Agents

A Conceptual Framework

文章

1. AI Agent（智能体）技术白皮书（Google，2024）
   • 中文：https://arthurchiao.art/blog/ai-agent-white-paper-zh/
   • 英文：https://github.com/MIG217/Agents/blob/main/Whitepaper/Newwhitepaper_Agents2.pdf
2. Building effective agents (Anthropic, 2024)
   • 中文：https://arthurchiao.art/blog/build-effective-ai-agent-zh/
   • 英文：https://www.anthropic.com/research/building-effective-agents
   • 文章中给的一些例子：https://github.com/anthropics/anthropic-cookbook/tree/main/patterns/agents
3. Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and Beyond(Amazon, 2023)
   • summary: 大语言模型（LLMs）实用指南, 主要关注下游 NLP 任务中如何使用 LLM
   • paper: https://arxiv.org/abs/2304.13712
   • github: https://github.com/Mooler0410/LLMsPracticalGuide

Relevant agent workshops and talks

• ICLR Workshop on LLM Agents: https://iclr.cc/virtual/2024/workshop/20575
• Trustworthy Multi-modal Foundation Models and AI Agents (TiFA): https://icml.cc/virtual/2024/workshop/29951
• Multi-modal Foundation Model meets Embodied AI ICML: https://icml.cc/virtual/2024/workshop/29957
• NeurIPS 2024 Workshop on Open-World Agents, Towards Safe & Trustworthy Agents
  • https://neurips.cc/virtual/2024/workshop/84729
• Princeton PLI Workshop on Useful and Reliable AI Agents
• CMU Agent Workshop 2024
• CoRL 2024 Workshop on Language and Robot Learning
• CoRL 2024 Workshop on X-Embodiment Robot Learning
• FAccT 2024 Tutorial on LM Agents: Prospects and Impacts

Blog

1. Jason Brownlee创建，侧重机器学习、深度学习和DS；Python； https://machinelearningmastery.com/
2. Julia Silge创建，侧重R语言和tidyverse；https://juliasilge.com/
3. Rob J. Hyndman 维护，侧重时间序列；https://robjhyndman.com/hyndsight/
4. caret R 包的官方文档；https://topepo.github.io/caret/
5. Richard S. Sutton：http://incompleteideas.net/
6. Shunyu Yao，CoALA和ReAct的论文 也很值得看 https://ysymyth.github.io/
7. https://lilianweng.github.io/

Datasets

1. GitHub 资源合集，收集了各类 公开可用的数据集；https://github.com/smuthubabu/awesome-public-datasets
2. AWS提供的开放数据存储平台; https://registry.opendata.aws/
3. 全球开放数据门户的集合: https://dataportals.org/search
4. 欧洲各国和地区发布的开放数据集: https://opendatamonitor.eu/frontend/web/index.php?r=datacatalogue%2Flist&page=1&per-page=10

Agent平台

1. Dify: https://cloud.dify.ai/apps
2. AutoGen 更适合multi-agent
3. Langchain
4. IBM watsonx.ai https://www.ibm.com/products/watsonx-ai/ai-agent-development
5. FastGPT https://cloud.tryfastgpt.ai/app/list
6. coze

Mooc

1. UC Berkeley CS294/194-196 Large Language Model Agents： CS294/194-196 Large Language Model Agents
2. UC Berkeley CS294/194-280 Advanced Large Language Model Agents: https://rdi.berkeley.edu/adv-llm-agents/sp25
3. DeepLearning.AI Multi AI Agent Systems with crewAI: https://learn.deeplearning.ai/courses/multi-ai-agent-systems-with-crewai

Prompt Engineering

1. OpenAI Cookbook有许多关于如何有效利用 LLM 的深入示例。
2. 提示词工程指南库包含有关prompt工程的相当全面的教育材料集合。