Search Results for "reasoning" - Page 2
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Showing 73 open source projects for "reasoning"
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Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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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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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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Think Bayes 2
Text and code for the second edition of Think Bayes, by Allen Downey
Think Bayes 2 is the companion repository for the second edition of Allen B. Downey’s introduction to Bayesian statistics. It teaches Bayesian reasoning through computational methods instead of relying mainly on symbolic mathematics. Each chapter is presented as a Jupyter notebook where readers can study the text, run examples, and complete exercises. Separate solution materials help learners check their work and explore alternative approaches. The lessons cover probability distributions, Bayesian updating, estimation, prediction, comparison, and decision-making. ... -
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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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Cookbook (Google Gemini)
Examples and guides for using the Gemini API
...The repository covers a wide range of Gemini capabilities, including text, images, video, speech, robotics, and multimodal interactions. It highlights newly introduced features such as Gemini 2.5 models (Flash and Pro), Gemini’s native image generation, Veo for video generation, robotics-focused reasoning models, and Lyria for TTS and music generation. The Cookbook also includes tutorials on advanced API workflows such as grounding answers with external tools, batch-mode request handling, and live multimodal interactivity with LiveAPI. Designed as a hands-on resource, it helps developers quickly explore Gemini’s potential while serving as a reference for integrating cutting-edge multimodal AI into applications. -
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k-skill
Skill collection for Koreans - SRT, KTX, KakaoTalk, Hangul
The k-skill project is an AI skill management framework designed to organize, structure, and execute reusable capabilities within AI-driven development environments. It focuses on defining skills as modular, composable units that can be invoked by agents to perform specific tasks such as coding, reasoning, or automation. The system provides a standardized structure for skills, enabling consistency across different workflows and improving interoperability between tools. It is designed to integrate with modern AI agent ecosystems, allowing developers to extend functionality without rewriting core logic. The project emphasizes simplicity and modularity, making it easier to manage large collections of skills in complex environments. ... -
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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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Mangle
Go library for Datalog-style logical reasoning and domain modeling
Mangle is a programming language developed by Google for deductive database programming, serving as an advanced extension of Datalog. It is designed to unify and query data from multiple sources in a structured, declarative way while allowing developers to model complex relationships and domain knowledge beyond binary predicates. Mangle enhances traditional Datalog by introducing features such as aggregation, function calls, and optional type-checking, which make it more practical for modern... -
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AWS IoT Fleet Provisioning Library
Client library for using AWS IoT Fleet Provisioning service
...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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Cats Effect
The pure asynchronous runtime for Scala
...Cats-Effect offers capabilities like deferred execution, cancellation, resource safety (Resource), fiber concurrency (lightweight threads), and interoperation with underlying runtime platforms (JVM, Java concurrency, etc.). It enables developers to write effectful code while preserving composability, purity, and modular reasoning about side effects. -
Build Securely on AWS with Proven FrameworksMoving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.
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Scalaz
Principled Functional Programming in Scala
Scalaz is a foundational functional-programming library for Scala that provides type classes, data types, and syntax to write pure, composable code. It implements classic abstractions such as Functor, Applicative, Monad, Monoid, Foldable, and Traverse, along with powerful transformers (ReaderT, StateT, WriterT, OptionT, and more) to structure effects. The library offers rich data structures—\/ (disjunction), Validation, NonEmptyList, IList, and Free—that help model errors, invariants, and... -
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Formik
Build forms in React
...No fancy subscriptions or observables under the hood, just plain React state and props. By staying within the core React framework and away from magic, Formik makes debugging, testing, and reasoning about your forms a breeze. If you know React, and you know a bit about forms, you know Formik! Since form state is inherently local and ephemeral, Formik does not use external state management libraries like Redux or MobX. This also makes Formik easy to adopt incrementally and keeps bundle size to a minimum. -
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ARC-AGI
The Abstraction and Reasoning Corpus
...Unlike traditional machine learning benchmarks, ARC emphasizes generalization and reasoning over statistical pattern recognition, making it particularly challenging for current AI systems. The repository also includes a browser-based interface that allows humans to attempt solving the tasks manually, providing a baseline for comparison. -
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EulerSharp
Euler Yet another proof Engine
EYE [1] is a reasoning engine supporting the Semantic Web layers [2]. It performs controlled chaining and it supports Euler paths [3]. Via N3 [4] it is interoperable with Cwm [5]. [1] http://eulersharp.sourceforge.net/README [2] http://www.w3.org/DesignIssues/diagrams/sweb-stack/2006a [3] http://mathworld.wolfram.com/KoenigsbergBridgeProblem.html [4] http://www.w3.org/TeamSubmission/n3/ [5] http://www.w3.org/2000/10/swap/doc/cwm -
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Prompt Engineering Interactive Tutorial
Anthropic's Interactive Prompt Engineering Tutorial
...The course leans heavily on realistic failure modes (ambiguity, hallucination, brittle instructions) and shows how to iteratively debug prompts the way you would debug code. Lessons include building prompts from scratch for common tasks like extraction, classification, transformation, and step-by-step reasoning, with checkpoints that let you compare your outputs against solid baselines. You’ll also practice advanced patterns such as tool use, constrained generation, and response validation so outputs are trustworthy and machine-consumable. -
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JavaScript Questions
A long list of (advanced) JavaScript questions, and their explanations
...It covers tricky corners—hoisting, closures, coercion, event loop, prototypes, this binding, async/await, and more—through short prompts followed by illuminating answers. Explanations often include runnable snippets and step-through reasoning so you can replicate results locally. The content is curated to sharpen mental models rather than memorize trivia, making it valuable for interviews and day-to-day debugging alike. Because questions range from beginner to advanced, you can use it as a progressive study set or a quick refresher before assessments. It’s equally helpful for mentors: the questions can anchor study groups, workshops, or code-review discussions. -
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Metatheory.jl
General purpose algebraic metaprogramming
Metatheory.jl is a general purpose term rewriting, metaprogramming and algebraic computation library for the Julia programming language, designed to take advantage of the powerful reflection capabilities to bridge the gap between symbolic mathematics, abstract interpretation, equational reasoning, optimization, composable compiler transforms, and advanced homoiconic pattern matching features. The core features of Metatheory.jl are a powerful rewrite rule definition language, a vast library of functional combinators for classical term rewriting and an e-graph rewriting, a fresh approach to term rewriting achieved through an equality saturation algorithm. ... -
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Spring Hand Penetration Column
Aims to learn Spring source code and understand principles of Spring
...The project is especially useful for Java developers who find the full Spring source code too large or difficult to approach directly. It also connects implementation details with design patterns and architectural reasoning. -
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Flora-2 is a powerful knowledge representation and reasoning system designed for building knowledge-intensive applications. It is based on F-logic, HiLog, Transaction Logic, and also supports defeasible reasoning. Applications include intelligent agents, Semantic Web, ontology management, and more. If you use Flora-2 and like it, please acknowledge it in your project!
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Learning Prompt
Free prompt engineering online course
Learning-Prompt is a curated repository of prompts, techniques, and instructional patterns designed to help people construct better prompts for AI systems, including generation, reasoning, and debugging tasks. It collects examples of effective prompt formats, chains of thought, strategy scaffolds, and comparative methods that help yield consistent, high-quality results. The project also includes meta-guidance: reflections on prompt failures, tips for prompt tuning, ways to mitigate model bias or misinterpretation, and how to adapt prompts for different AI capabilities. ... -
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FOML is an expressive logic rule language that supports object modeling, analysis, and inference. It naturally supports model-level activities, such as constraints (extending UML diagrams), dynamic compositional modeling, analysis and reasoning about models, model testing, design pattern modeling, specification of Domain Specific Modeling Languages, and meta-modeling. FOML can reason about: 1. The model meta-data (meta-model level reasoning, or syntax reasoning) 2. Data level: reason about a model and its data (instance model, i.e., diagram) FOML is built as a semantic layer on top of PathLP - a compact logic rule language of guarded path expressions, an adaptation of a subset of F-logic.
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Guide to Technical Interviews
Guided collection and roadmap for preparing technical interviews
...The README breaks down preparation into categories — coding problems, system design, mock interview sites — so you can identify gap areas and allocate study time accordingly. Because interviews blend knowledge, strategy and habits (e.g., whiteboarding, communication, trade-off reasoning), the repository also emphasizes preparation workflows rather than just raw practice. It is therefore, an excellent companion for developers who have the technical skill and now need to convert it into interview readiness. -
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Vale
Compiler for the Vale programming language
...Vale also pursues what they call Fearless FFI to make foreign function interface (e.g. interoperating with C libraries) safer and less error-prone. The language supports single ownership semantics (so values have a unique owner, which simplifies reasoning) while also enabling aliasing under controlled circumstances. -
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Differentiable Neural Computer
A TensorFlow implementation of the Differentiable Neural Computer
The Differentiable Neural Computer (DNC), developed by Google DeepMind, is a neural network architecture augmented with dynamic external memory, enabling it to learn algorithms and solve complex reasoning tasks. Published in Nature in 2016 under the paper “Hybrid computing using a neural network with dynamic external memory,” the DNC combines the pattern recognition power of neural networks with a memory module that can be written to and read from in a differentiable way. This allows the model to learn how to store and retrieve information across long time horizons, much like a traditional computer. ... -
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Solved by Flexbox
A showcase of problems once hard or impossible to solve with CSS
Solved by Flexbox is a collection of layout patterns that demonstrates how CSS Flexbox elegantly resolves classic web design problems. It tackles everyday challenges—vertical centering, equal-height columns, sticky footers, fluid media, and responsive grids—showing concise, production-ready CSS instead of elaborate hacks. Each pattern is presented with plain HTML, clear commentary, and minimal styling, making the underlying technique easy to adapt and extend. The project emphasizes... -
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Euler
A distributed graph deep learning framework.
...Graph is a data type in non-Euclidean space and cannot be directly applied to existing methods, requiring a specially designed graph neural network system. Graph-based learning methods such as graph neural networks combine end-to-end learning with inductive reasoning, and are expected to solve a series of problems such as relational reasoning and interpretability that deep learning cannot handle.