DistiLlama is a Chrome extension that leverages a locally running Large Language Model (LLM) to perform various tasks, including text summarization, chat, and document analysis. It utilizes Ollama as the locally running LLM instance and LangChain for text summarization. DistiLlama provides a user-friendly interface for interacting with the LLM, allowing users to summarize web pages, chat with documents (including PDFs), and engage in text-based conversations. The extension is easy to install and use, requiring only the installation of Ollama and a few simple steps to set up the environment. DistiLlama offers a range of customization options, including the choice of LLM model and the ability to configure the summarization chain. It also supports multimodal capabilities, allowing users to interact with the LLM through text, voice, and images. DistiLlama is a valuable tool for researchers, students, and professionals who seek to leverage the power of LLMs for various tasks without compromising data privacy.

Local Multimodal AI Chat is a hands-on project that teaches you how to build a multimodal chat application. It integrates different AI models to handle audio, images, and PDFs in a single chat interface. This project is perfect for anyone interested in AI and software development who wants to gain practical experience with these technologies.

This repository provides a ready-to-run basic Slack AI solution that allows users to summarize threads and channels using OpenAI. Users can generate thread summaries, channel overviews, channel summaries since a specific time, and full channel summaries. The tool is powered by GPT-3.5-Turbo and an ensemble of NLP models. It requires Python 3.8 or higher, an OpenAI API key, Slack App with associated API tokens, Poetry package manager, and ngrok for local development. Users can customize channel and thread summaries, run tests with coverage using pytest, and contribute to the project for future enhancements.

Local Multimodal AI Chat is a multimodal chat application that integrates various AI models to manage audio, images, and PDFs seamlessly within a single interface. It offers local model processing with Ollama for data privacy, integration with OpenAI API for broader AI capabilities, audio chatting with Whisper AI for accurate voice interpretation, and PDF chatting with Chroma DB for efficient PDF interactions. The application is designed for AI enthusiasts and developers seeking a comprehensive solution for multimodal AI technologies.

PDFToChat is a tool that allows users to chat with their PDF documents in seconds. It is powered by Together AI and Pinecone, utilizing a tech stack including Next.js, Mixtral, M2 Bert, LangChain.js, MongoDB Atlas, Bytescale, Vercel, Clerk, and Tailwind CSS. Users can deploy the tool to Vercel or any other host by setting up Together.ai, MongoDB Atlas database, Bytescale, Clerk, and Vercel. The tool enables users to interact with PDFs through chat, with future tasks including adding features like trash icon for deleting PDFs, exploring different embedding models, implementing auto scrolling, improving replies, benchmarking accuracy, researching chunking and retrieval best practices, adding demo video, upgrading to Next.js 14, adding analytics, customizing tailwind prose, saving chats in postgres DB, compressing large PDFs, implementing custom uploader, session tracking, error handling, and support for images in PDFs.

aiCoder is an AI-powered tool designed to streamline the coding process by automating repetitive tasks, providing intelligent code suggestions, and facilitating the integration of new features into existing codebases. It offers a chat interface for natural language interactions, methods and stubs lists for code modification, and settings customization for project-specific prompts. Users can leverage aiCoder to enhance code quality, focus on higher-level design, and save time during development.

OpenDAN is an open source Personal AI OS that consolidates various AI modules for personal use. It empowers users to create powerful AI agents like assistants, tutors, and companions. The OS allows agents to collaborate, integrate with services, and control smart devices. OpenDAN offers features like rapid installation, AI agent customization, connectivity via Telegram/Email, building a local knowledge base, distributed AI computing, and more. It aims to simplify life by putting AI in users' hands. The project is in early stages with ongoing development and future plans for user and kernel mode separation, home IoT device control, and an official OpenDAN SDK release.

RAGGENIE is a low-code RAG builder tool designed to simplify the creation of conversational AI applications. It offers out-of-the-box plugins for connecting to various data sources and building conversational AI on top of them, including integration with pre-built agents for actions. The tool is open-source under the MIT license, with a current focus on making it easy to build RAG applications and future plans for maintenance, monitoring, and transitioning applications from pilots to production.

Agentok Studio is a visual tool built for AutoGen, a cutting-edge agent framework from Microsoft and various contributors. It offers intuitive visual tools to simplify the construction and management of complex agent-based workflows. Users can create workflows visually as graphs, chat with agents, and share flow templates. The tool is designed to streamline the development process for creators and developers working on next-generation Multi-Agent Applications.

Dot is a standalone, open-source application designed for seamless interaction with documents and files using local LLMs and Retrieval Augmented Generation (RAG). It is inspired by solutions like Nvidia's Chat with RTX, providing a user-friendly interface for those without a programming background. Pre-packaged with Mistral 7B, Dot ensures accessibility and simplicity right out of the box. Dot allows you to load multiple documents into an LLM and interact with them in a fully local environment. Supported document types include PDF, DOCX, PPTX, XLSX, and Markdown. Users can also engage with Big Dot for inquiries not directly related to their documents, similar to interacting with ChatGPT. Built with Electron JS, Dot encapsulates a comprehensive Python environment that includes all necessary libraries. The application leverages libraries such as FAISS for creating local vector stores, Langchain, llama.cpp & Huggingface for setting up conversation chains, and additional tools for document management and interaction.

Podman AI Lab is an open source extension for Podman Desktop designed to work with Large Language Models (LLMs) on a local environment. It features a recipe catalog with common AI use cases, a curated set of open source models, and a playground for learning, prototyping, and experimentation. Users can quickly and easily get started bringing AI into their applications without depending on external infrastructure, ensuring data privacy and security.

lluminous is a fast and light open chat UI that supports multiple providers such as OpenAI, Anthropic, and Groq models. Users can easily plug in their API keys locally to access various models for tasks like multimodal input, image generation, multi-shot prompting, pre-filled responses, and more. The tool ensures privacy by storing all conversation history and keys locally on the user's device. Coming soon features include memory tool, file ingestion/embedding, embeddings-based web search, and prompt templates.

doc2plan is a browser-based application that helps users create personalized learning plans by extracting content from documents. It features a Creator for manual or AI-assisted plan construction and a Viewer for interactive plan navigation. Users can extract chapters, key topics, generate quizzes, and track progress. The application includes AI-driven content extraction, quiz generation, progress tracking, plan import/export, assistant management, customizable settings, viewer chat with text-to-speech and speech-to-text support, and integration with various Retrieval-Augmented Generation (RAG) models. It aims to simplify the creation of comprehensive learning modules tailored to individual needs.

A Python script leveraging advanced language models to summarize webpages and youtube videos directly from URLs. It integrates with LangChain and ChatOllama for state-of-the-art summarization, providing detailed summaries for quick understanding of web-based documents. The tool offers a command-line interface for easy use and integration into workflows, with plans to add support for translating to different languages and streaming text output on gradio. It can also be used via a web UI using the gradio app. The script is dockerized for easy deployment and is open for contributions to enhance functionality and capabilities.

Instrukt is a terminal-based AI integrated environment that allows users to create and instruct modular AI agents, generate document indexes for question-answering, and attach tools to any agent. It provides a platform for users to interact with AI agents in natural language and run them inside secure containers for performing tasks. The tool supports custom AI agents, chat with code and documents, tools customization, prompt console for quick interaction, LangChain ecosystem integration, secure containers for agent execution, and developer console for debugging and introspection. Instrukt aims to make AI accessible to everyone by providing tools that empower users without relying on external APIs and services.

Cerebellum is a lightweight browser agent that helps users accomplish user-defined goals on webpages through keyboard and mouse actions. It simplifies web browsing by treating it as navigating a directed graph, with each webpage as a node and user actions as edges. The tool uses a LLM to analyze page content and interactive elements to determine the next action. It is compatible with any Selenium-supported browser and can fill forms using user-provided JSON data. Cerebellum accepts runtime instructions to adjust browsing strategies and actions dynamically.

AnythingLLM is a full-stack application that enables you to turn any document, resource, or piece of content into context that any LLM can use as references during chatting. This application allows you to pick and choose which LLM or Vector Database you want to use as well as supporting multi-user management and permissions.

DistiLlama is a Chrome extension that leverages a locally running Large Language Model (LLM) to perform various tasks, including text summarization, chat, and document analysis. It utilizes Ollama as the locally running LLM instance and LangChain for text summarization. DistiLlama provides a user-friendly interface for interacting with the LLM, allowing users to summarize web pages, chat with documents (including PDFs), and engage in text-based conversations. The extension is easy to install and use, requiring only the installation of Ollama and a few simple steps to set up the environment. DistiLlama offers a range of customization options, including the choice of LLM model and the ability to configure the summarization chain. It also supports multimodal capabilities, allowing users to interact with the LLM through text, voice, and images. DistiLlama is a valuable tool for researchers, students, and professionals who seek to leverage the power of LLMs for various tasks without compromising data privacy.

SecureAI Tools is a private and secure AI tool that allows users to chat with AI models, chat with documents (PDFs), and run AI models locally. It comes with built-in authentication and user management, making it suitable for family members or coworkers. The tool is self-hosting optimized and provides necessary scripts and docker-compose files for easy setup in under 5 minutes. Users can customize the tool by editing the .env file and enabling GPU support for faster inference. SecureAI Tools also supports remote OpenAI-compatible APIs, with lower hardware requirements for using remote APIs only. The tool's features wishlist includes chat sharing, mobile-friendly UI, and support for more file types and markdown rendering.

The serverless-pdf-chat repository contains a sample application that allows users to ask natural language questions of any PDF document they upload. It leverages serverless services like Amazon Bedrock, AWS Lambda, and Amazon DynamoDB to provide text generation and analysis capabilities. The application architecture involves uploading a PDF document to an S3 bucket, extracting metadata, converting text to vectors, and using a LangChain to search for information related to user prompts. The application is not intended for production use and serves as a demonstration and educational tool.

Chat Your Doc is an experimental project exploring various applications based on LLM technology. It goes beyond being just a chatbot project, focusing on researching LLM applications using tools like LangChain and LlamaIndex. The project delves into UX, computer vision, and offers a range of examples in the 'Lab Apps' section. It includes links to different apps, descriptions, launch commands, and demos, aiming to showcase the versatility and potential of LLM applications.

Witsy is a generative AI desktop application that supports various models like OpenAI, Ollama, Anthropic, MistralAI, Google, Groq, and Cerebras. It offers features such as chat completion, image generation, scratchpad for content creation, prompt anywhere functionality, AI commands for productivity, expert prompts for specialization, LLM plugins for additional functionalities, read aloud capabilities, chat with local files, transcription/dictation, Anthropic Computer Use support, local history of conversations, code formatting, image copy/download, and more. Users can interact with the application to generate content, boost productivity, and perform various AI-related tasks.

Docs AI is a platform that allows users to train their documents, chat with their documents, and create chatbots to solve queries. It is built using NextJS, Tailwind, tRPC, ShadcnUI, Prisma, Postgres, NextAuth, Pinecone, and Cloudflare R2. The platform requires Node.js (Version: >=18.x), PostgreSQL, and Redis for setup. Users can utilize Docker for development by using the provided `docker-compose.yml` file in the `/app` directory.

LLM Tornado is a .NET library designed to simplify the consumption of various large language models (LLMs) from providers like OpenAI, Anthropic, Cohere, Google, Azure, Groq, and self-hosted APIs. It acts as an aggregator, allowing users to easily switch between different LLM providers with just a change in argument. Users can perform tasks such as chatting with documents, voice calling with AI, orchestrating assistants, generating images, and more. The library exposes capabilities through vendor extensions, making it easy to integrate and use multiple LLM providers simultaneously.

LLMStack is a no-code platform for building generative AI agents, workflows, and chatbots. It allows users to connect their own data, internal tools, and GPT-powered models without any coding experience. LLMStack can be deployed to the cloud or on-premise and can be accessed via HTTP API or triggered from Slack or Discord.

Daily Chinese ancient poetry and AI-generated images powered by Bing DALL-E-3. GitHub Action triggers the process automatically. Poetry is provided by Today's Poem API. The website is built with Astro.

EXIF Photo Blog is a full-stack photo blog application built with Next.js, Vercel, and Postgres. It features built-in authentication, photo upload with EXIF extraction, photo organization by tag, infinite scroll, light/dark mode, automatic OG image generation, a CMD-K menu with photo search, experimental support for AI-generated descriptions, and support for Fujifilm simulations. The application is easy to deploy to Vercel with just a few clicks and can be customized with a variety of environment variables.

SillyTavern is a user interface you can install on your computer (and Android phones) that allows you to interact with text generation AIs and chat/roleplay with characters you or the community create. SillyTavern is a fork of TavernAI 1.2.8 which is under more active development and has added many major features. At this point, they can be thought of as completely independent programs.

This project enables you to fetch liked tweets from Twitter (using Selenium), save it to JSON and Excel files, and perform initial data analysis and image captions. This is part of the initial steps for a larger personal project involving Large Language Models (LLMs).

Aila Desktop Application is a powerful tool that integrates multiple leading AI models into a single desktop application. It allows users to interact with various AI models simultaneously, providing diverse responses and insights to their inquiries. With its user-friendly interface and customizable features, Aila empowers users to engage with AI seamlessly and efficiently. Whether you're a researcher, student, or professional, Aila can enhance your AI interactions and streamline your workflow.

This project is an intelligent dialogue customer service tool based on a large model, which supports access to platforms such as WeChat, Qianniu, Bilibili, Douyin Enterprise, Douyin, Doudian, Weibo chat, Xiaohongshu professional account operation, Xiaohongshu, Zhihu, etc. You can choose GPT3.5/GPT4.0/ Lazy Treasure Box (more platforms will be supported in the future), which can process text, voice and pictures, and access external resources such as operating systems and the Internet through plug-ins, and support enterprise AI applications customized based on their own knowledge base.

LocalVocal is a live-streaming AI assistant plugin for OBS that allows you to transcribe audio speech into text and perform various language processing functions on the text using AI / LLMs (Large Language Models). It's privacy-first, with all data staying on your machine, and requires no GPU, cloud costs, network, or downtime.