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llm

A flexible AI coding agent for the CLI, powered by a customizable prompt engine.

🔎 Type @perplexity in browser omnibox to get results from Perplexity AI

https://monnef.gitlab.io/by-ai

💬 Epic prompts to turbo-charge your LLM chatbots.

Workflow Specific Language (WSL) provides a flexible architecture for creating complex, multi-step workflows with AI agents. It implements common enterprise integration patterns using a robust chain-based approach that allows for seamless composition of different processing units.

A utility for instant grammar correction in any text field via keyboard shortcut, powered by Large Language Models (LLM).

https://grammarchecker.sourceforge.net/

AIQA (AI Questions Answering) — локальный стек для построения сервиса вопросов-ответов на базе LLM и векторных представлений. Быстрое развертывание в Docker, устойчивое хранение знаний и удобный API для интеграции.

This project allows to launch your Telegram bot in a few minutes to communicate with free or paid AI models via OpenRouter.

High-level abstraction supporting code, data, and natural language description function definitions.

A modern TypeScript SDK for the Secton API with intelligent streaming and conversation management

Prompt Evaluator is a lightweight tool for evaluating and scoring AI-generated prompts and responses with CalypsoAI. It helps assess quality, relevance, and safety using customizable criteria, making it ideal for testing LLM outputs in a structured, repeatable way.

Emacs AI-powered text & code completion client

Pulse Agent is a lightweight, extensible platform for creating ephemeral AI agents using Microsoft’s AutoGen framework. It enables rapid deployment of task-specific agents without the need for persistent infrastructure. Ideal for use cases like customer support, data analysis, content generation, and research assistance, Pulse Agent allows you to dynamically configure and run AI agents that live only as long as they're needed.

🗒️Sample playground project that showcases dynamic document generation analysis using an LLM.