Data-Oriented GOAP (Goal-Oriented Action Planning) is a library that implements GOAP in a data-oriented way, allowing for dynamic setup of states, actions, and goals. It includes bevy_dogoap for Bevy integration. It is useful for NPCs performing tasks dependent on each other, enabling NPCs to improvise reaching goals, and offers a middle ground between Utility AI and HTNs. The library is inspired by the F.E.A.R GDC talk and provides a minimal Bevy example for implementation.

Deep Java Library (DJL) is an open-source, high-level, engine-agnostic Java framework for deep learning. It is designed to be easy to get started with and simple to use for Java developers. DJL provides a native Java development experience and allows users to integrate machine learning and deep learning models with their Java applications. The framework is deep learning engine agnostic, enabling users to switch engines at any point for optimal performance. DJL's ergonomic API interface guides users with best practices to accomplish deep learning tasks, such as running inference and training neural networks.

POML (Prompt Orchestration Markup Language) is a novel markup language designed to bring structure, maintainability, and versatility to advanced prompt engineering for Large Language Models (LLMs). It addresses common challenges in prompt development, such as lack of structure, complex data integration, format sensitivity, and inadequate tooling. POML provides a systematic way to organize prompt components, integrate diverse data types seamlessly, and manage presentation variations, empowering developers to create more sophisticated and reliable LLM applications.

Neuron AI is a PHP framework that provides an Agent class for creating fully functional agents to perform tasks like analyzing text for SEO optimization. The framework manages advanced mechanisms such as memory, tools, and function calls. Users can extend the Agent class to create custom agents and interact with them to get responses based on the underlying LLM. Neuron AI aims to simplify the development of AI-powered applications by offering a structured framework with documentation and guidelines for contributions under the MIT license.

ONNX Runtime Generative AI is a library that provides the generative AI loop for ONNX models, including inference with ONNX Runtime, logits processing, search and sampling, and KV cache management. Users can call a high level `generate()` method, or run each iteration of the model in a loop. It supports greedy/beam search and TopP, TopK sampling to generate token sequences, has built in logits processing like repetition penalties, and allows for easy custom scoring.

LABO is a time series forecasting and analysis framework that integrates pre-trained and fine-tuned LLMs with multi-domain agent-based systems. It allows users to create and tune agents easily for various scenarios, such as stock market trend prediction and web public opinion analysis. LABO requires a specific runtime environment setup, including system requirements, Python environment, dependency installations, and configurations. Users can fine-tune their own models using LABO's Low-Rank Adaptation (LoRA) for computational efficiency and continuous model updates. Additionally, LABO provides a Python library for building model training pipelines and customizing agents for specific tasks.

Trace is a new AutoDiff-like tool for training AI systems end-to-end with general feedback. It generalizes the back-propagation algorithm by capturing and propagating an AI system's execution trace. Implemented as a PyTorch-like Python library, users can write Python code directly and use Trace primitives to optimize certain parts, similar to training neural networks.

AXAR AI is a lightweight framework designed for building production-ready agentic applications using TypeScript. It aims to simplify the process of creating robust, production-grade LLM-powered apps by focusing on familiar coding practices without unnecessary abstractions or steep learning curves. The framework provides structured, typed inputs and outputs, familiar and intuitive patterns like dependency injection and decorators, explicit control over agent behavior, real-time logging and monitoring tools, minimalistic design with little overhead, model agnostic compatibility with various AI models, and streamed outputs for fast and accurate results. AXAR AI is ideal for developers working on real-world AI applications who want a tool that gets out of the way and allows them to focus on shipping reliable software.

SuperPrompt is an open-source project designed to help users understand AI agents. The project includes a prompt with theoretical, mathematical, and binary instructions for users to follow. It aims to serve as a universal catalyst for infinite conceptual evolution, focusing on metamorphic abstract reasoning and self-transcending objectives. The prompt encourages users to explore fundamental truths, create order from cognitive chaos, and prepare for paradigm shifts in understanding. It provides guidelines for analyzing multidimensional states, synthesizing emergent patterns, and integrating new paradigms.

LeRobot is a state-of-the-art AI library for real-world robotics in PyTorch. It aims to provide models, datasets, and tools to lower the barrier to entry to robotics, focusing on imitation learning and reinforcement learning. LeRobot offers pretrained models, datasets with human-collected demonstrations, and simulation environments. It plans to support real-world robotics on affordable and capable robots. The library hosts pretrained models and datasets on the Hugging Face community page.

Delphi OpenAI API is an unofficial library providing Delphi implementation over OpenAI public API. It allows users to access various models, make completions, chat conversations, generate images, and call functions using OpenAI service. The library aims to facilitate tasks such as content generation, semantic search, and classification through AI models. Users can fine-tune models, work with natural language processing, and apply reinforcement learning methods for diverse applications.

dLLM-RL is a revolutionary reinforcement learning framework designed for Diffusion Large Language Models. It supports various models with diverse structures, offers inference acceleration, RL training capabilities, and SFT functionalities. The tool introduces TraceRL for trajectory-aware RL and diffusion-based value models for optimization stability. Users can download and try models like TraDo-4B-Instruct and TraDo-8B-Instruct. The tool also provides support for multi-node setups and easy building of reinforcement learning methods. Additionally, it offers supervised fine-tuning strategies for different models and tasks.

LETSQL is a data processing library built on top of Ibis and DataFusion to write multi-engine data workflows. It is currently in development and does not have a stable release. Users can install LETSQL from PyPI and use it to connect to data sources, read data, filter, group, and aggregate data for analysis. Contributions to the project are welcome, and the library is actively maintained with support available for any issues. LETSQL heavily relies on Ibis and DataFusion for its functionality.

Skyrim is a weather forecasting tool that enables users to run large weather models using consumer-grade GPUs. It provides access to state-of-the-art foundational weather models through a well-maintained infrastructure. Users can forecast weather conditions, such as wind speed and direction, by running simulations on their own GPUs or using modal volume or cloud services like s3 buckets. Skyrim supports various large weather models like Graphcast, Pangu, Fourcastnet, and DLWP, with plans for future enhancements like ensemble prediction and model quantization.

aiomultiprocess is a Python library that combines AsyncIO and multiprocessing to achieve high levels of concurrency in Python applications. It allows running a full AsyncIO event loop on each child process, enabling multiple coroutines to execute simultaneously. The library provides a simple interface for executing asynchronous tasks on a pool of worker processes, making it easy to gather large amounts of network requests quickly. aiomultiprocess is designed to take Python codebases to the next level of performance by leveraging the combined power of AsyncIO and multiprocessing.

OpenDevin is an open-source project aiming to replicate Devin, an autonomous AI software engineer capable of executing complex engineering tasks and collaborating actively with users on software development projects. The project aspires to enhance and innovate upon Devin through the power of the open-source community. Users can contribute to the project by developing core functionalities, frontend interface, or sandboxing solutions, participating in research and evaluation of LLMs in software engineering, and providing feedback and testing on the OpenDevin toolset.

Data-Oriented GOAP (Goal-Oriented Action Planning) is a library that implements GOAP in a data-oriented way, allowing for dynamic setup of states, actions, and goals. It includes bevy_dogoap for Bevy integration. It is useful for NPCs performing tasks dependent on each other, enabling NPCs to improvise reaching goals, and offers a middle ground between Utility AI and HTNs. The library is inspired by the F.E.A.R GDC talk and provides a minimal Bevy example for implementation.

Community plugins repository for Google Firebase Genkit, containing various plugins for AI APIs and Vector Stores. Developed by The Fire Company, this repository offers plugins like genkitx-anthropic, genkitx-cohere, genkitx-groq, genkitx-mistral, genkitx-openai, genkitx-convex, and genkitx-hnsw. Users can easily install and use these plugins in their projects, with examples provided in the documentation. The repository also showcases products like Fireview and Giftit built using these plugins, and welcomes contributions from the community.

ComposeAI is an Android & iOS application similar to ChatGPT, built using Compose Multiplatform. It utilizes various technologies such as Compose Multiplatform, Material 3, OpenAI Kotlin, Voyager, Koin, SQLDelight, Multiplatform Settings, Coil3, Napier, BuildKonfig, Firebase Analytics & Crashlytics, and AdMob. The app architecture follows Google's latest guidelines. Users need to set up their own OpenAI API key before using the app.

aiogram is a modern and fully asynchronous framework for Telegram Bot API written in Python 3.8+ using asyncio and aiohttp. It helps users create faster and more powerful bots. The framework supports features such as asynchronous operations, type hints, PyPy support, Telegram Bot API integration, router updates, Finite State Machine, magic filters, middlewares, webhook replies, and I18n/L10n support with GNU Gettext or Fluent. Prior experience with asyncio is recommended before using aiogram.

Nerve is a tool that allows creating stateful agents with any LLM of your choice without writing code. It provides a framework of functionalities for planning, saving, or recalling memories by dynamically adapting the prompt. Nerve is experimental and subject to changes. It is valuable for learning and experimenting but not recommended for production environments. The tool aims to instrument smart agents without code, inspired by projects like Dreadnode's Rigging framework.

Reasonable Planning AI is a robust design and data-driven AI solution for game developers. It provides an AI Editor that allows creating AI without Blueprints or C++. The AI can think for itself, plan actions, adapt to the game environment, and act dynamically. It consists of Core components like RpaiGoalBase, RpaiActionBase, RpaiPlannerBase, RpaiReasonerBase, and RpaiBrainComponent, as well as Composer components for easier integration by Game Designers. The tool is extensible, cross-compatible with Behavior Trees, and offers debugging features like visual logging and heuristics testing. It follows a simple path of execution and supports versioning for stability and compatibility with Unreal Engine versions.

This repository is a curated list of papers related to World Models for General Video Generation, Embodied AI, and Autonomous Driving. It includes foundation papers, blog posts, technical reports, surveys, benchmarks, and specific world models for different applications. The repository serves as a valuable resource for researchers and practitioners interested in world models and their applications in robotics and AI.

DotRecast is a C# port of Recast & Detour, a navigation library used in many AAA and indie games and engines. It provides automatic navmesh generation, fast turnaround times, detailed customization options, and is dependency-free. Recast Navigation is divided into multiple modules, each contained in its own folder: - DotRecast.Core: Core utils - DotRecast.Recast: Navmesh generation - DotRecast.Detour: Runtime loading of navmesh data, pathfinding, navmesh queries - DotRecast.Detour.TileCache: Navmesh streaming. Useful for large levels and open-world games - DotRecast.Detour.Crowd: Agent movement, collision avoidance, and crowd simulation - DotRecast.Detour.Dynamic: Robust support for dynamic nav meshes combining pre-built voxels with dynamic objects which can be freely added and removed - DotRecast.Detour.Extras: Simple tool to import navmeshes created with A* Pathfinding Project - DotRecast.Recast.Toolset: All modules - DotRecast.Recast.Demo: Standalone, comprehensive demo app showcasing all aspects of Recast & Detour's functionality - Tests: Unit tests Recast constructs a navmesh through a multi-step mesh rasterization process: 1. First Recast rasterizes the input triangle meshes into voxels. 2. Voxels in areas where agents would not be able to move are filtered and removed. 3. The walkable areas described by the voxel grid are then divided into sets of polygonal regions. 4. The navigation polygons are generated by re-triangulating the generated polygonal regions into a navmesh. You can use Recast to build a single navmesh, or a tiled navmesh. Single meshes are suitable for many simple, static cases and are easy to work with. Tiled navmeshes are more complex to work with but better support larger, more dynamic environments. Tiled meshes enable advanced Detour features like re-baking, hierarchical path-planning, and navmesh data-streaming.

The 'bots' repository is a collection of guides, tools, and example bots for programming bots to play video games. It provides resources on running bots live, installing the BotLab client, debugging bots, testing bots in simulated environments, and more. The repository also includes example bots for games like EVE Online, Tribal Wars 2, and Elvenar. Users can learn about developing bots for specific games, syntax of the Elm programming language, and tools for memory reading development. Additionally, there are guides on bot programming, contributing to BotLab, and exploring Elm syntax and core library.

Half-Life-Resurgence is a recreation and expansion project that brings NPCs, entities, and weapons from the Half-Life series into Garry's Mod. The goal is to faithfully recreate original content while also introducing new features and custom content envisioned by the community. Users can expect a wide range of NPCs with new abilities, AI behaviors, and weapons, as well as support for playing as any character and replacing NPCs in Half-Life 1 & 2 campaigns.

Sword Coast Stratagems (SCS) is a mod that enhances Baldur's Gate games by adding over 130 optional components focused on improving monster AI, encounter difficulties, cosmetic enhancements, and ease-of-use tweaks. This repository serves as an archive for the project, with updates pushed only when new releases are made. It is not a collaborative project, and bug reports or suggestions should be made at the Gibberlings 3 forums. The mod is designed for offline workflow and should be downloaded from official releases.

LAMBS Danger FSM is an open-source mod developed for Arma3, aimed at enhancing the AI behavior by integrating buildings into the tactical landscape, creating distinct AI states, and ensuring seamless compatibility with vanilla, ACE3, and modded assets. Originally created for the Norwegian gaming community, it is now available on Steam Workshop and GitHub for wider use. Users are allowed to customize and redistribute the mod according to their requirements. The project is licensed under the GNU General Public License (GPLv2) with additional amendments.

Beehave is a powerful addon for Godot Engine that enables users to create robust AI systems using behavior trees. It simplifies the design of complex NPC behaviors, challenging boss battles, and other advanced setups. Beehave allows for the creation of highly adaptive AI that responds to changes in the game world and overcomes unexpected obstacles, catering to both beginners and experienced developers. The tool is currently in development for version 3.0.

Thinker is an AI improvement mod for Alpha Centauri: Alien Crossfire that enhances single player challenge and gameplay with features like improved production/movement AI, visual changes on map rendering, more config options, resolution settings, and automation features. It includes Scient's patches and requires the GOG version of Alpha Centauri with the official Alien Crossfire patch version 2.0 installed. The mod provides additional DLL features developed in C++ for a richer gaming experience.

MobChip is an all-in-one Entity AI and Bosses Library for Minecraft 1.13 and above. It simplifies the implementation of Minecraft's native entity AI into plugins, offering documentation, API usage, and utilities for ease of use. The library is flexible, using Reflection and Abstraction for modern functionality on older versions, and ensuring compatibility across multiple Minecraft versions. MobChip is open source, providing features like Bosses Library, Pathfinder Goals, Behaviors, Villager Gossip, Ender Dragon Phases, and more.