April 2026
Intermediate
292 pages
7h
Spanish
Content preview from Bases de datos vectoriales (Spanish Edition)
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Capítulo 6. Creación de un sistema de generación aumentada por recuperación con SQLite VSS y Ollama
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En los capítulos anteriores, nos enfocamos en los componentes individuales de la búsqueda vectorial: crear incrustaciones y realizar consultas de similitud. Ahora es el momento de juntar todas estas piezas para crear un sistema funcional de generación aumentada por recuperación (RAG).
A diferencia de las aplicaciones web a escala de producción que dependen de clústeres distribuidos en la nube, nuestro objetivo aquí es construir un sistema RAG de alto rendimiento, privado y totalmente local que se ejecute en una sola computadora de escritorio. Usaremos SQLite VSS para nuestro motor de búsqueda y Ollama como nuestro «cerebro» LLM local.
Los sistemas RAG resuelven una limitación fundamental de los LLMs: su conocimiento se congela en el momento del entrenamiento, lo que impide el acceso a información privada o reciente. Al complementar los LLMs con un mecanismo de recuperación, creamos un sistema que responde preguntas usando conocimiento actualizado y específico del dominio.
Nuestro objetivo es crear un sistema de preguntas y respuestas que responda de forma inteligente a consultas sobre el contenido de Reddit. Cuando un usuario haga una pregunta, el sistema (1) buscará entre las publicaciones almacenadas de Reddit para encontrar la información más relevante, (2) recuperará ...
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