OllamaKit is a Swift library designed to simplify interactions with the Ollama API. It handles network communication and data processing, offering an efficient interface for Swift applications to communicate with the Ollama API. The library is optimized for use within Ollamac, a macOS app for interacting with Ollama models.

This repository contains a Rest-Backend for a Conversational Agent that allows embedding documents, semantic search, QA based on documents, and document processing with Large Language Models. It uses Aleph Alpha and OpenAI Large Language Models to generate responses to user queries, includes a vector database, and provides a REST API built with FastAPI. The project also features semantic search, secret management for API keys, installation instructions, and development guidelines for both backend and frontend components.

GraphRAG Local with Interactive UI is an adaptation of Microsoft's GraphRAG, tailored to support local models and featuring a comprehensive interactive user interface. It allows users to leverage local models for LLM and embeddings, visualize knowledge graphs in 2D or 3D, manage files, settings, and queries, and explore indexing outputs. The tool aims to be cost-effective by eliminating dependency on costly cloud-based models and offers flexible querying options for global, local, and direct chat queries.

AgentIQ is a flexible library designed to seamlessly integrate enterprise agents with various data sources and tools. It enables true composability by treating agents, tools, and workflows as simple function calls. With features like framework agnosticism, reusability, rapid development, profiling, observability, evaluation system, user interface, and MCP compatibility, AgentIQ empowers developers to move quickly, experiment freely, and ensure reliability across agent-driven projects.

Open Assistant API is an open-source, self-hosted AI intelligent assistant API compatible with the official OpenAI interface. It supports integration with more commercial and private models, R2R RAG engine, internet search, custom functions, built-in tools, code interpreter, multimodal support, LLM support, and message streaming output. Users can deploy the service locally and expand existing features. The API provides user isolation based on tokens for SaaS deployment requirements and allows integration of various tools to enhance its capability to connect with the external world.

eShopSupport is a sample .NET application showcasing common use cases and development practices for building AI solutions in .NET, specifically Generative AI. It demonstrates a customer support application for an e-commerce website using a services-based architecture with .NET Aspire. The application includes support for text classification, sentiment analysis, text summarization, synthetic data generation, and chat bot interactions. It also showcases development practices such as developing solutions locally, evaluating AI responses, leveraging Python projects, and deploying applications to the Cloud.

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.

Chatflow is a tool that provides a chat interface for users to interact with systems using natural language. The engine understands user intent and executes commands for tasks, allowing easy navigation of complex websites/products. This approach enhances user experience, reduces training costs, and boosts productivity.

LLMFlex is a python package designed for developing AI applications with local Large Language Models (LLMs). It provides classes to load LLM models, embedding models, and vector databases to create AI-powered solutions with prompt engineering and RAG techniques. The package supports multiple LLMs with different generation configurations, embedding toolkits, vector databases, chat memories, prompt templates, custom tools, and a chatbot frontend interface. Users can easily create LLMs, load embeddings toolkit, use tools, chat with models in a Streamlit web app, and serve an OpenAI API with a GGUF model. LLMFlex aims to offer a simple interface for developers to work with LLMs and build private AI solutions using local resources.

NVIDIA NeMo Agent toolkit is a flexible, lightweight, and unifying library that allows you to easily connect existing enterprise agents to data sources and tools across any framework. It is framework agnostic, promotes reusability, enables rapid development, provides profiling capabilities, offers observability features, includes an evaluation system, features a user interface for interaction, and supports the Model Context Protocol (MCP). With NeMo Agent toolkit, users can move quickly, experiment freely, and ensure reliability across all agent-driven projects.

CSGHub Server is a part of the open source and reliable large model assets management platform - CSGHub. It focuses on management of models, datasets, and other LLM assets through REST API. Key features include creation and management of users and organizations, auto-tagging of model and dataset labels, search functionality, online preview of dataset files, content moderation for text and image, download of individual files, tracking of model and dataset activity data. The tool is extensible and customizable, supporting different git servers, flexible LFS storage system configuration, and content moderation options. The roadmap includes support for more Git servers, Git LFS, dataset online viewer, model/dataset auto-tag, S3 protocol support, model format conversion, and model one-click deploy. The project is licensed under Apache 2.0 and welcomes contributions.

A 3D AI desktop companion with endless possibilities! This repository provides a platform for enhancing the LLM API without code modification, supporting seamless integration of various functionalities such as knowledge bases, real-time networking, multimodal capabilities, automation, and deep thinking control. It offers one-click deployment to multiple terminals, ecological tool interconnection, standardized interface opening, and compatibility across all platforms. Users can deploy the tool on Windows, macOS, Linux, or Docker, and access features like intelligent agent deployment, VRM desktop pets, Tavern character cards, QQ bot deployment, and developer-friendly interfaces. The tool supports multi-service providers, extensive tool integration, and ComfyUI workflows. Hardware requirements are minimal, making it suitable for various deployment scenarios.

ToolMate AI is an advanced AI companion that integrates agents, tools, and plugins to excel in conversations, generative work, and task execution. It supports multi-step actions, allowing users to customize workflows for tackling complex projects with ease. The tool offers a wide range of AI backends and models, including Ollama, Llama.cpp, Groq Cloud API, OpenAI API, and Google Gemini via Vertex AI. Users can easily switch between backends and leverage AI models like wizardlm2 and mixtral. ToolMate AI stands out for its distinctive features such as tool calling for any LLMs, running multiple tools in one go, highly customizable plugins, and integration with popular AI tools. It also supports quick tool calling using '@' notation and enables the execution of computing tasks on demand. With features like multiple tools in one go, customizable plugins, system command and fabric integration, GPU offloading support, real-time data access, and device information retrieval, ToolMate AI offers a comprehensive solution for various tasks and content creation.

BlinkID SDK wrapper for React Native provides best-in-class ID scanning software for cross-platform apps built with React Native. It offers complete guidance on installing and linking BlinkID library with iOS and Android apps. The SDK requires a valid license key for scanning, with offline data extraction. It supports React Native v0.71.2 and includes installation and linking instructions for iOS and Android. The repository also contains a script to create a sample React Native project and dependencies. Video tutorials demonstrate using documentVerificationOverlay and CombinedRecognizer for scanning various document types.

Eidos is an extensible framework for managing personal data in one place. It runs inside the browser as a PWA with offline support. It integrates AI features for translation, summarization, and data interaction. Users can customize Eidos with Prompt extension, JavaScript for Formula functions, TypeScript/JavaScript for data processing logic, and build apps using any framework. Eidos is developer-friendly with API & SDK, and uses SQLite standardization for data tables.

Writer Framework is an open-source framework for creating AI applications. It allows users to build user interfaces using a visual editor and write the backend code in Python. The framework is fast, flexible, and developer-friendly, providing separation of concerns between UI and business logic. It is reactive and state-driven, allowing for highly customizable elements without the need for CSS. Writer Framework is designed to be fast, with minimal overhead on Python code, and uses WebSockets for synchronization. It is contained in a standard Python package, supports local code editing with instant refreshes, and enables editing the UI while the app is running.

OllamaKit is a Swift library designed to simplify interactions with the Ollama API. It handles network communication and data processing, offering an efficient interface for Swift applications to communicate with the Ollama API. The library is optimized for use within Ollamac, a macOS app for interacting with Ollama models.

API Improvement Proposals (AIPs) are design documents that provide high-level, concise documentation for API development at Google. The goal of AIPs is to serve as the source of truth for API-related documentation and to facilitate discussion and consensus among API teams. AIPs are similar to Python's enhancement proposals (PEPs) and are organized into different areas within Google to accommodate historical differences in customs, styles, and guidance.

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.

Speakeasy is a tool that helps developers create production-quality SDKs, Terraform providers, documentation, and more from OpenAPI specifications. It supports a wide range of languages, including Go, Python, TypeScript, Java, and C#, and provides features such as automatic maintenance, type safety, and fault tolerance. Speakeasy also integrates with popular package managers like npm, PyPI, Maven, and Terraform Registry for easy distribution.

ApiCat is an API documentation management tool that is fully compatible with the OpenAPI specification. With ApiCat, you can freely and efficiently manage your APIs. It integrates the capabilities of LLM, which not only helps you automatically generate API documentation and data models but also creates corresponding test cases based on the API content. Using ApiCat, you can quickly accomplish anything outside of coding, allowing you to focus your energy on the code itself.

Aiohttp pydantic is an aiohttp view to easily parse and validate requests. You define using function annotations what your methods for handling HTTP verbs expect, and Aiohttp pydantic parses the HTTP request for you, validates the data, and injects the parameters you want. It provides features like query string, request body, URL path, and HTTP headers validation, as well as Open API Specification generation.

Ain is a terminal HTTP API client designed for scripting input and processing output via pipes. It allows flexible organization of APIs using files and folders, supports shell-scripts and executables for common tasks, handles url-encoding, and enables sharing the resulting curl, wget, or httpie command-line. Users can put things that change in environment variables or .env-files, and pipe the API output for further processing. Ain targets users who work with many APIs using a simple file format and uses curl, wget, or httpie to make the actual calls.

OllamaKit is a Swift library designed to simplify interactions with the Ollama API. It handles network communication and data processing, offering an efficient interface for Swift applications to communicate with the Ollama API. The library is optimized for use within Ollamac, a macOS app for interacting with Ollama models.

Ollama4j is a Java library that serves as a wrapper or binding for the Ollama server. It facilitates communication with the Ollama server and provides models for deployment. The tool requires Java 11 or higher and can be installed locally or via Docker. Users can integrate Ollama4j into Maven projects by adding the specified dependency. The tool offers API specifications and supports various development tasks such as building, running unit tests, and integration tests. Releases are automated through GitHub Actions CI workflow. Areas of improvement include adhering to Java naming conventions, updating deprecated code, implementing logging, using lombok, and enhancing request body creation. Contributions to the project are encouraged, whether reporting bugs, suggesting enhancements, or contributing code.