L

Large Language Models

https://github.com/mlc-ai/web-llm High-performance In-browser LLM Inference Engine

🔧🔗https://github.com/flashinfer-ai/flashinfer

FlashInfer: Kernel Library for LLM Serving

🕸️🔗flashinfer.ai

🔧🔗https://github.com/google/dotprompt Executable GenAI prompt templates

🔧🔗https://github.com/sgl-project/sglang

SGLang is a fast serving framework for large language models and vision language models.

🔧🔗https://github.com/tensorzero/tensorzero TensorZero is an open-source stack for industrial-grade LLM applications. It unifies an LLM gateway, observability, optimization, evaluation, and experimentation

🔧🔗GitHub

The AI framework that adds the engineering to prompt engineering (Python/TS/Ruby/Java/C#/Rust/Go compatible)

🔧🔗https://github.com/microsoft/intelligence-toolkit

Interactive workflows for creating AI intelligence reports from real-world data sources

🔧🔗https://github.com/vllm-project/vllm

A high-throughput and memory-efficient inference and serving engine for LLMs

🔧🔗https://github.com/BerriAI/litellm

Python SDK, Proxy Server (LLM Gateway) to call 100+ LLM APIs in OpenAI format - [Bedrock, Azure, OpenAI, VertexAI, Cohere, Anthropic, Sagemaker, HuggingFace, Replicate, Groq] 🕸️🔗docs.litellm.ai/docs/

🔧🔗https://github.com/charmbracelet/catwalk

🐈 A collection of LLM inference providers and models

OpenLIT is an open-source LLM Observability tool built on OpenTelemetry. 📈🔥 Monitor GPU performance, LLM traces with input and output metadata, and metrics like cost, tokens, and user interactions along with complete APM for LLM Apps. 🖥️

🔧🔗https://github.com/openai/codex Lightweight coding agent that runs in your terminal

🔧🔗https://github.com/getzep/graphiti

Build and query dynamic, temporally-aware Knowledge Graphs

🔧🔗https://github.com/Skyvern-AI/skyvern

Automate browser-based workflows with LLMs and Computer Vision 🕸️🔗 www.skyvern.com/

🔧🔗https://github.com/getzep/zep

Zep | The Memory Foundation For Your AI Stack

https://github.com/joaomdmoura/crewAI Framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks.

crewai.com

LLM training in simple, raw C/CUDA LLMs in simple, pure C/CUDA with no need for 245MB of PyTorch or 107MB of cPython. Current focus is on pretraining, in particular reproducing the GPT-2 and GPT-3 miniseries, along with a parallel PyTorch ref

🔧🔗https://github.com/open-webui/open-webui User-friendly AI Interface (Supports Ollama, OpenAI API, ...)

🕸️🔗https://openwebui.com/

🔧🔗https://github.com/google/langfun

OO for LLMs

Implement a ChatGPT-like LLM in PyTorch from scratch, step by step 🔧🔗https://github.com/rasbt/LLMs-from-scratch