Search Results for "interface" - Page 18
Sort By:
Showing 987 open source projects for "interface"
View related business solutions-
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
-
Auth0 B2B Essentials: SSO, MFA, and RBAC Built InAuth0's B2B Essentials plan gives you everything you need to ship secure multi-tenant apps. Unlimited orgs, enterprise SSO, RBAC, audit log streaming, and higher auth and API limits included. Add on M2M tokens, enterprise MFA, or additional SSO connections as you scale.
-
1
Cognita
Open source RAG framework for building scalable modular AI apps
...Cognita provides reusable components such as parsers, data loaders, embedders, retrievers, and query controllers, allowing teams to customize each stage of the RAG pipeline independently. It includes both a backend service and a frontend interface, enabling users to upload documents, experiment with configurations, and perform question-answering tasks interactively. Cognita supports incremental indexing, meaning it processes only new or updated data to reduce computational overhead and improve efficiency. -
2
Office Agents
Agent plugins for Microsoft Office but BYOK for any model and provider
...It enables users to interact with large language models inside tools like Excel, Word, and PowerPoint, allowing real-time automation, content generation, and data manipulation within familiar productivity environments. The system is built as a monorepo with multiple packages, including a core SDK for agent runtime, a React-based chat interface, and specialized add-ins tailored to each Office application. It supports a bring-your-own-key model, allowing users to connect to a wide range of AI providers, including OpenAI, Anthropic, and other compatible APIs. The framework also includes advanced capabilities such as a sandboxed execution environment, virtual file systems, and extensible skill modules that expand agent functionality. -
3
llama.vim
Vim plugin for LLM-assisted code/text completion
...By integrating AI functionality directly into Vim workflows, the tool enables developers to write and edit code more efficiently while staying within a familiar development interface. -
4
OneFileLLM
Specify a github or local repo, github pull request
...The concept behind the project is to eliminate the complexity normally associated with deploying AI systems, which often require multiple dependencies, frameworks, and configuration steps. Instead, the entire runtime environment, model interface, and application logic are bundled together into a single executable artifact. This design allows developers to share AI tools in a format that can be easily distributed and executed across different machines without complicated installation procedures. Such packaging strategies help make AI software easier to use in educational settings, demonstrations, and lightweight deployments. -
$300 Free Credits for Your Google Cloud ProjectsLaunch your next project with $300 in free Google Cloud credits—no strings attached. Test, build, and deploy without risk. Use your credits across the entire Google Cloud platform to find what works best for your needs. After your credits are used, continue with always-free tier services. Only pay when you're ready to scale. Sign up in minutes and start exploring.
-
5
Casibase
Open-source enterprise-level AI knowledge base and MCP
...The project combines knowledge management, messaging, and forum features with large language model integration to create an interactive platform for storing and querying domain-specific knowledge. Built with a separated frontend and backend architecture, Casibase provides a web-based administrative interface and supports high concurrency for enterprise environments. The platform integrates embedding techniques and prompt engineering to enable semantic knowledge retrieval and conversational interactions with stored data. It also supports integration with existing systems through database synchronization, allowing organizations to migrate data into the platform without major infrastructure changes. -
6
MemOS
AI memory OS for LLM and Agent systems
MemOS is an experimental operating system and runtime built around the concept of memory-centric computing, where memory objects are first-class citizens and program execution is organized around efficient, persistent memory access rather than traditional process and file system boundaries. The project explores rethinking system abstractions by tightly coupling computation with memory objects so that programs can operate on large datasets without expensive serialization or context switching.... -
7
Google Workspace CLI
Command-line tool for Drive, Gmail, Calendar, Sheets, Docs, Chat, etc.
Google Workspace CLI (gws) is a command-line tool designed to interact with Google Workspace services such as Drive, Gmail, Calendar, Sheets, and more from a single interface. It dynamically generates its command structure using Google’s Discovery Service, allowing it to automatically support new API endpoints as they become available. The tool eliminates the need for manual REST API calls by providing structured commands and built-in help for each resource and method. It outputs structured JSON responses, making it easy for developers, scripts, and AI agents to process results programmatically. ... -
8
LOTUS
AI-Powered Data Processing: Use LOTUS to process all of your datasets
...The system provides a declarative programming model that allows developers to express complex AI data operations using high-level commands rather than manually orchestrating model calls. It offers a Python interface with a Pandas-like API, making it familiar for data scientists and engineers already working with data analysis libraries. The core concept of the framework is the use of semantic operators, which extend traditional relational database operations to support reasoning over text and other unstructured data. These operators allow tasks such as semantic filtering, ranking, clustering, and summarization to be expressed directly within data processing pipelines. ... -
9
Chatbot UI
AI chat for any model
Chatbot UI is an open-source, full-featured chat interface for AI models that aims to lower the barrier for anyone wanting to run their own AI-powered chatbot — whether using remote LLM APIs or local/self-hosted models. It bundles a modern frontend (Next.js + TypeScript + Tailwind) with a backend (Supabase by default) for persistent storage of chats, history, and user settings, replacing earlier local-storage-only approaches. -
Stop Cyber Threats with VM-Series Next-Gen Firewall on AzureGain integrated visibility across all traffic in a single pass. Deploy Palo Alto Networks VM-Series to determine application identity and content while automating security policy updates via rich APIs.
-
10
FastRTC
The python library for real-time communication
FastRTC is a Python library designed to simplify real-time communication (RTC), especially for audio and video streaming applications. It abstracts away much of the complexity that typically comes with implementing WebRTC by providing a simple interface — e.g. a Stream class — that can be mounted within a web backend (for example a FastAPI application). This makes it particularly well suited for building real-time voice (or video) interfaces for applications such as AI assistants, live chat, or collaborative audio/video tools. FastRTC also integrates nicely with UI frameworks (e.g. via a web demo using Gradio), so developers can rapidly prototype and deploy real-time streaming applications without deep knowledge of low-level WebRTC internals. ... -
11
Rubix ML
A high-level machine learning and deep learning library for PHP
...We provide tools for the entire machine learning life cycle from ETL to training, cross-validation, and production with over 40 supervised and unsupervised learning algorithms. In addition, we provide tutorials and other educational content to help you get started using ML in your projects. Our intuitive interface is quick to grasp while hiding alot of power and complexity. Write less code and iterate faster leaving the hard stuff to us. Rubix ML utilizes a versatile modular architecture that is defined by a few key abstractions and their types and interfaces. Train models in a fraction of the time by installing the optional Tensor extension powered by C. ... -
12
VideoChat
Real-time voice interactive digital human
...It supports both pure end-to-end voice solutions based on multimodal large language models (GLM-4-Voice feeding directly into talking-head generation) and a more traditional cascaded pipeline using ASR → LLM → TTS → talking head. It is built as a Gradio Python demo, exposing a web interface where users can talk to an animated avatar that lip-syncs to synthesized speech while responding intelligently. The system is customizable: you can define your own avatar appearance and voice, and it supports voice cloning so you can generate a new voice from a short 3–10 second reference sample. The tech stack integrates FunASR for speech recognition, Qwen for language understanding, multiple TTS engines like GPT-SoVITS, CosyVoice, or edge-tts, and MuseTalk for talking-head generation. -
13
MCP Server Langfuse
Model Context Protocol (MCP) Server for Langfuse Prompt Management
The Langfuse MCP Server is a Model Context Protocol server that allows users to access and manage Langfuse prompts through a standardized interface. It integrates with LLM Agent systems, enabling seamless interaction with Langfuse's prompt management capabilities. -
14
ToolUniverse
Democratizing AI scientists with ToolUniverse
...Instead of requiring custom pipelines or fine-tuning, ToolUniverse wraps around existing models and enables them to reason, experiment, and iterate on complex workflows such as drug discovery, data analysis, and hypothesis testing. The platform abstracts tool usage behind a consistent interface, allowing AI agents to compose multi-step workflows, refine tool definitions automatically, and even generate new tools from natural language descriptions. -
15
DeepAnalyze
Autonomous LLM agent for end-to-end data science workflows
...It integrates execution-based reasoning by generating and running code as part of its analysis process, allowing it to iteratively refine results and produce more accurate outputs. DeepAnalyze provides multiple interaction interfaces, including a web-based UI, a command-line interface, and a Jupyter-style notebook environment for interactive workflows. -
16
openv0
AI tool for generating modular UI components with live previews
openv0 is a generative UI component framework designed to help developers create interface elements using AI-assisted workflows. It enables users to generate, iterate, and refine UI components with a live preview system, making it easier to visualize results during development. openv0 is built around a modular architecture, allowing different parts of the generation process to be extended or replaced through plugins. -
17
WhatsApp MCP Server
WhatsApp MCP server enabling AI access to chats and messaging
whatsapp-mcp is an open source Model Context Protocol (MCP) server that enables AI agents to interact directly with a user’s WhatsApp account through a structured interface. It acts as a bridge between WhatsApp and large language models, allowing controlled access to messages, chats, and contacts. whatsapp-mcp is composed of two main components: a Go-based bridge that connects to the WhatsApp Web API and stores data locally, and a Python-based MCP server that exposes tools for AI interaction. All message data is stored in a local SQLite database and is only accessed when explicitly requested through defined tools, giving users control over how their data is used. ... -
18
ChatJS
Production-ready AI chat. Start here and make it your own
...Its stack is centered on modern TypeScript web development, using technologies such as Next.js, AI SDK tooling, PostgreSQL, Redis, and type-safe configuration patterns. The repository highlights access to more than 120 models through a unified interface, covering providers such as Claude, GPT, Gemini, and Grok. It also supports practical product features like attachments, resumable streams, branching conversations, sharing, web search, image generation, code execution, and MCP support. -
19
Paddler
Open-source LLM load balancer and serving platform for hosting LLMs
...Paddler also includes tools for monitoring, request buffering, and autoscaling integration so that deployments can adapt dynamically to changing workloads. A built-in administrative interface allows developers and operations teams to manage models, observe system performance, and test inference endpoints. -
20
Mysti
AI coding dream team of agents for VS Code
Mysti is a VS Code extension that provides a unified interface for AI coding assistants and agent workflows, with a strong emphasis on multi-agent collaboration. Instead of replacing the tools developers already use, it integrates with popular CLI-based coding assistants and routes work through a single, consistent UI inside the editor. The experience is organized around “personas” that change how the assistant approaches a task, such as architecture, debugging, security review, performance tuning, or refactoring, which helps structure the AI’s behavior for different goals. ... -
21
Docspell
Assist in organizing your piles of documents
Docspell is a personal document organizer. Or sometimes called a "Document Management System" (DMS). You'll need a scanner to convert your papers into files. Docspell can then assist in organizing the resulting mess. It can unify your files from scanners, emails, and other sources. It is targeted for home use, i.e. families, households, and also for smaller groups/companies. You can associate tags, set correspondent,s and lots of other predefined and custom metadata. If your documents are... -
22
Every Code
Local AI coding agent CLI with multi-agent orchestration tools
Every Code (often referred to simply as Code) is a fast, local AI-powered coding agent designed to run directly in the terminal environment. It is a community-driven fork of the Codex CLI, with a strong emphasis on improving real-world developer ergonomics and workflows. Every Code enhances the traditional coding assistant model by introducing multi-agent orchestration, allowing multiple AI agents to collaborate, compare solutions, and refine outputs in parallel. It supports integration with... -
23
The Arcade Learning Environment
The Arcade Learning Environment (ALE) -- a platform for AI research
Arcade Learning Environment (ALE) is a widely used open-source framework that wraps hundreds of Atari 2600 games via an emulator and presents them as RL environments for AI agents. It decouples the game/emulation aspects from the agent interface, providing a clean API (C++, Python, Gymnasium) so researchers can focus on agent design rather than game plumbing. This environment suite has been central to many RL breakthroughs, including value-based agents, deep Q-nets, and general-agent benchmarking, because the Atari games span many genres and present diverse learning challenges (pixels, actions, delayed rewards). ... -
24
iFlow CLI
iFlow cli is a comprehensive command-line intelligence
...It analyzes repositories, interprets developer intent, and executes tasks ranging from simple file manipulation to complex development operations, all within a unified interface. The tool emphasizes seamless integration into existing workflows, allowing developers to interact with AI without leaving their terminal environment. It supports multiple models and configurable APIs, enabling flexibility in how intelligence is applied to tasks. The system is capable of automating repetitive processes, accelerating development cycles, and reducing manual effort in code analysis and execution. ... -
25
Expect
Let agents test your code in a real browser
Expect is a developer-focused utility designed to simplify validation, testing, and assertion workflows across software environments by providing a clean and expressive interface for defining expected outcomes. The project likely centers on improving readability and maintainability in testing scenarios, allowing developers to write expectations in a concise and human-readable format. It may support chaining conditions, enabling complex validation logic without introducing unnecessary verbosity. The design suggests a focus on productivity, reducing cognitive load when writing and reviewing tests or validation scripts. ...
