Best AI tools for< Middleware Engineer >

The website offers Full-Stack Cloud Observability services with a focus on Middleware. It provides comprehensive monitoring and analysis tools for cloud-based applications, allowing users to gain insights into the performance and health of their middleware components. With a user-friendly interface and advanced features, it helps organizations optimize their cloud infrastructure and enhance overall system reliability.

Rozie AI is an AI partner that helps create personalized experiences at scale for leading brands. The platform offers a middleware solution, agentic AI capabilities, and pre-built experience kits to manage the entire process from ideation to implementation. Rozie AI specializes in experience design, digital engagement, and applying artificial intelligence to future-proof product experiences. The company empowers clients to own their experiences while off-loading the tech stack maintenance. With customizable solutions, Rozie AI delivers speed, scalability, and control for innovative CX solutions.

E.D.D.I (Enhanced Dialog Driven Interface) is an enterprise-certified chatbot middleware that offers advanced prompt and conversation management for Conversational AI APIs. Developed in Java using Quarkus, it is lean, RESTful, scalable, and cloud-native. E.D.D.I is highly scalable and designed to efficiently manage conversations in AI-driven applications, with seamless API integration capabilities. Notable features include configurable NLP and Behavior rules, support for multiple chatbots running concurrently, and integration with MongoDB, OAuth 2.0, and HTML/CSS/JavaScript for UI. The project requires Java 21, Maven 3.8.4, and MongoDB >= 5.0 to run. It can be built as a Docker image and deployed using Docker or Kubernetes, with additional support for integration testing and monitoring through Prometheus and Kubernetes endpoints.

Middleware is an open-source engineering management tool that helps engineering leaders measure and analyze team effectiveness using DORA metrics. It integrates with CI/CD tools, automates DORA metric collection and analysis, visualizes key performance indicators, provides customizable reports and dashboards, and integrates with project management platforms. Users can set up Middleware using Docker or manually, generate encryption keys, set up backend and web servers, and access the application to view DORA metrics. The tool calculates DORA metrics using GitHub data, including Deployment Frequency, Lead Time for Changes, Mean Time to Restore, and Change Failure Rate. Middleware aims to provide DORA metrics to users based on their Git data, simplifying the process of tracking software delivery performance and operational efficiency.

UniChat is a pipeline tool for creating online and offline chat-bots in Unity. It leverages Unity.Sentis and text vector embedding technology to enable offline mode text content search based on vector databases. The tool includes a chain toolkit for embedding LLM and Agent in games, along with middleware components for Text to Speech, Speech to Text, and Sub-classifier functionalities. UniChat also offers a tool for invoking tools based on ReActAgent workflow, allowing users to create personalized chat scenarios and character cards. The tool provides a comprehensive solution for designing flexible conversations in games while maintaining developer's ideas.

Gateway is a tool that streamlines requests to 100+ open & closed source models with a unified API. It is production-ready with support for caching, fallbacks, retries, timeouts, load balancing, and can be edge-deployed for minimum latency. It is blazing fast with a tiny footprint, supports load balancing across multiple models, providers, and keys, ensures app resilience with fallbacks, offers automatic retries with exponential fallbacks, allows configurable request timeouts, supports multimodal routing, and can be extended with plug-in middleware. It is battle-tested over 300B tokens and enterprise-ready for enhanced security, scale, and custom deployments.

hongbomiao.com is a personal research and development (R&D) lab that facilitates the sharing of knowledge. The repository covers a wide range of topics including web development, mobile development, desktop applications, API servers, cloud native technologies, data processing, machine learning, computer vision, embedded systems, simulation, database management, data cleaning, data orchestration, testing, ops, authentication, authorization, security, system tools, reverse engineering, Ethereum, hardware, network, guidelines, design, bots, and more. It provides detailed information on various tools, frameworks, libraries, and platforms used in these domains.

HAMi is a Heterogeneous AI Computing Virtualization Middleware designed to manage Heterogeneous AI Computing Devices in a Kubernetes cluster. It allows for device sharing, device memory control, device type specification, and device UUID specification. The tool is easy to use and does not require modifying task YAML files. It includes features like hard limits on device memory, partial device allocation, streaming multiprocessor limits, and core usage specification. HAMi consists of components like a mutating webhook, scheduler extender, device plugins, and in-container virtualization techniques. It is suitable for scenarios requiring device sharing, specific device memory allocation, GPU balancing, low utilization optimization, and scenarios needing multiple small GPUs. The tool requires prerequisites like NVIDIA drivers, CUDA version, nvidia-docker, Kubernetes version, glibc version, and helm. Users can install, upgrade, and uninstall HAMi, submit tasks, and monitor cluster information. The tool's roadmap includes supporting additional AI computing devices, video codec processing, and Multi-Instance GPUs (MIG).

The Caddy Defender plugin is a middleware for Caddy that allows you to block or manipulate requests based on the client's IP address. It provides features such as IP range filtering, predefined IP ranges for popular AI services, custom IP ranges configuration, and multiple responder backends for different actions like blocking, custom responses, dropping connections, returning garbage data, redirecting, and tarpitting to stall bots. The plugin can be easily installed using Docker or built with `xcaddy`. Configuration is done through the Caddyfile syntax with various options for responders, IP ranges, custom messages, and URLs.

WilmerAI is a middleware system designed to process prompts before sending them to Large Language Models (LLMs). It categorizes prompts, routes them to appropriate workflows, and generates manageable prompts for local models. It acts as an intermediary between the user interface and LLM APIs, supporting multiple backend LLMs simultaneously. WilmerAI provides API endpoints compatible with OpenAI API, supports prompt templates, and offers flexible connections to various LLM APIs. The project is under heavy development and may contain bugs or incomplete code.

MCP-Bridge is a middleware tool designed to provide an openAI compatible endpoint for calling MCP tools. It acts as a bridge between the OpenAI API and MCP tools, allowing developers to leverage MCP tools through the OpenAI API interface. The tool facilitates the integration of MCP tools with the OpenAI API by providing endpoints for interaction. It supports non-streaming and streaming chat completions with MCP, as well as non-streaming completions without MCP. The tool is designed to work with inference engines that support tool call functionalities, such as vLLM and ollama. Installation can be done using Docker or manually, and the application can be run to interact with the OpenAI API. Configuration involves editing the config.json file to add new MCP servers. Contributions to the tool are welcome under the MIT License.

The AI Horde is an enterprise-level ML-Ops crowdsourced distributed inference cluster for AI Models. This middleware can support both Image and Text generation. It is infinitely scalable and supports seamless drop-in/drop-out of compute resources. The Public version allows people without a powerful GPU to use Stable Diffusion or Large Language Models like Pygmalion/Llama by relying on spare/idle resources provided by the community and also allows non-python clients, such as games and apps, to use AI-provided generations.

The Spellbook Docker Compose repository contains the Docker Compose files for running the Spellbook AI Assistant stack. It requires ExLlama and a Nvidia Ampere or better GPU for real-time results. The repository provides instructions for installing Docker, building and starting containers with or without GPU, additional workers, Nvidia driver installation, port forwarding, and fresh installation steps. Users can follow the detailed guidelines to set up the Spellbook framework on Ubuntu 22, enabling them to run the UI, middleware, and additional workers for resource access.

AI System School is a curated list of research in machine learning systems, focusing on ML/DL infra, LLM infra, domain-specific infra, ML/LLM conferences, and general resources. It provides resources such as data processing, training systems, video systems, autoML systems, and more. The repository aims to help users navigate the landscape of AI systems and machine learning infrastructure, offering insights into conferences, surveys, books, videos, courses, and blogs related to the field.

Aino is an experimental HTTP framework for Elixir that uses elli instead of Cowboy like Phoenix and Plug. It focuses on writing handlers to process requests through middleware functions. Aino works on a token instead of a conn, allowing flexibility in adding custom keys. It includes built-in middleware for common tasks and a routing layer for defining routes. Handlers in Aino must return a token with specific keys for response rendering.

aiohttp is an async http client/server framework that supports both client and server side of HTTP protocol. It also supports both client and server Web-Sockets out-of-the-box and avoids Callback Hell. aiohttp provides a Web-server with middleware and pluggable routing.

FeedCraft is a powerful tool to process your rss feeds as a middleware. Use it to translate your feed, extract fulltext, emulate browser to render js-heavy page, use llm such as google gemini to generate brief for your rss article, use natural language to filter your rss feed, and more! It is an open-source tool that can be self-deployed and used with any RSS reader. It supports AI-powered processing using Open AI compatible LLMs, custom prompt, saving rules to apply to different RSS sources, portable mode for on-the-go usage, and dock mode for advanced customization of RSS sources and processing parameters.

Inspector is a code execution monitoring tool specifically designed for Laravel applications. It provides simple and efficient monitoring capabilities to track and analyze the performance of your Laravel code. With Inspector, you can easily monitor web requests, test the functionality of your application, and explore data through a user-friendly dashboard. The tool requires PHP version 7.2.0 or higher and Laravel version 5.5 or above. By configuring the ingestion key and attaching the middleware, users can seamlessly integrate Inspector into their Laravel projects. The official documentation provides detailed instructions on installation, configuration, and usage of Inspector. Contributions to the tool are welcome, and users are encouraged to follow the Contribution Guidelines to participate in the development of Inspector.

SimpleAI is a self-hosted alternative to the not-so-open AI API, focused on replicating main endpoints for LLM such as text completion, chat, edits, and embeddings. It allows quick experimentation with different models, creating benchmarks, and handling specific use cases without relying on external services. Users can integrate and declare models through gRPC, query endpoints using Swagger UI or API, and resolve common issues like CORS with FastAPI middleware. The project is open for contributions and welcomes PRs, issues, documentation, and more.

The jeecg-boot-starter is a module that simplifies projects and facilitates maintenance by extracting the starter module from jeecg-boot. It includes various sub-modules for common classes, cloud services, job scheduling, distributed locking, messaging middleware, distributed transactions, sharding databases, and MongoDB.

nlux is an open-source Javascript and React JS library that makes it super simple to integrate powerful large language models (LLMs) like ChatGPT into your web app or website. With just a few lines of code, you can add conversational AI capabilities and interact with your favourite LLM.

NLUX is an open-source JavaScript and React JS library that simplifies the integration of powerful large language models (LLMs) like ChatGPT into web apps or websites. With just a few lines of code, users can add conversational AI capabilities and interact with their favorite LLM. The library offers features such as building AI chat interfaces in minutes, React components and hooks for easy integration, LLM adapters for various APIs, customizable assistant and user personas, streaming LLM output, custom renderers, high customizability, and zero dependencies. NLUX is designed with principles of intuitiveness, performance, accessibility, and developer experience in mind. The mission of NLUX is to enable developers to build outstanding LLM front-ends and applications with a focus on performance and usability.

Expert instructor on Wwise, the game audio middleware

Nuxt coding assistant, with knowledge of the latest Nuxt documentation