{"id":2737,"date":"2025-02-03T12:00:44","date_gmt":"2025-02-03T13:00:44","guid":{"rendered":"https:\/\/fdswebdesign.com\/?p=2737"},"modified":"2025-02-04T23:44:23","modified_gmt":"2025-02-04T23:44:23","slug":"how-to-run-chat-assistant-that-works-offline","status":"publish","type":"post","link":"https:\/\/fdswebdesign.com\/index.php\/2025\/02\/03\/how-to-run-chat-assistant-that-works-offline\/","title":{"rendered":"How to Run Chat Assistant that Works Offline"},"content":{"rendered":"<p>AI chat assistants have become essential tools for productivity and creativity. They can help with many things, from answering questions to doing some tasks automatically. But most of these tools need to connect to services, like OpenAI and Claude, which means you always need internet access. While it is convenient, it also raises concerns about privacy, data security, and reliance on external servers.<\/p>\n<p>If you want to use <a href=\"https:\/\/www.hongkiat.com\/blog\/create-chatbot-with-openai\/\">AI chat assistants<\/a> without these concerns, you can host and run your own AI models on your local machine or server. This allows you to have full control over your data, as well as the ability to customize the models to suit your needs.<\/p>\n<p>In this article, we\u2019ll show you how to host and use AI chat assistants using <strong><a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/openwebui.com\/\">Open WebUI<\/a><\/strong> that work on your local machine or server, and could also work offline.<\/p>\n<div class=\"su-divider su-divider-style-list\" style=\"margin:15px 0;border-width:3px;border-color:#999999\"><\/div>\n<div class=\"su-box su-box-style-default su-box-v7\" id=\"\" style=\"border-color:#000000;border-radius:3px\">\n<div class=\"su-box-title\" style=\"background-color:#333333;color:#FFFFFF;border-top-left-radius:1px;border-top-right-radius:1px\">Table of Contents<\/div>\n<div class=\"su-box-content su-u-clearfix su-u-trim\" style=\"border-bottom-left-radius:1px;border-bottom-right-radius:1px\">\n<ul>\n<li><a href=\"#what-is-open-webui\">What is Open WebUI<\/a><\/li>\n<li><a href=\"#system-prerequisites\">System Prerequisites<\/a><\/li>\n<li><a href=\"#system-requirements\">System Requirements<\/a><\/li>\n<li><a href=\"#installation-process\">Installation Process<\/a><\/li>\n<li><a href=\"#creating-an-account\">Creating an Account<\/a><\/li>\n<li><a href=\"#selecting-a-model\">Selecting a Model<\/a><\/li>\n<li><a href=\"#model-comparison-guide\">Model Comparison Guide<\/a><\/li>\n<li><a href=\"#interacting-with-the-chat-assistant\">Interacting with the Chat Assistant<\/a><\/li>\n<li><a href=\"#troubleshooting-guide\">Troubleshooting Guide<\/a><\/li>\n<li><a href=\"#advanced-features\">Advanced Features<\/a><\/li>\n<li><a href=\"#leveraging-multimodal-capabilities\">Leveraging Multimodal Capabilities<\/a><\/li>\n<li><a href=\"#wrapping-up\">Wrapping Up<\/a><\/li>\n<\/ul>\n<\/div>\n<\/div>\n<div class=\"su-divider su-divider-style-list\" style=\"margin:15px 0;border-width:3px;border-color:#999999\"><\/div>\n<h4 id=\"what-is-open-webui\">What is Open WebUI<\/h4>\n<p><strong>Open WebUI<\/strong> is an open-source web interface designed for interacting with various Large Language Models (LLMs).<\/p>\n<p>It comes with a number of features such as Retrieval Augmented Generation (RAG) support, image generation, Markdown and Latex support, web search support with <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/github.com\/searxng\/searxng\">SearXNG<\/a>, Role-based Access Control, and a lot more which makes it comparable to popular services like ChatGPT and Claude.<\/p>\n<div class=\"su-divider su-divider-style-list\" style=\"margin:15px 0;border-width:3px;border-color:#999999\"><\/div>\n<h4 id=\"system-prerequisites\">System Prerequisites<\/h4>\n<p>To get the Open WebUI up and running, you\u2019ll need the following:<\/p>\n<ul>\n<li><strong><a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/www.docker.com\/\">Docker<\/a><\/strong>: In this article we are going to use Docker to run <strong>Open WebUI<\/strong>. This way the application is contained and does not interfere directly with your computer system.<\/li>\n<li><strong>Ollama<\/strong>: You will also need Ollama to run the models. Ollama is a tool that allows you to orchestrate multiple models. It is used to run the models in the Open WebUI. Follow the instructions on our article <a href=\"#\">Getting Started with Ollama<\/a> to install and set up Ollama in your computer.<\/li>\n<\/ul>\n<p>After you have installed Docker and Ollama, make sure that you have Ollama running with the API accessible at <code>127.0.0.1:11434<\/code> or <code>localhost:11434<\/code>. You can check this by running the following command to get the version of Ollama:<\/p>\n<pre>\r\ncurl http:\/\/localhost:11434\/api\/version\r\n<\/pre>\n<p>If it returns a version number, Ollama is running correctly and we are ready to proceed with the installation of Open WebUI.<\/p>\n<div class=\"su-divider su-divider-style-list\" style=\"margin:15px 0;border-width:3px;border-color:#999999\"><\/div>\n<h4 id=\"system-requirements\">System Requirements<\/h4>\n<p>Before installing Open WebUI and Ollama, ensure your system meets these minimum requirements:<\/p>\n<h5>Hardware Requirements:<\/h5>\n<div class=\"su-table su-table-alternate\">\n<table>\n<thead>\n<tr>\n<th>Component<\/th>\n<th>Requirements<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td><strong>CPU<\/strong><\/td>\n<td>Modern multi-core processor (4+ cores recommended)<\/td>\n<\/tr>\n<tr>\n<td><strong>RAM<\/strong><\/td>\n<td>Minimum 8GB, 16GB or more recommended for larger models<\/td>\n<\/tr>\n<tr>\n<td><strong>Storage<\/strong><\/td>\n<td>At least 10GB free space for base installation, plus additional space for models:<\/p>\n<ul>\n<li>llama3.2: ~4GB<\/li>\n<li>llama3.2-vision: ~8GB<\/li>\n<li>Additional models: 4-15GB each depending on model size<\/li>\n<\/ul>\n<\/td>\n<\/tr>\n<tr>\n<td><strong>GPU<\/strong><\/td>\n<td>Optional but recommended for better performance:<\/p>\n<ul>\n<li>NVIDIA GPU with CUDA support (8GB+ VRAM recommended)<\/li>\n<li>Or AMD GPU with ROCm support<\/li>\n<\/ul>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<h5>Software Requirements:<\/h5>\n<div class=\"su-table su-table-alternate\">\n<table>\n<thead>\n<tr>\n<th>Component<\/th>\n<th>Requirements<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td><strong>Operating System<\/strong><\/td>\n<td>\n<ul>\n<li>Linux (Ubuntu 20.04 or newer recommended)<\/li>\n<li>macOS 12 or newer (including M1\/M2 support)<\/li>\n<li>Windows 10\/11 with WSL2<\/li>\n<\/ul>\n<\/td>\n<\/tr>\n<tr>\n<td><strong>Docker<\/strong><\/td>\n<td>Latest stable version<\/td>\n<\/tr>\n<tr>\n<td><strong>Browser<\/strong><\/td>\n<td>Modern web browser (Chrome, Firefox, Safari, or Edge)<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<p>Note: These requirements are for running basic models. More demanding models or concurrent usage may require more powerful hardware.<\/p>\n<div class=\"su-divider su-divider-style-list\" style=\"margin:15px 0;border-width:3px;border-color:#999999\"><\/div>\n<h4 id=\"installation-process\">Installation Process<\/h4>\n<p>To install and run Open WebUI, you can run the following command:<\/p>\n<pre>\r\ndocker run -d -p 3000:8080 --add-host=host.docker.internal:host-gateway -v open-webui:\/app\/backend\/data --name open-webui --restart always ghcr.io\/open-webui\/open-webui:main\r\n<\/pre>\n<p>If this is the first run, this command will download the <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/github.com\/open-webui\/open-webui\/pkgs\/container\/open-webui\">open-webui<\/a> Docker image. It may take a while but subsequent runs will be faster. Once the image is downloaded, it will start the container and you can access the Open WebUI at <code>localhost:3000<\/code> in your browser.<\/p>\n<p>Note, that if you see an error when loading it in the browser, wait a bit for a few minutes. It may still be initializing and downloading some resources in the background to complete the setup.<\/p>\n<p>When you see the following screen, you have successfully installed Open WebUI and <strong>ready to get started<\/strong>.<\/p>\n<figure><img decoding=\"async\" loading=\"lazy\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" alt=\"Open WebUI start screen showing setup interface\" width=\"1000\" height=\"640\" class=\"lazyload\" data-src=\"https:\/\/fdswebdesign.com\/wp-content\/uploads\/2025\/02\/openweb-ui-start.jpg\"><\/figure>\n<div class=\"su-divider su-divider-style-list\" style=\"margin:15px 0;border-width:3px;border-color:#999999\"><\/div>\n<h4 id=\"creating-an-account\">Creating an Account<\/h4>\n<p>When you first access the Open WebUI, you will be prompted to create an admin account. You will need to input your name, email, and password.<\/p>\n<figure><img decoding=\"async\" loading=\"lazy\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" alt=\"Open WebUI account creation form\" width=\"1000\" height=\"640\" class=\"lazyload\" data-src=\"https:\/\/fdswebdesign.com\/wp-content\/uploads\/2025\/02\/openweb-ui-create-account.jpg\"><\/figure>\n<p>After you have created an account, you will be immediately logged in and see the following interface.<\/p>\n<figure><img decoding=\"async\" loading=\"lazy\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" alt=\"Open WebUI chat interface dashboard\" width=\"1000\" height=\"640\" class=\"lazyload\" data-src=\"https:\/\/fdswebdesign.com\/wp-content\/uploads\/2025\/02\/openweb-ui-chat-interface.jpg\"><\/figure>\n<div class=\"su-divider su-divider-style-list\" style=\"margin:15px 0;border-width:3px;border-color:#999999\"><\/div>\n<h4 id=\"selecting-a-model\">Selecting a Model<\/h4>\n<p>At this point, we still can\u2019t interact with the chat assistant because we haven\u2019t selected a model yet.<\/p>\n<p>To download the model, you can click on the top <strong>\u201cSelect a model\u201d<\/strong> option. Type in the model name e.g. llama3.2 and select the <strong>\u201cPull \u2018llama3.2\u2019 from Ollama.com\u201d<\/strong>, as you can see below.<\/p>\n<figure><img decoding=\"async\" loading=\"lazy\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" alt=\"Open WebUI model pull dialog showing llama3.2 selection\" width=\"1000\" height=\"640\" class=\"lazyload\" data-src=\"https:\/\/fdswebdesign.com\/wp-content\/uploads\/2025\/02\/openweb-ui-pull-model.jpg\"><\/figure>\n<p>Alternatively, since the model is downloaded from the Ollama library, we can also download it directly with the Ollama CLI. In our case, to download the <strong>\u201cllama3.2\u201d<\/strong> model, we can run:<\/p>\n<pre>\r\nollama pull llama3.2\r\n<\/pre>\n<p>Again, this process will take some time to download the model. Once it is downloaded, you can select the model from the <strong>\u201cSelect a model\u201d<\/strong> option.<\/p>\n<figure><img decoding=\"async\" loading=\"lazy\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" alt=\"Open WebUI model selection dropdown menu\" width=\"1000\" height=\"480\" class=\"lazyload\" data-src=\"https:\/\/fdswebdesign.com\/wp-content\/uploads\/2025\/02\/openweb-ui-select-model.jpg\"><\/figure>\n<div class=\"su-divider su-divider-style-list\" style=\"margin:15px 0;border-width:3px;border-color:#999999\"><\/div>\n<h4 id=\"model-comparison-guide\">Model Comparison Guide<\/h4>\n<p>Open WebUI supports various models through Ollama. Here\u2019s a comparison of commonly used models to help you choose the right one for your needs:<\/p>\n<div class=\"su-table su-table-alternate\">\n<table>\n<thead>\n<tr>\n<th>Model<\/th>\n<th>Size<\/th>\n<th>Key Features<\/th>\n<th>Best For<\/th>\n<th>Limitations<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>llama3.2<\/td>\n<td>~4GB<\/td>\n<td>\n<ul>\n<li>General text generation<\/li>\n<li>Code completion<\/li>\n<li>Analysis tasks<\/li>\n<\/ul>\n<\/td>\n<td>\n<ul>\n<li>General chat<\/li>\n<li>Writing assistance<\/li>\n<li>Code help<\/li>\n<\/ul>\n<\/td>\n<td>\n<ul>\n<li>No image processing<\/li>\n<li>Knowledge cutoff in 2023<\/li>\n<\/ul>\n<\/td>\n<\/tr>\n<tr>\n<td>llama3.2-vision<\/td>\n<td>~8GB<\/td>\n<td>\n<ul>\n<li>Image understanding<\/li>\n<li>Visual analysis<\/li>\n<li>Multi-modal tasks<\/li>\n<\/ul>\n<\/td>\n<td>\n<ul>\n<li>Image analysis<\/li>\n<li>Visual QA<\/li>\n<li>Image-based tasks<\/li>\n<\/ul>\n<\/td>\n<td>\n<ul>\n<li>Larger resource requirements<\/li>\n<li>Slower response times<\/li>\n<\/ul>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<p>When choosing a model, consider these factors:<\/p>\n<ul>\n<li><strong>Hardware Capabilities:<\/strong> Ensure your system can handle the model\u2019s requirements<\/li>\n<li><strong>Use Case:<\/strong> Match the model\u2019s capabilities to your specific needs<\/li>\n<li><strong>Response Time:<\/strong> Larger models generally have slower response times<\/li>\n<li><strong>Storage Space:<\/strong> Consider the available disk space for model storage<\/li>\n<\/ul>\n<div class=\"su-divider su-divider-style-list\" style=\"margin:15px 0;border-width:3px;border-color:#999999\"><\/div>\n<h4 id=\"interacting-with-the-chat-assistant\">Interacting with the Chat Assistant<\/h4>\n<p>Once you have selected the model, you can start interacting with the chat assistant. You can type in your questions or prompts in the chat box and the chat assistant will respond accordingly.<\/p>\n<p>The response would work best if you ask questions or prompts that are related to the model you have selected. For example, if you have selected the <strong>\u201cllama3.2\u201d<\/strong> model, you can ask questions related to general knowledge, trivia, or any other topic that the model is trained on.<\/p>\n<p>For example, you can ask questions like:<\/p>\n<ul>\n<li>What is the capital of Indonesia?<\/li>\n<li>Who is the author of the book \u201cLord of the Ring\u201d?<\/li>\n<li>What is the boiling point of water?<\/li>\n<\/ul>\n<figure><img decoding=\"async\" loading=\"lazy\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" alt=\"Open WebUI chat assistant conversation interface\" width=\"1000\" height=\"640\" class=\"lazyload\" data-src=\"https:\/\/fdswebdesign.com\/wp-content\/uploads\/2025\/02\/openweb-ui-chat-assistant.jpg\"><\/figure>\n<p>Keep in mind though the \u201cllama3.2\u201d may not be answering accurately for real-time events since the model is only trained with the data up to 2023.<\/p>\n<div class=\"su-divider su-divider-style-list\" style=\"margin:15px 0;border-width:3px;border-color:#999999\"><\/div>\n<h4 id=\"troubleshooting-guide\">Troubleshooting Guide<\/h4>\n<p>When using Open WebUI, you might encounter some common issues. Here\u2019s how to resolve them:<\/p>\n<h5>Docker Container Won\u2019t Start<\/h5>\n<ul>\n<li><strong>Symptom:<\/strong> Docker container fails to start or crashes immediately<\/li>\n<li>Check if port 3000 is already in use:\n<pre>lsof -i :3000<\/pre>\n<p>    If in use, either stop the conflicting service or change the port in the docker run command <\/p>\n<\/li>\n<li>Verify Docker daemon is running:\n<pre>systemctl status docker<\/pre>\n<\/li>\n<li>Check Docker logs:\n<pre>docker logs open-webui<\/pre>\n<\/li>\n<\/ul>\n<h5>Connection to Ollama Failed<\/h5>\n<ul>\n<li><strong>Symptom:<\/strong> \u201cCannot connect to Ollama\u201d error message<\/li>\n<li>Verify Ollama is running:\n<pre>curl http:\/\/localhost:11434\/api\/version<\/pre>\n<\/li>\n<li>Check if Ollama is accessible from Docker:\n<pre>docker exec open-webui curl http:\/\/host.docker.internal:11434\/api\/version<\/pre>\n<\/li>\n<li>Restart both services:\n<pre>systemctl restart ollama\r\ndocker restart open-webui<\/pre>\n<\/li>\n<\/ul>\n<h5>Model Download Issues<\/h5>\n<ul>\n<li><strong>Symptom:<\/strong> Model download fails or times out<\/li>\n<li>Check available disk space:\n<pre>df -h<\/pre>\n<\/li>\n<li>Try downloading through Ollama CLI:\n<pre>ollama pull modelname<\/pre>\n<\/li>\n<li>Clear Ollama cache and retry:\n<pre>rm -rf ~\/.ollama\/models\/*<\/pre>\n<\/li>\n<\/ul>\n<div class=\"su-divider su-divider-style-list\" style=\"margin:15px 0;border-width:3px;border-color:#999999\"><\/div>\n<h4 id=\"advanced-features\">Advanced Features<\/h4>\n<h5>Using RAG (Retrieval Augmented Generation)<\/h5>\n<p>RAG allows you to enhance the model\u2019s responses with your own knowledge base. Here\u2019s how to set it up:<\/p>\n<p><strong>1. Prepare Your Documents<\/strong><br \/>\n  Your knowledge base can include PDF, TXT, DOCX, and MD files. Simply place these documents in the designated knowledge base directory, making sure they\u2019re properly formatted and readable.<\/p>\n<p><strong>2. Configure RAG Settings<\/strong><\/p>\n<pre>\r\n{\r\n    \"rag_enabled\": true,\r\n    \"chunk_size\": 500,\r\n    \"chunk_overlap\": 50,\r\n    \"document_lang\": \"en\"\r\n}<\/pre>\n<h5>Setting Up Web Search with SearXNG<\/h5>\n<p>Integrate web search capabilities into your chat assistant:<\/p>\n<pre>\r\ndocker run -d \r\n  --name searxng \r\n  -p 8080:8080 \r\n  -v searxng-data:\/etc\/searxng \r\n  searxng\/searxng\r\n<\/pre>\n<p>Then configure Open WebUI to use SearXNG:<\/p>\n<ol class=\"steps\">\n<li>Go to Settings &gt; Advanced<\/li>\n<li>Enable Web Search<\/li>\n<li>Enter SearXNG URL: <code>http:\/\/localhost:8080<\/code><\/li>\n<li>Configure search parameters (optional)<\/li>\n<\/ol>\n<h5>Role-based Access Control<\/h5>\n<p>Configure different user roles and permissions:<\/p>\n<div class=\"su-table su-table-alternate\">\n<table>\n<thead>\n<tr>\n<th>Role<\/th>\n<th>Permissions<\/th>\n<th>Use Case<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>Admin<\/td>\n<td>Full system access<\/td>\n<td>System management<\/td>\n<\/tr>\n<tr>\n<td>Power User<\/td>\n<td>Model management, RAG configuration<\/td>\n<td>Advanced users<\/td>\n<\/tr>\n<tr>\n<td>Basic User<\/td>\n<td>Chat interaction only<\/td>\n<td>Regular users<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<div class=\"su-divider su-divider-style-list\" style=\"margin:15px 0;border-width:3px;border-color:#999999\"><\/div>\n<h4 id=\"leveraging-multimodal-capabilities\">Leveraging Multimodal Capabilities<\/h4>\n<p>Open WebUI also supports multimodal capabilities, which means you can generate images along with text or use an image as part of your prompt inputs.<\/p>\n<p>To do so, however, you\u2019d need a model with multimodal capabilities. In this example, we can use the <strong>\u201cllama3.2-vision\u201d<\/strong>. You can download the model from the Open WebUI interface as we did before or use the Ollama CLI to download it directly:<\/p>\n<pre>\r\nollama pull llama3.2-vision\r\n<\/pre>\n<p>After it\u2019s downloaded, select the model and upload an image to the chat assistant. You can do this by clicking on the <kbd>+<\/kbd> button and submit it along with your prompt.<\/p>\n<p>In this example, I\u2019d use an image, <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/openverse.org\/image\/a9e0bff3-3272-4c3a-bbd4-92e542e1f41a?q=bicycle&amp;p=7\">The Red Bicycle from Openverse<\/a> and ask <strong><q>What\u2019s the primary focus of this picture?<\/q><\/strong>.<\/p>\n<p>Indeed, it is able to answer the question, and it even knows the color of the bicycle, as we can see below.<\/p>\n<figure><img decoding=\"async\" loading=\"lazy\" src=\"data:image\/gif;base64,R0lGODlhAQABAAAAACH5BAEKAAEALAAAAAABAAEAAAICTAEAOw==\" alt=\"Open WebUI multimodal chat interface showing image analysis of a red bicycle\" width=\"1000\" height=\"640\" class=\"lazyload\" data-src=\"https:\/\/fdswebdesign.com\/wp-content\/uploads\/2025\/02\/openweb-ui-multimodal-model.jpg\"><\/figure>\n<div class=\"su-divider su-divider-style-list\" style=\"margin:15px 0;border-width:3px;border-color:#999999\"><\/div>\n<h4 id=\"wrapping-up\">Wrapping Up<\/h4>\n<p>Open WebUI is a powerful tool that allows you to host and use AI chat assistants on your local machine or server. It provides a user-friendly interface for interacting with various Large Language Models (LLMs).<\/p>\n<p>It\u2019s a perfect tool for those who are concerned about privacy, data security, and reliance on external servers. With Open WebUI, you can have full control over your data and privacy, as well as the ability to customize the models to suit your needs.<\/p>\n<p>It is also a great tool for developers who want to experiment with AI chat assistants and build their own custom models. With Open WebUI, you can easily host and run your models, and interact with them using a simple and intuitive interface.<\/p>\n<div class=\"su-divider su-divider-style-list\" style=\"margin:15px 0;border-width:3px;border-color:#999999\"><\/div>\n<p>The post <a href=\"https:\/\/www.hongkiat.com\/blog\/run-offline-chat-assistant\/\">How to Run Chat Assistant that Works Offline<\/a> appeared first on <a href=\"https:\/\/www.hongkiat.com\/blog\">Hongkiat<\/a>.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>AI chat assistants have become essential tools for productivity and creativity. They can help with many things, from answering questions to doing some tasks automatically. But most of these tools need to connect to services, like OpenAI and Claude, which means you always need internet access. While it is convenient, it also raises concerns about&#8230;<\/p>\n","protected":false},"author":1,"featured_media":2739,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[11],"tags":[],"class_list":["post-2737","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-inspiration"],"_links":{"self":[{"href":"https:\/\/fdswebdesign.com\/index.php\/wp-json\/wp\/v2\/posts\/2737","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/fdswebdesign.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/fdswebdesign.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/fdswebdesign.com\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/fdswebdesign.com\/index.php\/wp-json\/wp\/v2\/comments?post=2737"}],"version-history":[{"count":3,"href":"https:\/\/fdswebdesign.com\/index.php\/wp-json\/wp\/v2\/posts\/2737\/revisions"}],"predecessor-version":[{"id":2747,"href":"https:\/\/fdswebdesign.com\/index.php\/wp-json\/wp\/v2\/posts\/2737\/revisions\/2747"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/fdswebdesign.com\/index.php\/wp-json\/wp\/v2\/media\/2739"}],"wp:attachment":[{"href":"https:\/\/fdswebdesign.com\/index.php\/wp-json\/wp\/v2\/media?parent=2737"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/fdswebdesign.com\/index.php\/wp-json\/wp\/v2\/categories?post=2737"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/fdswebdesign.com\/index.php\/wp-json\/wp\/v2\/tags?post=2737"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}