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Showing 4841 open source projects for "can="
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Go From AI Idea to AI App FastAccess Gemini 3 and 200+ models. Build chatbots, agents, or custom models with built-in monitoring and scaling.
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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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Spring AI Alibaba Examples
Spring AI Alibaba examples for building and testing AI apps
...Each module focuses on a specific use case such as chat, image processing, audio handling, graph workflows, and retrieval-augmented generation. The examples highlight how to integrate AI models, manage prompts, handle memory, and build multi-model or multi-agent workflows. Developers can explore individual project folders for detailed instructions and implementation guidance. Spring AI Alibaba Examples also supports experimentation through playground modules and encourages contributions to expand real-world AI use cases and improve development practices. -
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DeepAudit
AI multi-agent platform for automated code security auditing system
...It also includes automated proof-of-concept validation using a sandboxed environment, allowing detected issues to be tested for real exploitability. DeepAudit integrates retrieval-augmented generation techniques to enhance contextual understanding and reduce false positives during analysis. Users can import projects and trigger a full audit workflow that includes risk identification, exploit generation, validation, and final report creation. -
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SMTP Tunnel Proxy
A high-speed covert tunnel that disguises TCP traffic as SMTP email
...The tool supports modern TLS encryption (STARTTLS) with HMAC-SHA256 authentication, per-user secrets, IP whitelisting, and multiplexed connections over a single tunnel. With a simple installer and systemd service setup, users can quickly deploy it on a Linux VPS as a tunneled access point, then connect from Windows, macOS, or Linux clients using auto-generated client packages. The project is useful for environments where standard VPNs or proxies are blocked, offering a combination of performance and stealth. -
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AskUI Vision Agent
Enable AI to control your desktop, mobile and HMI devices
AskUI’s Vision Agent is an automation framework that allows you—and AI agents—to control real desktops, mobile devices, and HMI systems by perceiving the UI and performing actions like clicking, typing, scrolling, and drag-and-drop. It is designed for multi-platform compatibility and supports multiple AI models so you can tailor perception and decision-making to your workload. The repository presents a feature overview, sample media, and frequent release notes, which show ongoing improvements such as CORS checks and other operational tweaks. The broader AskUI documentation covers the Python Vision Agent along with suite services and inference APIs, indicating a productized ecosystem rather than a single library. ... -
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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cheat.sh
The only cheat sheet you need
cheat.sh is a compact, network-accessible cheat-sheet service that serves concise examples and usage notes for hundreds of shell commands, programming languages, and tools via a simple HTTP interface. You can query it from the terminal (for example curl cht.sh/rsync or curl cheat.sh/ls) or browse the web front page; it also supports a shorthand hostname (cht.sh) and provides both online and standalone/local installation modes. The repository contains the server and client code, instructions to run a local standalone instance (including Python virtualenv setup), and tooling to fetch or maintain the upstream cheat-sheet data; installation documentation explains disk-space needs and dependency setup for offline use. ... -
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Synthetic Data Vault (SDV)
Synthetic Data Generation for tabular, relational and time series data
The Synthetic Data Vault (SDV) is a Synthetic Data Generation ecosystem of libraries that allows users to easily learn single-table, multi-table and timeseries datasets to later on generate new Synthetic Data that has the same format and statistical properties as the original dataset. Synthetic data can then be used to supplement, augment and in some cases replace real data when training Machine Learning models. Additionally, it enables the testing of Machine Learning or other data dependent software systems without the risk of exposure that comes with data disclosure. Underneath the hood it uses several probabilistic graphical modeling and deep learning based techniques. ... -
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OpenFreeMap
Free and open-source map hosting solution with custom styles
OpenFreeMap is a free and open-source map hosting platform that allows developers to display customizable maps in websites and applications without relying on commercial providers. It uses OpenStreetMap data and modern vector tile technologies to deliver high-quality maps with flexible styling options. The platform can be self-hosted or accessed through a public instance, offering full control or convenience depending on user needs. It removes common barriers such as API keys, usage limits, and tracking mechanisms, emphasizing privacy and accessibility. The system is designed for production use, with automated tile generation, load balancing, and scalable hosting architecture. ... -
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LLM Telegram Bot
A Telegram bot for Large Language Models
LLM Telegram Bot is a self-hosted Telegram chatbot that connects messaging interactions with large language models, typically powered by Ollama or similar backends. The project is designed to provide a customizable AI assistant that can operate within Telegram conversations, supporting dynamic responses based on user input and configurable parameters. It includes features such as conversation memory, allowing the bot to maintain context across multiple messages and provide more coherent responses. The system supports multiple modes or personas, enabling users to switch between different conversational styles or use cases. ... -
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ShoppingAgent
Custom Chinese chatbot with Seq2Seq, GPT, and agent features
...In addition to core chatbot functionality, the project introduces agent-based capabilities, enabling practical use cases like automated workflows and task-oriented assistants. It also includes support for small language models and local training scripts, making it accessible for users with limited computational resources. ShoppingAgent can be applied to scenarios such as customer service, question answering, and casual conversation. -
Streamline Azure Security with Palo Alto Networks VM-SeriesImprove your security posture and reduce incident response time. Use the VM-Series to natively analyze Azure traffic and dynamically drive policy updates based on workload changes.
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MathModelAgent
An Agent Designed for Mathematical Modeling
...The project uses a multi-agent architecture where different specialized agents handle tasks such as problem interpretation, modeling design, programming implementation, and paper writing. Through integration with multiple large language models, the system can coordinate these components to generate structured modeling solutions and formatted research papers suitable for submission. The platform also includes a code execution environment that allows generated programs to be tested, corrected, and refined during the modeling workflow. -
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Karpathy
An agentic Machine Learning Engineer
karpathy is an experimental agentic machine learning engineer framework designed to automate many aspects of the ML development workflow. The project sets up a sandboxed environment where an AI agent can access datasets, run experiments, and generate machine learning artifacts through a web interface. Its startup script automatically prepares the environment by creating a sandbox directory, installing key ML libraries, and launching the agent interface. The system is tightly integrated with the Claude Scientific Skills ecosystem, enabling the agent to leverage specialized scientific and machine learning tools. ... -
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claude-code-best-practice
Practice made claude perfect
...Rather than being a traditional software library, the project functions as a living playbook that demonstrates how to compose skills, agents, memory files, and rules into maintainable AI-assisted coding systems. The repository emphasizes modularity and progressive disclosure, encouraging developers to build reusable components that can be invoked on demand. It also explores operational concerns such as permissions management, sandboxing, debugging workflows, and context optimization. By combining conceptual guidance with concrete examples and configuration patterns, the project helps teams move from experimental AI usage toward more production-ready agent orchestration. -
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Flask RESTX
Fully featured framework for fast, easy and documented API development
Fork of Flask-RESTPlus fully featured framework for fast, easy and documented API development with Flask. Flask-RESTX is an extension for Flask that adds support for quickly building REST APIs. Flask-RESTX encourages best practices with minimal setup. If you are familiar with Flask, Flask-RESTX should be easy to pick up. It provides a coherent collection of decorators and tools to describe your API and expose its documentation properly using Swagger. With Flask-RESTX, you only import the api... -
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virtualenv
Virtual Python environment builder
...The basic problem being addressed is one of dependencies and versions, and indirectly permissions. Imagine you have an application that needs version 1 of LibFoo, but another application requires version 2. How can you use both these libraries? If you install everything into your host python (e.g. python3.8) it’s easy to end up in a situation where two packages have conflicting requirements. -
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brython
Implementation of Python 3 running in the browser
...It includes libraries to interact with DOM elements and events, and with existing Javascript libraries such as jQuery, D3, Highcharts, Raphael etc. It supports the latest specs of HTML5/CSS3, and can use CSS Frameworks like Bootstrap3, LESS, SASS etc. The most simple way to get started, without anything to install, is to use the distribution available online through jsDelivr. -
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UNO
A Universal Customization Method for Single and Multi Conditioning
...UNO likely offers tools to fine-tune or condition generation models so that they can incorporate novel subjects, enabling users to produce custom outputs beyond standard training distribution. -
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NVIDIA NeMo Framework
Scalable generative AI framework built for researchers and developers
...It provides collections of domain-specific modules and reference implementations that make it easier to pre-train, fine-tune, and deploy very large models on multi-GPU and multi-node infrastructure. NeMo 2.0 introduces a Python-based configuration system, replacing YAML with more flexible, programmable configs that can be versioned and composed for different experiments. The framework builds on PyTorch Lightning–style modular abstractions, so training scripts are composed from reusable components for data loading, models, optimizers, and schedulers, which simplifies experimentation and adaptation. NeMo is designed to scale: with tools like NeMo-Run, users can orchestrate large-scale experiments across thousands of GPUs. -
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LLMStack
No-code multi-agent framework to build LLM Agents, workflows
LLMStack is a no-code platform for building generative AI agents, workflows and chatbots, connecting them to your data and business processes. Build tailor-made generative AI agents, applications and chatbots that cater to your unique needs by chaining multiple LLMs. Seamlessly integrate your own data, internal tools and GPT-powered models without any coding experience using LLMStack's no-code builder. Trigger your AI chains from Slack or Discord. Deploy to the cloud or on-premise. -
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marqo
Tensor search for humans
A tensor-based search and analytics engine that seamlessly integrates with your applications, websites, and workflows. Marqo is a versatile and robust search and analytics engine that can be integrated into any website or application. Due to horizontal scalability, Marqo provides lightning-fast query times, even with millions of documents. Marqo helps you configure deep-learning models like CLIP to pull semantic meaning from images. It can seamlessly handle image-to-image, image-to-text and text-to-image search and analytics. ... -
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Douyin TikTok Download API
Douyin TikTok Download API
...This project is based on PyWebIO , FastAPI , HTTPX , a fast and asynchronous Douyin / TikTok data crawling tool, and realizes online batch parsing and downloading of watermark-free videos or atlases through the web, data crawling API, and iOS shortcut instructions for watermark-free download and other functions. You can deploy or transform this project yourself to achieve more functions, or you can directly call scraper.py in your project or install an existing pip package as a parsing library to easily crawl data, etc. Support input Douyin|TikTokuser homepage to crawl the author [homepage video data (remove watermark link, liked video list (permission must be public), video comment data, background music video list data, etc...). -
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Zappa - Serverless Python
Serverless Python
Zappa makes it super easy to build and deploy server-less, event-driven Python applications (including, but not limited to, WSGI web apps) on AWS Lambda + API Gateway. Think of it as "serverless" web hosting for your Python apps. That means infinite scaling, zero downtime, zero maintenance - and at a fraction of the cost of your current deployments! With a traditional HTTP server, the server is online 24/7, processing requests one by one as they come in. If the queue of incoming requests... -
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tika-python
Python binding to the Apache Tika™ REST services
...To use this library, you need to have Java 7+ installed on your system as tika-python starts up the Tika REST server in the background. To get this working in a disconnected environment, download a tika server file (both tika-server.jar and tika-server.jar.md5, which can be found here) and set the TIKA_SERVER_JAR environment variable to TIKA_SERVER_JAR="file:////tika-server.jar" which successfully tells python-tika to "download" this file and move it to /tmp/tika-server.jar and run as a background process. This is the only way to run python-tika without internet access. Without this set, the default is to check the tika version and pull latest every time from Apache. -
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txtai
Build AI-powered semantic search applications
...Backed by state-of-the-art machine learning models, data is transformed into vector representations for search (also known as embeddings). Innovation is happening at a rapid pace, models can understand concepts in documents, audio, images and more. Machine-learning pipelines to run extractive question-answering, zero-shot labeling, transcription, translation, summarization and text extraction. Cloud-native architecture that scales out with container orchestration systems (e.g. Kubernetes). Applications range from similarity search to complex NLP-driven data extractions to generate structured databases. ... -
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Mackup
Keep your application settings in sync
...Restores your configuration on any fresh install in one command line. If you have Dropbox installed and want to use it to save your config files, that's super easy. On macOS, if you want an easy install, you can install Homebrew and initialize it with it. If not running macOS, or you don't like Homebrew, you can use pip. On Ubuntu, pip will install to the current user's home directory rather than system-wide. Because of this, when installing pip on Ubuntu you will need to run pip install with the --system flag as well (on other platforms this is not needed). ... -
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Luigi
Python module that helps you build complex pipelines of batch jobs
...The purpose of Luigi is to address all the plumbing typically associated with long-running batch processes. You want to chain many tasks, automate them, and failures will happen. These tasks can be anything, but are typically long running things like Hadoop jobs, dumping data to/from databases, running machine learning algorithms, or anything else. You can build pretty much any task you want, but Luigi also comes with a toolbox of several common task templates that you use. It includes support for running Python mapreduce jobs in Hadoop, as well as Hive, and Pig, jobs. ...
