GitHub Trends

#typescript#agent#agents#ai#background_agents Open Agents is an open-source tool that lets you build AI coding agents running on Vercel. It separates the agent logic from the sandbox environment, meaning the AI runs outside the virtual machine and controls it through commands like file edits and shell operations. This architecture gives you flexibility—the agent isn't tied to a single request, sandboxes can pause and resume independently, and you can swap AI models or sandbox implementations without rebuilding everything. You get chat-driven coding with file tools, durable multi-step execution, isolated sandboxes, GitHub integration for cloning and creating pull requests, and optional voice input. The benefit is a scalable, modular system you can fork and customize for your own background coding agent needs without managing your laptop. https://github.com/vercel-labs/open-agents

#python#agent#finance#llm#multiagent#trading TradingAgents is a free, open-source framework using AI agents like analysts, researchers, traders, and risk managers to mimic real trading firms and make smart stock decisions. Install easily via GitHub, set API keys for models like GPT or Claude, and run CLI or Python code for quick analysis on any ticker. It boosts returns up to 30.5% yearly with low risk and clear explanations. You gain powerful, customizable tools to test and improve trading strategies fast, saving time and spotting better opportunities. https://github.com/TauricResearch/TradingAgents

#python#agent#agents#ai#anthropic#claudecode#llm#llms#openai Open SWE is a free, open-source framework to build internal coding agents like those at Stripe, Ramp, and Coinbase. Trigger it via Slack, Linear, or GitHub (@openswe) to research codebases, plan tasks, code, test, review, and auto-open PRs in secure cloud sandboxes—running parallel jobs without your machine's resources. Customize models, tools, and workflows easily. You benefit by automating routine coding, slashing review cycles and production time by 30-50%, freeing you to focus on high-value work while ensuring safe, high-quality changes. https://github.com/langchain-ai/open-swe

#python#agent#agentic_rag#ai_agents#clawbot#context_database#context_engineering#filesystem#llm#memory#openclaw#opencode#rag#skill OpenViking is a free open-source tool that acts as a context database for AI agents, using a simple file system to organize memories, resources, and skills under viking:// paths. It fixes issues like scattered data, high token costs, weak searches, and untraceable errors with tiered loading (L0 abstracts, L1 overviews, L2 details loaded on demand), recursive directory retrieval, visual traces, and auto-session memory updates. You benefit by building smarter, cheaper agents faster—like managing files—saving up to 96% on tokens while boosting task success by 50%+. https://github.com/volcengine/OpenViking

#typescript#agent#ai#ai_agents#browser_automation#javascript#typescript#ui_automation#web Page Agent is an open-source tool that lets you control webpages with simple natural language commands, like "Click the login button." It runs directly in your browser with one line of code—no extensions, Python, or screenshots needed—and works with your own AI models for privacy. Use it for fast form filling, AI copilots in apps, accessibility via voice, or multi-page tasks. This saves time by turning clicks into sentences, making complex web apps easy and accessible for everyone. https://github.com/alibaba/page-agent

#elixir#agent#ai#artificial_intelligence#elixir#event_driven_architecture#functional_programming#orchestration#workflow Jido is a pure functional framework for Elixir to build autonomous multi-agent workflows. Agents are immutable data with a simple `cmd/2` function that transforms state purely and outputs directives for effects like signals or spawning, handled by OTP runtime. It formalizes patterns like standard signals, reusable actions, and hierarchies over raw GenServer, adding AI tools, strategies (ReAct, FSM), and supervision. You benefit by creating scalable, testable, fault-tolerant agent systems easily for production AI apps, saving reinvented code. https://github.com/agentjido/jido

#python#agent#llm#llm_agent#llm_reasoning#machine_learning_systems#mlsys#reinforcement_learning#rl AReaL is a free, open-source system for fast asynchronous reinforcement learning to train large AI models in math, coding, search, and agents. It decouples generation and training for up to 2.77x speedup, stable performance, and easy setup on single or 1000+ GPUs with algorithms like GRPO/PPO. Install via git/pip, run examples like GSM8K math instantly. You benefit by building top AI agents affordably and quickly, reproducing results with shared data/models, saving time/money vs. slow synchronous tools. https://github.com/inclusionAI/AReaL

#python#agent#ai_agents#memory#memoryscope#rag#reme ReMe is a memory toolkit for AI agents with file-based (Markdown files for easy editing) and vector-based systems to fix limited context and stateless chats. It auto-summarizes talks, saves key facts like preferences, and recalls them next time using hybrid search. Install via `pip install reme-ai`, set API keys, and use ReMeCli or Python code for smart agents. You benefit by building persistent, learning agents that remember your needs, work faster on repeat tasks, and feel more natural without starting over. https://github.com/agentscope-ai/ReMe

#python#agent#chatbot#large_language_models#llm#llm_agent#mcp#multi_agent#multi_modal#react_agent AgentScope is a simple, production-ready framework to build AI agents fast. Install with `pip install agentscope` (Python 3.10+), then create ReAct agents with tools, memory, voice, human steering, multi-agent workflows, and finetuning in 5 minutes. It supports realtime voice, A2A protocols, RL training, and easy deployment locally, in cloud, or Kubernetes. You benefit by quickly making robust, scalable agents for tasks like games, research, or chats without complex coding, saving time and enabling real-world apps. https://github.com/agentscope-ai/agentscope

#python#agent#android#app#automation#copilot#gui#mllm#mobile#mobile_agents#multimodal#multimodal_agent#multimodal_large_language_models Mobile-Agent-v3.5 is Alibaba's top GUI agent family using GUI-Owl 1.5 models (2B to 235B sizes) for automating desktop, mobile, and browser tasks like stock checks, bookings, or document creation with planning, reflection, and memory. Try free online demos on ModelScope or Bailian, or use limited-time APIs—no setup needed. It leads 20+ benchmarks for real-world use. You benefit by saving time on repetitive tasks, boosting productivity, and handling complex operations hands-free across devices. https://github.com/X-PLUG/MobileAgent

#typescript#agent#agent_development#ai_agent#claude#claude_code#educational#llm#python#teaching#tutorial Claude Code is an AI agent framework that uses a simple loop: send messages to Claude, check if it needs tools, execute those tools, and repeat. The benefit is that you can build powerful autonomous agents by layering one feature at a time—from basic tool use to multi-agent teams—without rewriting the core loop. This modular approach lets you start simple with bash commands and scale to complex workflows with planning, skill loading, background tasks, and team coordination, making it easier to automate development work and delegate entire projects to AI agents. https://github.com/shareAI-lab/learn-claude-code

#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