An open-source project offering a functional RAG UI for document QA, suitable for both end-users and developers. It supports various LLM providers, is customizable, and offers multi-modal QA, citations, and complex reasoning methods.
pip install 'ragna builtin » ' # Install ragna with all extensions
ragna config # Initialize configuration
ragna ui # Launch the web app
ragna config # Initialize configuration
ragna ui # Launch the web app
A simple Python3 tool to detect similarities between files within a repository.
Document similarity code adapted from Jonathan Mugan's tutorial:
https://www.oreilly.com/learning/how-do-i-compare-document-similarity-using-python
'''
Document similarity code adapted from Jonathan Mugan's tutorial:
https://www.oreilly.com/learning/how-do-i-compare-document-similarity-using-python
'''
tokenizing and stemming each synopsis
transforming the corpus into vector space using tf-idf
calculating cosine distance between each document as a measure of similarity
clustering the documents using the k-means algorithm
using multidimensional scaling to reduce dimensionality within the corpus
plotting the clustering output using matplotlib and mpld3
conducting a hierarchical clustering on the corpus using Ward clustering
plotting a Ward dendrogram
topic modeling using Latent Dirichlet Allocation (LDA)
transforming the corpus into vector space using tf-idf
calculating cosine distance between each document as a measure of similarity
clustering the documents using the k-means algorithm
using multidimensional scaling to reduce dimensionality within the corpus
plotting the clustering output using matplotlib and mpld3
conducting a hierarchical clustering on the corpus using Ward clustering
plotting a Ward dendrogram
topic modeling using Latent Dirichlet Allocation (LDA)
