A modular Python toolkit developed by the University of Innsbruck that integrates information retrieval, re-ranking, and RAG generation, featuring 40+ pre-processed datasets and single-line pipeline construction.
A tutorial repository by Neural Maze for building WhatsApp AI Agents, guiding developers through deployment and development.
An agentic graph language assistant framework developed by HKUDS, based on Llama3-8B, unifying predictive tasks (e.g., node classification) and generative tasks (e.g., text summarization) on graph data through collaborative agents for generation, planning, and execution.
An open-source reinforcement learning framework that trains multi-step agents for real-world tasks using GRPO, supporting Qwen2.5, Qwen3, Llama, and other large language models.
A modern framework for probabilistic programming and Bayesian analysis designed for research and data analytics, featuring intuitive APIs and flexible model definition capabilities。
A deep research agent framework from Tencent AI Lab that enables deep research and agent foundation model training. It's built with open-source tools, requiring only a Google Search API (which can be replaced with DuckDuckGo).
A trainable agent for role-playing that learns from actual experiences, characteristics, and emotions to simulate historical figures without requiring additional prompts or reference documents.
LLaVA-Plus is a multimodal assistant system that learns to use tools, combining large language models with visual capabilities to enable AI agents to perform general vision tasks.
DeepResearch is an open-source deep research agent developed by Alibaba, designed for long-horizon, deep information-seeking tasks. With 30.5 billion total parameters but only 3.3 billion activated per token, it demonstrates state-of-the-art performance across various agentic search benchmarks like Humanity's Last Exam, BrowseComp, and WebWalkerQA.
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