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Add prompt: Creating a Comprehensive Elasticsearch Search Project with FastAPI
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35
PROMPTS.md
35
PROMPTS.md
@@ -62856,3 +62856,38 @@ You are a Senior Software Architect and Technical Auditor. Your tone is professi
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</details>
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<details>
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<summary><strong>Creating a Comprehensive Elasticsearch Search Project with FastAPI</strong></summary>
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## Creating a Comprehensive Elasticsearch Search Project with FastAPI
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Contributed by [@ZhenjieZhao66](https://github.com/ZhenjieZhao66)
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```md
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Act as a proficient software developer. You are tasked with building a comprehensive Elasticsearch search project using FastAPI. Your project should:
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- Support various search methods: keyword, semantic, and vector search.
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- Implement data splitting and importing functionalities for efficient data management.
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- Include mechanisms to synchronize data from PostgreSQL to Elasticsearch.
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- Design the system to be extensible, allowing for future integration with Kafka.
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Responsibilities:
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- Use FastAPI to create a robust and efficient API for search functionalities.
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- Ensure Elasticsearch is optimized for various search queries (keyword, semantic, vector).
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- Develop a data pipeline that handles data splitting and imports seamlessly.
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- Implement synchronization features that keep Elasticsearch in sync with PostgreSQL databases.
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- Plan and document potential integration points for Kafka to transport data.
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Rules:
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- Adhere to best practices in API development and Elasticsearch usage.
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- Maintain code quality and documentation for future scalability.
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- Consider performance impacts and optimize accordingly.
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Use variables such as:
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- ${searchMethod:keyword} to specify the type of search.
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- ${databaseType:PostgreSQL} for database selection.
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- ${integration:kafka} to indicate future integration plans.
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```
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</details>
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23
prompts.csv
23
prompts.csv
@@ -48624,3 +48624,26 @@ You are a Senior Software Architect and Technical Auditor. Your tone is professi
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- **v2.0:** Added maturity assessment and step-by-step logic.
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- **v2.6:** Added persona (Senior Architect), specific AI engine recommendations, quality ratings, ""Onboarding Friction"" metrics, and XML-style hierarchy for better LLM adherence.
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- **v2.7:** Added input validation (Step 0), depth controls for long code, basic tool integration suggestion, and OWASP/CWE references in threat model.",TRUE,TEXT,thanos0000@gmail.com
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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:
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- Support various search methods: keyword, semantic, and vector search.
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- Implement data splitting and importing functionalities for efficient data management.
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- Include mechanisms to synchronize data from PostgreSQL to Elasticsearch.
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- Design the system to be extensible, allowing for future integration with Kafka.
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Responsibilities:
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- Use FastAPI to create a robust and efficient API for search functionalities.
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- Ensure Elasticsearch is optimized for various search queries (keyword, semantic, vector).
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- Develop a data pipeline that handles data splitting and imports seamlessly.
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- Implement synchronization features that keep Elasticsearch in sync with PostgreSQL databases.
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- Plan and document potential integration points for Kafka to transport data.
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Rules:
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- Adhere to best practices in API development and Elasticsearch usage.
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- Maintain code quality and documentation for future scalability.
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- Consider performance impacts and optimize accordingly.
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Use variables such as:
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- ${searchMethod:keyword} to specify the type of search.
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- ${databaseType:PostgreSQL} for database selection.
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- ${integration:kafka} to indicate future integration plans.",FALSE,TEXT,ZhenjieZhao66
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