This project is a Node.js API example that utilizes the OpenAI API for grammar correction and speech-to-text conversion. It helps users correct their English sentences to standard English by leveraging the capabilities of the OpenAI API. The project consists of two applications: Angular and Node.js. Users can follow the installation steps to set up the project in their environment and utilize the OpenAI implementation to correct English sentences. The project also provides guidelines for contribution and support.

Yet Another Chatbot is a sophisticated multimodal chat interface powered by advanced AI models and equipped with a variety of tools. This chatbot can search and browse the web in real-time, query Wikipedia for information, perform news and map searches, execute Python code, compose long-form articles mixing text and images, generate, search, and compare images, analyze documents and images, search and download arXiv papers, save conversations as text and audio files, manage checklists, and track personal improvements. It offers tools for web interaction, Wikipedia search, Python scripting, content management, image handling, arXiv integration, conversation generation, file management, personal improvement, and checklist management.

AiDE is a lightweight framework for structuring AI-assisted development. It standardizes project context management, documentation, and collaboration, ensuring the assistant stays informed and productive throughout the project lifecycle. It offers drop-in simplicity with no dependencies, versatile usage for new and existing projects, and standardized templates for roadmaps, tasks, decisions, and sessions. The framework helps track project state, decision records, task management, and session tracking. It encourages best practices like starting each session by reviewing `.context` files, tracking task completion, documenting key decisions, and recording session summaries. The folder structure includes files for current state, roadmap, tasks, decisions, and sessions, with specific directories for active, completed, hold, and planned tasks. Contributions are welcome to enhance the usability of `.context`, and optional global rules for AI assistants are provided to optimize integration with the framework.

The AI Scientist is a comprehensive system for fully automatic scientific discovery, enabling Foundation Models to perform research independently. It aims to tackle the grand challenge of developing agents capable of conducting scientific research and discovering new knowledge. The tool generates papers on various topics using Large Language Models (LLMs) and provides a platform for exploring new research ideas. Users can create their own templates for specific areas of study and run experiments to generate papers. However, caution is advised as the codebase executes LLM-written code, which may pose risks such as the use of potentially dangerous packages and web access.

LLM-Minutes-of-Meeting is a project showcasing NLP & LLM's capability to summarize long meetings and automate the task of delegating Minutes of Meeting(MoM) emails. It converts audio/video files to text, generates editable MoM, and aims to develop a real-time python web-application for meeting automation. The tool features keyword highlighting, topic tagging, export in various formats, user-friendly interface, and uses Celery for asynchronous processing. It is designed for corporate meetings, educational institutions, legal and medical fields, accessibility, and event coverage.

Hexabot Community Edition is an open-source chatbot solution designed for flexibility and customization, offering powerful text-to-action capabilities. It allows users to create and manage AI-powered, multi-channel, and multilingual chatbots with ease. The platform features an analytics dashboard, multi-channel support, visual editor, plugin system, NLP/NLU management, multi-lingual support, CMS integration, user roles & permissions, contextual data, subscribers & labels, and inbox & handover functionalities. The directory structure includes frontend, API, widget, NLU, and docker components. Prerequisites for running Hexabot include Docker and Node.js. The installation process involves cloning the repository, setting up the environment, and running the application. Users can access the UI admin panel and live chat widget for interaction. Various commands are available for managing the Docker services. Detailed documentation and contribution guidelines are provided for users interested in contributing to the project.

The Neo4j GenAI Workshop repository contains notebooks for a workshop focusing on building a Neo4j Graph, text embedding, and providing demos for content generation. The workshop includes data staging, loading, and exploration using Cypher queries. It also covers improvements in LLM response quality, GPT-4 usage, and vector search speed. The repository has undergone multiple updates to enhance course quality, simplify content, and provide better explainers and examples.

Gemini PDF Chatbot is a Streamlit-based application that allows users to chat with a conversational AI model trained on PDF documents. The chatbot extracts information from uploaded PDF files and answers user questions based on the provided context. It features PDF upload, text extraction, conversational AI using the Gemini model, and a chat interface. Users can deploy the application locally or to the cloud, and the project structure includes main application script, environment variable file, requirements, and documentation. Dependencies include PyPDF2, langchain, Streamlit, google.generativeai, and dotenv.

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.

AiTimeline is a comprehensive timeline showcasing the evolution and advancements in artificial intelligence technologies from 2022 to 2024. It provides a detailed overview of key milestones, releases, and developments in the AI industry, organized chronologically by year. The timeline offers a responsive design for seamless viewing on various devices and includes brief descriptions for each event, making it a valuable resource for researchers, enthusiasts, and anyone interested in tracking the progress of AI technologies.

Tara is a powerful node for ComfyUI that integrates Large Language Models (LLMs) to enhance and automate workflow processes. With Tara, you can create complex, intelligent workflows that refine and generate content, manage API keys, and seamlessly integrate various LLMs into your projects. It comprises nodes for handling OpenAI-compatible APIs, saving and loading API keys, composing multiple texts, and using predefined templates for OpenAI and Groq. Tara supports OpenAI and Grok models with plans to expand support to together.ai and Replicate. Users can install Tara via Git URL or ComfyUI Manager and utilize it for tasks like input guidance, saving and loading API keys, and generating text suitable for chaining in workflows.

Burpference is an open-source extension designed to capture in-scope HTTP requests and responses from Burp's proxy history and send them to a remote LLM API in JSON format. It automates response capture, integrates with APIs, optimizes resource usage, provides color-coded findings visualization, offers comprehensive logging, supports native Burp reporting, and allows flexible configuration. Users can customize system prompts, API keys, and remote hosts, and host models locally to prevent high inference costs. The tool is ideal for offensive web application engagements to surface findings and vulnerabilities.

CyberScraper 2077 is an advanced web scraping tool powered by AI, designed to extract data from websites with precision and style. It offers a user-friendly interface, supports multiple data export formats, operates in stealth mode to avoid detection, and promises lightning-fast scraping. The tool respects ethical scraping practices, including robots.txt and site policies. With upcoming features like proxy support and page navigation, CyberScraper 2077 is a futuristic solution for data extraction in the digital realm.

RepoAgent is an LLM-powered framework designed for repository-level code documentation generation. It automates the process of detecting changes in Git repositories, analyzing code structure through AST, identifying inter-object relationships, replacing Markdown content, and executing multi-threaded operations. The tool aims to assist developers in understanding and maintaining codebases by providing comprehensive documentation, ultimately improving efficiency and saving time.

GraphRAG Local Ollama is a repository that offers an adaptation of Microsoft's GraphRAG, customized to support local models downloaded using Ollama. It enables users to leverage local models with Ollama for large language models (LLMs) and embeddings, eliminating the need for costly OpenAPI models. The repository provides a simple setup process and allows users to perform question answering over private text corpora by building a graph-based text index and generating community summaries for closely-related entities. GraphRAG Local Ollama aims to improve the comprehensiveness and diversity of generated answers for global sensemaking questions over datasets.

Hercules is the world’s first open-source testing agent designed to handle the toughest testing tasks for modern web applications. It turns simple Gherkin steps into fully automated end-to-end tests, making testing simple, reliable, and efficient. Hercules adapts to various platforms like Salesforce and is suitable for CI/CD pipelines. It aims to democratize and disrupt test automation, making top-tier testing accessible to everyone. The tool is transparent, reliable, and community-driven, empowering teams to deliver better software. Hercules offers multiple ways to get started, including using PyPI package, Docker, or building and running from source code. It supports various AI models, provides detailed installation and usage instructions, and integrates with Nuclei for security testing and WCAG for accessibility testing. The tool is production-ready, open core, and open source, with plans for enhanced LLM support, advanced tooling, improved DOM distillation, community contributions, extensive documentation, and a bounty program.

This project is a Node.js API example that utilizes the OpenAI API for grammar correction and speech-to-text conversion. It helps users correct their English sentences to standard English by leveraging the capabilities of the OpenAI API. The project consists of two applications: Angular and Node.js. Users can follow the installation steps to set up the project in their environment and utilize the OpenAI implementation to correct English sentences. The project also provides guidelines for contribution and support.

Zep is an open-source platform for building and deploying large language model (LLM) applications. It provides a suite of tools and services that make it easy to integrate LLMs into your applications, including chat history memory, embedding, vector search, and data enrichment. Zep is designed to be scalable, reliable, and easy to use, making it a great choice for developers who want to build LLM-powered applications quickly and easily.

E2B Sandbox is a secure sandboxed cloud environment made for AI agents and AI apps. Sandboxes allow AI agents and apps to have long running cloud secure environments. In these environments, large language models can use the same tools as humans do. For example: * Cloud browsers * GitHub repositories and CLIs * Coding tools like linters, autocomplete, "go-to defintion" * Running LLM generated code * Audio & video editing The E2B sandbox can be connected to any LLM and any AI agent or app.

LlamaIndex.TS is a data framework for your LLM application. Use your own data with large language models (LLMs, OpenAI ChatGPT and others) in Typescript and Javascript.

Floneum is a graph editor that makes it easy to develop your own AI workflows. It uses large language models (LLMs) to run AI models locally, without any external dependencies or even a GPU. This makes it easy to use LLMs with your own data, without worrying about privacy. Floneum also has a plugin system that allows you to improve the performance of LLMs and make them work better for your specific use case. Plugins can be used in any language that supports web assembly, and they can control the output of LLMs with a process similar to JSONformer or guidance.

This course has 18 lessons. Each lesson covers its own topic so start wherever you like! Lessons are labeled either "Learn" lessons explaining a Generative AI concept or "Build" lessons that explain a concept and code examples in both **Python** and **TypeScript** when possible. Each lesson also includes a "Keep Learning" section with additional learning tools. **What You Need** * Access to the Azure OpenAI Service **OR** OpenAI API - _Only required to complete coding lessons_ * Basic knowledge of Python or Typescript is helpful - *For absolute beginners check out these Python and TypeScript courses. * A Github account to fork this entire repo to your own GitHub account We have created a **Course Setup** lesson to help you with setting up your development environment. Don't forget to star (🌟) this repo to find it easier later. ## 🧠 Ready to Deploy? If you are looking for more advanced code samples, check out our collection of Generative AI Code Samples in both **Python** and **TypeScript**. ## 🗣️ Meet Other Learners, Get Support Join our official AI Discord server to meet and network with other learners taking this course and get support. ## 🚀 Building a Startup? Sign up for Microsoft for Startups Founders Hub to receive **free OpenAI credits** and up to **$150k towards Azure credits to access OpenAI models through Azure OpenAI Services**. ## 🙏 Want to help? Do you have suggestions or found spelling or code errors? Raise an issue or Create a pull request ## 📂 Each lesson includes: * A short video introduction to the topic * A written lesson located in the README * Python and TypeScript code samples supporting Azure OpenAI and OpenAI API * Links to extra resources to continue your learning ## 🗃️ Lessons | | Lesson Link | Description | Additional Learning | | :-: | :------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------: | ------------------------------------------------------------------------------ | | 00 | Course Setup | **Learn:** How to Setup Your Development Environment | Learn More | | 01 | Introduction to Generative AI and LLMs | **Learn:** Understanding what Generative AI is and how Large Language Models (LLMs) work. | Learn More | | 02 | Exploring and comparing different LLMs | **Learn:** How to select the right model for your use case | Learn More | | 03 | Using Generative AI Responsibly | **Learn:** How to build Generative AI Applications responsibly | Learn More | | 04 | Understanding Prompt Engineering Fundamentals | **Learn:** Hands-on Prompt Engineering Best Practices | Learn More | | 05 | Creating Advanced Prompts | **Learn:** How to apply prompt engineering techniques that improve the outcome of your prompts. | Learn More | | 06 | Building Text Generation Applications | **Build:** A text generation app using Azure OpenAI | Learn More | | 07 | Building Chat Applications | **Build:** Techniques for efficiently building and integrating chat applications. | Learn More | | 08 | Building Search Apps Vector Databases | **Build:** A search application that uses Embeddings to search for data. | Learn More | | 09 | Building Image Generation Applications | **Build:** A image generation application | Learn More | | 10 | Building Low Code AI Applications | **Build:** A Generative AI application using Low Code tools | Learn More | | 11 | Integrating External Applications with Function Calling | **Build:** What is function calling and its use cases for applications | Learn More | | 12 | Designing UX for AI Applications | **Learn:** How to apply UX design principles when developing Generative AI Applications | Learn More | | 13 | Securing Your Generative AI Applications | **Learn:** The threats and risks to AI systems and methods to secure these systems. | Learn More | | 14 | The Generative AI Application Lifecycle | **Learn:** The tools and metrics to manage the LLM Lifecycle and LLMOps | Learn More | | 15 | Retrieval Augmented Generation (RAG) and Vector Databases | **Build:** An application using a RAG Framework to retrieve embeddings from a Vector Databases | Learn More | | 16 | Open Source Models and Hugging Face | **Build:** An application using open source models available on Hugging Face | Learn More | | 17 | AI Agents | **Build:** An application using an AI Agent Framework | Learn More | | 18 | Fine-Tuning LLMs | **Learn:** The what, why and how of fine-tuning LLMs | Learn More |

The 'carrot' repository on GitHub provides a list of free and user-friendly ChatGPT mirror sites for easy access. The repository includes sponsored sites offering various GPT models and services. Users can find and share sites, report errors, and access stable and recommended sites for ChatGPT usage. The repository also includes a detailed list of ChatGPT sites, their features, and accessibility options, making it a valuable resource for ChatGPT users seeking free and unlimited GPT services.

PyAIML is a Python implementation of the AIML (Artificial Intelligence Markup Language) interpreter. It aims to be a simple, standards-compliant interpreter for AIML 1.0.1. PyAIML is currently in pre-alpha development, so use it at your own risk. For more information on PyAIML, see the CHANGES.txt and SUPPORTED_TAGS.txt files.

ChatFAQ is an open-source comprehensive platform for creating a wide variety of chatbots: generic ones, business-trained, or even capable of redirecting requests to human operators. It includes a specialized NLP/NLG engine based on a RAG architecture and customized chat widgets, ensuring a tailored experience for users and avoiding vendor lock-in.

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.

This guide is dedicated to Large Language Models (LLMs) that you can run on your home computer. It assumes your PC is a lower-end, non-gaming setup.

Supercharge WordPress Content Workflows and Engagement with Artificial Intelligence. Tap into leading cloud-based services like OpenAI, Microsoft Azure AI, Google Gemini and IBM Watson to augment your WordPress-powered websites. Publish content faster while improving SEO performance and increasing audience engagement. ClassifAI integrates Artificial Intelligence and Machine Learning technologies to lighten your workload and eliminate tedious tasks, giving you more time to create original content that matters.

mikupad is a lightweight and efficient language model front-end powered by ReactJS, all packed into a single HTML file. Inspired by the likes of NovelAI, it provides a simple yet powerful interface for generating text with the help of various backends.

Glide is a cloud-native LLM gateway that provides a unified REST API for accessing various large language models (LLMs) from different providers. It handles LLMOps tasks such as model failover, caching, key management, and more, making it easy to integrate LLMs into applications. Glide supports popular LLM providers like OpenAI, Anthropic, Azure OpenAI, AWS Bedrock (Titan), Cohere, Google Gemini, OctoML, and Ollama. It offers high availability, performance, and observability, and provides SDKs for Python and NodeJS to simplify integration.

ONNX Runtime Generative AI is a library that provides the generative AI loop for ONNX models, including inference with ONNX Runtime, logits processing, search and sampling, and KV cache management. Users can call a high level `generate()` method, or run each iteration of the model in a loop. It supports greedy/beam search and TopP, TopK sampling to generate token sequences, has built in logits processing like repetition penalties, and allows for easy custom scoring.

Firecrawl is an API service that takes a URL, crawls it, and converts it into clean markdown. It crawls all accessible subpages and provides clean markdown for each, without requiring a sitemap. The API is easy to use and can be self-hosted. It also integrates with Langchain and Llama Index. The Python SDK makes it easy to crawl and scrape websites in Python code.