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2 dépôts

Awesome GitHub RepositoriesNatural Language Function Executions

Execution of backend functions triggered by the translation of natural language prompts into structured calls.

Distinct from Multi-Caller Function Executions: Focuses on the trigger mechanism (NL translation) rather than just the caller identity

Explore 2 awesome GitHub repositories matching development tools & productivity · Natural Language Function Executions. Refine with filters or upvote what's useful.

Awesome Natural Language Function Executions GitHub Repositories

Trouvez les meilleurs dépôts grâce à l'IA.Nous recherchons les dépôts les plus pertinents grâce à l'IA.
  • katanemo/planoAvatar de katanemo

    katanemo/plano

    5,120Voir sur GitHub↗

    Plano is an AI agent orchestrator and LLM gateway proxy that unifies access to multiple AI providers through a single interoperable interface. It functions as a model routing engine that decouples applications from specific vendors using semantic aliases, allowing traffic to be shifted between providers without modifying application code. The system distinguishes itself with intent-based agent routing, which directs prompts to specialized agents based on semantic analysis. It features an interceptor-based filter chain system that acts as guardrail middleware to enforce safety policies, rewrit

    Translates natural language prompts into structured calls to perform transactional operations via backend functions.

    Rustai-gatewayai-gateway-supportenvoy
    Voir sur GitHub↗5,120
  • ed-donner/agentsAvatar de ed-donner

    ed-donner/agents

    4,017Voir sur GitHub↗

    This project is an LLM autonomous agent framework and orchestration tool designed to build goal-driven agents that automate complex workflows. It functions as a system for converting high-level objectives into a series of autonomous actions and managing the coordination of multiple specialized agents to solve multi-step problems. The framework features a tool integration layer that parses structured model outputs into executable functions and external API calls. It utilizes a non-blocking execution pipeline to manage task orchestration through recursive loops and asynchronous event handling.

    Translates natural language intentions from model outputs into structured, executable function calls.

    Jupyter Notebook
    Voir sur GitHub↗4,017
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