This repository contains lab files for Azure AI Language modules. It provides hands-on exercises and resources for learning about various AI language technologies on the Azure platform. The labs cover topics such as natural language processing, text analytics, language understanding, and more. By following the exercises in this repository, users can gain practical experience in implementing AI language solutions using Azure services.

Azure AI Docs is a repository that provides detailed documentation and resources for developers looking to leverage Microsoft's AI services on the Azure platform. The repository covers a wide range of topics including machine learning, natural language processing, computer vision, and more. Developers can find tutorials, code samples, best practices, and guidelines to help them integrate AI capabilities into their applications seamlessly.

The ai-workshop-code repository contains code examples and tutorials for various artificial intelligence concepts and algorithms. It serves as a practical resource for individuals looking to learn and implement AI techniques in their projects. The repository covers a wide range of topics, including machine learning, deep learning, natural language processing, computer vision, and reinforcement learning. By exploring the code and following the tutorials, users can gain hands-on experience with AI technologies and enhance their understanding of how these algorithms work in practice.

This repository serves as an archive for computer science learning notes, codes, and materials. It covers a wide range of topics including basic knowledge, AI, backend & big data, tools, and other related areas. The content is organized into sections and subsections for easy navigation and reference. Users can find learning resources, programming practices, and tutorials on various subjects such as languages, data structures & algorithms, AI, frameworks, databases, development tools, and more. The repository aims to support self-learning and skill development in the field of computer science.

This repository contains a collection of resources for learning about and using Large Language Models (LLMs). The resources include tutorials, code examples, and links to additional resources. LLMs are a type of artificial intelligence that can understand and generate human-like text. They have a wide range of potential applications, including natural language processing, machine translation, and chatbot development.

Spring AI Examples is a repository containing various examples of integrating artificial intelligence capabilities into Spring applications. The examples cover a wide range of AI technologies such as machine learning, natural language processing, computer vision, and more. These examples serve as a practical guide for developers looking to incorporate AI functionalities into their Spring projects.

Enterprise h2oGPTe - GenAI RAG is a repository containing code examples, notebooks, and benchmarks for the enterprise version of h2oGPTe, a powerful AI tool for generating text based on the RAG (Retrieval-Augmented Generation) architecture. The repository provides resources for leveraging h2oGPTe in enterprise settings, including implementation guides, performance evaluations, and best practices. Users can explore various applications of h2oGPTe in natural language processing tasks, such as text generation, content creation, and conversational AI.

Simple AI is a lightweight Python library for implementing basic artificial intelligence algorithms. It provides easy-to-use functions and classes for tasks such as machine learning, natural language processing, and computer vision. With Simple AI, users can quickly prototype and deploy AI solutions without the complexity of larger frameworks.

Open AI is a powerful tool for artificial intelligence research and development. It provides a wide range of machine learning models and algorithms, making it easier for developers to create innovative AI applications. With Open AI, users can explore cutting-edge technologies such as natural language processing, computer vision, and reinforcement learning. The platform offers a user-friendly interface and comprehensive documentation to support users in building and deploying AI solutions. Whether you are a beginner or an experienced AI practitioner, Open AI offers the tools and resources you need to accelerate your AI projects and stay ahead in the rapidly evolving field of artificial intelligence.

This repository contains a collection of AI projects implemented in Python, primarily in Jupyter notebooks. The projects cover various aspects of artificial intelligence, including machine learning, deep learning, natural language processing, computer vision, and more. Each project is designed to showcase different AI techniques and algorithms, providing a hands-on learning experience for users interested in exploring the field of artificial intelligence.

The mslearn-knowledge-mining repository contains lab files for Azure AI Knowledge Mining modules. It provides resources for learning and implementing knowledge mining techniques using Azure AI services. The repository is designed to help users explore and understand how to leverage AI for knowledge mining purposes within the Azure ecosystem.

GEN-AI is a versatile Python library for implementing various artificial intelligence algorithms and models. It provides a wide range of tools and functionalities to support machine learning, deep learning, natural language processing, computer vision, and reinforcement learning tasks. With GEN-AI, users can easily build, train, and deploy AI models for diverse applications such as image recognition, text classification, sentiment analysis, object detection, and game playing. The library is designed to be user-friendly, efficient, and scalable, making it suitable for both beginners and experienced AI practitioners.

Mirascope is an LLM toolkit for lightning-fast, high-quality development. Building with Mirascope feels like writing the Python code you’re already used to writing.

This repository provides a comprehensive framework for integrating Large Language Models (LLMs) into Odoo. It enables seamless interaction with AI providers like OpenAI, Anthropic, Ollama, and Replicate for chat completions, text embeddings, and more within the Odoo environment. The architecture includes external AI clients connecting via `llm_mcp_server` and Odoo AI Chat with built-in chat interface. The core module `llm` offers provider abstraction, model management, and security, along with tools for CRUD operations and domain-specific tool packs. Various AI providers, infrastructure components, and domain-specific tools are available for different tasks such as content generation, knowledge base management, and AI assistants creation.

FastGPT is a knowledge base Q&A system based on the LLM large language model, providing out-of-the-box data processing, model calling and other capabilities. At the same time, you can use Flow to visually arrange workflows to achieve complex Q&A scenarios!

The AI21 Labs Python SDK is a comprehensive tool for interacting with the AI21 API. It provides functionalities for chat completions, conversational RAG, token counting, error handling, and support for various cloud providers like AWS, Azure, and Vertex. The SDK offers both synchronous and asynchronous usage, along with detailed examples and documentation. Users can quickly get started with the SDK to leverage AI21's powerful models for various natural language processing tasks.

Phospho is a text analytics platform for LLM apps. It helps you detect issues and extract insights from text messages of your users or your app. You can gather user feedback, measure success, and iterate on your app to create the best conversational experience for your users.

Loki is an open-source tool designed to automate the process of verifying the factuality of information. It provides a comprehensive pipeline for dissecting long texts into individual claims, assessing their worthiness for verification, generating queries for evidence search, crawling for evidence, and ultimately verifying the claims. This tool is especially useful for journalists, researchers, and anyone interested in the factuality of information.

Open Parse is a Python library for visually discerning document layouts and chunking them effectively. It is designed to fill the gap in open-source libraries for handling complex documents. Unlike text splitting, which converts a file to raw text and slices it up, Open Parse visually analyzes documents for superior LLM input. It also supports basic markdown for parsing headings, bold, and italics, and has high-precision table support, extracting tables into clean Markdown formats with accuracy that surpasses traditional tools. Open Parse is extensible, allowing users to easily implement their own post-processing steps. It is also intuitive, with great editor support and completion everywhere, making it easy to use and learn.

spaCy is an industrial-strength Natural Language Processing (NLP) library in Python and Cython. It incorporates the latest research and is designed for real-world applications. The library offers pretrained pipelines supporting 70+ languages, with advanced neural network models for tasks such as tagging, parsing, named entity recognition, and text classification. It also facilitates multi-task learning with pretrained transformers like BERT, along with a production-ready training system and streamlined model packaging, deployment, and workflow management. spaCy is commercial open-source software released under the MIT license.

NanoLLM is a tool designed for optimized local inference for Large Language Models (LLMs) using HuggingFace-like APIs. It supports quantization, vision/language models, multimodal agents, speech, vector DB, and RAG. The tool aims to provide efficient and effective processing for LLMs on local devices, enhancing performance and usability for various AI applications.

OntoGPT is a Python package for extracting structured information from text using large language models, instruction prompts, and ontology-based grounding. It provides a command line interface and a minimal web app for easy usage. The tool has been evaluated on test data and is used in related projects like TALISMAN for gene set analysis. OntoGPT enables users to extract information from text by specifying relevant terms and provides the extracted objects as output.

LIMA is a multilingual linguistic analyzer developed by the CEA LIST, LASTI laboratory. It is Free Software available under the MIT license. LIMA has state-of-the-art performance for more than 60 languages using deep learning modules. It also includes a powerful rules-based mechanism called ModEx for extracting information in new domains without annotated data.

liboai is a simple C++17 library for the OpenAI API, providing developers with access to OpenAI endpoints through a collection of methods and classes. It serves as a spiritual port of OpenAI's Python library, 'openai', with similar structure and features. The library supports various functionalities such as ChatGPT, Audio, Azure, Functions, Image DALL·E, Models, Completions, Edit, Embeddings, Files, Fine-tunes, Moderation, and Asynchronous Support. Users can easily integrate the library into their C++ projects to interact with OpenAI services.

Sweep is an AI junior developer that turns bugs and feature requests into code changes. It automatically handles developer experience improvements like adding type hints and improving test coverage.

The Teams AI Library is a software development kit (SDK) that helps developers create bots that can interact with Teams and Microsoft 365 applications. It is built on top of the Bot Framework SDK and simplifies the process of developing bots that interact with Teams' artificial intelligence capabilities. The SDK is available for JavaScript/TypeScript, .NET, and Python.

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.

Chatbot UI is an open-source AI chat app that allows users to create and deploy their own AI chatbots. It is easy to use and can be customized to fit any need. Chatbot UI is perfect for businesses, developers, and anyone who wants to create a chatbot.

BricksLLM is a cloud native AI gateway written in Go. Currently, it provides native support for OpenAI, Anthropic, Azure OpenAI and vLLM. BricksLLM aims to provide enterprise level infrastructure that can power any LLM production use cases. Here are some use cases for BricksLLM: * Set LLM usage limits for users on different pricing tiers * Track LLM usage on a per user and per organization basis * Block or redact requests containing PIIs * Improve LLM reliability with failovers, retries and caching * Distribute API keys with rate limits and cost limits for internal development/production use cases * Distribute API keys with rate limits and cost limits for students

uAgents is a Python library developed by Fetch.ai that allows for the creation of autonomous AI agents. These agents can perform various tasks on a schedule or take action on various events. uAgents are easy to create and manage, and they are connected to a fast-growing network of other uAgents. They are also secure, with cryptographically secured messages and wallets.

Griptape is a modular Python framework for building AI-powered applications that securely connect to your enterprise data and APIs. It offers developers the ability to maintain control and flexibility at every step. Griptape's core components include Structures (Agents, Pipelines, and Workflows), Tasks, Tools, Memory (Conversation Memory, Task Memory, and Meta Memory), Drivers (Prompt and Embedding Drivers, Vector Store Drivers, Image Generation Drivers, Image Query Drivers, SQL Drivers, Web Scraper Drivers, and Conversation Memory Drivers), Engines (Query Engines, Extraction Engines, Summary Engines, Image Generation Engines, and Image Query Engines), and additional components (Rulesets, Loaders, Artifacts, Chunkers, and Tokenizers). Griptape enables developers to create AI-powered applications with ease and efficiency.