimodal#openai#qwen#rag#sentence_transformers#ui#vllm#vlm
UltraRAG is a lightweight framework that makes building retrieval-augmented generation (RAG) systems simple and fast. It uses a low-code approach where you write just dozens of lines of YAML configuration instead of complex code to create sophisticated AI workflows with conditional logic and loops. The framework includes a visual development environment where you can drag-and-drop to build pipelines, adjust parameters in real-time, and instantly convert your logic into interactive chat applications. This means you can deploy powerful AI systems that ground answers in your own data—reducing hallucinations and improving accuracy—without needing extensive coding expertise or lengthy development cycles.
https://github.com/OpenBMB/UltraRAG