Open Source BSD Artificial Intelligence Software - Page 4
Sort By:
Artificial Intelligence Software for BSD
-
Loan management software that makes it easy.Bryt Software is ideal for lending professionals who are looking for a feature rich loan management system that is intuitive and easy to use. We are 100% cloud-based, software as a service. We believe in providing our customers with fair and honest pricing. Our monthly fees are based on your number of users and we have a minimal implementation charge.
-
MicroStation by Bentley Systems is the trusted computer-aided design (CAD) software built specifically for infrastructure design.MicroStation is the only computer-aided design software for infrastructure design, helping architects and engineers like you bring their vision to life, present their designs to their clients, and deliver their projects to the community.
-
1
AI as Workspace
An elegant AI chat client. Full-featured, lightweight
AI as Workspace, short for AI as Workspace, is an open-source AI client application that provides a unified interface for interacting with multiple large language models and AI tools within a single workspace environment. The platform is designed as a lightweight yet powerful desktop or web application that organizes AI interactions through structured workspaces. Instead of managing individual chat sessions separately, users can group conversations, artifacts, and tasks within customizable workspaces that support different projects or contexts. AIaW supports multiple AI providers and models through a flexible interface compatible with common API formats used by services such as OpenAI-style endpoints. The application also includes a plugin system that allows developers to extend the platform with additional capabilities such as automation tools, integrations, or custom AI utilities. -
2
AIGCPanel
One-stop AI digital human system with video voice synthesis tools
AIGCPanel is an open source desktop application designed as a comprehensive, all-in-one platform for creating AI-powered digital humans and media content. It integrates multiple capabilities such as video synthesis, voice synthesis, and voice cloning into a unified interface, allowing users to generate realistic audiovisual outputs with minimal setup. AIGCPanel focuses heavily on simplifying the management of local AI models by providing streamlined workflows for importing, configuring, and running different models with minimal manual effort. It supports one-click model deployment, making it accessible even to beginners who may not be familiar with complex AI environments. AIGCPanel also includes tools for synchronizing lip movements with generated speech, enabling more realistic digital avatar videos. Built using modern desktop technologies, it delivers a cross-platform experience while maintaining a graphical interface for monitoring tasks and logs. -
3
Llama Coder
Open source Claude Artifacts – built with Llama 3.1 405B
Llama Coder is an open-source tool that lets you generate small applications (often React or web apps) from a single natural-language prompt using the Llama 3 family of models. It’s framed as an open-source “Claude Artifacts”-style experience: you describe the app you want, the tool calls an LLM hosted on Together.ai, and you get back a runnable code artifact. The project includes a web interface where you can enter prompts, see generated code, and run or tweak the result directly in the browser. Technically, it is built using a modern TypeScript/Next.js stack and integrates with Together’s API, making it a good blueprint for building your own AI-powered developer tools. By focusing on small self-contained apps or components, it keeps scope manageable while still showcasing the power of code generation. Developers can fork the repo to plug in different models, change the UI, or integrate it into their own IDE-adjacent workflows. -
4
SoniTranslate
Synchronized Translation for Videos
SoniTranslate is a video translation and dubbing system that produces synchronized target-language audio tracks for existing video content. It provides a web UI built with Gradio, allowing users to upload a video, choose source and target languages, and then run a pipeline that handles transcription, translation and re-synthesis of speech. Under the hood, it uses advanced speech and diarization models to separate speakers, align audio with timecodes and respect subtitle timing, which lets the generated dub track stay in sync with the original video structure. The project supports a wide range of languages for translation, spanning major world languages (English, Spanish, French, German, Chinese, Arabic, etc.) and many regional or less widely spoken languages, making it suitable for broad internationalization. It offers multiple usage modes, including a Colab notebook for cloud-based experimentation, a Hugging Face Space demo for quick trials, and instructions. -
The full-stack observability platform that protects your dataLayer, tags and conversion dataCode-Cube.io detects issues instantly, alerts you in real time and helps you resolve them fast. No manual QA. No unreliable data. Just data you can trust and act on.
-
5
BrowserGym
A Gym environment for web task automation
BrowserGym is an open framework for web task automation research that exposes browser interaction as a Gym-style environment for training and evaluating agents. It is intended for researchers building web agents rather than for end users looking for a consumer automation product. The project provides a common environment where agents can interact with websites, execute tasks, and be evaluated against standardized benchmarks. One of its main strengths is that it bundles several important benchmarks by default, including MiniWoB, WebArena, VisualWebArena, WorkArena, AssistantBench, WebLINX, and OpenApps. This gives researchers a unified way to compare agent behavior across diverse web environments and task types without stitching together separate evaluation stacks. BrowserGym is also designed to be extensible, and the repository notes that creating new benchmarks mainly involves inheriting its abstract task interface. -
6
HolmesGPT
CNCF Sandbox Project
HolmesGPT is an open-source AI agent designed to help DevOps and site reliability engineering teams diagnose and resolve production incidents. The system aggregates signals from observability tools such as logs, metrics, alerts, and distributed traces, then analyzes them using large language models to identify potential root causes. Rather than requiring engineers to manually correlate large volumes of monitoring data, HolmesGPT automatically synthesizes evidence and presents explanations in natural language. The project is developed by Robusta and has been accepted as a Cloud Native Computing Foundation Sandbox project, highlighting its relevance to the cloud-native ecosystem. It is designed to operate as an automated troubleshooting assistant that can analyze incidents continuously and support on-call engineers during outages. -
7
Ralph Orchestrator
An improved implementation of the Ralph Wiggum technique
Ralph Orchestrator is an AI workflow orchestration system designed to coordinate multiple agents, tools, and processes into structured pipelines that can execute complex tasks autonomously. It provides a framework for defining workflows where different components, such as LLMs, APIs, and custom functions, collaborate to achieve specific objectives. The system emphasizes modularity and composability, allowing developers to design workflows as reusable building blocks that can be combined or extended as needed. It supports asynchronous execution and task coordination, enabling efficient handling of multi-step processes that involve decision-making and conditional branching. Ralph Orchestrator is particularly useful for building agent-based systems, automation pipelines, and AI-driven applications that require coordination across multiple services. It also includes logging and monitoring capabilities to track workflow execution and debug issues effectively. -
8
Strix
Open-source AI hackers to find and fix your app’s vulnerabilities
Strix is an open source agent-driven security platform that uses autonomous AI agents to identify, investigate, and validate vulnerabilities in software applications. The system is designed to mimic the behavior of real attackers by executing dynamic testing and verifying findings through proof-of-concept exploitation. Unlike traditional vulnerability scanners that rely heavily on static analysis, Strix agents actively run code, probe systems, and attempt exploitation to confirm whether vulnerabilities are genuinely exploitable. The platform is intended for developers and security teams that need rapid security assessments without the overhead of manual penetration testing engagements. Strix can orchestrate multiple cooperating agents that divide investigation tasks and collaboratively analyze complex applications or infrastructure. -
9
VibeVoice
Open-source multi-speaker long-form text-to-speech model
VibeVoice-1.5B is Microsoft’s frontier open-source text-to-speech (TTS) model designed for generating expressive, long-form, multi-speaker conversational audio such as podcasts. Unlike traditional TTS systems, it excels in scalability, speaker consistency, and natural turn-taking for up to 90 minutes of continuous speech with as many as four distinct speakers. A key innovation is its use of continuous acoustic and semantic speech tokenizers operating at an ultra-low frame rate of 7.5 Hz, enabling high audio fidelity with efficient processing of long sequences. The model integrates a Qwen2.5-based large language model with a diffusion head to produce realistic acoustic details and capture conversational context. Training involved curriculum learning with increasing sequence lengths up to 65K tokens, allowing VibeVoice to handle very long dialogues effectively. Safety mechanisms include an audible disclaimer and imperceptible watermarking in all generated audio to mitigate misuse risks. -
Award-Winning Medical Office Software Designed for Your SpecialtyRXNT is an ambulatory healthcare technology pioneer that empowers medical practices and healthcare organizations to succeed and scale through innovative, data-backed, AI-powered software.
-
10
Alpa
Training and serving large-scale neural networks
Alpa is a system for training and serving large-scale neural networks. Scaling neural networks to hundreds of billions of parameters has enabled dramatic breakthroughs such as GPT-3, but training and serving these large-scale neural networks require complicated distributed system techniques. Alpa aims to automate large-scale distributed training and serving with just a few lines of code. -
11
DeepSeek-V3.2-Exp
An experimental version of DeepSeek model
DeepSeek-V3.2-Exp is an experimental release of the DeepSeek model family, intended as a stepping stone toward the next generation architecture. The key innovation in this version is DeepSeek Sparse Attention (DSA), a sparse attention mechanism that aims to optimize training and inference efficiency in long-context settings without degrading output quality. According to the authors, they aligned the training setup of V3.2-Exp with V3.1-Terminus so that benchmark results remain largely comparable, even though the internal attention mechanism changes. In public evaluations across a variety of reasoning, code, and question-answering benchmarks (e.g. MMLU, LiveCodeBench, AIME, Codeforces, etc.), V3.2-Exp shows performance very close to or in some cases matching that of V3.1-Terminus. The repository includes tools and kernels to support the new sparse architecture—for instance, CUDA kernels, logit indexers, and open-source modules like FlashMLA and DeepGEMM are invoked for performance. -
12
MemU
MemU is an open-source memory framework for AI companions
MemU is an agentic memory layer for LLM applications, specifically designed for AI companions. Transform your memory into an intelligent file system that automatically organizes, connects, and evolves with your memories. Simple, fast, and reliable memory infrastructure for AI applications. Powerful tools and dedicated support to scale your AI applications with confidence. Full proprietary features, commercial usage rights, and white-labeling options for your enterprise needs. SSO/RBAC integration and a dedicated algorithm team for scenario-specific optimization. User behavior analysis, real-time monitoring, and automated agent optimization tools. 24/7 dedicated support team, custom SLAs, and professional implementation services. -
13
Whisper-WebUI
A Web UI for easy subtitle using whisper model
Whisper WebUI is an open-source browser-based interface that simplifies the use of Whisper speech recognition models by providing an intuitive graphical environment for transcription, translation, and subtitle generation. Built with Gradio, it allows users to upload audio or video files, process them locally, and generate accurate text outputs without relying on command-line tools. The platform integrates optimized implementations such as faster-whisper, significantly improving transcription speed and reducing memory usage compared to standard models. It supports multiple input sources including local files, YouTube content, and microphone input, making it versatile for different workflows. Whisper WebUI also includes advanced preprocessing and postprocessing features such as voice activity detection, background music separation, and speaker diarization, enabling more accurate and structured outputs. -
14
FLUX.1
Official inference repo for FLUX.1 models
FLUX.1 repository contains inference code and tooling for the FLUX.1 text-to-image diffusion models, enabling developers and researchers to generate and edit images from natural-language prompts using open-weight versions of the model on their own hardware or within custom applications. The project is part of a larger family of FLUX models developed by Black Forest Labs, designed to produce high-quality, detailed visuals from text descriptions with competitive prompt adherence and artistic fidelity. This repo focuses on running the open-source model variants efficiently, providing scripts, model loading logic, and examples for local installations, and supports integration with Python toolchains like PyTorch and popular generative pipelines. Users can launch CLI tools to generate images, experiment with different FLUX variants, and extend the base code for research-oriented applications. -
15
VideoCaptioner
AI-powered tool for generating, optimizing, and translating subtitles
VideoCaptioner is an open source AI-powered subtitle processing tool designed to simplify the workflow of creating subtitles for videos. It integrates speech recognition, language processing, and translation technologies to automatically generate and refine subtitles from video or audio sources. VideoCaptioner uses speech-to-text engines such as Whisper variants to transcribe spoken content and convert it into subtitle text with accurate timestamps. After transcription, large language models are used to intelligently restructure subtitles into natural sentences, correct wording, and improve readability for viewers. It can also translate subtitles into other languages while preserving the original timing, making it suitable for multilingual video publishing and accessibility. In addition to generating subtitles, it supports editing, formatting, and embedding subtitles into videos as either hard or soft subtitles. -
16
Dlib is a C++ toolkit containing machine learning algorithms and tools for creating complex software in C++ to solve real world problems.
-
17
GLM-OCR
Accurate × Fast × Comprehensive
GLM-OCR is an open-source multimodal optical character recognition (OCR) model built on a GLM-V encoder–decoder foundation that brings robust, accurate document understanding to complex real-world layouts and modalities. Designed to handle text recognition, table parsing, formula extraction, and general information retrieval from documents containing mixed content, GLM-OCR excels across major benchmarks while remaining highly efficient with a relatively compact parameter size (~0.9B), enabling deployment in high-concurrency services and edge environments. The model’s multimodal capabilities allow it to reason across image and text content holistically, capturing structured and unstructured information from pages that include dense tables, seals, code snippets, and varied document graphics. GLM-OCR integrates a comprehensive SDK and inference toolchain that makes it easy for developers to install, invoke, and embed into production pipelines with simple commands or APIs. -
18
Mooncake
Mooncake is the serving platform for Kimi
Mooncake is an open-source infrastructure platform designed to optimize large language model serving by focusing on efficient management and transfer of model data and KV cache. The platform was originally developed as part of the serving infrastructure for the Kimi large language model system. Its architecture centers on a high-performance transfer engine that provides unified data transfer across different storage and networking technologies. This engine enables efficient movement of tensors and model data across heterogeneous environments such as GPU memory, system memory, and distributed storage systems. Mooncake also introduces distributed key-value cache storage that allows inference systems to reuse previously computed attention states, significantly improving throughput in large-scale deployments. The system supports advanced networking technologies such as RDMA and NVMe over Fabric, enabling high-speed communication across clusters. -
19
OpenClaw Medical Skills
The largest open-source medical AI skills library for OpenClaw
OpenClaw-Medical-Skills is an open-source library that provides a large collection of specialized medical capabilities designed for the OpenClaw AI agent ecosystem. The project organizes domain-specific “skills” that enable autonomous agents to perform tasks related to biomedical research, healthcare analysis, and clinical data interpretation. Each skill is packaged as a modular component that can be integrated into an OpenClaw-based AI assistant, allowing the agent to perform expert-level reasoning and workflows in medical contexts. Instead of relying on general-purpose language model responses, the repository equips AI agents with structured instructions and tools tailored to medical knowledge and datasets. This modular design allows developers and researchers to build AI systems that can access specialized medical reasoning processes, retrieve relevant biomedical information, and generate structured outputs suitable for analysis or downstream processing. -
20
Paperclip
Open-source orchestration for zero-human companies
Paperclip is an open-source tool designed to help AI systems and developer tools access academic research papers through a standardized interface. The project implements a server based on the Model Context Protocol (MCP), a framework that allows large language models and AI agents to connect to external data sources and tools in a consistent way. By acting as a middleware layer, Paperclip aggregates multiple academic databases and exposes them through a single interface, allowing AI applications to search and retrieve scholarly papers without needing to integrate with each provider individually. The system supports repositories such as arXiv, OpenAlex, and the Open Science Framework, giving AI agents access to a large body of research literature. Instead of requiring separate APIs and authentication flows for each service, Paperclip provides unified search and retrieval capabilities that simplify integration into AI workflows. -
21
Qwen3.5
Qwen3.5 is the large language model series developed by Qwen team
Qwen3.5 is part of Alibaba’s Qwen family of large language and multimodal foundation models, designed to power advanced AI applications such as chatbots, coding assistants, and autonomous agents. The project represents a significant step toward “agentic AI,” meaning models that can reason through multi-step tasks and interact with external tools or environments rather than only generating text. Qwen3.5 builds on earlier Qwen generations by improving multilingual understanding, reasoning ability, and efficiency, while also introducing native multimodal capabilities that allow the model to work with both language and visual inputs. Architecturally, the system leverages modern large-scale training techniques and mixture-of-experts style efficiency so that very large parameter counts can be used while keeping inference practical. -
22
AingDesk
AI assistant that supports knowledge bases, model APIs
AingDesk is an open-source desktop and server-based AI assistant platform designed to provide a user-friendly environment for interacting with language models and building AI-powered tools. The software enables users to run local AI models or connect to external model APIs through a unified interface. One of its primary goals is to simplify the process of building knowledge-based assistants by allowing users to create local knowledge bases that the AI can search and analyze. The system supports additional features such as web search, intelligent agent workflows, and multi-model conversations within a single session. AingDesk can be deployed locally on personal machines or installed as a server using containerized environments. Its design emphasizes accessibility, making it suitable for both beginners and experienced developers who want to experiment with AI tools. -
23
Claude Code SDK Python
Python SDK for Claude Agent
claude-code-sdk-python is the Python SDK for Claude Code, Anthropic’s agentic coding system. It provides abstractions to easily query Claude Code (with streaming support) and conduct interactive sessions. The SDK includes core client classes, asynchronous query functions, and support for custom tools and hooks within Claude sessions. It is designed to integrate with local Python workflows and allow developers to embed Claude Code capabilities directly in their applications or scripts. The repo is MIT-licensed and includes documentation and installation instructions (requires Python 3.10+, Node installation of Claude Code). Example usage shows how to stream responses, parse structured message blocks, or create persistent client sessions. -
24
OpenAI.fm
Code for openai.fm, a demo for the OpenAI Speech API
OpenAI.fm is an official interactive demo application built to showcase the OpenAI Speech API and its advanced text-to-speech capabilities, providing developers and creators with a hands-on web interface to convert text into high-quality, customizable audio using state-of-the-art TTS models. Developed using Next.js and the OpenAI Speech API, this demo illustrates how the latest neural voice models can produce natural, expressive speech with adjustable styles and voices, highlighting features like emotional range, tone, and real-time playback. Users can experiment with different input text and voice options directly in their browser, gaining a sense of how high-fidelity AI audio can be integrated into applications ranging from podcasts and narration to accessibility tools and interactive agents. Although the web demo is free to explore, production use of the underlying API requires an OpenAI API key and may incur costs based on usage. -
25
Rogue
AI Agent Evaluator & Red Team Platform
Rogue is an open-source evaluation and red-team framework designed to test the reliability, safety, and policy compliance of AI agents. The platform automatically interacts with an AI agent by generating dynamic scenarios and multi-turn conversations that simulate real-world interactions. Instead of relying solely on static test scripts, Rogue uses an agent-as-a-judge architecture where one agent probes another agent to detect failures or unexpected behaviors. The system allows developers to define specific scenarios, expected outcomes, and business rules so that the framework can verify whether an agent behaves according to required policies. During testing, Rogue records conversations and produces detailed reports that explain whether the agent passed or failed each scenario. These reports include reasoning and evidence, helping developers understand why a particular failure occurred.
