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Posted on • Originally published at hermes-agent.nousresearch.com

hermes-memory-installer Update: Claude-Obsidian Fusion Patterns — Deep Dive into Hot Cache (P0)

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The latest documentation update for hermes-memory-installer introduces a structured approach to enhancing the Knowledge Memory Module (KMM) for Claude-Obsidian fusion. The new docs lay out six patterns, with Hot Cache prioritized as P0. If you’re integrating Claude with an Obsidian vault and need sub‑second memory retrieval, this update gives you the architectural blueprint.

Context: Why KMM Matters

Claude’s ability to reference past context depends on how quickly the memory layer can surface relevant knowledge. A full scan of embedded Obsidian notes is too slow for fluid conversation. The KMM sits between Claude and your vault, acting as a persistent, queryable store. Without optimization, retrieval latency kills the interactive experience. The six patterns in the new docs address this bottleneck at different levels, and Hot Cache tackles the most immediate one: speed.

The Six Patterns Overview

The documentation doesn’t just dump configuration flags; it describes coherent patterns. While the full list is in the update, the patterns cover caching (Hot Cache), compression (Semantic Pruning), tiered storage (Warm/Cold separation), forgetting (TTL-based expiry), conflict resolution (versioned entries), and indexing (sharded retrieval). Each pattern has a priority level, and Hot Cache is the only P0—meaning you must implement it before considering the others.

Hot Cache: The P0 Pattern

The Hot Cache pattern is simple: maintain a small, in‑memory cache of the most recently or frequently accessed memory entries. When Claude asks for context, the KMM first checks the hot cache. A hit avoids embedding lookup and similarity search entirely, cutting retrieval time from hundreds of milliseconds to microseconds.

The new documentation defines three configuration knobs:

  • Size – maximum number of entries in the hot cache (default 50).
  • TTL – how long an entry stays hot (default 300 seconds).
  • Eviction strategy – LRU (the only supported option in the current release).

Here’s an example configuration excerpt from the documented hermes-memory.yaml that ships with the installer:

kmm:
  hot_cache:
    enabled: true
    max_entries: 100
    ttl_seconds: 600
    eviction: "lru"
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Enabling this gives an immediate latency reduction for queries that hit recently used memories. The docs recommend setting max_entries proportional to the average conversation turn length—10–20 entries per turn works well. TTL should match the expected conversation duration; too short and you lose context, too long and stale memories pollute the cache.

Integration with Obsidian

The hot cache is not just a general‑purpose LRU; the documentation details how to populate it from Obsidian’s graph structure. When Claude accesses a note, all its linked notes are pre‑fetched into the hot cache. Similarly, tags or folders can be configured as “always hot” – for example, #active-project notes stay cached until you remove the tag. This bridges Obsidian’s relational model with Claude’s need for rapid context assembly.

Code‑Level Usage

Beyond configuration, the docs show how to interact with the hot cache programmatically via the HermesMemory API:

from hermes_memory import HotCache

cache = HotCache(size=100, ttl=600, eviction='lru')

# Manual pre‑fetch for critical entries
cache.prefetch(['note_2024_10_01.md', 'arch_schema.md'])

# Check hit rate in logs
print(cache.hit_rate)  # 0.92
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This API lets advanced users override the automatic population rules or inject external memory sources.

Why P0?

Without hot cache, every Claude turn triggers a full similarity search against your entire Obsidian vault – even for trivial follow‑ups like “elaborate on the point you just made.” That kills user experience. The Hot Cache pattern is the cheapest, highest‑impact optimization you can apply. The other five patterns further improve fidelity and scalability, but they are pointless if retrieval is already too slow to use.

Next Steps

If you’re already running hermes-memory-installer, update the docs with the latest changelog and review the full pattern list. Implement Hot Cache first – it takes five minutes to configure and will transform your Claude‑Obsidian interaction from sluggish to instantaneous.

The full documentation now lives under docs/kmm-patterns.md in the repository. The six patterns are there, each with implementation notes, trade‑offs, and recommended priority. Hot Cache is clearly marked as P0 – start there.

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