Best AI tools for< Middleware Developer >

The website provides a platform for Full-Stack Cloud Observability with a focus on Middleware. It offers comprehensive monitoring and analysis tools for cloud-based applications, enabling users to gain insights into the performance and health of their middleware components. The platform supports real-time data collection, visualization, and alerting to help users optimize their cloud infrastructure and ensure seamless operation.

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.

The Microsoft AI Chat Protocol SDK is a library for easily building AI Chat interfaces from services that follow the AI Chat Protocol API Specification. By agreeing on a standard API contract, AI backend consumption and evaluation can be performed easily and consistently across different services. It allows developers to develop AI chat interfaces, consume and evaluate AI inference backends, and incorporate HTTP middleware for logging and authentication.

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.

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.

aiohttp_debugtoolbar provides a debug toolbar for aiohttp web applications. It is a port of pyramid_debugtoolbar and offers basic functionality such as basic panels, intercepting redirects, pretty printing exceptions, an interactive python console, and showing source code. The library is still in early development stages and offers various debug panels for monitoring different aspects of the web application. It is a useful tool for developers working with aiohttp to debug and optimize their applications.

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.

LangServe helps developers deploy `LangChain` runnables and chains as a REST API. This library is integrated with FastAPI and uses pydantic for data validation. In addition, it provides a client that can be used to call into runnables deployed on a server. A JavaScript client is available in LangChain.js.

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 Azure AI Samples repository is a collection of official Azure AI sample code and examples, including notebooks and code snippets for common developer tasks. It provides end-to-end samples for trying out Azure AI scenarios on a local machine. The repository is open source and offers guidance on contributing and links to additional repositories for various AI-related tasks and projects.

AIGES is a core component of the Athena Serving Framework, designed as a universal encapsulation tool for AI developers to deploy AI algorithm models and engines quickly. By integrating AIGES, you can deploy AI algorithm models and engines rapidly and host them on the Athena Serving Framework, utilizing supporting auxiliary systems for networking, distribution strategies, data processing, etc. The Athena Serving Framework aims to accelerate the cloud service of AI algorithm models and engines, providing multiple guarantees for cloud service stability through cloud-native architecture. You can efficiently and securely deploy, upgrade, scale, operate, and monitor models and engines without focusing on underlying infrastructure and service-related development, governance, and operations.

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.

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_session is a Python library that provides session management for aiohttp.web applications. It allows storing user-specific data in session objects with a dict-like interface. The library offers different session storage options, including SimpleCookieStorage for testing, EncryptedCookieStorage for secure data storage, and RedisStorage for storing data in Redis. Users can easily integrate session management into their aiohttp.web applications by registering the session middleware. The library is designed to simplify session handling and enhance the security of web applications.

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.

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.

Sandbox is an open-source cloud-based code editing environment with custom AI code autocompletion and real-time collaboration. It consists of a frontend built with Next.js, TailwindCSS, Shadcn UI, Clerk, Monaco, and Liveblocks, and a backend with Express, Socket.io, Cloudflare Workers, D1 database, R2 storage, Workers AI, and Drizzle ORM. The backend includes microservices for database, storage, and AI functionalities. Users can run the project locally by setting up environment variables and deploying the containers. Contributions are welcome following the commit convention and structure provided in the repository.

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.

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.

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.

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.

Nuxt coding assistant, with knowledge of the latest Nuxt documentation

Expert instructor on Wwise, the game audio middleware