AIKA (Artificial Intelligence for Knowledge Acquisition) is a new type of artificial neural network designed to mimic the behavior of a biological brain more closely and bridge the gap to classical AI. The network conceptually separates activations from neurons, creating two separate graphs to represent acquired knowledge and inferred information. It uses different types of neurons and synapses to propagate activation values, binding signals, causal relations, and training gradients. The network structure allows for flexible topology and supports the gradual population of neurons and synapses during training.

agentUniverse is a multi-agent framework based on large language models, providing flexible capabilities for building individual agents. It focuses on multi-agent collaborative patterns, integrating domain experience to help agents solve problems in various fields. The framework includes pattern components like PEER and DOE for event interpretation, industry analysis, and financial report generation. It offers features for agent construction, multi-agent collaboration, and domain expertise integration, aiming to create intelligent applications with professional know-how.

This repository contains the source code and datasets for Graph Chain-of-Thought: Augmenting Large Language Models by Reasoning on Graphs accepted to ACL 2024. It proposes a framework called Graph Chain-of-thought (Graph-CoT) to enable Language Models to traverse graphs step-by-step for reasoning, interaction, and execution. The motivation is to alleviate hallucination issues in Language Models by augmenting them with structured knowledge sources represented as graphs.

AI2Apps is a visual IDE for building LLM-based AI agent applications, enabling developers to efficiently create AI agents through drag-and-drop, with features like design-to-development for rapid prototyping, direct packaging of agents into apps, powerful debugging capabilities, enhanced user interaction, efficient team collaboration, flexible deployment, multilingual support, simplified product maintenance, and extensibility through plugins.

Aligner is a model-agnostic alignment tool that learns correctional residuals between preferred and dispreferred answers using a small model. It can be directly applied to various open-source and API-based models with only one-off training, suitable for rapid iteration and improving model performance. Aligner has shown significant improvements in helpfulness, harmlessness, and honesty dimensions across different large language models.

Open-DocLLM is an open-source project that addresses data extraction and processing challenges using OCR and LLM technologies. It consists of two main layers: OCR for reading document content and LLM for extracting specific content in a structured manner. The project offers a larger context window size compared to JP Morgan's DocLLM and integrates tools like Tesseract OCR and Mistral for efficient data analysis. Users can run the models on-premises using LLM studio or Ollama, and the project includes a FastAPI app for testing purposes.

LLMOps with Prompt flow is a template and guidance for building LLM-infused apps using Prompt flow. It provides centralized code hosting, lifecycle management, variant and hyperparameter experimentation, A/B deployment, many-to-many dataset/flow relationships, multiple deployment targets, comprehensive reporting, BYOF capabilities, configuration-based development, local prompt experimentation and evaluation, endpoint testing, and optional Human-in-loop validation. The tool is customizable to suit various application needs.

Nucleoid is a declarative (logic) runtime environment that manages both data and logic under the same runtime. It uses a declarative programming paradigm, which allows developers to focus on the business logic of the application, while the runtime manages the technical details. This allows for faster development and reduces the amount of code that needs to be written. Additionally, the sharding feature can help to distribute the load across multiple instances, which can further improve the performance of the system.

This repository contains the official codebase for Bittensor Subnet 1 (SN1) v1.0.0+, released on 22nd January 2024. It defines an incentive mechanism to create a distributed conversational AI for Subnet 1. Validators and miners are based on large language models (LLM) using internet-scale datasets and goal-driven behavior to drive human-like conversations. The repository requires python3.9 or higher and provides compute requirements for running validators and miners. Users can run miners or validators using specific commands and are encouraged to run on the testnet before deploying on the main network. The repository also highlights limitations and provides resources for understanding the architecture and methodology of SN1.

DNAnalyzer is a nonprofit organization dedicated to revolutionizing DNA analysis through AI-powered tools. It aims to democratize access to DNA analysis for a deeper understanding of human health and disease. The tool provides innovative AI-powered analysis and interpretive tools to empower geneticists, physicians, and researchers to gain deep insights into DNA sequences, revolutionizing how we understand human health and disease.

AIShield Watchtower is a tool designed to fortify the security of AI/ML models and Jupyter notebooks by automating model and notebook discoveries, conducting vulnerability scans, and categorizing risks into 'low,' 'medium,' 'high,' and 'critical' levels. It supports scanning of public GitHub repositories, Hugging Face repositories, AWS S3 buckets, and local systems. The tool generates comprehensive reports, offers a user-friendly interface, and aligns with industry standards like OWASP, MITRE, and CWE. It aims to address the security blind spots surrounding Jupyter notebooks and AI models, providing organizations with a tailored approach to enhancing their security efforts.

Aligner is a model-agnostic alignment tool designed to efficiently correct responses from large language models. It redistributes initial answers to align with human intentions, improving performance across various LLMs. The tool can be applied with minimal training, enhancing upstream models and reducing hallucination. Aligner's 'copy and correct' method preserves the base structure while enhancing responses. It achieves significant performance improvements in helpfulness, harmlessness, and honesty dimensions, with notable success in boosting Win Rates on evaluation leaderboards.

KDB.AI is a time-based vector database that allows developers to build scalable, reliable, and real-time applications by providing advanced search, recommendation, and personalization for Generative AI applications. It supports multiple index types, distance metrics, top-N and metadata filtered retrieval, as well as Python and REST interfaces. The repository contains samples demonstrating various use-cases such as temporal similarity search, document search, image search, recommendation systems, sentiment analysis, and more. KDB.AI integrates with platforms like ChatGPT, Langchain, and LlamaIndex. The setup steps require Unix terminal, Python 3.8+, and pip installed. Users can install necessary Python packages and run Jupyter notebooks to interact with the samples.

Awesome OpenVINO is a curated list of AI projects based on the OpenVINO toolkit, offering a rich assortment of projects, libraries, and tutorials covering various topics like model optimization, deployment, and real-world applications across industries. It serves as a valuable resource continuously updated to maximize the potential of OpenVINO in projects, featuring projects like Stable Diffusion web UI, Visioncom, FastSD CPU, OpenVINO AI Plugins for GIMP, and more.

Chinese-Tiny-LLM is a repository containing procedures for cleaning Chinese web corpora and pre-training code. It introduces CT-LLM, a 2B parameter language model focused on the Chinese language. The model primarily uses Chinese data from a 1,200 billion token corpus, showing excellent performance in Chinese language tasks. The repository includes tools for filtering, deduplication, and pre-training, aiming to encourage further research and innovation in language model development.

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.

Sorrentum is an open-source project that aims to combine open-source development, startups, and brilliant students to build machine learning, AI, and Web3 / DeFi protocols geared towards finance and economics. The project provides opportunities for internships, research assistantships, and development grants, as well as the chance to work on cutting-edge problems, learn about startups, write academic papers, and get internships and full-time positions at companies working on Sorrentum applications.

TiDB is an open-source distributed SQL database that supports Hybrid Transactional and Analytical Processing (HTAP) workloads. It is MySQL compatible and features horizontal scalability, strong consistency, and high availability.

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.

This repository codifies the Airflow cluster that is deployed at workflow.telemetry.mozilla.org (behind SSO) and commonly referred to as "WTMO" or simply "Airflow". Some links relevant to users and developers of WTMO: * The `dags` directory in this repository contains some custom DAG definitions * Many of the DAGs registered with WTMO don't live in this repository, but are instead generated from ETL task definitions in bigquery-etl * The Data SRE team maintains a WTMO Developer Guide (behind SSO)

Mojo is a new programming language that bridges the gap between research and production by combining Python syntax and ecosystem with systems programming and metaprogramming features. Mojo is still young, but it is designed to become a superset of Python over time.

PandasAI is a Python library that makes it easy to ask questions to your data in natural language. It helps you to explore, clean, and analyze your data using generative AI.

Databend is an open-source cloud data warehouse that serves as a cost-effective alternative to Snowflake. With its focus on fast query execution and data ingestion, it's designed for complex analysis of the world's largest datasets.

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.