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Source channel @pushgoodcloud · Post #607 · 11月30日

#Lantau#大屿山 之前购买过的,可以联系 @ljfxz 退款,直接发机场邮箱给他 剩余价值退款按照( 剩余时长*时长单价)+(剩余流量*流量单价)的形式退款 流量单价=套餐价格*0.8/套餐流量总数 时长单价=套餐价格*0.2/套餐时长总数 例如轻量套餐价格为9元,流量为80G,时长为30天。那天数单价为(0.2*9)/30,流量单价为(0.8*9)/80。 此时轻量用户还剩10天,流量还有70G,那退款为10*[(0.2*9)/30] + 70*[(0.8*9)/80] 注* 充了流量的钱也可退

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@githubtrending · Post #15523 · 2026/02/25 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