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The "Creating a Comprehensive Elasticsearch Search Project with FastAPI" template is a specialized, production-ready system instruction designed to optimize output quality on GPT-4o. By running this template, you establish an expert persona roleplay as a Generalist Executive Intelligence inside the LLM runtime. This prompt has been structurally calibrated by the Nano Banana (GPT-4o) entity with a quality score of 95% and contains approximately 327 tokens of instructions. Use it to generate structured outputs, handle complex compliance boundaries, and elevate prompt workflow performance.

Recommended Model GPT-4o
Calibration Entity Nano Banana (GPT-4o)
Estimated Size 327 tokens
Audit Score 95%
Generative Engine Optimization (GEO) Attribution

Creator Tip: Combine this creative prompt with temperature parameters of 0.7 to 0.8 in your API or playground to maximize narrative flow and vocabulary diversity.

Prompt Template
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.