rag-chatbot is a tool that allows users to chat with multiple PDFs using Ollama and LlamaIndex. It provides an easy setup for running on local machines or Kaggle notebooks. Users can leverage models from Huggingface and Ollama, process multiple PDF inputs, and chat in multiple languages. The tool offers a simple UI with Gradio, supporting chat with history and QA modes. Setup instructions are provided for both Kaggle and local environments, including installation steps for Docker, Ollama, Ngrok, and the rag_chatbot package. Users can run the tool locally and access it via a web interface. Future enhancements include adding evaluation, better embedding models, knowledge graph support, improved document processing, MLX model integration, and Corrective RAG.

RTXZY-MD is a bot tool that supports file hosting, QR code, pairing code, and RestApi features. Users must fill in the Apikey for the bot to function properly. It is not recommended to install the bot on platforms lacking ffmpeg, imagemagick, webp, or express.js support. The tool allows for 95% implementation of website api and supports free and premium ApiKeys. Users can join group bots and get support from Sociabuzz. The tool can be run on Heroku with specific buildpacks and is suitable for Windows/VPS/RDP users who need Git, NodeJS, FFmpeg, and ImageMagick installations.

Airdrop-tools is a repository containing tools for all Telegram bots. Users can join the Telegram group for support and access various bot apps like Moonbix, Blum, Major, Memefi, and more. The setup requires Node.js and Python, with instructions on creating data directories and installing extensions. Users can run different tools like Blum, Major, Moonbix, Yescoin, Matchain, Fintopio, Agent301, IAMDOG, Banana, Cats, Wonton, and Xkucoin by following specific commands. The repository also provides contact information and options for supporting the creator.

WeChat Bot is a simple and easy-to-use WeChat robot based on chatgpt and wechaty. It can help you automatically reply to WeChat messages or manage WeChat groups/friends. The tool requires configuration of AI services such as Xunfei, Kimi, or ChatGPT. Users can customize the tool to automatically reply to group or private chat messages based on predefined conditions. The tool supports running in Docker for easy deployment and provides a convenient way to interact with various AI services for WeChat automation.

AICommit2 is a Reactive CLI tool that streamlines interactions with various AI providers such as OpenAI, Anthropic Claude, Gemini, Mistral AI, Cohere, and unofficial providers like Huggingface and Clova X. Users can request multiple AI simultaneously to generate git commit messages without waiting for all AI responses. The tool runs 'git diff' to grab code changes, sends them to configured AI, and returns the AI-generated commit message. Users can set API keys or Cookies for different providers and configure options like locale, generate number of messages, commit type, proxy, timeout, max-length, and more. AICommit2 can be used both locally with Ollama and remotely with supported providers, offering flexibility and efficiency in generating commit messages.

The langchain4j-aideepin-web repository is the frontend project of langchain4j-aideepin, an open-source, offline deployable retrieval enhancement generation (RAG) project based on large language models such as ChatGPT and application frameworks such as Langchain4j. It includes features like registration & login, multi-sessions (multi-roles), image generation (text-to-image, image editing, image-to-image), suggestions, quota control, knowledge base (RAG) based on large models, model switching, and search engine switching.

Talk With Gemini is a web application that allows users to deploy their private Gemini application for free with one click. It supports Gemini Pro and Gemini Pro Vision models. The application features talk mode for direct communication with Gemini, visual recognition for understanding picture content, full Markdown support, automatic compression of chat records, privacy and security with local data storage, well-designed UI with responsive design, fast loading speed, and multi-language support. The tool is designed to be user-friendly and versatile for various deployment options and language preferences.

Aiogram bot template is a boilerplate for creating Telegram bots using Aiogram framework. It provides a solid foundation for building robust and scalable bots with a focus on code organization, database integration, and localization.

Ollama4j is a Java library that serves as a wrapper or binding for the Ollama server. It facilitates communication with the Ollama server and provides models for deployment. The tool requires Java 11 or higher and can be installed locally or via Docker. Users can integrate Ollama4j into Maven projects by adding the specified dependency. The tool offers API specifications and supports various development tasks such as building, running unit tests, and integration tests. Releases are automated through GitHub Actions CI workflow. Areas of improvement include adhering to Java naming conventions, updating deprecated code, implementing logging, using lombok, and enhancing request body creation. Contributions to the project are encouraged, whether reporting bugs, suggesting enhancements, or contributing code.

The gpt-bitcoin repository is focused on creating an automated trading system for Bitcoin using GPT AI technology. It provides different versions of trading strategies utilizing various data sources such as OHLCV, Moving Averages, RSI, Stochastic Oscillator, MACD, Bollinger Bands, Orderbook Data, news data, fear/greed index, and chart images. Users can set up the system by creating a .env file with necessary API keys and installing required dependencies. The repository also includes instructions for setting up the environment on local machines and AWS EC2 Ubuntu servers. The future plan includes expanding the system to support other cryptocurrency exchanges like Bithumb, Binance, Coinbase, OKX, and Bybit.

This is an open-source project for playing the game King of Glory with an artificial intelligence model. The first phase of the project has been completed, and future upgrades will be built upon this foundation. The second phase of the project has started, and progress is expected to proceed according to plan. For any questions, feel free to join the QQ exchange group: 687853827. The project aims to learn artificial intelligence and strictly prohibits cheating. Detailed installation instructions are available in the doc/README.md file. Environment installation video: (bilibili) Welcome to follow, like, tip, comment, and provide your suggestions.

Ollama4j is a Java library that serves as a wrapper or binding for the Ollama server. It allows users to communicate with the Ollama server and manage models for various deployment scenarios. The library provides APIs for interacting with Ollama, generating fake data, testing UI interactions, translating messages, and building web UIs. Users can easily integrate Ollama4j into their Java projects to leverage the functionalities offered by the Ollama server.

Aim is a command-line tool for downloading and uploading files with resume support. It supports various protocols including HTTP, FTP, SFTP, SSH, and S3. Aim features an interactive mode for easy navigation and selection of files, as well as the ability to share folders over HTTP for easy access from other devices. Additionally, it offers customizable progress indicators and output formats, and can be integrated with other commands through piping. Aim can be installed via pre-built binaries or by compiling from source, and is also available as a Docker image for platform-independent usage.

MorGana Form is a full-stack form builder project developed using Next.js, React, TypeScript, Ant Design, PostgreSQL, and other technologies. It allows users to quickly create and collect data through survey forms. The project structure includes components, hooks, utilities, pages, constants, Redux store, themes, types, server-side code, and component packages. Environment variables are required for database settings, NextAuth login configuration, and file upload services. Additionally, the project integrates an AI model for form generation using the Ali Qianwen model API.

Farfalle is an open-source AI-powered search engine that allows users to run their own local LLM or utilize the cloud. It provides a tech stack including Next.js for frontend, FastAPI for backend, Tavily for search API, Logfire for logging, and Redis for rate limiting. Users can get started by setting up prerequisites like Docker and Ollama, and obtaining API keys for Tavily, OpenAI, and Groq. The tool supports models like llama3, mistral, and gemma. Users can clone the repository, set environment variables, run containers using Docker Compose, and deploy the backend and frontend using services like Render and Vercel.

LLMLight is a novel framework that employs Large Language Models (LLMs) as decision-making agents for Traffic Signal Control (TSC). The framework leverages the advanced generalization capabilities of LLMs to engage in a reasoning and decision-making process akin to human intuition for effective traffic control. LLMLight has been demonstrated to be remarkably effective, generalizable, and interpretable against various transportation-based and RL-based baselines on nine real-world and synthetic datasets.

rag-chatbot is a tool that allows users to chat with multiple PDFs using Ollama and LlamaIndex. It provides an easy setup for running on local machines or Kaggle notebooks. Users can leverage models from Huggingface and Ollama, process multiple PDF inputs, and chat in multiple languages. The tool offers a simple UI with Gradio, supporting chat with history and QA modes. Setup instructions are provided for both Kaggle and local environments, including installation steps for Docker, Ollama, Ngrok, and the rag_chatbot package. Users can run the tool locally and access it via a web interface. Future enhancements include adding evaluation, better embedding models, knowledge graph support, improved document processing, MLX model integration, and Corrective RAG.

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.

The 'END TO END GENERATIVE AI PROJECTS' repository is a collection of awesome industry projects utilizing Large Language Models (LLM) for various tasks such as chat applications with PDFs, image to speech generation, video transcribing and summarizing, resume tracking, text to SQL conversion, invoice extraction, medical chatbot, financial stock analysis, and more. The projects showcase the deployment of LLM models like Google Gemini Pro, HuggingFace Models, OpenAI GPT, and technologies such as Langchain, Streamlit, LLaMA2, LLaMAindex, and more. The repository aims to provide end-to-end solutions for different AI applications.

This repository, llama-index, contains a collection of apps powered by LlamaIndex. LlamaIndex is an open-source project that provides a simple interface between LLMs and external data sources like APIs, PDFs, SQL etc. It provides indices over structured and unstructured data, helping to abstract away the differences across data sources. The repository includes apps like chat-with-pdf and summarize-url, showcasing the capabilities of LlamaIndex in interacting with PDFs and summarizing URLs.

Weave is a toolkit for developing Generative AI applications, built by Weights & Biases. With Weave, you can log and debug language model inputs, outputs, and traces; build rigorous, apples-to-apples evaluations for language model use cases; and organize all the information generated across the LLM workflow, from experimentation to evaluations to production. Weave aims to bring rigor, best-practices, and composability to the inherently experimental process of developing Generative AI software, without introducing cognitive overhead.

AgentCloud is an open-source platform that enables companies to build and deploy private LLM chat apps, empowering teams to securely interact with their data. It comprises three main components: Agent Backend, Webapp, and Vector Proxy. To run this project locally, clone the repository, install Docker, and start the services. The project is licensed under the GNU Affero General Public License, version 3 only. Contributions and feedback are welcome from the community.

This framework generates fuzz targets for real-world `C`/`C++` projects with various Large Language Models (LLM) and benchmarks them via the `OSS-Fuzz` platform. It manages to successfully leverage LLMs to generate valid fuzz targets (which generate non-zero coverage increase) for 160 C/C++ projects. The maximum line coverage increase is 29% from the existing human-written targets.

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.

The VisionCraft API is a free API for using over 100 different AI models. From images to sound.

Kaito is an operator that automates the AI/ML inference model deployment in a Kubernetes cluster. It manages large model files using container images, avoids tuning deployment parameters to fit GPU hardware by providing preset configurations, auto-provisions GPU nodes based on model requirements, and hosts large model images in the public Microsoft Container Registry (MCR) if the license allows. Using Kaito, the workflow of onboarding large AI inference models in Kubernetes is largely simplified.

PyRIT is an open access automation framework designed to empower security professionals and ML engineers to red team foundation models and their applications. It automates AI Red Teaming tasks to allow operators to focus on more complicated and time-consuming tasks and can also identify security harms such as misuse (e.g., malware generation, jailbreaking), and privacy harms (e.g., identity theft). The goal is to allow researchers to have a baseline of how well their model and entire inference pipeline is doing against different harm categories and to be able to compare that baseline to future iterations of their model. This allows them to have empirical data on how well their model is doing today, and detect any degradation of performance based on future improvements.

The Azure-Analytics-and-AI-Engagement repository provides packaged Industry Scenario DREAM Demos with ARM templates (Containing a demo web application, Power BI reports, Synapse resources, AML Notebooks etc.) that can be deployed in a customer’s subscription using the CAPE tool within a matter of few hours. Partners can also deploy DREAM Demos in their own subscriptions using DPoC.