5 prompts
Build a semantic code search engine using embeddings. Search by intent ('function that validates email') rather than exact text matches.
Build a Retrieval-Augmented Generation pipeline with hybrid search (vector + keyword) and a reranking step for higher precision answers.
Generate a JSON Schema from sample data. Infers types, required fields, patterns, and constraints. Ready for API validation or documentation.
Intermediate code generation prompt. Python Data Pipeline with customizable parameters for professional results.
Clean, transform, and restructure messy CSV data. Handle missing values, standardize formats, merge columns, and output clean structured data.