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Context for your AI agentsBuild data pipelines that feed your AI models and agents without managing infrastructure. Crawl any website, transform content, and push directly to your preferred vector store. Use 10,000+ tools for RAG applications, AI assistants, and real-time knowledge bases. Monitor site changes, trigger workflows on new data, and keep your AIs fed with fresh, structured information. Cloud-native, API-first, and free to start until you need to scale.
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Kodus
AI code reviews, just like your senior dev would do
Kodus-AI is a framework for building, training, and deploying intelligent agents and models, especially focusing on practical AI workflows for businesses and automation. It provides a structured set of tools and abstractions that help teams design agent behaviors, orchestrate data pipelines, optimize inference, and integrate AI capabilities with applications or services. The platform often includes model management, scalable training workflows, and orchestration patterns that help teams move... -
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Cross Platform Node Guide
Improve front-end engineer workflow & standard, powered by TypeScript
...With 80+ WEB/IOS/Andriod stable users, the cumulative production project reached 240+. Feflow refers to the thinking of Pipeline and divides work into five steps: init, develop, build, test, deploy. And corresponding to five basic commands: init, dev, build, test, and deploy. In addition to serving basic development workflows and specifications, Feflow provides an easy-to-expand plug-in mechanism for creating a team-wide toolchain ecosystem. Feflow only provides a CLI and kernel. The CLI is responsible for interacting with the command line terminal.
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