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europilot

AI coding

Train autonomous driving with games. Europilot is an open-source project that uses Python to control Euro Truck Simulator 2 as a toolkit for developing self-driving algorithms. Use the popular Euro Truck Simulator (ETS2) to develop autonomous driving algorithms. With europilot, you can capture game screen input and programmatically control the truck in the simulator. Europilot can be used in one of two ways: training or testing. For training, europilot can capture screen input in real time and output a numpy array, while also obtaining wheel joystick values. For testing, europilot can create a virtual joystick driver that can be recognized in the game and can programmatically control the truck. Using this joystick, you can create a real-time inference network that performs real-time inference

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evalscope

AI developer platforms

EvalScope is a one-stop large model evaluation framework built by the ModelScope community, supporting model capability evaluation, inference performance stress testing, and result visualization. It comes with multiple industry evaluation benchmarks such as MMLU, C-Eval, GSM8K, etc., can evaluate various model types such as LLM, VLM, Embedding, Reranker, AIGC, and integrates evaluation backends such as OpenCompass, VLMEvalKit, RAGEval. EvalScope provides an Agent evaluation mode, inference performance testing (TTFT, TPOT and other metrics), Web Dashboard interactive reports, Arena multi-model battle mode, and supports custom datasets, models, and evaluation metric extensions.

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EvoAgentX

AI developer platforms

EvoAgentX is an open-source framework for building, evaluating, and evolving LLM-based agents or agent workflows in an automated, modular, and goal-driven manner. At its core, it introduces a self-evolving agent ecosystem, enabling AI agents to be constructed, evaluated, and optimized through iterative feedback loops. Key features include: automatic construction of multi-agent workflows from a single prompt, built-in automatic evaluators, a self-evolution engine, integration of popular models such as OpenAI, Qwen, Claude, Deepseek, and kimi through LiteLLM, siliconflow, or openrouter, as well as local deployment support. The framework comes with a rich set of built-in tools (code interpreter, search, file system, database, image, browser automation, etc.), supports short-term and long-term memory modules, and supports human-in-the-loop (HITL) interaction. EvoAgentX is suitable for AI researchers, workflow engineers, and startup teams, helping to quickly build fully functional agent systems from vague ideas. The project is installed via pip and provides detailed documentation, tutorials, and examples.

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