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Redis search

Skill SyntaxArc/archipy-plugin/skills/redis-search

Scaffold Redis search adapters for full-text search (RediSearch), vector search, and search caching patterns. Use when adding search infrastructure to ArchiPy apps. Prefer RedisAdapter.search_index() over raw client.ft().From its SKILL.md

Install
npx -y skills add SyntaxArc/archipy-plugin --skill redis-search

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

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SKILL.md

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Redis Search Skills

Overview

Redis search via ArchiPy (archipy[redis]):

  • RediSearch: full-text via RedisAdapter.search_index(name) → RedisSearchHandle
  • Vector search: KNN / range via SearchQueryDTO.from_knn / from_range
  • Search caching: cache-aside around expensive search results

Canonical layout and ArchiPy constraints: ../archipy-docs/reference.md (Adapters + Redis Search). Templates: reference/fulltext_adapter.py, reference/vector_adapter.py, reference/search_cache_adapter.py.

Before writing files

Ask the user for:

  1. Search type: full-text, vector, or caching
  2. Domain name (e.g. product, document)
  3. Data structure to index (HASH vs JSON)
  4. Search patterns needed (autocomplete, faceted search, …)
  5. Sync or async (or both as separate classes)

Prefer ArchiPy

uv add "archipy[redis]"

Thin domain wrapper around RedisAdapter.search_index() — not raw client.ft().

Key library symbols:

  • RedisAdapter.search_index(name) / list_search_indexes()
  • DTOs: IndexSchemaDTO, TextFieldConfig, TagFieldConfig, NumericFieldConfig, VectorFieldConfig
  • Queries: SearchQueryDTO, SearchQueryDTO.from_knn(...), SearchQueryDTO.from_range(...)
  • Documents: HashDocumentUpsertDTO, JsonDocumentUpsertDTO
  • Types: RedisIndexType, VectorAlgorithm, VectorDistanceMetric, …
  • Helpers: pack_vector / unpack_vector from archipy.adapters.redis.search

Requires Redis 8+ (query engine). Cluster needs hash-tagged prefixes (e.g. {products}:).

Generate

repositories/<domain>/
├── adapters/
│   └── <domain>_search_adapter.py      # or _vector_ / _search_cache_
└── <domain>_repository.py
  1. Copy the matching template from reference/, rename class/index/prefix to the domain.
  2. Define a domain error (e.g. ProductSearchError) under models/errors/ — templates import it.
  3. Wire via DI in configs/containers.py.
  4. Map Redis/RediSearch failures with raise DomainError(...) from e.

Full-text

Use reference/fulltext_adapter.py: ensure_index via info() → create_index(IndexSchemaDTO, …) only when missing; search via handle.search(SearchQueryDTO(...)).

Vector

Use reference/vector_adapter.py: VectorFieldConfig + SearchQueryDTO.from_knn. Adjust DIM / algorithm.

Search caching

Use reference/search_cache_adapter.py: cache-aside with Redis get/setex. Repository orchestrates search + cache; logics own invalidation rules.

Constraints

  • Sync and async must be separate classes.
  • No business logic in adapters — map data and talk to infrastructure only.
  • Do not create a top-level adapters/<name>/ package — domain adapters live under repositories.
  • Prefer ArchiPy search handle API; only drop to raw Redis for operations the handle does not cover.
  • Use specific exceptions; always raise ... from e.

Docs

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