L

Large Language Models

🔧🔗https://github.com/langfuse/langfuse-docs 🪢 Langfuse documentation -- Langfuse is the open source LLM Engineering Platform. Observability, evals, prompt management, playground and metrics to debug and

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

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

🔧🔗https://github.com/gpustack/gpustack

Manage GPU clusters for running LLMs

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/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/All-Hands-AI/OpenHands

🙌 OpenHands: Code Less, Make More

🔧🔗https://github.com/bytedance/deer-flow DeerFlow is a community-driven framework for Deep Research, combining language models with tools like web search, crawling, and Python execution, while contributing back to the open-source community.

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

🐈 A collection of LLM inference providers and models

🔧🔗https://github.com/charmbracelet/crush The glamourous AI coding agent for your favourite terminal 💘

🔧🔗https://github.com/modelscope/evalscope A streamlined and customizable framework for efficient large model evaluation and performance benchmarking

🔧🔗https://github.com/vllm-project/vllm-ascend Community maintained hardware plugin for vLLM on Ascend

🔧🔗https://github.com/langfuse/langfuse 🪢 Open source LLM engineering platform: LLM Observability, metrics, evals, prompt management, playground, datasets. Integrates with LlamaIndex, Langchain, OpenAI SDK, L

🔧🔗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

https://github.com/charmbracelet/fantasy Build AI agents with Go. Multiple providers, multiple models, one API 🧙

🔧🔗https://github.com/google/adk-python An open-source, code-first Python toolkit for building, evaluating, and deploying sophisticated AI agents with flexibility and control.

🔧🔗https://github.com/dyad-sh/dyad Free, local, open-source AI app builder ✨ v0 / lovable / Bolt alternative 🌟 Star if you like it!

🔧🔗https://github.com/google/ml-metrics Ml-metrics provides performant and distributed friendly ML metrics implementations.

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

FlashInfer: Kernel Library for LLM Serving

🕸️🔗flashinfer.ai

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

https://github.com/hybridgroup/yzma Write Go applications that directly integrate llama.cpp for local inference using hardware acceleration.