Showing 701-720 of 1,105 projects
An AI-powered tool to generate knowledge graphs from text data, with visualization capabilities.
An AI-powered framework for building web agents and deploying serverless automation on reliable browser infrastructure.
A tool that makes it easy to scrape and ingest content from various sources like GitHub, arXiv, and YouTube for use with large language models.
A Vim plugin that provides LLM-assisted code and text completion to boost developer productivity.
A Rust-based CLI tool that provides an agentic chat experience to build applications using natural language.
A Mac app for Ollama, a platform for developers focused on building with AI tools and prompts.
A developer-focused platform for text-to-speech, RAG, and LLMs, with local-first architecture.
Compares the performance of multiple NVIDIA GPUs and Apple Silicon for running large language model inference.
A comprehensive collection of tools, prompts, frameworks, and models for creating LLM agents and AI-powered applications.
Python bindings for Transformer models implemented in C/C++ using the GGML library.
A curated reading list for security, safety, and privacy of large language models (LLMs) and AI systems.
Text Generator is an Obsidian plugin that allows you to generate text content using various AI providers.
A Python library that trains a large language model on data from specific time periods to reduce modern bias.
Builds lightweight, extensible, and testable LLM Agents for developers
A secure low-code honeypot framework that leverages AI for system virtualization and preemptive cybersecurity.
An on-premises, OCR-free unstructured data extraction, markdown conversion and benchmarking toolkit.
Comprehensive resources for developers working with Generative AI, including projects, use cases, and interview prep.
Personal AI assistant in Rust with multi-provider LLMs, memory, sandboxed execution & MCP tools
This is a curated list of papers related to large language model (LLM) systems, useful for developers working with AI tools.
A comprehensive guide for building production-ready RAG-based LLM applications using the Ray framework.
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