# Copyright 2013 AlchemyAPI # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. require './alchemyapi' demo_text = 'Yesterday dumb Bob destroyed my fancy iPhone in beautiful Denver, Colorado. I guess I will have to head over to the Apple Store and buy a new one.' demo_url= 'http://www.npr.org/2013/11/26/247336038/dont-stuff-the-turkey-and-other-tips-from-americas-test-kitchen' demo_html = '
Well, you do now.
' alchemyapi = AlchemyAPI.new() puts '' puts '' puts '############################################' puts '# Entity Extraction Example #' puts '############################################' puts '' puts '' puts 'Processing text: ' + demo_text puts '' response = alchemyapi.entities('text', demo_text, { 'sentiment'=>1 }) if response['status'] == 'OK' puts '## Response Object ##' puts JSON.pretty_generate(response) puts '' puts '## Entities ##' for entity in response['entities'] puts 'text: ' + entity['text'] puts 'type: ' + entity['type'] puts 'relevance: ' + entity['relevance'] print 'sentiment: ' + entity['sentiment']['type'] #Make sure score exists (it's not returned for neutral sentiment if entity['sentiment'].key?('score') print ' (' + entity['sentiment']['score'] + ')' end puts '' end else puts 'Error in entity extraction call: ' + response['statusInfo'] end puts '' puts '' puts '' puts '############################################' puts '# Keyword Extration Example #' puts '############################################' puts '' puts '' puts 'Processing text: ' + demo_text puts '' response = alchemyapi.keywords('text', demo_text, { 'sentiment'=>1 }) if response['status'] == 'OK' puts '## Response Object ##' puts JSON.pretty_generate(response) puts '' puts '## Keywords ##' for keyword in response['keywords'] puts 'text: ' + keyword['text'] puts 'relevance: ' + keyword['relevance'] print 'sentiment: ' + keyword['sentiment']['type'] #Make sure score exists (it's not returned for neutral sentiment if keyword['sentiment'].key?('score') print ' (' + keyword['sentiment']['score'] + ')' end puts '' end else puts 'Error in keyword extraction call: ' + response['statusInfo'] end puts '' puts '' puts '' puts '############################################' puts '# Concept Tagging Example #' puts '############################################' puts '' puts '' puts 'Processing text: ' + demo_text puts '' response = alchemyapi.concepts('text', demo_text) if response['status'] == 'OK' puts '## Response Object ##' puts JSON.pretty_generate(response) puts '' puts '## Concepts ##' for concept in response['concepts'] puts 'text: ' + concept['text'] puts 'relevance: ' + concept['relevance'] puts '' end else puts 'Error in concept tagging call: ' + response['statusInfo'] end puts '' puts '' puts '' puts '############################################' puts '# Sentiment Analysis Example #' puts '############################################' puts '' puts '' puts 'Processing html: ' + demo_html puts '' response = alchemyapi.sentiment('html', demo_html) if response['status'] == 'OK' puts '## Response Object ##' puts JSON.pretty_generate(response) puts '' puts '## Document Sentiment ##' puts 'type: ' + response['docSentiment']['type'] #Make sure score exists (it's not returned for neutral sentiment if response['docSentiment'].key?('score') puts 'score: ' + response['docSentiment']['score'] end else puts 'Error in sentiment analysis call: ' + response['statusInfo'] end puts '' puts '' puts '' puts '############################################' puts '# Targeted Sentiment Analysis Example #' puts '############################################' puts '' puts '' puts 'Processing text: ' + demo_text puts '' response = alchemyapi.sentiment_targeted('text', demo_text, 'Denver') if response['status'] == 'OK' puts '## Response Object ##' puts JSON.pretty_generate(response) puts '' puts '## Targeted Sentiment ##' puts 'type: ' + response['docSentiment']['type'] #Make sure score exists (it's not returned for neutral sentiment if response['docSentiment'].key?('score') puts 'score: ' + response['docSentiment']['score'] end else puts 'Error in targeted sentiment analysis call: ' + response['statusInfo'] end puts '' puts '' puts '' puts '############################################' puts '# Text Extraction Example #' puts '############################################' puts '' puts '' puts 'Processing url: ' + demo_url puts '' response = alchemyapi.text('url', demo_url) if response['status'] == 'OK' puts '## Response Object ##' puts JSON.pretty_generate(response) puts '' puts '## Extracted Text ##' puts 'text: ' + response['text'] puts '' else puts 'Error in text extraction call: ' + response['statusInfo'] end puts '' puts '' puts '' puts '############################################' puts '# Author Extraction Example #' puts '############################################' puts '' puts '' puts 'Processing url: ' + demo_url puts '' response = alchemyapi.author('url', demo_url) if response['status'] == 'OK' puts '## Response Object ##' puts JSON.pretty_generate(response) puts '' puts '## Author ##' puts 'author: ' + response['author'] else puts 'Error in author extraction call: ' + response['statusInfo'] end puts '' puts '' puts '' puts '############################################' puts '# Language Detection Example #' puts '############################################' puts '' puts '' puts 'Processing text: ' + demo_text puts '' response = alchemyapi.language('text', demo_text) if response['status'] == 'OK' puts '## Response Object ##' puts JSON.pretty_generate(response) puts '' puts '## Language ##' puts 'text: ' + response['language'] puts 'iso-639-1: ' + response['iso-639-1'] puts 'native speakers: ' + response['native-speakers'] else puts 'Error in language detection call: ' + response['statusInfo'] end puts '' puts '' puts '' puts '############################################' puts '# Title Extraction Example #' puts '############################################' puts '' puts '' puts 'Processing url: ' + demo_url puts '' response = alchemyapi.title('url', demo_url) if response['status'] == 'OK' puts '## Response Object ##' puts JSON.pretty_generate(response) puts '' puts '## Title ##' puts 'title: ' + response['title'] else puts 'Error in title extraction call: ' + response['statusInfo'] end puts '' puts '' puts '' puts '############################################' puts '# Relation Extraction Example #' puts '############################################' puts '' puts '' puts 'Processing text: ' + demo_text puts '' response = alchemyapi.relations('text', demo_text) if response['status'] == 'OK' puts '## Response Object ##' puts JSON.pretty_generate(response) puts '' puts '## Relations ##' for relation in response['relations'] if relation.key?('subject') puts 'subject: ' + relation['subject']['text'] end if relation.key?('action') puts 'action: ' + relation['action']['text'] end if relation.key?('object') puts 'object: ' + relation['object']['text'] end puts '' end else puts 'Error in relation extraction call: ' + response['statusInfo'] end puts '' puts '' puts '' puts '############################################' puts '# Text Categorization Example #' puts '############################################' puts '' puts '' puts 'Processing text: ' + demo_text puts '' response = alchemyapi.category('text', demo_text) if response['status'] == 'OK' puts '## Response Object ##' puts JSON.pretty_generate(response) puts '' puts '## Category ##' puts 'text: ' + response['category'] puts 'score: ' + response['score'] else puts 'Error in text categorization call: ' + response['statusInfo'] end puts '' puts '' puts '' puts '############################################' puts '# Feed Detection Example #' puts '############################################' puts '' puts '' puts 'Processing url: ' + demo_url puts '' response = alchemyapi.feeds('url', demo_url) if response['status'] == 'OK' puts '## Response Object ##' puts JSON.pretty_generate(response) puts '' puts '## Feeds ##' for feed in response['feeds'] puts 'feed: ' + feed['feed'] end else puts 'Error in feed detection call: ' + response['statusInfo'] end puts '' puts '' puts '' puts '############################################' puts '# Microformats Parsing Example #' puts '############################################' puts '' puts '' puts 'Processing url: ' + demo_url puts '' response = alchemyapi.microformats('url', demo_url) if response['status'] == 'OK' puts '## Response Object ##' puts JSON.pretty_generate(response) puts '' puts '## Microformats ##' for microformat in response['microformats'] puts 'field: ' + microformat['field'] puts 'data: ' + microformat['data'] puts '' end else puts 'Error in microformats parsing call: ' + response['statusInfo'] end puts '' puts '' puts '' puts '' puts '' puts '############################################' puts '# Taxonomy Example #' puts '############################################' puts '' puts '' puts 'Processing url: ' + demo_url puts '' response = alchemyapi.taxonomy('url', demo_url) if response['status'] == 'OK' puts '## Response Object ##' puts JSON.pretty_generate(response) puts '' puts '## Taxonomy ##' for taxonomy in response['taxonomy'] puts 'label: ' + taxonomy['label'] puts 'score: ' + taxonomy['score'] if taxonomy.key?('confident') puts 'confident: ' + taxonomy['confident'] end puts '' end else puts 'Error in taxonomy call: ' + response['statusInfo'] end puts '' puts '' puts '' puts '' puts '' puts '############################################' puts '# Image Extraction Example #' puts '############################################' puts '' puts '' puts 'Processing url: ' + demo_url puts '' response = alchemyapi.image_extract('url', demo_url, { 'extractMode'=>'trust-metadata' }) if response['status'] == 'OK' puts '## Response Object ##' puts JSON.pretty_generate(response) puts '' puts '## Image Extraction ##' if response.key?('image') puts 'image: ' + response['image'] end puts '' else puts 'Error in image extraction call: ' + response['statusInfo'] end puts '' puts '' puts '' puts '' puts '' puts '############################################' puts '# Combined Example #' puts '############################################' puts '' puts '' puts 'Processing url: ' + demo_url puts '' response = alchemyapi.combined('url', demo_url, { 'extract'=>'page-image,keyword,entity' }) if response['status'] == 'OK' puts '## Response Object ##' puts JSON.pretty_generate(response) puts '' puts '## Combined Data ##' if response.key?('keywords') puts 'Keywords:' for keyword in response['keywords'] puts "\ttext: " + keyword['text'] puts "\trelevance: " + keyword['relevance'] puts '' end end if response.key?('image') puts 'image: ' + response['image'] puts '' end if response.key?('entities') puts 'Entities:' for entity in response['entities'] puts "\trelevance: " + entity['relevance'] puts "\ttext: " + entity['text'] puts "\tcount: " + entity['count'] puts "\ttype: " + entity['type'] if entity.key?('disambiguated') puts "\tdisambiguated: " if entity['disambiguated'].key?('dbpedia') puts "\t\tdbpedia: " + entity['disambiguated']['dbpedia'] end if entity['disambiguated'].key?('freebase') puts "\t\tfreebase: " + entity['disambiguated']['freebase'] end end puts '' end end puts '' else puts 'Error in combined call: ' + response['statusInfo'] end puts '' puts '' puts '' puts '' puts '' puts '############################################' puts '# Image Tagging Example #' puts '############################################' puts '' puts '' puts 'Processing url: ' + demo_url puts '' response = alchemyapi.image_tag('url', demo_url, { 'extractMode'=>'trust-metadata' }) if response['status'] == 'OK' puts '## Response Object ##' puts JSON.pretty_generate(response) puts '' puts '## Image Tagging ##' if response.key?('imageKeywords') puts 'Keywords:' for keyword in response['imageKeywords'] puts "\ttext: " + keyword['text'] puts "\tscore: " + keyword['score'] end end puts '' else puts 'Error in image tag call: ' + response['statusInfo'] end path_to_test_image = 'dog.jpg' test_image = File.binread(path_to_test_image) puts 'Processing image: ' + path_to_test_image puts '' response = alchemyapi.image_tag('image', '', { 'imagePostMode'=>'raw' }, test_image) if response['status'] == 'OK' puts '## Response Object ##' puts JSON.pretty_generate(response) puts '' puts '## Image Tagging ##' if response.key?('imageKeywords') puts 'Keywords:' for keyword in response['imageKeywords'] puts "\ttext: " + keyword['text'] puts "\tscore: " + keyword['score'] end end puts '' else puts 'Error in image tag call: ' + response['statusInfo'] end puts '' puts ''