{"id":1248,"date":"2024-07-21T17:04:05","date_gmt":"2024-07-21T19:04:05","guid":{"rendered":"https:\/\/sites.usp.br\/keml\/?page_id=1248"},"modified":"2024-10-13T00:06:46","modified_gmt":"2024-10-13T02:06:46","slug":"codes","status":"publish","type":"page","link":"https:\/\/sites.usp.br\/keml\/en\/codes\/","title":{"rendered":"Code"},"content":{"rendered":"<h6 style=\"text-align: right;\"><\/h6>\n<div id=\"attachment_1194\" style=\"width: 310px\" class=\"wp-caption alignleft\"><a href=\"https:\/\/sites.usp.br\/keml\/wp-content\/uploads\/sites\/1460\/2024\/05\/codigo-2.jpeg\"><img loading=\"lazy\" decoding=\"async\" aria-describedby=\"caption-attachment-1194\" class=\"wp-image-1194 size-medium\" src=\"https:\/\/sites.usp.br\/keml\/wp-content\/uploads\/sites\/1460\/2024\/05\/codigo-2-300x300.jpeg\" alt=\"\" width=\"300\" height=\"300\" srcset=\"https:\/\/sites.usp.br\/keml\/wp-content\/uploads\/sites\/1460\/2024\/05\/codigo-2-300x300.jpeg 300w, https:\/\/sites.usp.br\/keml\/wp-content\/uploads\/sites\/1460\/2024\/05\/codigo-2-150x150.jpeg 150w, https:\/\/sites.usp.br\/keml\/wp-content\/uploads\/sites\/1460\/2024\/05\/codigo-2-768x768.jpeg 768w, https:\/\/sites.usp.br\/keml\/wp-content\/uploads\/sites\/1460\/2024\/05\/codigo-2-250x250.jpeg 250w, https:\/\/sites.usp.br\/keml\/wp-content\/uploads\/sites\/1460\/2024\/05\/codigo-2-174x174.jpeg 174w, https:\/\/sites.usp.br\/keml\/wp-content\/uploads\/sites\/1460\/2024\/05\/codigo-2-45x45.jpeg 45w, https:\/\/sites.usp.br\/keml\/wp-content\/uploads\/sites\/1460\/2024\/05\/codigo-2-200x200.jpeg 200w, https:\/\/sites.usp.br\/keml\/wp-content\/uploads\/sites\/1460\/2024\/05\/codigo-2-400x400.jpeg 400w, https:\/\/sites.usp.br\/keml\/wp-content\/uploads\/sites\/1460\/2024\/05\/codigo-2.jpeg 1024w\" sizes=\"auto, (max-width: 300px) 100vw, 300px\" \/><\/a><p id=\"caption-attachment-1194\" class=\"wp-caption-text\">AI-generated image (Copilot)<\/p><\/div>\n<p>Since its inception in 2021, the KEML team has created a series of implementations for various purposes: text2SQL translators, language models predating the advent of large language models, architectures for implementing conversational agents, etc. Here you will find a list of GitHub repositories that illustrate the work already carried out by the group.<\/p>\n<p>More information about these implementations can be obtained on this website, in the <a href=\"https:\/\/sites.usp.br\/keml\/en\/resources\/\">Resources<\/a> menu options, or by <a href=\"https:\/\/sites.usp.br\/keml\/en\/contact\/\">contacting the team<\/a>.<\/p>\n<ul>\n<li><strong>ArGPT<\/strong>: implementations associated with the creation of the dataset for argumentation, based on large language models. Access <a href=\"https:\/\/github.com\/C4AI\/ArGPT\" target=\"_blank\" rel=\"noopener\">here.<\/a><\/li>\n<\/ul>\n<hr \/>\n<ul>\n<li><strong>Pir\u00e1<\/strong>: implementations associated with the construction and curation of the Pir\u00e1 dataset: Access here &#8211; <a href=\"https:\/\/github.com\/C4AI\/data-set-result-pira-qa\" target=\"_blank\" rel=\"noopener\">construction<\/a> &#8211; <a href=\"https:\/\/github.com\/C4AI\/Pira\" target=\"_blank\" rel=\"noopener\">curation<\/a>.<\/li>\n<li>Implementations regarding unsupervised topic analysis using matrix factorization on the Pir\u00e1 dataset. Access <a href=\"https:\/\/github.com\/C4AI\/unsupervised-topic-model\" target=\"_blank\" rel=\"noopener\">here<\/a>.<\/li>\n<\/ul>\n<hr \/>\n<ul>\n<li><strong>Framework BLAB<\/strong>: implementations that allow the use of the client-server orchestration architecture of a conversational agent. Access all the codes <a href=\"https:\/\/github.com\/C4AI\/BLAB\" target=\"_blank\" rel=\"noopener\">here<\/a>.<\/li>\n<li><strong>BLAB Q&amp;A<\/strong>: implementations associated with a question and answering system about the Blue Amazon, with content extracted from Wikipedia. Access <a href=\"https:\/\/github.com\/C4AI\/blab-qa-viz\" target=\"_blank\" rel=\"noopener\">here<\/a>.<\/li>\n<li><strong>BLAB Reporter<\/strong>: Implementation for the BLAB Reporter, the journalist robot covering data on the Blue Amazon. Access <a href=\"https:\/\/github.com\/C4AI\/blab-reporter\" target=\"_blank\" rel=\"noopener\">here<\/a>.<\/li>\n<li><strong>Blabinha:<\/strong> Implementation of the Blabinha Framework, a gamified conversational agent focused on the Blue Amazon. Access <a href=\"https:\/\/github.com\/C4AI\/Blabinha\" target=\"_blank\" rel=\"noopener\">here<\/a>.<\/li>\n<\/ul>\n<hr \/>\n<ul>\n<li><strong>Framework dPASP<\/strong>: implementations that enable the use of the framework dPASP &#8211; A high-level declarative language for describing sophisticated probabilistic reasoning tasks that can combine perception and logical reasoning. Access <a href=\"https:\/\/github.com\/kamel-usp\/dpasp\" target=\"_blank\" rel=\"noopener\">here<\/a>.<\/li>\n<\/ul>\n<hr \/>\n<ul>\n<li><strong>GAP-text2SQL<\/strong>: implementations associated with research on contextual representations for semantic analysis of text-to-SQL. Access <a href=\"https:\/\/github.com\/C4AI\/gap-text2sql\" target=\"_blank\" rel=\"noopener\">here<\/a>.<\/li>\n<li>Implementations associated with research on the integration of &#8220;question and answering&#8221; and &#8220;text-to-SQL&#8221; in Portuguese. Access <a href=\"https:\/\/github.com\/C4AI\/Integrating-Question-Answering-and-Text-to-SQL-in-Portuguese\" target=\"_blank\" rel=\"noopener\">here<\/a>.<\/li>\n<\/ul>\n<hr \/>\n<ul>\n<li><strong>Deepag\u00e9<\/strong>: Implementation for the construction of the Deepag\u00e9 model, a question and answer model about the Brazilian environment. Access <a href=\"https:\/\/github.com\/C4AI\/deepage\" target=\"_blank\" rel=\"noopener\">here<\/a>.<\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>Since its inception in 2021, the KEML team has created a series of implementations for various purposes: text2SQL translators, language models predating the advent of large language models, architectures for implementing conversational agents, etc. Here you will find a list of GitHub repositories that illustrate the work already carried out by the group. More information<a href=\"https:\/\/sites.usp.br\/keml\/en\/codes\/\">[&#8230;]<\/a><\/p>\n","protected":false},"author":24022,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"inline_featured_image":false,"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":"","_links_to":"","_links_to_target":""},"class_list":["post-1248","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/sites.usp.br\/keml\/wp-json\/wp\/v2\/pages\/1248","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/sites.usp.br\/keml\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/sites.usp.br\/keml\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/sites.usp.br\/keml\/wp-json\/wp\/v2\/users\/24022"}],"replies":[{"embeddable":true,"href":"https:\/\/sites.usp.br\/keml\/wp-json\/wp\/v2\/comments?post=1248"}],"version-history":[{"count":4,"href":"https:\/\/sites.usp.br\/keml\/wp-json\/wp\/v2\/pages\/1248\/revisions"}],"predecessor-version":[{"id":1671,"href":"https:\/\/sites.usp.br\/keml\/wp-json\/wp\/v2\/pages\/1248\/revisions\/1671"}],"wp:attachment":[{"href":"https:\/\/sites.usp.br\/keml\/wp-json\/wp\/v2\/media?parent=1248"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}