Search Results for "path-setting"
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Showing 8 open source projects for "path-setting"
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Qwen Code
Qwen Code is a coding agent that lives in the digital world
...Qwen Code automates various development workflows, including handling pull requests and performing complex git rebases. It runs on Node.js (version 20 or higher) and can be installed globally via npm or from source. Users configure Qwen Code by setting API keys and endpoints, supporting both mainland China and international access. With Qwen Code, developers can explore codebases, refactor and optimize code, generate documentation, and automate repetitive tasks directly from the terminal. -
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Get Physics Done (GPD)
The first open-source agentic AI physicist
...It aims to simplify the process of performing simulations, calculations, and experimental analysis by providing structured workflows that integrate computational physics methods with reproducible research practices. The project focuses on reducing the friction involved in setting up experiments, running simulations, and analyzing results, allowing researchers to focus more on scientific insight rather than infrastructure. It emphasizes automation and reproducibility, ensuring that experiments can be easily replicated and extended by other researchers. The framework is adaptable to different areas of physics, making it suitable for both theoretical and applied research scenarios. -
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Flint Chart
Visualization language that lets AI agents create expressive charts
Flint Chart is a visualization language and compiler built for AI-era chart creation. It lets agents and humans write compact, editable chart specifications without manually tuning every axis, label, scale, legend, or layout setting. The compiler uses data, semantic types, chart type, and encodings to derive polished chart settings automatically. One Flint input can compile into native Vega-Lite, ECharts, or Chart.js specifications. The repository includes a TypeScript library, an MCP server, a demo site, documentation, test data, and an early Python port. ... -
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TencentDB Agent Memory
TencentDB Agent Memory delivers fully local long-term memory for AI
...For personalization, it organizes memory from raw conversations into atoms, scenarios, and persona-level knowledge. The design keeps high-level memory inspectable while preserving a drill-down path back to raw evidence. It is built for OpenClaw and Hermes-style agent workflows that need lower token usage, better continuity, and no external API dependency. -
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5
Sandbox Agent
Run Coding Agents in Sandboxes
...The project focuses on enabling more reliable and auditable agent behavior by separating execution from the host environment, which is especially important for applications involving automation, code generation, or system-level operations. Developers can use Sandbox Agent to simulate real-world workflows, debug agent decisions, and evaluate outcomes in a contained setting before deploying to production. It also supports extensibility, allowing integration with custom tools, APIs, and workflows tailored to specific use cases. -
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DeepSeek Engineer v2
A powerful coding assistant application
...Version 2.0 focuses on native function calling instead of rigid structured JSON responses. The assistant can read files, read multiple files, create files, create multiple files, and edit specific snippets when needed. It includes safeguards such as path validation, directory traversal protection, file size limits, and binary file exclusion. Overall, it is designed for developers who want a conversational coding tool that can inspect, modify, and reason about project files from the command line. -
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Keep Codex Fast
A backup-first Codex skill for keeping local Codex state fast
...When applied manually, it backs up first, archives old sessions, rotates large logs, moves stale worktrees, and prunes dead references instead of deleting important state. It also includes an optional repair path for oversized thread title and preview metadata. Its main value is helping users preserve continuity through handoff documents while reducing local drag in Codex. -
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Hello-Agents
Building an Intelligent Agent from Scratch
...It walks users through core concepts such as ReAct-style reasoning, tool usage, memory handling, and multi-step task execution, enabling hands-on experimentation with modern LLM-powered agent systems. The repository is structured as a progressive learning path, combining theory, exercises, and runnable code so users can incrementally build more capable agents. Its goal is to demystify agent engineering and help developers move from simple prompt scripts to robust autonomous systems.
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