MichiganDataScienceTeam/llm-augmentation
Applying LLMs, augmented with information retrieval (RAG) and function calling, to a variety of tasks in different domains.
This project offers practical tutorials for developers looking to enhance Large Language Models (LLMs) with custom data and external tools. It guides you through integrating your domain-specific information and enabling LLMs to execute functions, resulting in more accurate and capable AI solutions for specialized tasks. The target audience is Python developers and data scientists seeking to build advanced LLM applications.
No commits in the last 6 months.
Use this if you are a developer or data scientist who wants to learn how to build more powerful and context-aware LLM applications using techniques like Retrieval Augmented Generation (RAG) and function calling.
Not ideal if you are a non-technical end-user looking for a ready-to-use application, as this project provides development tutorials and not a finished product.
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Last pushed
Dec 05, 2024
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