Showing 3 open source projects for "no code ai design"

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  • Context for your AI agents Icon
    Context for your AI agents

    Crawl websites, sync to vector databases, and power RAG applications. Pre-built integrations for LLM pipelines and AI assistants.

    Build 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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  • 1
    Elixir Code Smells

    Elixir Code Smells

    Catalog of Elixir-specific code smells

    Elixir-Code-Smells is a research-driven catalog of code smells specific to the Elixir programming language. Unlike generic code smell lists, this project identifies issues emerging from Elixir’s functional, concurrent, and process-based nature. Initially compiled via grey literature (blogs, talks, forums), the catalog now includes 23 Elixir-specific smells plus 12 traditional smells adapted to Elixir.
    Downloads: 7 This Week
    Last Update:
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  • 2
    Elixir Koans

    Elixir Koans

    Elixir learning exercises

    ...The project is ideal for both complete beginners and developers transitioning from other languages who want to learn Elixir in a structured, exploratory way. Its design emphasizes discovery, experimentation, and reflection, making it a powerful tool for deepening understanding of Elixir’s unique paradigms.
    Downloads: 2 This Week
    Last Update:
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  • 3
    Swarm

    Swarm

    Easy clustering, registration, and distribution of worker processes

    ...It focuses on automatic distribution and rebalancing, so when nodes join or leave, Swarm can move work and hand off state to keep the system stable. The library offers a global name registry, conflict resolution for name ownership, and hooks for reacting to membership changes. Its design embraces OTP principles, using supervised processes and fault-tolerant messaging to keep the registry resilient under failures. Developers can co-locate Swarm with their existing supervision trees to scale workers horizontally without writing custom clustering code. Typical use cases include globally unique workers, sharded consumers, and presence-like coordination where node churn is expected. ...
    Downloads: 0 This Week
    Last Update:
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