Creating a Comprehensive Elasticsearch Search Project with FastAPI — ChatGPT Prompt

The Prompt

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.