Local LLM helper using Ollama for simple prompts, web searches and asking question on your own pdfs

The all-in-one Desktop & Docker AI application with full RAG and AI Agent capabilities.

Witsy: desktop AI assistant

REST API proxy to Vertex AI with the interface of ollama. HTTP server for accessing Vertex AI via the REST API interface of ollama.

An Art-Deco bot that utilizes RAG. Benchmarking of RAG vs. LLMs on QA and timing

VSCode coding companion for software teams 🦆 Turn your team insights into a portable plug-and-play context for code generation. Alternative to GitHub Copilot & OpenAI GPT powered by OSS LLMs (Phi 3, Llama 3, CodeQwen, Mistral, etc.), made with ❤️ using FastAPI & Ollama.

Get up and running with Llama 3, Mistral, Gemma, and other large language models.

No-code AI Chatbot using Ollama.

🤯 Lobe Chat - an open-source, modern-design LLMs/AI chat framework. Supports Multi AI Providers( OpenAI / Claude 3 / Gemini / Ollama / Bedrock / Azure / Mistral / Perplexity ), Multi-Modals (Vision/TTS) and plugin system. One-click FREE deployment of your private ChatGPT chat application.

LLM IRC bot with SASL-plain and syntax-hilighting

Chat with ChatGPT, Claude, Llama 3, Phi 3, Mistral, Gemma and more from a powerful terminal user interface.

HTML UI for Ollama. Minimal & responsive UI: mobile & desktop. Cross-browser support. Simple installation: host on your own server, run in your browser.

VirtualWife是一个虚拟数字人项目，支持B站直播，支持openai、ollama

Instant timestamped chapters for your YouTube videos with just one click! chapters 10x faster, and 10x detailed as manually generated content

Create a ChatGPT Clone with Ollama and HyperDiv

User-friendly WebUI for LLMs (Formerly Ollama WebUI)

GUI for ChatGPT API and many LLMs. Supports agents, file-based QA, GPT finetuning and query with web search. All with a neat UI.

A multi-platform desktop application to evaluate and compare LLM models, written in Rust and React.

Jupyter Notebooks for Ollama integration

10_36个常用linux命令_每3个命令成为一个单独的课程_每个课程是一个club的工作空间_共12个课程 12_每个3个命令是1个独立的课程_教师在8分钟内讲解完成_学员可以在后继的时间中直接在club.cloudstudio中操作