second experiment as a flask interactive application to jump between recommended sentences using the similarity matrix
Dorian
2 years ago
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8ae06f04df
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from flask import Flask
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from flask import request, render_template
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from markdown import markdown
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import sys
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app = Flask("recommend")
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# appending a path
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sys.path.append('../')
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# importing customised module
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import summa.edits
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from summa.edits import scored_sentences, similarity_graph
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import wikipage
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from wikipage.page import get_wikipage
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context = {
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'page_name' : "door",
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'page' : None,
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'graph' : None,
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'sentences' : None,
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'current_sentence' : None
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}
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# TextRank
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# ------------------------------------------------------------------------
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def get_similar_sentences(s0, sentences, graph):
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# return a list of all the sentences ordered by similarity to s0
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similar_sentences = sorted(sentences, key=lambda s: graph.edge_weight((s0.token, s.token)), reverse=True)
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return similar_sentences
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# main
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# ------------------------------------------------------------------------
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def new_page(page_name):
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# from a pagename get
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# 1. get the page text
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# 2. graph and scored sentences
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# --- WIKI REQUEST ---
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# get text from wikipedia
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print('--- WIKI ---')
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context['page'] = get_wikipage(page_name)
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if not context['page']:
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sys.exit("--- STOP ---")
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text = context['page'].content
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# print text in terminal
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print('--- TXT ---')
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print(text)
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# --- APPLY TEXTRANK ---
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# apply textrank
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context['sentences'] = scored_sentences(text)
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context['graph'] = similarity_graph(text)
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@app.route("/")
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def index():
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if 'token' in request.args:
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token = request.args['token']
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context['current_sentence'] = [s for s in context['sentences'] if s.token == token][0]
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else:
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new_page(context['page_name'])
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sorted_sentences = sorted(context['sentences'], key=lambda s: s.score, reverse=True)
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best_sentence = sorted_sentences[0]
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print("--- START/BEST ---")
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print(best_sentence.text)
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context['current_sentence'] = best_sentence
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# sentences ordered by similarity to the best one
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similar_sentences = get_similar_sentences(context['current_sentence'] , context['sentences'], context['graph'])
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current_sentence=context['current_sentence']
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return render_template('index.html', current_sentence=current_sentence , similar_sentences=similar_sentences)
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# # --- APPLY TEXTRANK ---
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# # apply textrank
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# sentences = scored_sentences(text)
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# graph = similarity_graph(text)
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# # print ranked sentences in terminal
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# print('--- GRAPH ---')
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# # notes:
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# # * the matrix/graph does not contain the sentences but their .token
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# sorted_sentences = sorted(sentences, key=lambda s: s.score, reverse=True)
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# best_sentence = sorted_sentences[0]
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# print("START/BEST: \n")
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# print(best_sentence.text + "\n")
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# # sentences ordered by similarity to the best one
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# similar_sentences = similar_sentences(best_sentence, sentences, graph)
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# for i in range(len(similar_sentences)):
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# print(str(i) + ". " + similar_sentences[i].text)
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# # for s1 in sentences:
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# # for s2 in sentences:
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# # if s1 != s2:
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# # if graph.has_node(s1.token) and graph.has_node(s2.token):
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# # weight = graph.edge_weight((s1.token, s2.token))
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# # print('---')
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# # print('1. ' + s1.text)
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# # print('2. ' + s2.text)
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# # print('similarity: ' + str(weight))
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@ -1,56 +0,0 @@
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from jinja2 import Template
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from markdown import markdown
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import sys
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# appending a path
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sys.path.append('../')
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# importing customised module
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import summa.edits
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from summa.edits import scored_sentences, similarity_graph
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import wikipage
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from wikipage.page import get_wikipage
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wikipedia_page = "mushroom"
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# main
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# ------------------------------------------------------------------------
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if __name__ == '__main__':
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# --- WIKI REQUEST ---
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# get text from wikipedia
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print('--- WIKI ---')
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page = get_wikipage(wikipedia_page)
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if not page:
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sys.exit("--- STOP ---")
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title = '<h1>'+page.title+'</h1>'
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text = page.content
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# print text in terminal
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print('--- TXT ---')
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print(text)
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# --- APPLY TEXTRANK ---
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# apply textrank
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graph = similarity_graph(text)
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# print ranked sentences in terminal
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print('--- GRAPH ---')
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# for i in len(graph.nodes()):
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# for j in len(graph.nodes()):
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# s1 = graph.nodes()[i]
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# s2 = graph.nodes()[j]
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# weight = graph.edge_weight((i, j))
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# print('---')
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# print('1. ' + s1)
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# print('2. ' + s1)
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# print('similarity: ' + weight)
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export FLASK_APP=app
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export FLASK_ENV=development
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flask run
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:root{
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--lh: 1.35;
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}
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body{
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line-height: var(--lh);
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display: grid;
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grid-template-columns: 2fr 1fr;
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gap: 6em;
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}
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main{
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padding: 6em;
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padding-right: 0;
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}
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main p{
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border: thin solid lightgrey;
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box-sizing: border-box;
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border-radius: 1em;
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padding: 4em;
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height: 100%;
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display: flex;
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justify-content: center;
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align-items: center;
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}
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aside{
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font-size: 0.8em;
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box-sizing: border-box;
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padding: 2em 0;
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padding-left: 0;
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padding-right: 6em;
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height: 100vh;
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overflow: auto;
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}
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aside li{
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padding: 2em 0;
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}
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h2{
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font-weight: bold;
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}
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/* http://meyerweb.com/eric/tools/css/reset/
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v2.0 | 20110126
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License: none (public domain)
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*/
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html, body, div, span, applet, object, iframe,
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h1, h2, h3, h4, h5, h6, p, blockquote, pre,
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a, abbr, acronym, address, big, cite, code,
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del, dfn, em, img, ins, kbd, q, s, samp,
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small, strike, strong, sub, sup, tt, var,
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b, u, i, center,
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dl, dt, dd, ol, ul, li,
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fieldset, form, label, legend,
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table, caption, tbody, tfoot, thead, tr, th, td,
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article, aside, canvas, details, embed,
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figure, figcaption, footer, header, hgroup,
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menu, nav, output, ruby, section, summary,
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time, mark, audio, video {
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margin: 0;
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padding: 0;
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border: 0;
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font-size: 100%;
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font: inherit;
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vertical-align: baseline;
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}
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/* HTML5 display-role reset for older browsers */
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article, aside, details, figcaption, figure,
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footer, header, hgroup, menu, nav, section {
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display: block;
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}
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body {
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line-height: 1;
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}
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ol, ul {
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list-style: none;
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}
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blockquote, q {
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quotes: none;
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}
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blockquote:before, blockquote:after,
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q:before, q:after {
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content: '';
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content: none;
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}
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table {
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border-collapse: collapse;
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border-spacing: 0;
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}
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<!DOCTYPE html>
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<html lang="en">
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<head>
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<meta charset="UTF-8" />
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<title>Recommended Reading</title>
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<meta name="description" content="">
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<meta name="viewport" content="width=device-width, initial-scale=1">
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<link rel="stylesheet" type="text/css" href="static/css/reset.css" />
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<link rel="stylesheet" type="text/css" href="static/css/main.css" />
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</head>
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<body>
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<main>
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<p>
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{{ current_sentence.text }}
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</p>
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</main>
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<aside>
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<nav>
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<h2>recommended:</h2>
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<ul>
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{% for s in similar_sentences %}
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<li>
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<a href="/?token={{ s.token }}">{{ s.text }}</a>
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</li>
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{% endfor %}
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</ul>
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</nav>
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</aside>
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</body>
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</html>
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