L

Large Language Models

🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

huggingface.co/transformers https://github.com/huggingface/transformers

🔧🔗https://github.com/modelscope/ms-swift

SWIFT (Scalable lightWeight Infrastructure for Fine-Tuning) Use PEFT or Full-parameter to finetune 400+ LLMs or 100+ MLLMs.

🔧🔗https://github.com/getzep/graphiti

Build and query dynamic, temporally-aware Knowledge Graphs

https://github.com/run-llama/llama_index LlamaIndex is a data framework for your LLM applications

🔧🔗https://github.com/All-Hands-AI/OpenHands

🙌 OpenHands: Code Less, Make More

yzma

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

Easy Edit

🔧🔗https://github.com/zjunlp/EasyEdit [ACL 2024] An Easy-to-use Knowledge Editing Framework for LLMs.

🔧🔗https://github.com/getzep/zep-python

Zep: Long-Term Memory for ‍AI Assistants (Python Client)

gai

🔧🔗https://github.com/maragudk/gai Go Artificial Intelligence (GAI) helps you work with foundational models, large language models, and other AI models.

python sdk

https://github.com/agentclientprotocol/python-sdk

Python SDK for ACP clients and agents.

🔧🔗https://github.com/aurelio-labs/semantic-router

Superfast AI decision making and intelligent processing of multi-modal data.

🤖 𝗟𝗲𝗮𝗿𝗻 for 𝗳𝗿𝗲𝗲 how to 𝗯𝘂𝗶𝗹𝗱 an end-to-end 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻-𝗿𝗲𝗮𝗱𝘆 𝗟𝗟𝗠 & 𝗥𝗔𝗚 𝘀𝘆𝘀𝘁𝗲𝗺 using 𝗟𝗟𝗠𝗢𝗽𝘀 best practices: ~ 𝘴𝘰𝘶𝘳𝘤𝘦 𝘤𝘰𝘥𝘦 + 11 𝘩𝘢𝘯𝘥𝘴-𝘰𝘯 𝘭𝘦𝘴𝘴𝘰𝘯𝘴 https://github.com/decodingml/llm-twin-course

🔧🔗https://github.com/getzep/zep

Zep | The Memory Foundation For Your AI Stack

🔧🔗https://github.com/decodingml/production-llm-rag-course

Second Brain Semantic AI Engine: Powered by LLMs & RAG

🔧🔗https://github.com/IBM/mcp-context-forge A Model Context Protocol (MCP) Gateway & Registry. Serves as a central management point for tools, resources, and prompts that can be accessed by MCP-compatible LLM applications. Converts REST API endpoints to MCP, composes virtual MCP servers with added security and observability, and converts between protocols (stdio, SSE, Streamable HTTP).

🔧🔗https://github.com/om-ai-lab/VLM-R1 Solve Visual Understanding with Reinforced VLMs

full attention

🔧🔗https://github.com/maragudk/fullattention

Full Attention is an AI chat app with personas.

gai starter kit

🔧🔗https://github.com/maragudk/gai-starter-kit Get started with LLMs, FTS and vector search, RAG, and more, in Go!

evals

🔧🔗https://github.com/maragudk/evals a CLI to work with LLM Evals

🔧🔗https://github.com/microsoft/Trace End-to-end Generative Optimization for AI Agents