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소스 채널 @phpdevelopersuz · Post #2382 · 3월 15일

Dasturchilar uchun Google tomonidan Code Jam onlayn musobaqasi. Tanlov g'oliblariga pul mukofotlari topshiriladi Talablar — Tanlovda 18 yoshdan katta bo'lgan dasturchilik sohasiga qiziquvchi yoshlar qatnashishlari mumkin; — Dasturchilarning Google accountlarida o'z ism-shariflari, telefon nomerlari va qaysi davlatda yashashlari aniq va batafsil keltirib o'tishlari so'raladi; — Dastur ishchi tili ingliz tili ekanligi uchun shu tildan xabardor bo'lishi kerak (sertifikat shartmas). Foydali tomonlari — 1-raunddan 2-raundga o'tgan eng yaxshi 1000 ta dasturchi ichiga kirgan nomzodlarga Code Jam futbolkalari beriladi; — Code Jam musobaqasida oxirgi 5-bosqichiga yetib kelgan ishtirokchilar quyidagi miqdordagi pul mukofotlari bilan taqdirlanadilar: — 1-o'rin - $15 000; — 2-oʻrin — $2000; — 3-oʻrin — $1000; — 4-25-oʻrin — $100. Oxirgi muddat 03.04.2022 23:59 Batafsil https://grantgo.uz/go/56580 #tanlovlar#mukofot#AQSh

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@githubtrending · Post #15523 · 2026. 02. 25. PM 12:30

#typescript#agent#agentic#agentic_framework#agentic_workflow#ai#ai_agents#bytedance#deep_research#harness#langchain#langgraph#langmanus#llm#multi_agent#nodejs#podcast#python#superagent#typescript DeerFlow 2.0 is an open-source super agent harness that orchestrates multiple sub-agents, memory systems, and sandboxed execution environments to accomplish complex tasks. Built on LangGraph and LangChain, it combines research, coding, and content creation capabilities with extensible skills and tools. The platform features isolated Docker containers for safe execution, long-term memory that learns your preferences, and the ability to spawn sub-agents that work in parallel on different task angles. You benefit from dramatically reduced research and automation time—tasks that typically take hours complete in minutes—while maintaining full transparency and control over agent decisions through human-in-the-loop collaboration. Whether you need deep research reports, data analysis, slide decks, or custom workflows, DeerFlow handles multi-step complexity without requiring extensive coding knowledge. https://github.com/bytedance/deer-flow