semantic-router

The Semantic Router is an intelligent routing tool that utilizes a Mixture-of-Models (MoM) approach to direct OpenAI API requests to the most suitable models based on semantic understanding. It enhances inference accuracy by selecting models tailored to different types of tasks. The tool also automatically selects relevant tools based on the prompt to improve tool selection accuracy. Additionally, it includes features for enterprise security such as PII detection and prompt guard to protect user privacy and prevent misbehavior. The tool implements similarity caching to reduce latency. The comprehensive documentation covers setup instructions, architecture guides, and API references.

Superlinked is a compute framework for information retrieval and feature engineering systems, focusing on converting complex data into vector embeddings for RAG, Search, RecSys, and Analytics stack integration. It enables custom model performance in machine learning with pre-trained model convenience. The tool allows users to build multimodal vectors, define weights at query time, and avoid postprocessing & rerank requirements. Users can explore the computational model through simple scripts and python notebooks, with a future release planned for production usage with built-in data infra and vector database integrations.

SuperAgentX is a lightweight open-source AI framework designed for multi-agent applications with Artificial General Intelligence (AGI) capabilities. It offers goal-oriented multi-agents with retry mechanisms, easy deployment through WebSocket, RESTful API, and IO console interfaces, streamlined architecture with no major dependencies, contextual memory using SQL + Vector databases, flexible LLM configuration supporting various Gen AI models, and extendable handlers for integration with diverse APIs and data sources. It aims to accelerate the development of AGI by providing a powerful platform for building autonomous AI agents capable of executing complex tasks with minimal human intervention.

PPTAgent is an innovative system that automatically generates presentations from documents. It employs a two-step process for quality assurance and introduces PPTEval for comprehensive evaluation. With dynamic content generation, smart reference learning, and quality assessment, PPTAgent aims to streamline presentation creation. The tool follows an analysis phase to learn from reference presentations and a generation phase to develop structured outlines and cohesive slides. PPTEval evaluates presentations based on content accuracy, visual appeal, and logical coherence.

A.I.G (AI-Infra-Guard) is an AI red teaming platform by Tencent Zhuque Lab that integrates capabilities such as AI infra vulnerability scan, MCP Server risk scan, and Jailbreak Evaluation. It aims to provide users with a comprehensive, intelligent, and user-friendly solution for AI security risk self-examination. The platform offers features like AI Infra Scan, AI Tool Protocol Scan, and Jailbreak Evaluation, along with a modern web interface, complete API, multi-language support, cross-platform deployment, and being free and open-source under the MIT license.

Local Deep Research is a powerful AI-powered research assistant that performs deep, iterative analysis using multiple LLMs and web searches. It can be run locally for privacy or configured to use cloud-based LLMs for enhanced capabilities. The tool offers advanced research capabilities, flexible LLM support, rich output options, privacy-focused operation, enhanced search integration, and academic & scientific integration. It also provides a web interface, command line interface, and supports multiple LLM providers and search engines. Users can configure AI models, search engines, and research parameters for customized research experiences.

OpenResearcher is a fully open agentic large language model designed for long-horizon deep research scenarios. It achieves an impressive 54.8% accuracy on BrowseComp-Plus, surpassing performance of GPT-4.1, Claude-Opus-4, Gemini-2.5-Pro, DeepSeek-R1, and Tongyi-DeepResearch. The tool is fully open-source, providing the training and evaluation recipe—including data, model, training methodology, and evaluation framework for everyone to progress deep research. It offers features like a fully open-source recipe, highly scalable and low-cost generation of deep research trajectories, and remarkable performance on deep research benchmarks.

OSA (Open-Source-Advisor) is a tool designed to improve the quality of scientific open source projects by automating the generation of README files, documentation, CI/CD scripts, and providing advice and recommendations for repositories. It supports various LLMs accessible via API, local servers, or osa_bot hosted on ITMO servers. OSA is currently under development with features like README file generation, documentation generation, automatic implementation of changes, LLM integration, and GitHub Action Workflow generation. It requires Python 3.10 or higher and tokens for GitHub/GitLab/Gitverse and LLM API key. Users can install OSA using PyPi or build from source, and run it using CLI commands or Docker containers.

DeepChat is a versatile chat tool that supports multiple model cloud services and local model deployment. It offers multi-channel chat concurrency support, platform compatibility, complete Markdown rendering, and easy usability with a comprehensive guide. The tool aims to enhance chat experiences by leveraging various AI models and ensuring efficient conversation management.

Automatic is an Image Diffusion implementation with advanced features. It supports multiple diffusion models, built-in control for text, image, batch, and video processing, and is compatible with various platforms and backends. The tool offers optimized processing with the latest torch developments, built-in support for torch.compile, and multiple compile backends. It also features platform-specific autodetection, queue management, enterprise-level logging, and a built-in installer with automatic updates and dependency management. Automatic is mobile compatible and provides a main interface using StandardUI and ModernUI.

OpenHealth is an AI health assistant that helps users manage their health data by leveraging AI and personal health information. It allows users to consolidate health data, parse it smartly, and engage in contextual conversations with GPT-powered AI. The tool supports various data sources like blood test results, health checkup data, personal physical information, family history, and symptoms. OpenHealth aims to empower users to take control of their health by combining data and intelligence for actionable health management.

DroidRun is a powerful framework for controlling Android and iOS devices through LLM agents. It allows you to automate device interactions using natural language commands. The tool supports multiple LLM providers and offers planning capabilities for complex multi-step tasks. It provides an easy-to-use CLI with enhanced debugging features, an extendable Python API for custom automations, screenshot analysis for visual understanding of the device, and execution tracing with Arize Phoenix.

Aegra is a self-hosted AI agent backend platform that provides LangGraph power without vendor lock-in. Built with FastAPI + PostgreSQL, it offers complete control over agent orchestration for teams looking to escape vendor lock-in, meet data sovereignty requirements, enable custom deployments, and optimize costs. Aegra is Agent Protocol compliant and perfect for teams seeking a free, self-hosted alternative to LangGraph Platform with zero lock-in, full control, and compatibility with existing LangGraph Client SDK.

AI Runner is a multi-modal AI interface that allows users to run open-source large language models and AI image generators on their own hardware. The tool provides features such as voice-based chatbot conversations, text-to-speech, speech-to-text, vision-to-text, text generation with large language models, image generation capabilities, image manipulation tools, utility functions, and more. It aims to provide a stable and user-friendly experience with security updates, a new UI, and a streamlined installation process. The application is designed to run offline on users' hardware without relying on a web server, offering a smooth and responsive user experience.

This project aims to create a RESTful API server compatible with the OpenAI API using open-source backends like llama/llama2. With this project, various GPT tools/frameworks can be compatible with your own model. Key features include: - **Compatibility with OpenAI API**: The API server follows the OpenAI API structure, allowing seamless integration with existing tools and frameworks. - **Support for Multiple Backends**: The server supports both llama.cpp and pyllama backends, providing flexibility in model selection. - **Customization Options**: Users can configure model parameters such as temperature, top_p, and top_k to fine-tune the model's behavior. - **Batch Processing**: The API supports batch processing for embeddings, enabling efficient handling of multiple inputs. - **Token Authentication**: The server utilizes token authentication to secure access to the API. This tool is particularly useful for developers and researchers who want to integrate large language models into their applications or explore custom models without relying on proprietary APIs.

Lingo is an interactive platform for language learning that provides a modern UI/UX experience. It offers features like courses, quests, and a shop for users to engage with. The tech stack includes React JS, Next JS, Typescript, Tailwind CSS, Vercel, and Postgresql. Users can contribute to the project by submitting changes via pull requests. The platform utilizes resources from CodeWithAntonio, Kenney Assets, Freesound, Elevenlabs AI, and Flagpack. Key dependencies include @clerk/nextjs, @neondatabase/serverless, @radix-ui/react-avatar, and more. Users can follow the project creator on GitHub and Twitter, as well as subscribe to their YouTube channel for updates. To learn more about Next.js, users can refer to the Next.js documentation and interactive tutorial.

The Semantic Router is an intelligent routing tool that utilizes a Mixture-of-Models (MoM) approach to direct OpenAI API requests to the most suitable models based on semantic understanding. It enhances inference accuracy by selecting models tailored to different types of tasks. The tool also automatically selects relevant tools based on the prompt to improve tool selection accuracy. Additionally, it includes features for enterprise security such as PII detection and prompt guard to protect user privacy and prevent misbehavior. The tool implements similarity caching to reduce latency. The comprehensive documentation covers setup instructions, architecture guides, and API references.

Weave is a toolkit for developing Generative AI applications, built by Weights & Biases. With Weave, you can log and debug language model inputs, outputs, and traces; build rigorous, apples-to-apples evaluations for language model use cases; and organize all the information generated across the LLM workflow, from experimentation to evaluations to production. Weave aims to bring rigor, best-practices, and composability to the inherently experimental process of developing Generative AI software, without introducing cognitive overhead.

LLMStack is a no-code platform for building generative AI agents, workflows, and chatbots. It allows users to connect their own data, internal tools, and GPT-powered models without any coding experience. LLMStack can be deployed to the cloud or on-premise and can be accessed via HTTP API or triggered from Slack or Discord.

The VisionCraft API is a free API for using over 100 different AI models. From images to sound.

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.

PyRIT is an open access automation framework designed to empower security professionals and ML engineers to red team foundation models and their applications. It automates AI Red Teaming tasks to allow operators to focus on more complicated and time-consuming tasks and can also identify security harms such as misuse (e.g., malware generation, jailbreaking), and privacy harms (e.g., identity theft). The goal is to allow researchers to have a baseline of how well their model and entire inference pipeline is doing against different harm categories and to be able to compare that baseline to future iterations of their model. This allows them to have empirical data on how well their model is doing today, and detect any degradation of performance based on future improvements.

Tabby is a self-hosted AI coding assistant, offering an open-source and on-premises alternative to GitHub Copilot. It boasts several key features: * Self-contained, with no need for a DBMS or cloud service. * OpenAPI interface, easy to integrate with existing infrastructure (e.g Cloud IDE). * Supports consumer-grade GPUs.

SPEAR (Simulator for Photorealistic Embodied AI Research) is a powerful tool for training embodied agents. It features 300 unique virtual indoor environments with 2,566 unique rooms and 17,234 unique objects that can be manipulated individually. Each environment is designed by a professional artist and features detailed geometry, photorealistic materials, and a unique floor plan and object layout. SPEAR is implemented as Unreal Engine assets and provides an OpenAI Gym interface for interacting with the environments via Python.

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.