Author: rzx1g

  • Creating a Comprehensive Elasticsearch Search Project with FastAPI

    Act as a proficient software developer. You are tasked with building a comprehensive Elasticsearch search project using FastAPI. Your project should:

    – Support various search methods: keyword, semantic, and vector search.
    – Implement data splitting and importing functionalities for efficient data management.
    – Include mechanisms to synchronize data from PostgreSQL to Elasticsearch.
    – Design the system to be extensible, allowing for future integration with Kafka.

    Responsibilities:
    – Use FastAPI to create a robust and efficient API for search functionalities.
    – Ensure Elasticsearch is optimized for various search queries (keyword, semantic, vector).
    – Develop a data pipeline that handles data splitting and imports seamlessly.
    – Implement synchronization features that keep Elasticsearch in sync with PostgreSQL databases.
    – Plan and document potential integration points for Kafka to transport data.

    Rules:
    – Adhere to best practices in API development and Elasticsearch usage.
    – Maintain code quality and documentation for future scalability.
    – Consider performance impacts and optimize accordingly.

    Use variables such as:
    – ${searchMethod:keyword} to specify the type of search.
    – ${databaseType:PostgreSQL} for database selection.
    – ${integration:kafka} to indicate future integration plans.

  • Daiquiri Cocktail Cinematic Video

    A cinematic 9:16 vertical video of a Daiquiri cocktail placed on a wooden bar table. The camera is positioned at a slight angle on the front of the glass. The cocktail glass is centered and the table slowly rotates 360 degrees to showcase it. Soft, warm lighting and realistic reflections on the glass. Background slightly blurred. Smooth slow zoom in. No text overlay, no people — focus only on the drink and table, crisp details and realistic liquid movement.