deep-talk 0.1.0

DeepTalk: Python and Prolog based dialogue agent

Project Description

** The system uses package text_graph_crafts based on dependency links for building Text Graphs, that with help of a centrality algorithm like PageRank, extract relevant keyphrases, summaries and relations from text documents.

A SWI-Prolog based module adds an interactive shell for talking about the document with a dialog agent that extracts for each query the most relevant sentences covering the document. Spoken dialog is also available if the OS supports it. Developed with Python 3, on OS X, but portable to Linux.**

Dependencies:

• python 3.7 or newer, pip3, java 9.x or newer, SWI-Prolog 8.x or newer, graphviz
• also, having git installed is recommended for easy updates
• pip3 install text_graph_crafts

see how to activate other outputs in file

https://github.com/ptarau/TextGraphCrafts/blob/master/text_graph_crafts/deepRank.py

The second is activated with

python3 -i qpro.py

or the shorthand script qgo.

It requires SWI-Prolog to be installed and available in the path as the executable swipl and the Python to Prolog interface pyswip, to be installed with

pip3 install pyswip

It activates a Prolog process to which Python sends interactively queries about a selected document. Answers are computed by Prolog and then, if the parameter quiet is off, spoken using the say OS-level facility (available on OS X and Linux machines.

Prolog relation files, generated on the Python side are associated to each document as well as the queries about it. They are stored in the same directory as the document.

Try

>>> t1() 
...
>>> t9()
>>> t0()

or

>>> chat('const')

to interactively chat about the US Constitution. The same
for other documents in the examples folder.

### Handling PDF documents

The easiest way to do this is to install *pdftotext*, which is part of [Poppler tools](https://poppler.freedesktop.org/).

If pdftotext is installed, you can place a file like *textrank.pdf*
already in subdirectory pdfs/ and try something similar to:

pdf_chat('textrank')

which activates a dialog about the TextRank paper. Also

pdf_chat('logrank')

activates a dialog about *pdfs/logrank.pdf*, which describes
the architecture of the current system.

Change setting in file params.py to use the system with
other global parameter settings.