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.

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.

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.

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.

Eino is an ultimate LLM application development framework in Golang, emphasizing simplicity, scalability, reliability, and effectiveness. It provides a curated list of component abstractions, a powerful composition framework, meticulously designed APIs, best practices, and tools covering the entire development cycle. Eino standardizes and improves efficiency in AI application development by offering rich components, powerful orchestration, complete stream processing, highly extensible aspects, and a comprehensive framework structure.

RAGxplorer is a tool designed to build visualisations for Retrieval Augmented Generation (RAG). It provides functionalities to interact with RAG models, visualize queries, and explore information retrieval tasks. The tool aims to simplify the process of working with RAG models and enhance the understanding of retrieval and generation processes.

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.

BeeAI Framework is a versatile tool for building production-ready multi-agent systems. It offers flexibility in orchestrating agents, seamless integration with various models and tools, and production-grade controls for scaling. The framework supports Python and TypeScript libraries, enabling users to implement simple to complex multi-agent patterns, connect with AI services, and optimize token usage and resource management.

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.

Burr is a Python library and UI that makes it easy to develop applications that make decisions based on state (chatbots, agents, simulations, etc...). Burr includes a UI that can track/monitor those decisions in real time.

Nous is an open-source TypeScript platform for autonomous AI agents and LLM based workflows. It aims to automate processes, support requests, review code, assist with refactorings, and more. The platform supports various integrations, multiple LLMs/services, CLI and web interface, human-in-the-loop interactions, flexible deployment options, observability with OpenTelemetry tracing, and specific agents for code editing, software engineering, and code review. It offers advanced features like reasoning/planning, memory and function call history, hierarchical task decomposition, and control-loop function calling options. Nous is designed to be a flexible platform for the TypeScript community to expand and support different use cases and integrations.

Codellm-devkit (CLDK) is a Python library that serves as a multilingual program analysis framework bridging traditional static analysis tools and Large Language Models (LLMs) specialized for code (CodeLLMs). It simplifies the process of analyzing codebases across multiple programming languages, enabling the extraction of meaningful insights and facilitating LLM-based code analysis. The library provides a unified interface for integrating outputs from various analysis tools and preparing them for effective use by CodeLLMs. Codellm-devkit aims to enable the development and experimentation of robust analysis pipelines that combine traditional program analysis tools and CodeLLMs, reducing friction in multi-language code analysis and ensuring compatibility across different tools and LLM platforms. It is designed to seamlessly integrate with popular analysis tools like WALA, Tree-sitter, LLVM, and CodeQL, acting as a crucial intermediary layer for efficient communication between these tools and CodeLLMs. The project is continuously evolving to include new tools and frameworks, maintaining its versatility for code analysis and LLM integration.

Chainlit is an open-source async Python framework which allows developers to build scalable Conversational AI or agentic applications. It enables users to create ChatGPT-like applications, embedded chatbots, custom frontends, and API endpoints. The framework provides features such as multi-modal chats, chain of thought visualization, data persistence, human feedback, and an in-context prompt playground. Chainlit is compatible with various Python programs and libraries, including LangChain, Llama Index, Autogen, OpenAI Assistant, and Haystack. It offers a range of examples and a cookbook to showcase its capabilities and inspire users. Chainlit welcomes contributions and is licensed under the Apache 2.0 license.

OpenAGI is a framework designed to make the development of autonomous human-like agents accessible to all. It aims to pave the way towards open agents and eventually AGI for everyone. The initiative strongly believes in the transformative power of AI and offers developers a platform to create autonomous human-like agents. OpenAGI features a flexible agent architecture, streamlined integration and configuration processes, and automated/manual agent configuration generation. It can be used in education for personalized learning experiences, in finance and banking for fraud detection and personalized banking advice, and in healthcare for patient monitoring and disease diagnosis.

MineStudio is a simple and efficient Minecraft development kit for AI research. It contains tools and APIs for developing Minecraft AI agents, including a customizable simulator, trajectory data structure, policy models, offline and online training pipelines, inference framework, and benchmarking automation. The repository is under development and welcomes contributions and suggestions.

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.