ruihuihou's starred repositories
Qwen-Agent
Agent framework and applications built upon Qwen2, featuring Function Calling, Code Interpreter, RAG, and Chrome extension.
openai-cookbook
Examples and guides for using the OpenAI API
one-api
OpenAI 接口管理 & 分发系统,支持 Azure、Anthropic Claude、Google PaLM 2 & Gemini、智谱 ChatGLM、百度文心一言、讯飞星火认知、阿里通义千问、360 智脑以及腾讯混元,可用于二次分发管理 key,仅单可执行文件,已打包好 Docker 镜像,一键部署,开箱即用. OpenAI key management & redistribution system, using a single API for all LLMs, and features an English UI.
llama_index
LlamaIndex is a data framework for your LLM applications
Conference-Acceptance-Rate
Acceptance rates for the major AI conferences
LLMAgentPapers
Must-read Papers on LLM Agents.
agentscope
Start building LLM-empowered multi-agent applications in an easier way.
KwaiAgents
A generalized information-seeking agent system with Large Language Models (LLMs).
modelscope-agent
ModelScope-Agent: An agent framework connecting models in ModelScope with the world
Awesome-Papers-Autonomous-Agent
A collection of recent papers on building autonomous agent. Two topics included: RL-based / LLM-based agents.
Awesome-LLM-Healthcare
The paper list of the review on LLMs in medicine - "Large Language Models Illuminate a Progressive Pathway to Artificial Healthcare Assistant: A Review".
LLaMA-Factory
Efficiently Fine-Tune 100+ LLMs in WebUI (ACL 2024)
AgentTuning
AgentTuning: Enabling Generalized Agent Abilities for LLMs
OpenAgents
[COLM 2024] OpenAgents: An Open Platform for Language Agents in the Wild
opencompass
OpenCompass is an LLM evaluation platform, supporting a wide range of models (Llama3, Mistral, InternLM2,GPT-4,LLaMa2, Qwen,GLM, Claude, etc) over 100+ datasets.
gpt_academic
为GPT/GLM等LLM大语言模型提供实用化交互接口,特别优化论文阅读/润色/写作体验,模块化设计,支持自定义快捷按钮&函数插件,支持Python和C++等项目剖析&自译解功能,PDF/LaTex论文翻译&总结功能,支持并行问询多种LLM模型,支持chatglm3等本地模型。接入通义千问, deepseekcoder, 讯飞星火, 文心一言, llama2, rwkv, claude2, moss等。
Agently
[AI Agent Application Development Framework] - 🚀 Build AI agent native application in very few code 💬 Easy to interact with AI agent in code using structure data and chained-calls syntax 🧩 Enhance AI Agent using plugins instead of rebuild a whole new agent