Tag

The Claude Agent SDK for Python is an official library from Anthropic that enables developers to build, query, and interact with AI agents powered by Claude models, supporting tools, custom MCP servers, and hooks for advanced agentic workflows.

vLLM is a high-throughput, memory-efficient inference and serving engine for large language models (LLMs), built to deliver state-of-the-art performance on GPUs with features such as PagedAttention and continuous batching.

LightRAG is an open-source framework designed for simple and fast Retrieval-Augmented Generation (RAG), integrating knowledge graphs, vector search, and efficient LLM-based processing to enhance question-answering over large document collections.

The OpenAI Agents SDK is a lightweight yet powerful framework for building multi-agent workflows. It is provider-agnostic, supporting the OpenAI Responses and Chat Completions APIs, as well as 100+ other LLMs via integrations like LiteLLM.

Milvus is a high-performance, cloud-native vector database built for scalable vector ANN search. It powers AI applications by efficiently organizing and searching vast amounts of unstructured data, such as text, images, and multi-modal information.

Claude Quickstarts is a collection of projects by Anthropic to help developers quickly build deployable applications using the Claude API. It includes quickstarts for a customer support agent, financial data analyst, computer use demo, and autonomous coding agent, demonstrating Claude's capabilities in natural language processing, data analysis, computer control, and automated coding.

Cognee is an open-source tool that provides persistent and dynamic AI memory for agents by combining vector search with graph databases, replacing traditional RAG systems with scalable ECL pipelines.

An open-source, code-first Python toolkit for building, evaluating, and deploying sophisticated AI agents with flexibility and control.

A free, open-source Python library that offers a unified API for classical machine-learning algorithms, data-pre-processing, model selection and evaluation.

Memori is an open-source SQL-native memory engine designed for LLMs, AI agents, and multi-agent systems, providing persistent, queryable memory using standard SQL databases with a single line of code integration.

A lightweight open-source platform for running, managing, and integrating large language models locally via a simple CLI and REST API.

Open-source framework that accelerates fine-tuning and full training of transformer LLMs by up to 30 × while cutting VRAM requirements by roughly 90 %, letting developers train custom models quickly on commodity GPUs.