A large language model (LLM) is a type of machine learning model designed for understanding, generating, and interacting with human language. These models are trained on extensive datasets containing text from books, articles, websites, and other sources to learn patterns, context, and semantics in language. LLMs are widely used in applications like chatbots, code generation, translation, summarization, and more. They are often built using transformer architectures and are central to the field of generative AI.
User-friendly AI Interface (Supports Ollama, OpenAI API, ...)
The all-in-one Desktop & Docker AI application with built-in RAG, AI agents, No-code agent builder, MCP compatibility, and more.
🔍 An LLM-based Multi-agent Framework of Web Search Engine (like Perplexity.ai Pro and SearchGPT)
A powerful tool for creating fine-tuning datasets for LLM
Context7 MCP Server -- Up-to-date code documentation for LLMs and AI code editors
Transformer Explained Visually: Learn How LLM Transformer Models Work with Interactive Visualization
The python library for real-time communication
Cursor Talk To Figma MCP
LangServe 🦜️🏓
Text-To-Speech, RAG, and LLMs. All local!
Calculate token/s & GPU memory requirement for any LLM. Supports llama.cpp/ggml/bnb/QLoRA quantization
A minimal smart resume maker we all need !