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High accuracy RAG for answering questions from course documents and files with citations

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CourseRAG

CourseRAG is a package for performing high-accuracy retrieval augmented generation (RAG) on PDFs, Common Cartridge LMS Exports (IMSCC), PPTX, DOCX, lecture recordings, quizzes, assignments, or text files, with a focus on the teaching and learning.

Quickstart

In this example we take a folder containing a PDF textbook and an IMSCC export of a course from an LMS, extract their metadata, parse and vectorize their contents, and finally answer the user question with an LLM agent using the context of the materials.

pip install course-rag
cd my_course
crag ask 'What are the topics I should study for the midterm?'

Example Output

Question: ---

Answer: ---

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High accuracy RAG for answering questions from course documents and files with citations

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