Transform your ideas with structured AI-powered brainstorming methods Built with Next.js, TypeScript, and OpenAI's GPT models
Les fonctionnalités principales de azzedde/brainstormers sont : Developer Toolkits.
Les alternatives open-source à azzedde/brainstormers incluent : andrestorres123/delve — This project implements TnT-LLM, a framework designed for large-scale text mining using Large Language Models (LLMs).… bessouat40/raglight — RAGLight is a lightweight and modular Python library for implementing Retrieval-Augmented Generation (RAG). It… chopratejas/headroom — Headroom is an AI gateway proxy and token optimizer designed to reduce the cost and latency of large language model… cryxnet/deepmcpagent — The foundation layer for agentic intelligence. cubaseuser123/cellwise-langraph-notebook-agent — Automated Documentation: Generates a parallel docs.md file for every notebook you run. - Context-Aware: Uses… akamai/patchdiff-ai — Feed it CVE-2025-29824. Get back a markdown report that names the buggy function, shows the pre/post-patch decompiled…
This project implements TnT-LLM, a framework designed for large-scale text mining using Large Language Models (LLMs). TnT-LLM automates two core tasks: label taxonomy generation and text classification, both of which traditionally require significant manual effort and domain expertise.
RAGLight is a lightweight and modular Python library for implementing Retrieval-Augmented Generation (RAG). It enhances the capabilities of Large Language Models (LLMs) by combining document retrieval with natural language inference.
Headroom is an AI gateway proxy and token optimizer designed to reduce the cost and latency of large language model interactions. It functions as an intermediary that intercepts traffic between clients and providers to apply context compression, request routing, and format translation. The system differentiates itself through a Model Context Protocol server implementation that delivers compression and retrieval tools to compatible AI hosts. It employs a content-aware compression pipeline and tiered importance scoring to trim redundant data from logs and tool outputs while preserving essential
Feed it CVE-2025-29824. Get back a markdown report that names the buggy function, shows the pre/post-patch decompiled C, walks the trigger flow, and attaches a confidence score and per-call cost trace.