Beehave is a powerful addon for Godot Engine that enables users to create robust AI systems using behavior trees. It simplifies the design of complex NPC behaviors, challenging boss battles, and other advanced setups. Beehave allows for the creation of highly adaptive AI that responds to changes in the game world and overcomes unexpected obstacles, catering to both beginners and experienced developers. The tool is currently in development for version 3.0.

Pathway is a Python data processing framework for analytics and AI pipelines over data streams. It's the ideal solution for real-time processing use cases like streaming ETL or RAG pipelines for unstructured data. Pathway comes with an **easy-to-use Python API** , allowing you to seamlessly integrate your favorite Python ML libraries. Pathway code is versatile and robust: **you can use it in both development and production environments, handling both batch and streaming data effectively**. The same code can be used for local development, CI/CD tests, running batch jobs, handling stream replays, and processing data streams. Pathway is powered by a **scalable Rust engine** based on Differential Dataflow and performs incremental computation. Your Pathway code, despite being written in Python, is run by the Rust engine, enabling multithreading, multiprocessing, and distributed computations. All the pipeline is kept in memory and can be easily deployed with **Docker and Kubernetes**. You can install Pathway with pip: `pip install -U pathway` For any questions, you will find the community and team behind the project on Discord.

CodeProject.AI Server is a standalone, self-hosted, fast, free, and open-source Artificial Intelligence microserver designed for any platform and language. It can be installed locally without the need for off-device or out-of-network data transfer, providing an easy-to-use solution for developers interested in AI programming. The server includes a HTTP REST API server, backend analysis services, and the source code, enabling users to perform various AI tasks locally without relying on external services or cloud computing. Current capabilities include object detection, face detection, scene recognition, sentiment analysis, and more, with ongoing feature expansions planned. The project aims to promote AI development, simplify AI implementation, focus on core use-cases, and leverage the expertise of the developer community.

Basalt is a lightweight and flexible CSS framework designed to help developers quickly build responsive and modern websites. It provides a set of pre-designed components and utilities that can be easily customized to create unique and visually appealing web interfaces. With Basalt, developers can save time and effort by leveraging its modular structure and responsive design principles to create professional-looking websites with ease.

Argilla is a collaboration platform for AI engineers and domain experts that require high-quality outputs, full data ownership, and overall efficiency. It helps users improve AI output quality through data quality, take control of their data and models, and improve efficiency by quickly iterating on the right data and models. Argilla is an open-source community-driven project that provides tools for achieving and maintaining high-quality data standards, with a focus on NLP and LLMs. It is used by AI teams from companies like the Red Cross, Loris.ai, and Prolific to improve the quality and efficiency of AI projects.

ByteChef is an open-source, low-code, extendable API integration and workflow automation platform. It provides an intuitive UI Workflow Editor, event-driven & scheduled workflows, multiple flow controls, built-in code editor supporting Java, JavaScript, Python, and Ruby, rich component ecosystem, extendable with custom connectors, AI-ready with built-in AI components, developer-ready to expose workflows as APIs, version control friendly, self-hosted, scalable, and resilient. It allows users to build and visualize workflows, automate tasks across SaaS apps, internal APIs, and databases, and handle millions of workflows with high availability and fault tolerance.

Dream Textures is a tool integrated into Blender that allows users to create textures, concept art, background assets, and more using simple text prompts. It offers features like seamless texture creation, texture projection for entire scenes, restyling animations, and running models on the user's machine for faster iteration. The tool supports CUDA and Apple Silicon GPUs, with over 4GB of VRAM recommended. Users can troubleshoot issues by checking Blender's system console or seeking help from the community on Discord.

Data Formulator is an AI-powered tool developed by Microsoft Research to help data analysts create rich visualizations iteratively. It combines user interface interactions with natural language inputs to simplify the process of describing chart designs while delegating data transformation to AI. Users can utilize features like blended UI and NL inputs, data threads for history navigation, and code inspection to create impressive visualizations. The tool supports local installation for customization and Codespaces for quick setup. Developers can build new data analysis tools on top of Data Formulator, and research papers are available for further reading.

5ire is a cross-platform desktop client that integrates a local knowledge base for multilingual vectorization, supports parsing and vectorization of various document formats, offers usage analytics to track API spending, provides a prompts library for creating and organizing prompts with variable support, allows bookmarking of conversations, and enables quick keyword searches across conversations. It is licensed under the GNU General Public License version 3.

Sail is a tool designed to unify stream processing, batch processing, and compute-intensive workloads, serving as a drop-in replacement for Spark SQL and the Spark DataFrame API in single-process settings. It aims to streamline data processing tasks and facilitate AI workloads.

**Prompt flow** is a suite of development tools designed to streamline the end-to-end development cycle of LLM-based AI applications, from ideation, prototyping, testing, evaluation to production deployment and monitoring. It makes prompt engineering much easier and enables you to build LLM apps with production quality.

Agentok Studio is a visual tool built for AutoGen, a cutting-edge agent framework from Microsoft and various contributors. It offers intuitive visual tools to simplify the construction and management of complex agent-based workflows. Users can create workflows visually as graphs, chat with agents, and share flow templates. The tool is designed to streamline the development process for creators and developers working on next-generation Multi-Agent Applications.

AI Exploits is a repository that showcases practical attacks against AI/Machine Learning infrastructure, aiming to raise awareness about vulnerabilities in the AI/ML ecosystem. It contains exploits and scanning templates for responsibly disclosed vulnerabilities affecting machine learning tools, including Metasploit modules, Nuclei templates, and CSRF templates. Users can use the provided Docker image to easily run the modules and templates. The repository also provides guidelines for using Metasploit modules, Nuclei templates, and CSRF templates to exploit vulnerabilities in machine learning tools.

CSGHub is an open source, trustworthy large model asset management platform that can assist users in governing the assets involved in the lifecycle of LLM and LLM applications (datasets, model files, codes, etc). With CSGHub, users can perform operations on LLM assets, including uploading, downloading, storing, verifying, and distributing, through Web interface, Git command line, or natural language Chatbot. Meanwhile, the platform provides microservice submodules and standardized OpenAPIs, which could be easily integrated with users' own systems. CSGHub is committed to bringing users an asset management platform that is natively designed for large models and can be deployed On-Premise for fully offline operation. CSGHub offers functionalities similar to a privatized Huggingface(on-premise Huggingface), managing LLM assets in a manner akin to how OpenStack Glance manages virtual machine images, Harbor manages container images, and Sonatype Nexus manages artifacts.

Pathway's LLM (Large Language Model) Apps provide a platform to quickly deploy AI applications using the latest knowledge from data sources. The Python application examples in this repository are Docker-ready, exposing an HTTP API to the frontend. These apps utilize the Pathway framework for data synchronization, API serving, and low-latency data processing without the need for additional infrastructure dependencies. They connect to document data sources like S3, Google Drive, and Sharepoint, offering features like real-time data syncing, easy alert setup, scalability, monitoring, security, and unification of application logic.

The Spring AI project provides a Spring-friendly API and abstractions for developing AI applications. It offers a portable client API for interacting with generative AI models, enabling developers to easily swap out implementations and access various models like OpenAI, Azure OpenAI, and HuggingFace. Spring AI also supports prompt engineering, providing classes and interfaces for creating and parsing prompts, as well as incorporating proprietary data into generative AI without retraining the model. This is achieved through Retrieval Augmented Generation (RAG), which involves extracting, transforming, and loading data into a vector database for use by AI models. Spring AI's VectorStore abstraction allows for seamless transitions between different vector database implementations.

Beehave is a powerful addon for Godot Engine that enables users to create robust AI systems using behavior trees. It simplifies the design of complex NPC behaviors, challenging boss battles, and other advanced setups. Beehave allows for the creation of highly adaptive AI that responds to changes in the game world and overcomes unexpected obstacles, catering to both beginners and experienced developers. The tool is currently in development for version 3.0.

The Portkey Python SDK is a control panel for AI apps that allows seamless integration of Portkey's advanced features with OpenAI methods. It provides features such as AI gateway for unified API signature, interoperability, automated fallbacks & retries, load balancing, semantic caching, virtual keys, request timeouts, observability with logging, requests tracing, custom metadata, feedback collection, and analytics. Users can make requests to OpenAI using Portkey SDK and also use async functionality. The SDK is compatible with OpenAI SDK methods and offers Portkey-specific methods like feedback and prompts. It supports various providers and encourages contributions through Github issues or direct contact via email or Discord.

**Prompt flow** is a suite of development tools designed to streamline the end-to-end development cycle of LLM-based AI applications, from ideation, prototyping, testing, evaluation to production deployment and monitoring. It makes prompt engineering much easier and enables you to build LLM apps with production quality.

DeepEval is a simple-to-use, open-source LLM evaluation framework specialized for unit testing LLM outputs. It incorporates various metrics such as G-Eval, hallucination, answer relevancy, RAGAS, etc., and runs locally on your machine for evaluation. It provides a wide range of ready-to-use evaluation metrics, allows for creating custom metrics, integrates with any CI/CD environment, and enables benchmarking LLMs on popular benchmarks. DeepEval is designed for evaluating RAG and fine-tuning applications, helping users optimize hyperparameters, prevent prompt drifting, and transition from OpenAI to hosting their own Llama2 with confidence.

MegaDetector is an AI model that identifies animals, people, and vehicles in camera trap images (which also makes it useful for eliminating blank images). This model is trained on several million images from a variety of ecosystems. MegaDetector is just one of many tools that aims to make conservation biologists more efficient with AI. If you want to learn about other ways to use AI to accelerate camera trap workflows, check out our of the field, affectionately titled "Everything I know about machine learning and camera traps".

LeapfrogAI is a self-hosted AI platform designed to be deployed in air-gapped resource-constrained environments. It brings sophisticated AI solutions to these environments by hosting all the necessary components of an AI stack, including vector databases, model backends, API, and UI. LeapfrogAI's API closely matches that of OpenAI, allowing tools built for OpenAI/ChatGPT to function seamlessly with a LeapfrogAI backend. It provides several backends for various use cases, including llama-cpp-python, whisper, text-embeddings, and vllm. LeapfrogAI leverages Chainguard's apko to harden base python images, ensuring the latest supported Python versions are used by the other components of the stack. The LeapfrogAI SDK provides a standard set of protobuffs and python utilities for implementing backends and gRPC. LeapfrogAI offers UI options for common use-cases like chat, summarization, and transcription. It can be deployed and run locally via UDS and Kubernetes, built out using Zarf packages. LeapfrogAI is supported by a community of users and contributors, including Defense Unicorns, Beast Code, Chainguard, Exovera, Hypergiant, Pulze, SOSi, United States Navy, United States Air Force, and United States Space Force.

This Docker image for LLaVA (Large Language and Vision Assistant) provides a convenient way to run LLaVA locally or on RunPod. LLaVA is a powerful AI tool that combines natural language processing and computer vision capabilities. With this Docker image, you can easily access LLaVA's functionalities for various tasks, including image captioning, visual question answering, text summarization, and more. The image comes pre-installed with LLaVA v1.2.0, Torch 2.1.2, xformers 0.0.23.post1, and other necessary dependencies. You can customize the model used by setting the MODEL environment variable. The image also includes a Jupyter Lab environment for interactive development and exploration. Overall, this Docker image offers a comprehensive and user-friendly platform for leveraging LLaVA's capabilities.

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.

TrustLLM is a comprehensive study of trustworthiness in LLMs, including principles for different dimensions of trustworthiness, established benchmark, evaluation, and analysis of trustworthiness for mainstream LLMs, and discussion of open challenges and future directions. Specifically, we first propose a set of principles for trustworthy LLMs that span eight different dimensions. Based on these principles, we further establish a benchmark across six dimensions including truthfulness, safety, fairness, robustness, privacy, and machine ethics. We then present a study evaluating 16 mainstream LLMs in TrustLLM, consisting of over 30 datasets. The document explains how to use the trustllm python package to help you assess the performance of your LLM in trustworthiness more quickly. For more details about TrustLLM, please refer to project website.

AI-YinMei is an AI virtual anchor Vtuber development tool (N card version). It supports fastgpt knowledge base chat dialogue, a complete set of solutions for LLM large language models: [fastgpt] + [one-api] + [Xinference], supports docking bilibili live broadcast barrage reply and entering live broadcast welcome speech, supports Microsoft edge-tts speech synthesis, supports Bert-VITS2 speech synthesis, supports GPT-SoVITS speech synthesis, supports expression control Vtuber Studio, supports painting stable-diffusion-webui output OBS live broadcast room, supports painting picture pornography public-NSFW-y-distinguish, supports search and image search service duckduckgo (requires magic Internet access), supports image search service Baidu image search (no magic Internet access), supports AI reply chat box [html plug-in], supports AI singing Auto-Convert-Music, supports playlist [html plug-in], supports dancing function, supports expression video playback, supports head touching action, supports gift smashing action, supports singing automatic start dancing function, chat and singing automatic cycle swing action, supports multi scene switching, background music switching, day and night automatic switching scene, supports open singing and painting, let AI automatically judge the content.