Search Results for "reasoning"
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Showing 14 open source projects for "reasoning"
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MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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EasyR1
An Efficient, Scalable, Multi-Modality RL Training Framework
...It emphasizes memory-efficient training strategies so you can train long-context or reasoning-dense models on commodity GPUs. The framework is also organized to help you compare training strategies (e.g., pure SFT vs. preference optimization) so you can see what actually moves metrics in math, code, and multi-step reasoning. For teams exploring open reasoning models, EasyR1 provides an opinionated yet flexible path from dataset to deployable checkpoints. -
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Quint Code
Structured reasoning framework for Claude Code, Gemini, and Cursor
Quint Code is a structured reasoning and decision-support framework aimed at making AI-assisted software engineering and decision workflows more rigorous and auditable. It implements the First Principles Framework (FPF) to guide users and AI tools through hypothesis generation, logical verification, evidence gathering, and documented decision making, reducing reliance on ad hoc or “vibe” coding. -
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Fulcro
A library for development of single-page full-stack web applications
Fulcro is a batteries-included, full-stack library for building data-driven web applications in Clojure and ClojureScript. It integrates seamlessly with React, supports web, native, and desktop (Electron) targets, and enables strong local reasoning while facilitating rapid development and scalable production-level UIs. The rewrite of Fulcro Inspect is available via the releases page of Fulcro Inspect. And there are preliminary instructions for using it with the latest Fulcro. The alpha versions of Fulcro 3.8 are alpha purely because of this development-time change and its potential issues, and are otherwise production-ready. -
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Workflow
A Swift and Kotlin library for making composable state machines
...Optimized for composability and scalability of features and screens. A library that supports writing business logic and complex UI navigation logic as state machines, thereby enabling confident reasoning about the state and validation of correctness. A unidirectional data flow library that uses immutable data within each Workflow. Data flows in a single direction from the source to the UI, and events in a single direction from the UI to the business logic. Each logical component area is separated into a Workflow with a finite set of states and the logic to transition between them. -
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Synkra AIOS
AI-Orchestrated System for Full Stack Development
...The framework includes features for project setup, environment configuration, deployment scaffolding, and intelligent code generation, potentially reducing time spent on boilerplate and repetitive engineering tasks. Synkra AIOS positions itself as a productivity middleware that integrates AI reasoning within traditional devops, front-end, and back-end workflows, allowing teams to produce production-ready applications faster. -
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Substrate
An Open-source Framework for Human Understanding, Meaning, Progress
Substrate is an open-source framework focused on human understanding, meaning, and progress. It aims to surface and structure conceptual objects—ideas, problems, beliefs, models, frames, goals, arguments, sources—to make them more transparent, discussable and actionable. The goal is to enable communities to collectively build and maintain a repository of these objects so that complex systems of meaning and progress can be mapped, analyzed and improved. It is relatively ambitious in... -
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AWS SigV4 Library
AWS library to sign AWS HTTP requests with Signature Version 4
...Deviations from the MISRA C:2012 guidelines are documented under MISRA Deviations. This library has also undergone static code analysis using Coverity static analysis, and validation of memory safety through the CBMC automated reasoning tool. -
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Make It heavy
A Python framework that emulates Grok Heavy functionality
...The framework uses OpenRouter for model access and can also run in single-agent mode for simpler tasks. Overall, it is useful for users who want broader research coverage, richer reasoning diversity, and structured multi-agent responses from one command-line workflow. -
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TradingAgents
Chinese Financial Trading Framework Based on Multi-Agent LLM
TradingAgents-CN is a Chinese-enhanced, multi-agent LLM framework aimed at building financial analysis and trading-oriented workflows, with an emphasis on collaboration between specialized agents rather than a single monolithic prompt. It organizes market-related tasks into roles and stages so different agents can contribute research, reasoning, aggregation, and decision support in a structured pipeline. The project is oriented toward practical usage, including a stack that can be run in a modern development environment and commonly paired with containerized backends, configuration files, and service components. It also pays attention to distribution and misuse risks, clearly warning users about unauthorized commercial repackaging and stating that commercial use requires explicit authorization while personal use is open. -
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Madara
Middleware for distributed applications
...MADARA was originally developed as an agent-based middleware specifically for real-time, distributed artificial intelligence, but is now more general purpose for distributed timing, control, knowledge and reasoning, and quality-of-service. MADARA is composed of several tools and middleware, and the main entry point into the system is the Knowledge and Reasoning Language (KaRL) Engine, which provides a real-time scripting language for nanosecond execution times hooked into a flexible transport layer for distributed reasoning. The KaRL engine also supports object-oriented C++, Java, and Python programming through Containers, classes that provide abstractions and references for variable location within the KaRL Knowledge Base. ... -
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The Panini Language
Better Modularity, Better Concurrency
...A central goal of the Panini language is to make concurrent programming easier and less error-prone. The main new feature in Panini is called a capsule. A capsule is like an actor but better because it largely retains the traditional approach for reasoning about programs as a sequence of operations, abstracts away all details of thread creation and locking, and supports fully-automatic compile-time analysis of common concurrency hazards. Panini is simple and efficient. We invite you to try it out. Downloads are available from http://paninij.org/download/ -
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The power provided by OWL reasoning engines can be translated into Java applications and vice versas with this framework. A binding among OWL and Java concepts has been done in order to incorporate the semantic features of OWL into Java.
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Hippal is an integrating GUI-framework for a multimodular symbolic A.I.-system IPAL, which combines A.I. Planning, Inductive Program Synthesis, Analogical Reasoning and Learning. Hippal is client-/server-based and uses the Lili Lisp Interpreter as Centr
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SATIN is a component model for mobile systems. It is a research project, and allows systems to adapt by a) Reasoning about what they can currently do b) send and recieve classes, objects, components and data. It is used in a number of projects.
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