Search Results for "can"
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Showing 95 open source projects for "can"
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$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.
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Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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1
Ollama
Run models like Kimi-K2.5, GLM-5, DeepSeek, gpt-oss, Gemma, Qwen etc.
Ollama is an open-source platform that enables developers to run large language models locally on their own machines. It simplifies working with modern AI models by providing a unified interface to download, manage, and interact with them. Users can run models like Llama, Gemma, Qwen, and others directly from the command line or through APIs. Ollama also integrates with popular developer tools and AI agents, allowing seamless workflows across coding environments and applications. It supports REST APIs, Python, and JavaScript SDKs, making it easy to build AI-powered features into software projects. ... -
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Ninjabot
A fast cryptocurrency platform for trading bot in Go
...Currently, we only support Binance exchange. If you want to include support for other exchanges, you need to implement a new struct that implements the interface Exchange. You can check some examples in the exchange directory. You can create bots in telegram accessing BotFather. Telegram bot requires that your bot is running to control and get information about your account. -
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Gitleaks
Protect and discover secrets using Gitleaks
...In addition, Gitleaks can be implemented as a pre-commit hook directly in your repo or as a GitHub action using Gitleaks-Action. -
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PhotoPrism
AI-Powered Photos App for the Decentralized Web 🌈💎✨
PhotoPrism® is an AI-Powered Photos App for the Decentralized Web. It makes use of the latest technologies to tag and find pictures automatically without getting in your way. You can run it at home, on a private server, or in the cloud. Our mission is to provide the most user- and privacy-friendly solution to keep your pictures organized and accessible. That's why PhotoPrism was built from the ground up to run wherever you need it, without compromising freedom, privacy, or functionality. -
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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ZeroBot-Plugin
OneBot plugin based on ZeroBot
ZeroBot-Plugin is a Go-based plugin collection for the ZeroBot ecosystem and OneBot-compatible bot frameworks. It packages many bot capabilities into a ready-to-run project that can be used through release binaries, direct local execution, or custom compilation. The repository is aimed mainly at QQ and OneBot-style chatbot deployments, with plugins that can be enabled, modified, or extended by developers. It is designed for users who want a richer bot feature set without writing every plugin from scratch. The project supports a community-oriented workflow where plugins can evolve and new ideas can be tested in related playground repositories. ... -
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Katib
Automated Machine Learning on Kubernetes
Katib is a Kubernetes-native project for automated machine learning (AutoML). Katib supports Hyperparameter Tuning, Early Stopping and Neural Architecture Search. Katib is a project that is agnostic to machine learning (ML) frameworks. It can tune hyperparameters of applications written in any language of the users’ choice and natively supports many ML frameworks, such as TensorFlow, Apache MXNet, PyTorch, XGBoost, and others. Katib can perform training jobs using any Kubernetes Custom Resources with out-of-the-box support for Kubeflow Training Operator, Argo Workflows, Tekton Pipelines, and many more. -
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BotKube
An app that helps you monitor your Kubernetes cluster
...You can customize the objects and level of events you want to get from the Kubernetes cluster. You can turn on/off notifications simply by sending a message to @BotKube. BotKube can execute kubectl commands on Kubernetes cluster without giving access to Kubeconfig or underlying infrastructure. With BotKube you can debug your deployment, services or anything about your cluster right from your messaging window. -
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Pinchtab
High-performance browser automation bridge and orchestrator
...The tool emphasizes accessibility-first snapshots that dramatically reduce token usage compared to screenshot-based approaches, making it cost-effective for large-scale automation. It launches and manages its own Chrome instance while remaining framework-agnostic, so it can be used with any language or agent system. Pinchtab also supports persistent sessions, stealth automation, and both headless and headed operation modes. The project’s goal is to provide fast, cheap, and portable browser control infrastructure for modern AI workflows. -
9
td
Telegram client, in Go. (MTProto API)
Telegram MTProto API client in Go for users and bots. -
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xiaohongshu-mcp
MCP for xiaohongshu.com
...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 packaged so MCP-capable clients (e.g., Claude Desktop, Cursor) can discover its tools via schemas instead of prompt guesswork, which improves reliability and reduces brittle automation. The repo highlights a growing community and provides links to a hosted landing page, signaling that the server is intended for practical use beyond a proof of concept. By exposing typed resources and procedures, it enables repeatable, auditable automation in social workflows where UI changes are frequent. -
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kagent
Kubernetes native framework for building AI agents
...A major focus is tool integration via MCP: agents can connect to MCP servers for tool access, and kagent includes an MCP server with tools for common Kubernetes and platform engineering systems. -
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CyberStrikeAI
CyberStrikeAI is an AI-native security testing platform built in Go
CyberStrikeAI is an AI-native security testing platform built in Go that brings autonomous penetration testing, vulnerability discovery, and attack chain analysis into a unified interface. The platform integrates over 100 security tools out of the box and pairs them with an intelligent orchestration engine that can be directed via natural language or policy definitions, allowing users to automate reconnaissance, scanning, exploitation, and reporting without manual sequencing of tools. It supports role-based testing, letting teams define security roles with tailored tool access and prompts, and includes a skills system that encapsulates specialized testing strategies that the AI can incorporate into its planning. ... -
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GitHub Agentic Workflows
GitHub Agentic Workflows
GitHub Agentic Workflows is an experimental CLI extension and framework for the gh GitHub CLI that lets developers author automation driven by natural language specifications instead of hand-written code, compiling those descriptions into GitHub Actions workflows that run AI agents (like Copilot, Claude Code, or Codex) on schedule or in response to repository events. By writing intent in markdown files, a developer can quickly generate .yml Actions workflows that perform tasks such as summarizing issues, automating triage, generating reports, or maintaining documentation, all without manually crafting YAML logic from scratch. The system emphasizes safety and guardrails, running agents in sandboxed environments with minimal permissions by default, and using “safe outputs” to constrain what the workflow can write back into the repository. ... -
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LocalAI
The free, Open Source alternative to OpenAI, Claude and others
...It acts as a drop-in replacement for APIs such as OpenAI, enabling developers to build AI-powered applications without relying on external cloud services. The platform supports a wide range of model types, including text generation, image creation, speech processing, and embeddings. LocalAI can run on consumer-grade hardware and does not necessarily require a GPU, making it accessible for local development and private deployments. It integrates with multiple backends like llama.cpp, transformers, and diffusers to support different AI workloads. With its self-hosted architecture and OpenAI-compatible API, LocalAI enables developers to build secure, local-first AI applications. -
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Docker Agent
AI Agent Builder and Runtime by Docker Engineering
...The runtime supports multi-agent collaboration, allowing specialized agents to delegate tasks to each other and operate as coordinated systems rather than isolated units. It is provider-agnostic, meaning it can integrate with multiple AI model providers such as OpenAI, Anthropic, and local inference engines, helping avoid vendor lock-in. cagent also supports the Model Context Protocol, enabling seamless integration with external tools, APIs, and services. -
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PicoClaw
Ultra-Efficient AI Assistant in Go
...Inspired by earlier AI assistant projects like “nanobot,” it was refactored to emphasize resource efficiency while still supporting meaningful AI-driven interactions such as conversational workflows, planning tasks, and automation. PicoClaw can run on hardware costing as little as $10 and on resource-constrained environments like RISC-V or ARM boards, with cross-architecture portability achieved through a single self-contained binary. The project’s goals include broad platform support (including Linux, macOS, and multiple CPU architectures), rapid startup times that make the assistant feel responsive, and integration with popular messaging platforms via gateways or bots. -
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GitHub MCP Server
GitHub's official MCP Server
The GitHub MCP Server exposes GitHub as a Model Context Protocol server so AI assistants can safely act on repos, issues, pull requests, gists, and more through a consistent tool interface. It’s designed to run locally or remotely and then be attached to MCP-capable clients (for example, Copilot Chat) so an LLM can search code, open files, create branches, draft PRs, label or triage issues, and query metadata without hard-coding GitHub APIs. -
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Vearch
A distributed system for embedding-based vector retrieval
...Otherwise, you can easily customize your own image, video, or text feature extraction algorithm plugin. This GIF provides a clear demonstration of the project vearch usage and its internal structure. The use of vearch is mainly divided into three steps. Firstly, create DB and Space, then import your data, and finally, you can search on your own dataset. -
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openclaw-kapso-whatsapp
Give your OpenClaw AI agent a WhatsApp number
...Projects like this make it possible for OpenClaw users to automate tasks, interact with personal contacts, or provide AI-driven services without building a custom bot infrastructure from scratch. Because OpenClaw itself runs on the user’s own hardware and can access external services, this WhatsApp extension serves as a bridge between the AI agent and daily messaging workflows. -
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DS2API
A lightweight, high-performance full-stack middleware
...The project focuses on reverse engineering and structuring game data into usable endpoints. It allows access to in-game entities, player states, and events for analysis or modification. The API can be used for automation, experimentation, or extending gameplay experiences. It is particularly useful for modders and developers interested in game internals. The design emphasizes flexibility and extensibility. -
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AgentHub
GitHub is for humans. AgentHub is for agents
...The project functions as a lightweight infrastructure layer that combines a Git repository with a message-board-style communication system, allowing multiple agents to coordinate development tasks within the same workspace. Rather than focusing solely on human collaboration, the system is designed around an “agent-first” paradigm where AI agents can contribute code, discuss changes, and coordinate problem solving. The platform treats code repositories not just as storage for files but as active environments where agents can propose modifications, review changes, and exchange structured messages. This approach reflects emerging research in multi-agent software development where groups of AI systems collaborate on complex engineering problems. -
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PentAGI
Perform penetration testing tasks
...It leverages agent-based architecture and AI reasoning to chain together tools and strategies in a way that mimics experienced human testers. The project is built to be modular and extensible so researchers and red teams can customize behavior or integrate additional tools as needed. By focusing on autonomous decision-making in cybersecurity contexts, PentAGI represents part of the broader trend toward AI-assisted offensive security automation. -
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AxonHub
Use any SDK to call 100+ LLMs
...The system acts as a compatibility layer that allows developers to use the same SDK interface while routing requests to various AI services behind the scenes. Instead of rewriting code when switching providers such as OpenAI or Anthropic, developers can simply change configuration settings within the gateway. AxonHub translates requests from one provider’s API format into another, enabling seamless interoperability across different AI platforms. The system also provides infrastructure features such as request routing, failover mechanisms, load balancing, and cost management for AI applications. ... -
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agentsview
Local-first session intelligence and analytics for coding agents
...It tracks token usage, cost, models, projects, tools, and session behavior across different agents. Its web interface adds dashboards, heatmaps, full-text search, and live updates while sessions are active. It can also support team-oriented workflows through optional PostgreSQL sync and DuckDB mirroring. -
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Weaviate
Weaviate is a cloud-native, modular, real-time vector search engine
Weaviate in a nutshell: Weaviate is a vector search engine and vector database. Weaviate uses machine learning to vectorize and store data, and to find answers to natural language queries. With Weaviate you can also bring your custom ML models to production scale. Weaviate in detail: Weaviate is a low-latency vector search engine with out-of-the-box support for different media types (text, images, etc.). It offers Semantic Search, Question-Answer-Extraction, Classification, Customizable Models (PyTorch/TensorFlow/Keras), and more. Built from scratch in Go, Weaviate stores both objects and vectors, allowing for combining vector search with structured filtering with the fault-tolerance of a cloud-native database, all accessible through GraphQL, REST, and various language clients.