Scalability API Reference¶
Overview¶
The opifex.scalability package provides components for scaling scientific machine learning workflows, including distributed computing, load balancing, orchestration, and a neural functional search engine.
Search Engine¶
The search engine provides full search capabilities for the neural functional registry, including text search, semantic search, filtering, and recommendation systems. The opifex.scalability package re-exports SearchEngine, SearchQuery, SearchResult, and SearchType; the implementation lives in the registry (see the Platform API reference).
Neural Functional Search Engine.
Provides full search capabilities for neural functionals including text search, semantic search with neural embeddings, advanced filtering, and recommendation systems for the Opifex community platform.
dataclass
¶
SearchQuery(*, query_text: str = '', functional_type: str | None = None, domain: str | None = None, tags: list[str] | None = None, author_id: str | None = None, min_rating: float | None = None, min_accuracy: float | None = None, max_memory_gb: float | None = None, gpu_required: bool | None = None, limit: int = 50, offset: int = 0, search_type: SearchType = HYBRID)
Search query for neural functionals.
dataclass
¶
SearchResult(*, functional_id: str, name: str, description: str, functional_type: str, author_id: str, tags: list[str] = list(), relevance_score: float = 0.0, metadata: dict[str, Any] = dict())
Search result for a neural functional.
SearchEngine(registry_service: RegistryService, enable_semantic_search: bool = True, similarity_threshold: float = 0.7)
Neural functional search engine.
Provides full search capabilities including text-based search, semantic search with neural embeddings, advanced filtering, and recommendation systems.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
registry_service
|
RegistryService
|
Registry service for functional access |
required |
enable_semantic_search
|
bool
|
Whether to enable neural embeddings |
True
|
similarity_threshold
|
float
|
Minimum similarity for semantic matches |
0.7
|
async
¶
search(query: SearchQuery) -> list[SearchResult]
Execute search query for neural functionals.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
query
|
SearchQuery
|
Search query with criteria and options |
required |
Returns:
| Type | Description |
|---|---|
list[SearchResult]
|
List of matching functionals ranked by relevance |
async
¶
suggest_functionals(functional_id: str, limit: int = 5) -> list[SearchResult]
Suggest similar functionals based on a reference functional.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
functional_id
|
str
|
ID of reference functional |
required |
limit
|
int
|
Maximum number of suggestions |
5
|
Returns:
| Type | Description |
|---|---|
list[SearchResult]
|
List of similar functionals |
async
¶
search_by_problem(problem_description: str, domain: str | None = None, limit: int = 10) -> list[SearchResult]
Search for functionals suitable for a specific problem.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
problem_description
|
str
|
Description of the problem to solve |
required |
domain
|
str | None
|
Optional domain filter |
None
|
limit
|
int
|
Maximum number of results |
10
|
Returns:
| Type | Description |
|---|---|
list[SearchResult]
|
List of suitable functionals |