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How to Utilize Obsidian‘s Generative AI Tools. Two plug-ins created by the community demonstrate how RTX AI PCs can support large language models for the next generation of app developers.

Obsidian Meaning

Obsidian is a note-taking and personal knowledge base program that works with Markdown files. Users may create internal linkages for notes using it, and they can see the relationships as a graph. It is intended to assist users in flexible, non-linearly structuring and organizing their ideas and information. Commercial licenses are available for purchase, however personal usage of the program is free.

Obsidian Features

Electron is the foundation of Obsidian. It is a cross-platform program that works on mobile operating systems like iOS and Android in addition to Windows, Linux, and macOS. The program does not have a web-based version. By installing plugins and themes, users may expand the functionality of Obsidian across all platforms by integrating it with other tools or adding new capabilities.

Obsidian distinguishes between community plugins, which are submitted by users and made available as open-source software via GitHub, and core plugins, which are made available and maintained by the Obsidian team. A calendar widget and a task board in the Kanban style are two examples of community plugins. The software comes with more than 200 community-made themes.

Every new note in Obsidian creates a new text document, and all of the documents are searchable inside the app. Obsidian works with a folder of text documents. Obsidian generates an interactive graph that illustrates the connections between notes and permits internal connectivity between notes. While Markdown is used to accomplish text formatting in Obsidian, Obsidian offers quick previewing of produced content.

Generative AI Tools In Obsidian

A group of AI aficionados is exploring with methods to incorporate the potent technology into standard productivity practices as generative AI develops and speeds up industry.

Community plug-in-supporting applications empower users to investigate the ways in which large language models (LLMs) might improve a range of activities. Users using RTX AI PCs may easily incorporate local LLMs by employing local inference servers that are powered by the NVIDIA RTX-accelerated llama.cpp software library.

It previously examined how consumers might maximize their online surfing experience by using Leo AI in the Brave web browser. Today, it examine Obsidian, a well-known writing and note-taking tool that uses the Markdown markup language and is helpful for managing intricate and connected records for many projects. Several of the community-developed plug-ins that add functionality to the app allow users to connect Obsidian to a local inferencing server, such as LM Studio or Ollama.

To connect Obsidian to LM Studio, just select the “Developer” button on the left panel, load any downloaded model, enable the CORS toggle, and click “Start.” This will enable LM Studio’s local server capabilities. Because the plug-ins will need this information to connect, make a note of the chat completion URL from the “Developer” log console (“http://localhost:1234/v1/chat/completions” by default).

Next, visit the “Settings” tab after launching Obsidian. After selecting “Community plug-ins,” choose “Browse.” Although there are a number of LLM-related community plug-ins, Text Generator and Smart Connections are two well-liked choices.

For creating notes and summaries on a study subject, for example, Text Generator is useful in an Obsidian vault.

Asking queries about the contents of an Obsidian vault, such the solution to a trivia question that was stored years ago, is made easier using Smart Connections.

Open the Text Generator settings, choose “Custom” under “Provider profile,” and then enter the whole URL in the “Endpoint” section. After turning on the plug-in, adjust the settings for Smart Connections. For the model platform, choose “Custom Local (OpenAI Format)” from the options panel on the right side of the screen. Next, as they appear in LM Studio, type the model name (for example, “gemma-2-27b-instruct”) and the URL into the corresponding fields.

The plug-ins will work when the fields are completed. If users are interested in what’s going on on the local server side, the LM Studio user interface will also display recorded activities.

Transforming Workflows With Obsidian AI Plug-Ins

Consider a scenario where a user want to organize a trip to the made-up city of Lunar City and come up with suggestions for things to do there. “What to Do in Lunar City” would be the title of the new note that the user would begin. A few more instructions must be included in the query submitted to the LLM in order to direct the results, since Lunar City is not an actual location. The model will create a list of things to do while traveling if you click the Text Generator plug-in button.

Obsidian will ask LM Studio to provide a response using the Text Generator plug-in, and LM Studio will then execute the Gemma 2 27B model. The model can rapidly provide a list of tasks if the user’s machine has RTX GPU acceleration.

Or let’s say that years later, the user’s buddy is visiting Lunar City and is looking for a place to dine. Although the user may not be able to recall the names of the restaurants they visited, they can review the notes in their vault Obsidian‘s word for a collection of notes to see whether they have any written notes.

A user may ask inquiries about their vault of notes and other material using the Smart Connections plug-in instead of going through all of the notes by hand. In order to help with the process, the plug-in retrieves pertinent information from the user’s notes and responds to the request using the same LM Studio server. The plug-in uses a method known as retrieval-augmented generation to do this.

Although these are entertaining examples, users may see the true advantages and enhancements in daily productivity after experimenting with these features for a while. Two examples of how community developers and AI fans are using AI to enhance their PC experiences are Obsidian plug-ins.

Thousands of open-source models are available for developers to include into their Windows programs using NVIDIA GeForce RTX technology.

How RTX AI PCs Unlock AI Agents That Use Generative AI to Autonomously Solve Complex Problems.

RTX-accelerated NVIDIA AnythingLLM introduces a Community Hub for exchanging AI agent skills, slash commands, and prompts.

The way humans realize their ideas has changed as a result of generative AI. This is furthered by agentic AI, which uses advanced, autonomous reasoning and iterative planning to assist in the resolution of intricate, multi-step problems.

With the help of the open-source desktop program AnythingLLM, users may easily incorporate large language model (LLM) functionality into a variety of locally installed PC applications. RTX AI PCs allows users to customize tools to suit certain needs by utilizing AI for tasks like content creation, summarization, and more.

AnythingLLM, which is accelerated on NVIDIA RTX AI PCs, has introduced a new Community Hub where users may experiment with creating and executing AI agents locally while exchanging prompts, slash commands, and AI agent skills.

Autonomously Solve Complex, Multi-Step Problems With Agentic AI

Chatbot capabilities can be expanded by AI agents. They usually comprehend the jobs’ context, are able to assess difficulties and devise solutions, and some are even capable of completing assignments completely.

For instance, an AI agent may display the restaurant’s phone number for a reservation and add reminders to the user’s calendar, even though a chatbot could respond to a prompt asking for restaurant recommendations.

Agents don’t get bogged down at the task level and assist in achieving larger objectives. Numerous agentic apps are being developed to aid with to-do lists, schedule management, task organization, email reply automation, individualized fitness recommendations, and travel planning.

An AI agent can collect and process data from databases and other sources when instructed to do so. For instance, it can employ an LLM to comprehend the task and then produce solutions and particular functions. An AI agent can then carry out the task if it is integrated with external tools and applications.

A feedback loop can even be used to enhance certain highly advanced agents. The AI agent gets faster and wiser when the data it creates is sent back into the system.

An in-depth examination of the methodology underlying agentic AI systems. To provide outcomes that can be put into action, AI agents receive user input, retrieve data from databases and other sources, and improve activities in real time.

These agents can execute tasks and do inferencing more quickly than any other PC with to NVIDIA RTX AI PCs. Even without an internet connection, users can run the agent locally to help protect data privacy.

AnythingLLM: A Collective Initiative, Boosted by RTX

The field of artificial intelligence is already exploring the potential of agentic AI and trying to develop more intelligent and powerful systems.

With the use of tools like LM Studio and Ollama, as well as their preferred models like Llama and Mistral, developers can quickly create, modify, and unlock agentic AI with apps like AnythingLLM. RTX AI PCs and workstations with high-performance Tensor Cores specialized hardware that offers the compute capacity required to run the newest and most complex AI models are used to accelerate AnythingLLM.

The goal of AnythingLLM is to make working with AI easy, efficient, and available to anyone. It enables customers to run state-of-the-art LLMs locally on RTX-powered PCs and workstations, utilize AI agents to execute intricate and customized tasks, and communicate with their documents using user-friendly interfaces. This entails unrestricted access to local resources, tools, and applications that are usually incompatible with browser-based or cloud-based apps, or that necessitate a great deal of setup and expertise to develop. AnythingLLM provides quicker, smarter, and more responsive AI for a range of operations within a single desktop application by utilizing the power of NVIDIA RTX GPUs.

Through AnythingLLM’s Community Hub, AI aficionados may quickly access on-device resources, learn productivity-boosting slash commands, develop specific AI agent abilities for certain workflows and bespoke tools, and get system prompts that can assist guide LLM behavior.

Microsoft Outlook email assistants, calendar agents, web search agents, home assistant controllers, and agents for populating and even integrating custom application programming interface endpoints and services for a particular use case are a few examples of agent skills that are available in the Community Hub.

Whether creating a spreadsheet assistant or taking on more complex workflows, AnythingLLM is fostering creativity and making it simpler to experiment with the newest technologies by allowing AI enthusiasts to download, modify, and use agentic AI workflows on their own systems in complete anonymity.

Powered by People, Driven by Innovation

AnythingLLM demonstrates how AI may actively boost creativity and productivity in addition to providing answers to queries. These kinds of applications show how AI is evolving into a crucial workflow collaborator.

The possible uses of agentic AI are numerous and call for imagination, knowledge, and processing power. Peak performance is provided by NVIDIA RTX AI PCs when agents are operating locally, whether they are managing more complicated use cases like coordinating corporate software or completing straightforward activities like creating and sharing content.