llmops

Hamilton helps data scientists and engineers define testable, modular, self-documenting dataflows, that encode lineage and metadata. Runs and scales everywhere python does.

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/

Build applications that make decisions (chatbots, agents, simulations, etc...). Monitor, persist, and execute on your own infrastructure. burr.dagworks.io

https://github.com/ComposioHQ/composio Composio equip's your AI agents & LLMs with 100+ high-quality integrations via function calling

A Blazing Fast AI Gateway. Route to 100+ LLMs with 1 fast & friendly API. https://github.com/Portkey-AI/gateway

🤖 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/distantmagic/llmops-handbook Practical and advanced guide to LLMOps. It provides a solid understanding of large language models’ general concepts, deployment techniques, and software engineering practices.