PR Pilot is an AI-powered tool designed to assist users in their daily workflow by delegating routine work to AI with confidence and predictability. It integrates seamlessly with popular development tools and allows users to interact with it through a Command-Line Interface, Python SDK, REST API, and Smart Workflows. Users can automate tasks such as generating PR titles and descriptions, summarizing and posting issues, and formatting README files. The tool aims to save time and enhance productivity by providing AI-powered solutions for common development tasks.

Gollama is a delightful tool that brings Ollama, your offline conversational AI companion, directly into your terminal. It provides a fun and interactive way to generate responses from various models without needing internet connectivity. Whether you're brainstorming ideas, exploring creative writing, or just looking for inspiration, Gollama is here to assist you. The tool offers an interactive interface, customizable prompts, multiple models selection, and visual feedback to enhance user experience. It can be installed via different methods like downloading the latest release, using Go, running with Docker, or building from source. Users can interact with Gollama through various options like specifying a custom base URL, prompt, model, and enabling raw output mode. The tool supports different modes like interactive, piped, CLI with image, and TUI with image. Gollama relies on third-party packages like bubbletea, glamour, huh, and lipgloss. The roadmap includes implementing piped mode, support for extracting codeblocks, copying responses/codeblocks to clipboard, GitHub Actions for automated releases, and downloading models directly from Ollama using the rest API. Contributions are welcome, and the project is licensed under the MIT License.

StableToolBench is a new benchmark developed to address the instability of Tool Learning benchmarks. It aims to balance stability and reality by introducing features like Virtual API System, Solvable Queries, and Stable Evaluation System. The benchmark ensures consistency through a caching system and API simulators, filters queries based on solvability using LLMs, and evaluates model performance using GPT-4 with metrics like Solvable Pass Rate and Solvable Win Rate.

Vision Parse is a tool that leverages Vision Language Models to parse PDF documents into beautifully formatted markdown content. It offers smart content extraction, content formatting, multi-LLM support, PDF document support, and local model hosting using Ollama. Users can easily convert PDFs to markdown with high precision and preserve document hierarchy and styling. The tool supports multiple Vision LLM providers like OpenAI, LLama, and Gemini for accuracy and speed, making document processing efficient and effortless.

mLoRA (Multi-LoRA Fine-Tune) is an open-source framework for efficient fine-tuning of multiple Large Language Models (LLMs) using LoRA and its variants. It allows concurrent fine-tuning of multiple LoRA adapters with a shared base model, efficient pipeline parallelism algorithm, support for various LoRA variant algorithms, and reinforcement learning preference alignment algorithms. mLoRA helps save computational and memory resources when training multiple adapters simultaneously, achieving high performance on consumer hardware.

Factorio Learning Environment is an open source framework designed for developing and evaluating LLM agents in the game of Factorio. It provides two settings: Lab-play with structured tasks and Open-play for building large factories. Results show limitations in spatial reasoning and automation strategies. Agents interact with the environment through code synthesis, observation, action, and feedback. Tools are provided for game actions and state representation. Agents operate in episodes with observation, planning, and action execution. Tasks specify agent goals and are implemented in JSON files. The project structure includes directories for agents, environment, cluster, data, docs, eval, and more. A database is used for checkpointing agent steps. Benchmarks show performance metrics for different configurations.

StableToolBench is a new benchmark developed to address the instability of Tool Learning benchmarks. It aims to balance stability and reality by introducing features such as a Virtual API System with caching and API simulators, a new set of solvable queries determined by LLMs, and a Stable Evaluation System using GPT-4. The Virtual API Server can be set up either by building from source or using a prebuilt Docker image. Users can test the server using provided scripts and evaluate models with Solvable Pass Rate and Solvable Win Rate metrics. The tool also includes model experiments results comparing different models' performance.

This AI-powered git commit plugin for VSCode streamlines your commit and push processes, eliminating the need for manual confirmation. With a focus on minimizing keystrokes, the plugin leverages LLM to generate commit messages and automate the entire process. Key features include AI-assisted git commit and push, eliminating the need for the 'git add .' command, and customizable OpenAI model selection. The plugin supports multiple languages, making it accessible to developers worldwide. Additionally, it offers advanced settings for specifying the OpenAI API key, base URL, and conventional commit format. Developers can contribute to the project by following the provided development instructions.

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

Large Language Models Play StarCraft II is a project that explores the capabilities of large language models (LLMs) in playing the game StarCraft II. The project introduces TextStarCraft II, a textual environment for the game, and a Chain of Summarization method for analyzing game information and making strategic decisions. Through experiments, the project demonstrates that LLM agents can defeat the built-in AI at a challenging difficulty level. The project provides benchmarks and a summarization approach to enhance strategic planning and interpretability in StarCraft II gameplay.

Distributed Llama is a tool that allows you to run large language models (LLMs) on weak devices or make powerful devices even more powerful by distributing the workload and dividing the RAM usage. It uses TCP sockets to synchronize the state of the neural network, and you can easily configure your AI cluster by using a home router. Distributed Llama supports models such as Llama 2 (7B, 13B, 70B) chat and non-chat versions, Llama 3, and Grok-1 (314B).

Evalchemy is a unified and easy-to-use toolkit for evaluating language models, focusing on post-trained models. It integrates multiple existing benchmarks such as RepoBench, AlpacaEval, and ZeroEval. Key features include unified installation, parallel evaluation, simplified usage, and results management. Users can run various benchmarks with a consistent command-line interface and track results locally or integrate with a database for systematic tracking and leaderboard submission.

AutoGPTQ is an easy-to-use LLM quantization package with user-friendly APIs, based on GPTQ algorithm (weight-only quantization). It provides a simple and efficient way to quantize large language models (LLMs) to reduce their size and computational cost while maintaining their performance. AutoGPTQ supports a wide range of LLM models, including GPT-2, GPT-J, OPT, and BLOOM. It also supports various evaluation tasks, such as language modeling, sequence classification, and text summarization. With AutoGPTQ, users can easily quantize their LLM models and deploy them on resource-constrained devices, such as mobile phones and embedded systems.

DaoCloud Enterprise 5.0 Documentation provides detailed information on using DaoCloud, a Certified Kubernetes Service Provider. The documentation covers current and legacy versions, workflow control using GitOps, and instructions for opening a PR and previewing changes locally. It also includes naming conventions, writing tips, references, and acknowledgments to contributors. Users can find guidelines on writing, contributing, and translating pages, along with using tools like MkDocs, Docker, and Poetry for managing the documentation.

optillm is an OpenAI API compatible optimizing inference proxy implementing state-of-the-art techniques to enhance accuracy and performance of LLMs, focusing on reasoning over coding, logical, and mathematical queries. By leveraging additional compute at inference time, it surpasses frontier models across diverse tasks.

GraphRAG Visualizer is an application designed to visualize Microsoft GraphRAG artifacts by uploading parquet files generated from the GraphRAG indexing pipeline. Users can view and analyze data in 2D or 3D graphs, display data tables, search for specific nodes or relationships, and process artifacts locally for data security and privacy.

Magick is a groundbreaking visual AIDE (Artificial Intelligence Development Environment) for no-code data pipelines and multimodal agents. Magick can connect to other services and comes with nodes and templates well-suited for intelligent agents, chatbots, complex reasoning systems and realistic characters.

Danswer is an open-source Gen-AI Chat and Unified Search tool that connects to your company's docs, apps, and people. It provides a Chat interface and plugs into any LLM of your choice. Danswer can be deployed anywhere and for any scale - on a laptop, on-premise, or to cloud. Since you own the deployment, your user data and chats are fully in your own control. Danswer is MIT licensed and designed to be modular and easily extensible. The system also comes fully ready for production usage with user authentication, role management (admin/basic users), chat persistence, and a UI for configuring Personas (AI Assistants) and their Prompts. Danswer also serves as a Unified Search across all common workplace tools such as Slack, Google Drive, Confluence, etc. By combining LLMs and team specific knowledge, Danswer becomes a subject matter expert for the team. Imagine ChatGPT if it had access to your team's unique knowledge! It enables questions such as "A customer wants feature X, is this already supported?" or "Where's the pull request for feature Y?"

Semantic Kernel is an SDK that integrates Large Language Models (LLMs) like OpenAI, Azure OpenAI, and Hugging Face with conventional programming languages like C#, Python, and Java. Semantic Kernel achieves this by allowing you to define plugins that can be chained together in just a few lines of code. What makes Semantic Kernel _special_ , however, is its ability to _automatically_ orchestrate plugins with AI. With Semantic Kernel planners, you can ask an LLM to generate a plan that achieves a user's unique goal. Afterwards, Semantic Kernel will execute the plan for the user.

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.

MindsDB is a platform for customizing AI from enterprise data. You can create, serve, and fine-tune models in real-time from your database, vector store, and application data. MindsDB "enhances" SQL syntax with AI capabilities to make it accessible for developers worldwide. With MindsDB’s nearly 200 integrations, any developer can create AI customized for their purpose, faster and more securely. Their AI systems will constantly improve themselves — using companies’ own data, in real-time.

AiScript is a lightweight scripting language that runs on JavaScript. It supports arrays, objects, and functions as first-class citizens, and is easy to write without the need for semicolons or commas. AiScript runs in a secure sandbox environment, preventing infinite loops from freezing the host. It also allows for easy provision of variables and functions from the host.

Activepieces is an open source replacement for Zapier, designed to be extensible through a type-safe pieces framework written in Typescript. It features a user-friendly Workflow Builder with support for Branches, Loops, and Drag and Drop. Activepieces integrates with Google Sheets, OpenAI, Discord, and RSS, along with 80+ other integrations. The list of supported integrations continues to grow rapidly, thanks to valuable contributions from the community. Activepieces is an open ecosystem; all piece source code is available in the repository, and they are versioned and published directly to npmjs.com upon contributions. If you cannot find a specific piece on the pieces roadmap, please submit a request by visiting the following link: Request Piece Alternatively, if you are a developer, you can quickly build your own piece using our TypeScript framework. For guidance, please refer to the following guide: Contributor's Guide

Superagent is an open source framework that enables any developer to integrate production ready AI Assistants into any application in a matter of minutes.

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.

This repository contains assets related to AI/ML workloads on Google Kubernetes Engine (GKE). Run optimized AI/ML workloads with Google Kubernetes Engine (GKE) platform orchestration capabilities. A robust AI/ML platform considers the following layers: Infrastructure orchestration that support GPUs and TPUs for training and serving workloads at scale Flexible integration with distributed computing and data processing frameworks Support for multiple teams on the same infrastructure to maximize utilization of resources

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.

Nvidia GPU exporter for prometheus, using `nvidia-smi` binary to gather metrics.

Tracecat is an open-source automation platform for security teams. It's designed to be simple but powerful, with a focus on AI features and a practitioner-obsessed UI/UX. Tracecat can be used to automate a variety of tasks, including phishing email investigation, evidence collection, and remediation plan generation.

OpenInference is a set of conventions and plugins that complement OpenTelemetry to enable tracing of AI applications. It provides a way to capture and analyze the performance and behavior of AI models, including their interactions with other components of the application. OpenInference is designed to be language-agnostic and can be used with any OpenTelemetry-compatible backend. It includes a set of instrumentations for popular machine learning SDKs and frameworks, making it easy to add tracing to your AI applications.

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

Kong, or Kong API Gateway, is a cloud-native, platform-agnostic, scalable API Gateway distinguished for its high performance and extensibility via plugins. It also provides advanced AI capabilities with multi-LLM support. By providing functionality for proxying, routing, load balancing, health checking, authentication (and more), Kong serves as the central layer for orchestrating microservices or conventional API traffic with ease. Kong runs natively on Kubernetes thanks to its official Kubernetes Ingress Controller.