Automated ingestion of prompt: Creating a Comprehensive Elasticsearch Search Project with FastAPI

prompts/coding/creating_a_comprehensive_elasticsearch_search_proj_1174.md

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+---
+title: "Creating a Comprehensive Elasticsearch Search Project with FastAPI"
+contributor: "@ZhenjieZhao66"
+tags: #coding, #zhenjiezhao66
+---
+
+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.