{"id":4076,"date":"2024-07-12T10:24:08","date_gmt":"2024-07-12T10:24:08","guid":{"rendered":"https:\/\/ai4app.pl\/?p=4076"},"modified":"2024-07-12T10:30:18","modified_gmt":"2024-07-12T10:30:18","slug":"kluczowe-aspekty-budowy-zaawansowanych-chatbotow-wspomaganych-wyszukiwaniem","status":"publish","type":"post","link":"https:\/\/ai4app.pl\/en\/key-aspects-of-building-advanced-search-assisted-chatbots\/","title":{"rendered":"Key Aspects of Building Advanced Search-Assisted Chatbots"},"content":{"rendered":"<div data-elementor-type=\"wp-post\" data-elementor-id=\"4076\" class=\"elementor elementor-4076\" data-elementor-post-type=\"post\">\n\t\t\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-63de7028 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"63de7028\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-f5582f\" data-id=\"f5582f\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-2f8f1007 elementor-widget elementor-widget-text-editor\" data-id=\"2f8f1007\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<h2><strong>Introduction to Generative Chatbots<\/strong><\/h2>\r\nChatbots are gaining popularity as productivity tools in companies. They help in finding information from various fields, such as HR, IT, sales or engineering. With the introduction of Chat-GPT technology and vector databases, it has become possible to create chatbots that generate accurate and consistent answers by combining LLM and RAG models.\r\n<h2><strong>Example of use case at NVIDIA<\/strong><\/h2>\r\nNVIDIA has built three chatbots: NVInfo Bot, NVHelp Bot, and Scout Bot, using the NVBot platform. Each of these chatbots supports different areas of information: from general corporate data, to IT and HR support, to financial information. Each bot uses advanced technologies and processes that allow it to operate effectively in different contexts.\r\n\r\n<img fetchpriority=\"high\" decoding=\"async\" class=\"wp-image-4079 aligncenter\" src=\"https:\/\/ai4app.pl\/wp-content\/uploads\/2024\/07\/RAG_arch_new-1-300x197.jpg\" alt=\"\" width=\"581\" height=\"381\" srcset=\"https:\/\/ai4app.pl\/wp-content\/uploads\/2024\/07\/RAG_arch_new-1-300x197.jpg 300w, https:\/\/ai4app.pl\/wp-content\/uploads\/2024\/07\/RAG_arch_new-1-768x505.jpg 768w, https:\/\/ai4app.pl\/wp-content\/uploads\/2024\/07\/RAG_arch_new-1-18x12.jpg 18w, https:\/\/ai4app.pl\/wp-content\/uploads\/2024\/07\/RAG_arch_new-1.jpg 936w\" sizes=\"(max-width: 581px) 100vw, 581px\" \/>\r\n\r\n&nbsp;\r\n<h2><strong>Ensuring the current status of company data (F)<\/strong><\/h2>\r\nA key challenge is ensuring that LLM models have access to the latest data. Base models are often static and can generate incorrect answers. The RAG process involves taking up-to-date information from the vector databases and feeding it to the LLM to generate answers. NVIDIA uses various techniques, such as metadata enrichment, document fragmentation, query paraphrasing, and result re-ranking, to improve the accuracy of the answers.\r\n<h2><strong>Building Flexible Chatbot Architectures (A)<\/strong><\/h2>\r\nIn a dynamic technological environment, it is crucial to create flexible platforms that can adapt to new tools and technologies. NVBot is a modular platform that allows for the selection of different LLM models, vector bases and agents, while supporting security, authorization and monitoring. This allows for the creation of chatbots that can evolve with technological advances.\r\n\r\n<img decoding=\"async\" class=\"wp-image-4080 aligncenter\" src=\"https:\/\/ai4app.pl\/wp-content\/uploads\/2024\/07\/Complex_agent_arch-300x100.png\" alt=\"\" width=\"552\" height=\"184\" srcset=\"https:\/\/ai4app.pl\/wp-content\/uploads\/2024\/07\/Complex_agent_arch-300x100.png 300w, https:\/\/ai4app.pl\/wp-content\/uploads\/2024\/07\/Complex_agent_arch-18x6.png 18w, https:\/\/ai4app.pl\/wp-content\/uploads\/2024\/07\/Complex_agent_arch.png 695w\" sizes=\"(max-width: 552px) 100vw, 552px\" \/>\r\n<h2><strong>Economics of chatbot implementation costs (C)<\/strong><\/h2>\r\nThe cost of implementing LLM-based generative chatbots can be high. NVIDIA considered both large, commercial LLM models and smaller, open-source models that offer comparable quality at a lower cost. A key aspect is also implementing an internal LLM gateway that helps manage subscriptions and data security.\r\n<h2><strong>Testing RAG-based chatbots (T)<\/strong><\/h2>\r\nTesting generative AI solutions requires long test cycles and human validation of responses. Test automation and the creation of representative reference data sets are key to effective testing. NVIDIA implements feedback mechanisms and automated testing to continuously improve chatbot performance.\r\n\r\n<img decoding=\"async\" class=\"wp-image-4081 aligncenter\" src=\"https:\/\/ai4app.pl\/wp-content\/uploads\/2024\/07\/HSA_query_nvhelp-300x276.png\" alt=\"\" width=\"444\" height=\"408\" srcset=\"https:\/\/ai4app.pl\/wp-content\/uploads\/2024\/07\/HSA_query_nvhelp-300x276.png 300w, https:\/\/ai4app.pl\/wp-content\/uploads\/2024\/07\/HSA_query_nvhelp-13x12.png 13w, https:\/\/ai4app.pl\/wp-content\/uploads\/2024\/07\/HSA_query_nvhelp.png 324w\" sizes=\"(max-width: 444px) 100vw, 444px\" \/>\r\n<h2><strong>Securing RAG-based chatbots (S)<\/strong><\/h2>\r\nTrust in generative chatbots is key, so it\u2019s important to implement safeguards against hallucinations, toxicity, lack of fairness, lack of transparency, and security breaches. NVIDIA focuses on securing access to corporate content and implementing compliance policies to ensure safe use of chatbots.\r\n\r\n&nbsp;\r\n<h2><strong>The future of chatbots<\/strong><\/h2>\r\nIn the future, RAG-based chatbots will become increasingly sophisticated and complex. Work will focus on developing agent architectures that can handle complex, multi-part queries and provide analytical responses. It will also be important to efficiently summarize large amounts of frequently updated enterprise data and automate various RAG checkpoints to optimize the entire process. As the technology evolves, chatbots will play an increasingly important role in increasing the efficiency and accessibility of information in the workplace.\r\n\r\n<img loading=\"lazy\" decoding=\"async\" class=\"wp-image-4082 aligncenter\" src=\"https:\/\/ai4app.pl\/wp-content\/uploads\/2024\/07\/NVHelp_metrics-300x191.png\" alt=\"\" width=\"609\" height=\"388\" srcset=\"https:\/\/ai4app.pl\/wp-content\/uploads\/2024\/07\/NVHelp_metrics-300x191.png 300w, https:\/\/ai4app.pl\/wp-content\/uploads\/2024\/07\/NVHelp_metrics-1024x652.png 1024w, https:\/\/ai4app.pl\/wp-content\/uploads\/2024\/07\/NVHelp_metrics-768x489.png 768w, https:\/\/ai4app.pl\/wp-content\/uploads\/2024\/07\/NVHelp_metrics-1536x978.png 1536w, https:\/\/ai4app.pl\/wp-content\/uploads\/2024\/07\/NVHelp_metrics-2048x1305.png 2048w, https:\/\/ai4app.pl\/wp-content\/uploads\/2024\/07\/NVHelp_metrics-18x12.png 18w\" sizes=\"(max-width: 609px) 100vw, 609px\" \/>\r\n<h2><strong>Summary<\/strong><\/h2>\r\nNVIDIA presents the FACTS framework, which covers the most important aspects of building chatbots: data freshness (F), architecture (A), costs (C), testing (T), and security (S). NVIDIA shares its experiences and strategies for optimizing chatbot performance at each stage. Future work will focus on developing agent architectures to handle complex queries and automate various RAG checkpoints. Creating effective RAG-based chatbots requires careful planning, continuous evaluation, and optimization. It is also crucial to take into account specific security requirements and cost management. Source: &quot;<a href=\"https:\/\/arxiv.org\/html\/2407.07858v1\">FACTS About Building Retrieval Augmented Generation-based Chatbots<\/a>&#8222;\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<\/div>","protected":false},"excerpt":{"rendered":"<p>Wprowadzenie do generatywnych chatbot\u00f3w Chatboty zyskuj\u0105 na popularno\u015bci jako narz\u0119dzia zwi\u0119kszaj\u0105ce produktywno\u015b\u0107 w firmach. Pomagaj\u0105 one w znajdowaniu informacji z r\u00f3\u017cnych dziedzin, takich jak HR, IT, sprzeda\u017c czy in\u017cynieria. Wraz z wprowadzeniem technologii Chat-GPT oraz baz danych wektorowych, mo\u017cliwe sta\u0142o si\u0119 tworzenie chatbot\u00f3w generuj\u0105cych trafne i sp\u00f3jne odpowiedzi dzi\u0119ki po\u0142\u0105czeniu modeli LLM i RAG. Przyk\u0142ad [&hellip;]<\/p>\n","protected":false},"author":5,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"default","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","ast-disable-related-posts":"","theme-transparent-header-meta":"default","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"set","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"footnotes":""},"categories":[1],"tags":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v22.3 (Yoast SEO v23.5) - 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