#framework

Graph of Thoughts offers a flexible framework for tackling complex problems using large language models. Users can create custom Graphs of Operations for intuitive resolution or emulate conventional techniques like CoT and ToT. The framework seamlessly integrates with large language models to boost computational power. Comprehensive documentation and examples facilitate usage, catering to developers and general users alike. Installation is simple via PyPI or from the source for those interested in modification.

The framework facilitates organizing and maintaining pre-commit hooks in various programming languages, aiding in streamlining development workflows while ensuring code quality. It integrates seamlessly with Git to automate pre-change code standard enforcement. Known for its dependability and adaptability, it is a valuable tool for efficient code review processes. Explore the official website for detailed guides and resources to enhance its application in projects.

DDDplus, formerly known as cp-ddd-framework, is a lightweight framework enhancing Domain Driven Design (DDD) through forward and reverse business modeling, facilitating complex system architecture evolution. It fills the gaps in DDD by refining building blocks and enables domain model construction with visualized domain knowledge from code. Key features include effective forward modeling techniques, a comprehensive DSL for reverse modeling to visualize domain knowledge, and multiple extension point routing mechanisms suitable for complex business environments. Used in several central platform projects, DDDplus expedites design and development, ensuring adaptable and reliable software solutions. It offers seamless integration with SpringBoot for managing intricate business scenarios.

Discover an open-source framework for prompt-learning that enhances pre-trained language models to adapt to diverse NLP tasks through textual templates and PLMs. Key features include seamless integration with Huggingface transformers and flexible adaptable strategies for various applications. Stay informed about the latest project updates like UltraChat for supervised instruction tuning. OpenPrompt offers a standardized platform for simplified and efficient NLP model deployment.

Crafted to maintain stability in high-traffic environments, this framework incorporates advanced engineering practices such as adaptive circuit breakers, chained timeout control, and adaptive load shedding for effective microservice architecture management. It provides versatile code generation tools compatible with languages like Go and JavaScript, facilitating seamless API development and streamlining system deployments to boost productivity and service reliability.

RealWorld provides developers the flexibility to select from various frontend and backend technologies including React, Angular, Node, and Django, helping transition from demos to real projects. With over 100 implementations available, it acts as an extensive resource for learning full-stack development. Join discussions on GitHub to engage with the community and use available guides to craft your own RealWorld stack.

Caffe2 is an advanced deep learning framework, originally based on Caffe, now part of PyTorch for better scalability and adaptability.

Tauri empowers developers to produce compact, high-performance binaries for leading desktop platforms using its unique Rust-based backend. By utilizing familiar front-end frameworks, Tauri offers valuable tools such as app bundling, self-updates, and system tray integration. It supports an extensive range of systems, including Windows, macOS, Linux, iOS, and Android, ensuring broad usability. Developers benefit from seamless integration into existing workflows, backed by extensive documentation and active community support. Ideal for those aiming to create efficient, sustainable desktop applications with optimal speed and robust performance.

Pipcook is a JavaScript framework designed to simplify the integration of machine learning into web development. It supports modular architecture, including components like the Pipcook Pipeline and Bridge to Python, providing a flexible approach for training and deploying ML models. The framework offers tools for model training, serving predictions, and enhances the JavaScript ecosystem by allowing the use of Python libraries. It is ideal for web developers looking to incorporate intelligent features into their applications.

Explore an innovative machine learning framework specifically crafted for integration with Arm processors. This streamlined solution, derived from TensorFlow, allows developers to deploy and test models on embedded systems with minimal memory utilization, approximately 2KB. The architecture is designed for low-power usage, guaranteeing system safety and ease of debugging. It offers tutorials, high-level APIs, and customizable operators for operation optimization. Whether developing locally or using Arm Mbed OS, this framework assures adaptability and performance for cutting-edge edge computing applications.