mirror of
https://github.com/MODSetter/SurfSense.git
synced 2026-06-20 21:18:13 +02:00
91d947ff79
The cached payload is the indexing pipeline's embeddings (markdown is chunked then embedded), so "embedding cache" names the expensive output directly and removes the "index" ambiguity (DB index vs vector index vs indexing phase). Renames the service, settings, eligibility, eviction task, metrics, config flags (INDEX_CACHE_* -> EMBEDDING_CACHE_*), object prefix, and the table (index_cache_embedding_sets -> embedding_cache_sets) with its constraint and indexes. Migration 161 renamed accordingly.
30 lines
877 B
Python
30 lines
877 B
Python
"""Embedding-cache configuration resolved from the central ``Config``.
|
|
|
|
The blob backend is intentionally not configured here: it is shared with the ETL
|
|
parse cache (see ``ETL_CACHE_STORAGE_*``).
|
|
"""
|
|
|
|
from __future__ import annotations
|
|
|
|
from dataclasses import dataclass
|
|
|
|
|
|
@dataclass(frozen=True)
|
|
class EmbeddingCacheSettings:
|
|
enabled: bool
|
|
chunker_version: int
|
|
ttl_days: int
|
|
max_total_bytes: int
|
|
eviction_batch: int
|
|
|
|
|
|
def load_embedding_cache_settings() -> EmbeddingCacheSettings:
|
|
from app.config import config
|
|
|
|
return EmbeddingCacheSettings(
|
|
enabled=config.EMBEDDING_CACHE_ENABLED,
|
|
chunker_version=config.EMBEDDING_CACHE_CHUNKER_VERSION,
|
|
ttl_days=config.EMBEDDING_CACHE_TTL_DAYS,
|
|
max_total_bytes=config.EMBEDDING_CACHE_MAX_TOTAL_MB * 1024 * 1024,
|
|
eviction_batch=config.EMBEDDING_CACHE_EVICTION_BATCH,
|
|
)
|