AI Engineering Hub
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In-depth tutorials on LLMs, RAGs and real-world AI agent applications. Rich notebook examples for learning AI engineering practices.
In-depth tutorials on LLMs, RAGs and real-world AI agent applications. Rich notebook examples for learning AI engineering practices.
All-in-one AI framework for semantic search, LLM orchestration, and language model workflows with agent support, RAG, and vector database
A Python library by Google for extracting structured information from unstructured text using LLMs with precise source grounding and interactive visualization, designed for data annotation and knowledge extraction workflows.
PromptTools provides open-source tools for prompt testing and experimentation, supporting multiple LLMs (OpenAI, LLaMA) and vector databases (Chroma, Weaviate, LanceDB) to help developers systematically evaluate and optimize RAG systems.
A MemAgent framework that can extrapolate to 3.5M context tokens, along with a training framework for RL training of any agent workflow.