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3 repositorios

Awesome GitHub RepositoriesContext Pre-loading

Injection of relevant background information into the prompt prior to query processing.

Distinct from On-Demand Context Loading: Distinct from on-demand loading: focuses on the proactive injection of context to ensure informed initial responses.

Explore 3 awesome GitHub repositories matching software engineering & architecture · Context Pre-loading. Refine with filters or upvote what's useful.

Awesome Context Pre-loading GitHub Repositories

Encuentra los mejores repositorios con IA.Buscaremos los repositorios que mejor coincidan usando IA.
  • microsoft/ai-agents-for-beginnersAvatar de microsoft

    microsoft/ai-agents-for-beginners

    67,369Ver en GitHub↗

    This project is a structured educational resource and technical guide for designing and implementing autonomous systems using large language models. It provides a comprehensive curriculum and code samples focused on agentic design patterns, autonomous development, and the creation of systems capable of planning and executing multi-step tasks. The resource details the implementation of agentic retrieval-augmented generation, where models autonomously plan and refine data searches. It covers a wide array of orchestrators and design patterns, including metacognitive reflection for self-correctin

    Injects relevant background information into the model before processing a query to ensure informed responses.

    Jupyter Notebookagentic-aiagentic-frameworkagentic-rag
    Ver en GitHub↗67,369
  • feast-dev/feastAvatar de feast-dev

    feast-dev/feast

    6,727Ver en GitHub↗

    Feast is an open-source feature store for machine learning that provides a central platform for defining, storing, and serving features across both training and inference workflows. It operates as a declarative system where feature definitions are written as code in Python files, synchronized to a central registry, and made available for low-latency online retrieval or point-in-time correct historical joins for training datasets. The project abstracts storage behind a pluggable architecture, allowing offline and online backends to be swapped without changing retrieval logic, and coordinates ma

    Pre-loads heavy resources like models and lookup tables at server startup to reduce per-request overhead.

    Pythonbig-datadata-engineeringdata-quality
    Ver en GitHub↗6,727
  • opencx-labs/copilotAvatar de opencx-labs

    opencx-labs/copilot

    5,113Ver en GitHub↗

    Copilot es una plataforma de soporte al cliente autohospedada que utiliza modelos de lenguaje grandes (LLM) y bases de conocimiento vectorizadas para automatizar la asistencia al usuario. El sistema consiste en un widget de chat de IA incrustable para integración en sitios web, un panel de gestión contenedorizado y una base de conocimiento de base de datos vectorial. La plataforma incluye un orquestador de API que procesa especificaciones de API estructuradas, permitiendo que los modelos de lenguaje interactúen con endpoints y operaciones externas. Gestiona contexto especializado para las respuestas indexando definiciones de API y documentación dentro de una base de datos vectorial. La infraestructura cubre la orquestación de servicios contenedorizados para servidores y trabajadores en segundo plano, procesamiento asíncrono basado en colas y una interfaz administrativa para monitorear las interacciones de los usuarios en tiempo real. El sistema también maneja migraciones de esquemas de bases de datos e indexación de conocimiento.

    Injects structured API definitions as context into the language model to enable automated interaction with external operations.

    TypeScriptai-copilotcopilotllm
    Ver en GitHub↗5,113
  1. Home
  2. Software Engineering & Architecture
  3. Project Context Managers
  4. On-Demand Context Loading
  5. Context Pre-loading

Explorar subetiquetas

  • API Specification ContextsDynamic injection of API definition data into language model prompts to enable tool use and endpoint interaction. **Distinct from Context Pre-loading:** Focuses specifically on API specifications as the context source, rather than general background information.
  • Model and Lookup Table Pre-LoadingLoads models or lookup tables once at server start so on-demand transforms pay only inference cost per request. **Distinct from Context Pre-loading:** Distinct from Context Pre-loading: focuses on loading ML models and lookup tables for feature computation, not prompt context injection.