Query structured documents using a lightweight LLM workflow
This Blueprint demonstrates how to use open-source models and a simple LLM workflow to answer questions based on structured documents.
It is designed to showcase a simpler alternative to more complex and/or resource demanding alternatives, such as RAG systems that rely on vectorDBs and/or long-context models with large token windows.
If you encounter any issues with the hosted demo below, try the Blueprint in the GPU-enabled Google Colab Notebook available here.
Trusted open source tools used for this Blueprint
Detailed guidance on GitHub walking you through this project installation.
View MoreGet involved in improving the Blueprint by visiting the GitHub Blueprint issues.
Join inWindows, macOS, or Linux. Python 3.10 or higher. Min RAM: 10 GB. Disk space: 32 GB min
Learn MoreExplore how the Blueprint configuration parameters have been adjusted to create solutions that fit your specific needs.
Explore how the Blueprint components have been extended to expand its scope and unlock new capabilities
Insights into our motivations and key technical decisions throughout the development process.