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‎web/blog/2023-08-08-introducing-llmstack.md‎

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---
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title: Introducing LLMStack
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description: LLMStack is a low-code AI platform that allows you to build powerful AI applications using pre-trained language models.
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slug: /introducing-llmstack
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authors: [ajhai]
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tags: [llmstack, introduction]
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hide_table_of_contents: false
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---
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import ReactPlayer from "react-player";
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# Introducing LLMStack
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Excited to introduce LLMStack, an open source, low-code platform to build powerful AI experiences using LLMs.
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<!--truncate-->
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## Overview
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LLMStack is an end to end platform that allows you to build powerful AI applications using LLMs. You can build AI applications that can generate text, answer questions, summarize text, translate text, generate media and more. You can also chain multiple LLMs together to build complex AI applications. You can connect your data to LLMStack and use it to augment the language models. You can also connect your business processes to LLMStack and use it to automate your workflows.
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LLMStack comes with everything you need to build AI applications. It comes with a no-code builder that allows you to build AI applications without writing any code. It comes with a vector database that allows you to store your data and use it to augment the language models. Using its powerful API, you can integrate your AI applications with your existing products and services.
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<ReactPlayer
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playing
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controls
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url="/img/llmstack-demo.m4v"
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width="100%"
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height="100%"
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loop
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/>
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## Features
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- **🔗 Chain multiple models:** LLMStack allows you to chain multiple LLMs together to build complex generative AI applications.
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- **📊 Use generative AI on your Data:** Import your data into your accounts and use it in AI chains. LLMStack allows importing various types (_CSV, TXT, PDF, DOCX, PPTX etc.,_) of data from a variety of sources (_gdrive, notion, websites, direct uploads etc.,_). Platform will take care of preprocessing and vectorization of your data and store it in the vector database that is provided out of the box.
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- **🛠️ No-code builder:** LLMStack comes with a no-code builder that allows you to build AI chains without any coding experience. You can chain multiple LLMs together and connect them to your data and business processes.
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- **☁️ Deploy to the cloud or on-premise:** LLMStack can be deployed to the cloud or on-premise. You can deploy it to your own infrastructure or use our cloud offering at [Promptly](https://trypromptly.com).
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- **🚀 API access:** Apps or chatbots built with LLMStack can be accessed via HTTP API. You can also trigger your AI chains from **_Slack_** or **_Discord_**.
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- **🏢 Multi-tenant:** LLMStack is multi-tenant. You can create multiple organizations and add users to them. Users can only access the data and AI chains that belong to their organization.
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## What can you build with LLMStack?
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Using LLMStack you can build a variety of generative AI applications, chatbots and agents. Here are some examples:
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- **Chatbots:** Build chatbots that can answer questions, generate text, summarize text, translate text, classify text and more.
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- **AI Assistants:** Build AI assistants that can automate your workflows and business processes.
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- **AI Agents:** Build AI agents that can help you with your day to day tasks.
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- **AI Applications:** Build AI applications that can generate text, answer questions, summarize text, translate text, classify text and more.
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## Getting Started
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Head over to our github repository to get started with LLMStack: [https://github.com/trypromptly/LLMStack](https://github.com/trypromptly/LLMStack) or check out our cloud offering at [Promptly](https://trypromptly.com).
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We are excited to see what you build with LLMStack. If you have any questions or feedback, please leave a message in repository's discussions at [https://github.com/trypromptly/LLMStack/discussions](https://github.com/trypromptly/LLMStack/discussions).

‎web/blog/2023-08-17-run-os-llms-with-localai.md‎

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---
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title: Open Source LLMs with LocalAI
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description: Build AI Apps with Open Source LLMs like Llama2 using LocalAI and LLMStack.
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slug: /run-os-llms-on-llmstack-with-localai
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authors: [ajhai, vegito22]
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tags: [llmstack, localai, llama2, open-source]
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hide_table_of_contents: false
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---
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Now build AI Apps using Open Source LLMs like Llama2 on LLMStack using [LocalAI](https://localai.io)
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<!--truncate-->
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LLMStack now includes [LocalAI](https://github.com/go-skynet/LocalAI/) support which means you can now run Open Source LLMs like Llama2, stable diffusion etc., locally and build apps on top of them using LLMStack.
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![LocalAI](/img/ui/localai-example.png)
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## What is LocalAI?
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LocalAI is a drop-in replacement REST API that’s compatible with OpenAI API specifications for local inferencing. Read more about LocalAI [here](https://localai.io/).
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## How to use LocalAI with LLMStack?
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To use LocalAI with LLMStack, you need to have LocalAI running on your machine. You can follow the deployment instructions [here](https://localai.io/) to install LocalAI on your machine. Once LocalAI is up and running, you can configure LLMStack to use LocalAI by going to `Settings` and filling in the `LocalAI Base URL` and `LocalAI API Key` if any. Once done, click `Update` to save the configuration.
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![LocalAI Configuration](/img/ui/localai-settings.png)
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Once LocalAI is configured, you can use it in your apps by selecting `LocalAI` as the provider for processor and selecting the processor and model you want to use.
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Are there any other open source LLM frameworks that you would like to see on LLMStack? Let us know in our github discussions [here](https://github.com/trypromptly/LLMStack/discussions).

‎web/blog/authors.yml‎

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ajhai:
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name: Ajay Chintala
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title: Co-Founder & CTO, Promptly
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url: https://github.com/ajhai
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image_url: https://github.com/ajhai.png
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vegito22:
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name: Vignesh Aigal
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title: Co-Founder, Promptly
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url: https://github.com/vegito22
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image_url: https://github.com/vegito22.png

‎web/docusaurus.config.js‎

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position: "left",
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label: "Docs",
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},
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{
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label: "Blog",
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to: "/blog",
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},
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{
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href: "https://github.com/trypromptly/LLMStack",
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label: "GitHub",
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items: [
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{
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label: "Blog",
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href: "https://blog.trypromptly.com",
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to: "/blog",
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},
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{
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label: "GitHub",

‎web/static/img/ui/localai-example.png‎

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‎web/static/img/ui/localai-settings.png‎

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