o1

Enhanced ChatGPT Clone: Features Agents, MCP, Skills, DeepSeek, Anthropic, AWS, OpenAI, Responses API, Azure, Groq, o1, GPT-5, Mistral, OpenRouter, Vertex AI, Gemini, Artifacts, AI model switching, message search, Code Interpreter, langchain, DALL-E-3, OpenAPI Actions, Functions, Secure Multi-User Auth, Presets, open-source for self-hosting. Active

OpenAI API + Ruby! 🤖❤️ GPT-5 & Realtime WebRTC compatible!

LLM Agent Framework in ComfyUI includes MCP sever, Omost,GPT-sovits, ChatTTS,GOT-OCR2.0, and FLUX prompt nodes,access to Feishu,discord,and adapts to all llms with similar openai / aisuite interfaces, such as o1,ollama, gemini, grok, qwen, GLM, deepseek, kimi,doubao. Adapted to local llms, vlm, gguf such as llama-3.3 Janus-Pro, Linkage graphRAG

[NeurIPS 2025] 🌐 WebThinker: Empowering Large Reasoning Models with Deep Research Capability

Latest Advances on System-2 Reasoning

🔍 Search-o1: Agentic Search-Enhanced Large Reasoning Models [EMNLP 2025]

AI tutor powered by Theory-of-Mind reasoning

Latest Advances on Long Chain-of-Thought Reasoning

OpenAI API client library for Rust (unofficial)

This benchmark tests how well LLMs incorporate a set of 10 mandatory story elements (characters, objects, core concepts, attributes, motivations, etc.) in a short creative story

Collect every awesome work about r1!

Official codebase for "Can 1B LLM Surpass 405B LLM? Rethinking Compute-Optimal Test-Time Scaling".

Official implementation of GUI-R1 : A Generalist R1-Style Vision-Language Action Model For GUI Agents

Hallucinations (Confabulations) Document-Based Benchmark for RAG. Includes human-verified questions and answers.

Exploring the Limit of Outcome Reward for Learning Mathematical Reasoning

Building open version of OpenAI o1 via reasoning traces (Groq, ollama, Anthropic, Gemini, OpenAI, Azure supported) Demo: https://huggingface.co/spaces/pseudotensor/open-strawberry

The Multi-Agent Reasoning framework creates an interactive chatbot where AI agents collaborate via structured reasoning and Swarm Integration for optimal answers. Simulating a team that discusses, debates, and refines responses, it enables complex problem-solving and precise results. Now with Prompt Caching to reduce latency and costs.

A comprehensive collection of process reward models.

Official code for the paper, "Stop Summation: Min-Form Credit Assignment Is All Process Reward Model Needs for Reasoning"

Harnessing the Reasoning Economy: A Survey of Efficient Reasoning for Large Language Models