Search Results for "pc-basic - a gw-basic emulator"
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Showing 19 open source projects for "pc-basic - a gw-basic emulator"
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OpenAI Assistants Quickstart
OpenAI Assistants API quickstart with Next.js
...Server handlers for threads are provided under api/assistants/threads/..., giving a reference for wiring the API into Next.js routes. The Chat component can be copied directly into other projects, along with its styles from app/components/chat.module.css. Example pages include a basic chat, a function calling demo, a file search demo, and a full-featured example, allowing developers to explore each feature in isolation or together. -
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DeepChat
A smart assistant that connects powerful AI to your personal world
...Whether you're using cloud APIs like OpenAI, Gemini, Anthropic, or locally deployed Ollama models, DeepChat delivers a smooth user experience. As a cross-platform AI assistant application, DeepChat not only supports basic chat functionality but also offers advanced features such as search enhancement, tool calling, and multimodal interaction, making AI capabilities more accessible and efficient. -
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Glowby
Glowby Basic helps you create your own voice-based AI assistants
Glowby is an open-source platform designed to assist users in creating and sharing interactive educational content, enabling collaborative learning experiences. -
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Lecca.io
Lecca.io | AI Agents & Automations
Lecca.io is an AI platform that allows you to configure and deploy Large Language Models (LLMs) equipped with powerful tools and workflows. Build, customize, and automate your AI agents with ease. -
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LiteMultiAgent
The Library for LLM-based multi-agent applications
LiteMultiAgent is a lightweight and extensible multi-agent reinforcement learning (MARL) platform designed for rapid experimentation. It allows researchers to design and test coordination, competition, and collaboration scenarios in simulated environments. -
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Hindsight
Hindsight: Agent Memory That Learns
...It addresses one of the core limitations of modern AI agents, which is their inability to retain and meaningfully use past experiences over time, by introducing a structured, biomimetic memory architecture inspired by how human memory works. Instead of relying solely on vector similarity or basic retrieval techniques, Hindsight organizes information into distinct categories such as facts, experiences, beliefs, and observations, allowing agents to differentiate between raw data and inferred knowledge. The system operates through three core mechanisms—retain, recall, and reflect—which respectively handle storing information, retrieving relevant context, and generating new insights based on accumulated experience. -
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Swift Concurrency Agent Skill
Add expert Swift Concurrency guidance to your AI coding tool
...The skill codifies practical best practices for writing efficient, safe, and modern concurrent Swift code and outlines how to modernize existing legacy code toward Swift 6 conventions. Rather than teaching basic Swift, it targets the nuanced behaviors of concurrency primitives, actor isolation, and safety annotations like @MainActor and Sendable. It also clarifies how to reason about structured tasks, cancellation, and performance trade-offs. -
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AI Agents Masterclass
Follow along with my AI Agents Masterclass videos
...Students of the masterclass can follow written modules or Jupyter notebooks that illustrate concepts step by step and progressively build more capable agents. The content is suitable for both beginners and intermediate developers because it starts with basic principles and escalates to advanced architectures like multi-agent coordination. -
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Mini Agent
A minimal yet professional single agent demo project
...The project exposes an Anthropic-compatible API interface and fully supports interleaved thinking, letting the agent alternate between reasoning steps and tool invocations during long, complex tasks. It includes a basic toolset for file-system operations and shell commands, plus integrations with MCP tools such as web search and knowledge graph access. Mini-Agent also comes with “Claude Skills”-style predefined skills for tasks like document processing, design work, and testing, packaged as reusable behaviors that can be invoked by the agent as needed. -
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MASLua
Multi-agent system modeling with Lua
A framework to simulate systems of agents in Lua on a 2D grid map, with modules for describing agent behavior and communication. A working example of a taxi fleet is given. The "basic" version uses conventional belief-desire-intention module (BDI.lua) for agent programming and a textual I/O. The "basic_EFSSM" version uses only state-oriented programming for agents. (Available soon.) --- Ribas-Xirgo, Ll.: Multi-agent system model of taxi fleets. In Advances in Physical Agents II, Springer International Publishing, 2021. ... -
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ILA - teachable voice assistant
ILA is a fully customizable and teachable voice assistant for Java
ILA stands for (kind of) intelligent, learning assistant and is a speech recognition system aka voice assistant very similar to Siri, Google Now and Cortana. ILA is fully customizable and you can teach her/him/it new things by yourself like executing system commands, opening web pages, programs and apps or just some basic conversation :-) ILA runs on Java und thus is compatible to Windows, Mac and Linux. It is designed to integrate with your home enviroment and for example build up your own, free and open Amazon Echo replacement ;-) Right now the key components of ILA are the open source speech recognition CMU Sphinx-4, Google (Speech Recognition/Text-To-Speech) and MaryTTS (Text-To-Speech). ... -
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ANGie
Alice Next Generation (internet entity)
...The ANGie project strives to have intelligent and sensible responses, but to allow the bot to have no response when the meaning of the input is inconclusive, when additional context would be required to properly respond, or in general for questions for which the bot is unprepared - in order to create a bot that is capable of carrying on basic conversations with a human similar to the sort of small talk that two humans might have. Requires PyAIMLng, PyGOAPng, and aimlGOAP. -
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The Star Ships Learning Framework (SSLF) provides basic routines and methods in order to interact with the space shooter Star Ships V2.1. It provides the necessary interfaces for controlling the program's ships and its logic from outside the game.
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...With the help of jGeohash, software developers will be able to quickly and easily generate a geohash code using user-defined latitude and longitude values. By using the GeoHash algorithm, the space can be divided into multiple grid shapes. This library is a basic implementation from the GeoHash algorithm written in the java can be applied to generate from the latitude and longitude a geohash code and reverse. The library is kept simple and have no dependencies to other libraries. For more information about the GeoHash algorithm go to (http://en.wikipedia.org/wiki/Geohash) Snapshot from source code are available at: https://github.com/astrapi69/jgeohash.git If you have suggestions or improvements of bugfixes please contribute back via github
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TuCSoN
TuCSoN tuple-based coordination middleware
TuCSoN (Tuple Centres Spread over the Network) is a tuple-based middleware for the coordination of distributed systems – including multi-agent systems, mobile agents and pervasive systems. -
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Multiagentsystem Ellipsis
Modular, agent-oriented and extendable agent toolkit.
...Ellipsis already comes with a predefined set of agents, offering basic services like agency, loader, holdingarea and migration. -
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A Checkers game implementation in Java that is optimized for AI's. It includes a basic GUI and a trainer for learning AI's. This started as a Checkers program for a Checkers AI contest in the Stanford EPGY 2008 summer AI course.
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The aim of this project is to develop an agent for Robocup3d. Evolution algorithms will be used to teach the agent all the required things, from basic movement to more complicated things like formations and team play.
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