Search Results for "plug"
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Showing 97 open source projects for "plug"
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Go from Code to Production URL in SecondsSkip the Kubernetes configs. Cloud Run handles HTTPS, scaling, and infrastructure automatically. Two million requests free per month.
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Our Free Plans just got better! | Auth0You asked, we delivered! Auth0 is excited to expand our Free and Paid plans to include more options so you can focus on building, deploying, and scaling applications without having to worry about your security. Auth0 now, thank yourself later.
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PentestAgent
AI agent framework for black-box security testing
...Users configure rules, policies, and environments, and the agent continuously probes for weaknesses, prioritizes findings, and generates contextual reports that help both technical and non-technical stakeholders understand risk exposure. Because it supports a range of plug-ins and external security tools, pentestagent can be adapted for web applications, network infrastructure, API surfaces, and even cloud environments, making it flexible for diverse security programs. -
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NoneBot
Asynchronous multi-platform robot framework written in Python
Use NB-CLI to quickly build your own robot. Plug-in development, modular management. Supports multiple platforms and multiple incident response methods. Asynchronous priority development to improve operational efficiency. Simple and clear dependency injection system, built-in dependency functions reduce user code. NoneBot2 is a modern, cross-platform, and extensible Python chatbot framework. -
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ChatGPT Academic
ChatGPT extension for scientific research work
ChatGPT extension for scientific research work, specially optimized academic paper polishing experience, supports custom shortcut buttons, supports custom function plug-ins, supports markdown table display, double display of Tex formulas, complete code display function, new local Python/C++/Go project tree Analysis function/Project source code self-translation ability, newly added PDF and Word document batch summary function/PDF paper full-text translation function. All buttons are dynamically generated by reading functional.py, you can add custom functions at will, and liberate the pasteboard. ... -
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FinRobot
An Open-Source AI Agent Platform for Financial Analysis using LLMs
...It provides developers and quants with structured modules to fetch market data, process time series, generate technical indicators, and construct features appropriate for machine learning models, while also supporting backtesting and evaluation metrics to measure strategy performance. Built with modularity in mind, FinRobot allows users to plug in custom models — from classical algorithms to deep learning architectures — and orchestrate components in pipelines that can run reproducibly across experiments. The framework also tends to include automation layers for deployment, enabling trained models to operate in live or simulated environments with scheduled re-training and risk controls in place. -
Custom VMs From 1 to 96 vCPUs With 99.95% UptimeLive migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
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Pixelle-Video
AI Fully Automated Short Video Engine
...It is built to support experimentation with generative video models, making it useful for research and creative applications. The system emphasizes modularity, allowing developers to plug in different models or processing steps depending on the use case. It can be used for tasks such as content generation, video editing, or visual storytelling. Overall, Pixelle-Video provides a flexible environment for building AI-powered video generation and processing workflows. -
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SageAttention
NeurIPS2025 Spotlight] Quantized Attention
...The system achieves this by using low-precision numerical formats such as INT4, FP8, or INT8 to represent key matrices within the attention computation. These optimizations allow models to perform matrix operations faster and consume less memory during inference. SageAttention is designed to function as a plug-and-play replacement for standard attention implementations, enabling developers to accelerate existing models without modifying their architecture. -
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xiaohongshu-mcp
MCP for xiaohongshu.com
xiaohongshu-mcp is a Model Context Protocol (MCP) server that equips AI assistants with first-class tools for working on Xiaohongshu (Little Red Book), focusing on day-to-day creator and operator workflows rather than generic browsing. The project centers on authenticated actions and data access that matter to content operations, such as checking login state, publishing or scheduling content, fetching recommendations and search results, reading post details, and acting on comments. It’s... -
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DeerFlow
Deep Research framework, combining language models with tools
DeerFlow is an open-source, community-driven “deep research” framework / multi-agent orchestration platform developed by ByteDance. It aims to combine the reasoning power of large language models (LLMs) with automated tool-use — such as web search, web crawling, Python execution, and data processing — to enable complex, end-to-end research workflows. Instead of a monolithic AI assistant, DeerFlow defines multiple specialized agents (e.g. “planner,” “searcher,” “coder,” “report generator”)... -
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ONNX Runtime
ONNX Runtime: cross-platform, high performance ML inferencing
ONNX Runtime is a cross-platform inference and training machine-learning accelerator. ONNX Runtime inference can enable faster customer experiences and lower costs, supporting models from deep learning frameworks such as PyTorch and TensorFlow/Keras as well as classical machine learning libraries such as scikit-learn, LightGBM, XGBoost, etc. ONNX Runtime is compatible with different hardware, drivers, and operating systems, and provides optimal performance by leveraging hardware accelerators... -
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.
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OmniRoute
OmniRoute is an AI gateway for multi-provider LLM
...It focuses on providing a flexible abstraction layer where developers can define routing logic that dynamically directs traffic based on conditions, context, or predefined rules. The project emphasizes modularity and extensibility, allowing users to plug in different services or handlers without tightly coupling components. It is particularly useful in distributed systems where requests need to be intelligently routed between APIs, microservices, or processing pipelines. OmniRoute aims to reduce boilerplate by centralizing routing logic and providing reusable patterns for managing complex flows. ... -
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EasyOCR
Ready-to-use OCR with 80+ supported languages
...EasyOCR will choose the latest model by default but you can also specify which model to use. Model weights for the chosen language will be automatically downloaded or you can download them manually from the model hub. The idea is to be able to plug-in any state-of-the-art model into EasyOCR. There are a lot of geniuses trying to make better detection/recognition models, but we are not trying to be geniuses here. We just want to make their works quickly accessible to the public. -
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Vision Transformer Pytorch
Implementation of Vision Transformer, a simple way to achieve SOTA
...It’s widely used as an educational reference for people learning transformers in vision and as a lightweight baseline for research prototypes. The project encourages experimentation—swap optimizers, change augmentations, or plug the transformer backbone into downstream tasks. -
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Evals
Evals is a framework for evaluating LLMs and LLM systems
...The framework supports templated YAML eval definitions, solver-based evaluations, custom metrics, and composition of multi-step evaluations. It includes utilities and APIs to plug in completion functions, manage prompts, wrap retries or error handling, and register new evaluation types. It also maintains a growing registry of standard benchmarks or “evals” that users can reuse (for example, tasks measuring reasoning, factual accuracy, or chain-of-thought capabilities). The design is modular so you can extend or compose new evals, integrate with your own model APIs, and capture rich metadata about each run (prompt, responses, metrics). -
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Code-Mode
Plug-and-play library to enable agents to call MCP and UTCP tools
Code-Mode is a plug-and-play library that lets AI agents call tools by executing TypeScript (or via a Python wrapper) instead of making many individual function calls. Its core philosophy is that language models are very good at writing code, so rather than exposing hundreds of separate tool endpoints, you give the model a single “code execution” tool that has access to your full toolkit through code. -
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BEIR
A Heterogeneous Benchmark for Information Retrieval
BEIR is a benchmark framework for evaluating information retrieval models across various datasets and tasks, including document ranking and question answering. -
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DeepSeek V2
Strong, Economical, and Efficient Mixture-of-Experts Language Model
...Because DeepSeek is pushing open-weight competition, this V2 iteration is meant to solidify its position in benchmark rankings and in developer adoption. The code in the repository may include description files, support for tool use or plug-in architectures, and artifacts showing fine-tuning or prompt templates. -
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Llama Coder
Open source Claude Artifacts – built with Llama 3.1 405B
...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. -
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Open ChatGPT Atlas
Open Source and Free Alternative to ChatGPT Atlas
...The project includes utilities for session management to preserve context across interactions, structured interfaces for streaming responses, and integration layers that let you plug in third-party tools and services. It often forms the basis for research, prototyping, or production systems where the default ChatGPT interface isn’t flexible enough. -
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ChatGPT Clone
ChatGPT interface with better UI
ChatGPT Clone demonstrates a ChatGPT-style conversational interface wired to large-language-model backends, packaged so developers can self-host and extend. The goal is to replicate the core chat UX—message history, streaming tokens, code blocks, and system prompts—while letting you plug in different provider APIs or local models. It showcases a clean separation between the web client and the message orchestration layer so you can experiment with prompts, roles, and memory strategies. The project is useful for prototyping assistants, documentation bots, and internal developer tools without committing to a specific vendor or UI framework. ... -
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GenericAgent
Self-evolving autonomous agent framework
...It integrates with modern language models to provide planning, execution, and iterative reasoning capabilities, making it suitable for complex workflows. The project also focuses on extensibility, allowing developers to plug in custom tools or APIs and tailor agent behavior to specific use cases. By abstracting common agent patterns, it reduces the overhead of building agent systems from scratch. Overall, GenericAgent provides a foundation for scalable and reusable AI agent development. -
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AGI
The first distributed AGI system
...The project typically explores concepts such as agent orchestration, memory systems, task decomposition, and decision-making loops, enabling the development of more generalized and adaptive AI behaviors. It is designed to be extensible, allowing developers to plug in different models, tools, and data sources to enhance agent performance. The framework encourages experimentation with AGI-like architectures, making it useful for researchers and developers interested in advancing beyond narrow AI applications. -
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Trail of Bits Skills Marketplace
Trail of Bits Claude Code skills for security research, vulnerability
Trail of Bits Skills Marketplace is a specialized Claude Code skills marketplace built by the security research firm Trail of Bits that focuses on enhancing AI-assisted workflows for vulnerability discovery, testing, and secure development. The repository groups a set of plug-in skills tailored toward static analysis, code auditing, secure defaults detection, and other practices that matter in software security. Users can easily add the marketplace to a Claude Code environment, browse available plugins, and install specific skills for tasks like automatic Semgrep rule creation, entry-point analysis in smart contracts, or insecure defaults detection. ... -
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CopilotKit
Build in-app AI chatbots, and AI-powered Textareas
A bridge between your copilot and your app. A programmable 2-way bridge between your copilot, and your application state (client & cloud). Supports 3rd party integrations (e.g. Salesforce, Zendesk, etc.). Plug-and-play, fully customizable, copilot infrastructure. Build in-app AI chatbots that can "see" the current app state + take action inside your app. The AI chatbot can talk to your app frontend & backend, and to 3rd party services (Salesforce, Dropbox, etc.) via plugins. Autocompletion + AI editing + generate from scratch. Indexed on your users' content. -
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memsearch
A Markdown-first memory system, a standalone library for any AI agent
...It integrates with vector databases like Milvus, enabling scalable storage and retrieval of large datasets. Memsearch is designed to be agent-friendly, making it easy to plug into existing AI workflows and enhance reasoning capabilities. Its markdown-first approach ensures transparency and portability of stored knowledge. Overall, it provides a robust foundation for building AI systems with persistent and intelligent memory. -
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Bytebot
Bytebot is an AI desktop agent that automates computer tasks
...Bytebot can be embedded into editors, terminals, or CI/CD pipelines to provide contextual recommendations, highlight quality issues, and propose fixes based on understanding of code and project context. The framework is often extensible, allowing teams to define custom commands, workflows, or plug-ins that connect to internal APIs, coding standards, or proprietary repositories.
