mirror of
https://github.com/NousResearch/hermes-agent.git
synced 2026-04-25 00:51:20 +00:00
Several correctness and cost-safety fixes to the Honcho dialectic path
after a multi-turn investigation surfaced a chain of silent failures:
- dialecticCadence default flipped 3 → 1. PR #10619 changed this from 1 to
3 for cost, but existing installs with no explicit config silently went
from per-turn dialectic to every-3-turns on upgrade. Restores pre-#10619
behavior; 3+ remains available for cost-conscious setups. Docs + wizard
+ status output updated to match.
- Session-start prewarm now consumed. Previously fired a .chat() on init
whose result landed in HonchoSessionManager._dialectic_cache and was
never read — pop_dialectic_result had zero call sites. Turn 1 paid for
a duplicate synchronous dialectic. Prewarm now writes directly to the
plugin's _prefetch_result via _prefetch_lock so turn 1 consumes it with
no extra call.
- Prewarm is now dialecticDepth-aware. A single-pass prewarm can return
weak output on cold peers; the multi-pass audit/reconcile cycle is
exactly the case dialecticDepth was built for. Prewarm now runs the
full configured depth in the background.
- Silent dialectic failure no longer burns the cadence window.
_last_dialectic_turn now advances only when the result is non-empty.
Empty result → next eligible turn retries immediately instead of
waiting the full cadence gap.
- Thread pile-up guard. queue_prefetch skips when a prior dialectic
thread is still in-flight, preventing stacked races on _prefetch_result.
- First-turn sync timeout is recoverable. Previously on timeout the
background thread's result was stored in a dead local list. Now the
thread writes into _prefetch_result under lock so the next turn
picks it up.
- Cadence gate applies uniformly. At cadence=1 the old "cadence > 1"
guard let first-turn sync + same-turn queue_prefetch both fire.
Gate now always applies.
- Restored query-length reasoning-level scaling, dropped in 9a0ab34c.
Scales dialecticReasoningLevel up on longer queries (+1 at ≥120 chars,
+2 at ≥400), clamped at reasoningLevelCap. Two new config keys:
`reasoningHeuristic` (bool, default true) and `reasoningLevelCap`
(string, default "high"; previously parsed but never enforced).
Respects dialecticDepthLevels and proportional lighter-early passes.
- Restored short-prompt skip, dropped in ef7f3156. One-word
acknowledgements ("ok", "y", "thanks") and slash commands bypass
both injection and dialectic fire.
- Purged dead code in session.py: prefetch_dialectic, _dialectic_cache,
set_dialectic_result, pop_dialectic_result — all unused after prewarm
refactor.
Tests: 542 passed across honcho_plugin/, agent/test_memory_provider.py,
and run_agent/test_run_agent.py. New coverage:
- TestTrivialPromptHeuristic (classifier + prefetch/queue skip)
- TestDialecticCadenceAdvancesOnSuccess (empty-result retry, pile-up guard)
- TestSessionStartDialecticPrewarm (prewarm consumed, sync fallback)
- TestReasoningHeuristic (length bumps, cap clamp, interaction with depth)
- TestDialecticLifecycleSmoke (end-to-end 8-turn session walk)
504 lines
20 KiB
Markdown
504 lines
20 KiB
Markdown
---
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sidebar_position: 4
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title: "Memory Providers"
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description: "External memory provider plugins — Honcho, OpenViking, Mem0, Hindsight, Holographic, RetainDB, ByteRover, Supermemory"
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---
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# Memory Providers
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Hermes Agent ships with 8 external memory provider plugins that give the agent persistent, cross-session knowledge beyond the built-in MEMORY.md and USER.md. Only **one** external provider can be active at a time — the built-in memory is always active alongside it.
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## Quick Start
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```bash
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hermes memory setup # interactive picker + configuration
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hermes memory status # check what's active
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hermes memory off # disable external provider
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```
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You can also select the active memory provider via `hermes plugins` → Provider Plugins → Memory Provider.
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Or set manually in `~/.hermes/config.yaml`:
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```yaml
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memory:
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provider: openviking # or honcho, mem0, hindsight, holographic, retaindb, byterover, supermemory
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```
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## How It Works
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When a memory provider is active, Hermes automatically:
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1. **Injects provider context** into the system prompt (what the provider knows)
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2. **Prefetches relevant memories** before each turn (background, non-blocking)
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3. **Syncs conversation turns** to the provider after each response
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4. **Extracts memories on session end** (for providers that support it)
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5. **Mirrors built-in memory writes** to the external provider
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6. **Adds provider-specific tools** so the agent can search, store, and manage memories
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The built-in memory (MEMORY.md / USER.md) continues to work exactly as before. The external provider is additive.
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## Available Providers
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### Honcho
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AI-native cross-session user modeling with dialectic reasoning, session-scoped context injection, semantic search, and persistent conclusions. Base context now includes the session summary alongside user representation and peer cards, giving the agent awareness of what has already been discussed.
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| | |
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|---|---|
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| **Best for** | Multi-agent systems with cross-session context, user-agent alignment |
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| **Requires** | `pip install honcho-ai` + [API key](https://app.honcho.dev) or self-hosted instance |
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| **Data storage** | Honcho Cloud or self-hosted |
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| **Cost** | Honcho pricing (cloud) / free (self-hosted) |
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**Tools (5):** `honcho_profile` (read/update peer card), `honcho_search` (semantic search), `honcho_context` (session context — summary, representation, card, messages), `honcho_reasoning` (LLM-synthesized), `honcho_conclude` (create/delete conclusions)
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**Architecture:** Two-layer context injection — a base layer (session summary + representation + peer card, refreshed on `contextCadence`) plus a dialectic supplement (LLM reasoning, refreshed on `dialecticCadence`). The dialectic automatically selects cold-start prompts (general user facts) vs. warm prompts (session-scoped context) based on whether base context exists.
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**Three orthogonal config knobs** control cost and depth independently:
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- `contextCadence` — how often the base layer refreshes (API call frequency)
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- `dialecticCadence` — how often the dialectic LLM fires (LLM call frequency)
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- `dialecticDepth` — how many `.chat()` passes per dialectic invocation (1–3, depth of reasoning)
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**Setup Wizard:**
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```bash
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hermes honcho setup # (legacy command)
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# or
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hermes memory setup # select "honcho"
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```
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**Config:** `$HERMES_HOME/honcho.json` (profile-local) or `~/.honcho/config.json` (global). Resolution order: `$HERMES_HOME/honcho.json` > `~/.hermes/honcho.json` > `~/.honcho/config.json`. See the [config reference](https://github.com/hermes-ai/hermes-agent/blob/main/plugins/memory/honcho/README.md) and the [Honcho integration guide](https://docs.honcho.dev/v3/guides/integrations/hermes).
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<details>
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<summary>Full config reference</summary>
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| Key | Default | Description |
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|-----|---------|-------------|
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| `apiKey` | -- | API key from [app.honcho.dev](https://app.honcho.dev) |
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| `baseUrl` | -- | Base URL for self-hosted Honcho |
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| `peerName` | -- | User peer identity |
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| `aiPeer` | host key | AI peer identity (one per profile) |
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| `workspace` | host key | Shared workspace ID |
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| `contextTokens` | `null` (uncapped) | Token budget for auto-injected context per turn. Truncates at word boundaries |
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| `contextCadence` | `1` | Minimum turns between `context()` API calls (base layer refresh) |
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| `dialecticCadence` | `1` | Minimum turns between `peer.chat()` LLM calls. Only applies to `hybrid`/`context` modes |
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| `dialecticDepth` | `1` | Number of `.chat()` passes per dialectic invocation. Clamped 1–3. Pass 0: cold/warm prompt, pass 1: self-audit, pass 2: reconciliation |
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| `dialecticDepthLevels` | `null` | Optional array of reasoning levels per pass, e.g. `["minimal", "low", "medium"]`. Overrides proportional defaults |
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| `dialecticReasoningLevel` | `'low'` | Base reasoning level: `minimal`, `low`, `medium`, `high`, `max` |
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| `dialecticDynamic` | `true` | When `true`, model can override reasoning level per-call via tool param |
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| `dialecticMaxChars` | `600` | Max chars of dialectic result injected into system prompt |
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| `recallMode` | `'hybrid'` | `hybrid` (auto-inject + tools), `context` (inject only), `tools` (tools only) |
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| `writeFrequency` | `'async'` | When to flush messages: `async` (background thread), `turn` (sync), `session` (batch on end), or integer N |
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| `saveMessages` | `true` | Whether to persist messages to Honcho API |
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| `observationMode` | `'directional'` | `directional` (all on) or `unified` (shared pool). Override with `observation` object |
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| `messageMaxChars` | `25000` | Max chars per message (chunked if exceeded) |
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| `dialecticMaxInputChars` | `10000` | Max chars for dialectic query input to `peer.chat()` |
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| `sessionStrategy` | `'per-directory'` | `per-directory`, `per-repo`, `per-session`, `global` |
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</details>
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<details>
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<summary>Minimal honcho.json (cloud)</summary>
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```json
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{
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"apiKey": "your-key-from-app.honcho.dev",
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"hosts": {
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"hermes": {
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"enabled": true,
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"aiPeer": "hermes",
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"peerName": "your-name",
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"workspace": "hermes"
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}
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}
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}
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```
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</details>
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<details>
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<summary>Minimal honcho.json (self-hosted)</summary>
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```json
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{
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"baseUrl": "http://localhost:8000",
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"hosts": {
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"hermes": {
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"enabled": true,
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"aiPeer": "hermes",
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"peerName": "your-name",
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"workspace": "hermes"
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}
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}
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}
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```
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</details>
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:::tip Migrating from `hermes honcho`
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If you previously used `hermes honcho setup`, your config and all server-side data are intact. Just re-enable through the setup wizard again or manually set `memory.provider: honcho` to reactivate via the new system.
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:::
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**Multi-agent / Profiles:**
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Each Hermes profile gets its own Honcho AI peer while sharing the same workspace -- all profiles see the same user representation, but each agent builds its own identity and observations.
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```bash
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hermes profile create coder --clone # creates honcho peer "coder", inherits config from default
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```
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What `--clone` does: creates a `hermes.coder` host block in `honcho.json` with `aiPeer: "coder"`, shared `workspace`, inherited `peerName`, `recallMode`, `writeFrequency`, `observation`, etc. The peer is eagerly created in Honcho so it exists before first message.
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For profiles created before Honcho was set up:
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```bash
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hermes honcho sync # scans all profiles, creates host blocks for any missing ones
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```
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This inherits settings from the default `hermes` host block and creates new AI peers for each profile. Idempotent -- skips profiles that already have a host block.
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<details>
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<summary>Full honcho.json example (multi-profile)</summary>
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```json
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{
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"apiKey": "your-key",
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"workspace": "hermes",
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"peerName": "eri",
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"hosts": {
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"hermes": {
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"enabled": true,
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"aiPeer": "hermes",
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"workspace": "hermes",
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"peerName": "eri",
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"recallMode": "hybrid",
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"writeFrequency": "async",
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"sessionStrategy": "per-directory",
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"observation": {
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"user": { "observeMe": true, "observeOthers": true },
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"ai": { "observeMe": true, "observeOthers": true }
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},
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"dialecticReasoningLevel": "low",
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"dialecticDynamic": true,
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"dialecticCadence": 1,
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"dialecticDepth": 1,
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"dialecticMaxChars": 600,
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"contextCadence": 1,
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"messageMaxChars": 25000,
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"saveMessages": true
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},
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"hermes.coder": {
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"enabled": true,
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"aiPeer": "coder",
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"workspace": "hermes",
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"peerName": "eri",
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"recallMode": "tools",
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"observation": {
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"user": { "observeMe": true, "observeOthers": false },
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"ai": { "observeMe": true, "observeOthers": true }
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}
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},
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"hermes.writer": {
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"enabled": true,
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"aiPeer": "writer",
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"workspace": "hermes",
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"peerName": "eri"
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}
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},
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"sessions": {
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"/home/user/myproject": "myproject-main"
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}
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}
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```
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</details>
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See the [config reference](https://github.com/hermes-ai/hermes-agent/blob/main/plugins/memory/honcho/README.md) and [Honcho integration guide](https://docs.honcho.dev/v3/guides/integrations/hermes).
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---
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### OpenViking
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Context database by Volcengine (ByteDance) with filesystem-style knowledge hierarchy, tiered retrieval, and automatic memory extraction into 6 categories.
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| **Best for** | Self-hosted knowledge management with structured browsing |
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| **Requires** | `pip install openviking` + running server |
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| **Data storage** | Self-hosted (local or cloud) |
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| **Cost** | Free (open-source, AGPL-3.0) |
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**Tools:** `viking_search` (semantic search), `viking_read` (tiered: abstract/overview/full), `viking_browse` (filesystem navigation), `viking_remember` (store facts), `viking_add_resource` (ingest URLs/docs)
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**Setup:**
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```bash
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# Start the OpenViking server first
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pip install openviking
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openviking-server
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# Then configure Hermes
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hermes memory setup # select "openviking"
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# Or manually:
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hermes config set memory.provider openviking
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echo "OPENVIKING_ENDPOINT=http://localhost:1933" >> ~/.hermes/.env
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```
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**Key features:**
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- Tiered context loading: L0 (~100 tokens) → L1 (~2k) → L2 (full)
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- Automatic memory extraction on session commit (profile, preferences, entities, events, cases, patterns)
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- `viking://` URI scheme for hierarchical knowledge browsing
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---
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### Mem0
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Server-side LLM fact extraction with semantic search, reranking, and automatic deduplication.
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| **Best for** | Hands-off memory management — Mem0 handles extraction automatically |
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| **Requires** | `pip install mem0ai` + API key |
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| **Data storage** | Mem0 Cloud |
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| **Cost** | Mem0 pricing |
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**Tools:** `mem0_profile` (all stored memories), `mem0_search` (semantic search + reranking), `mem0_conclude` (store verbatim facts)
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**Setup:**
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```bash
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hermes memory setup # select "mem0"
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# Or manually:
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hermes config set memory.provider mem0
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echo "MEM0_API_KEY=your-key" >> ~/.hermes/.env
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```
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**Config:** `$HERMES_HOME/mem0.json`
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| Key | Default | Description |
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|-----|---------|-------------|
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| `user_id` | `hermes-user` | User identifier |
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| `agent_id` | `hermes` | Agent identifier |
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---
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### Hindsight
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Long-term memory with knowledge graph, entity resolution, and multi-strategy retrieval. The `hindsight_reflect` tool provides cross-memory synthesis that no other provider offers. Automatically retains full conversation turns (including tool calls) with session-level document tracking.
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|---|---|
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| **Best for** | Knowledge graph-based recall with entity relationships |
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| **Requires** | Cloud: API key from [ui.hindsight.vectorize.io](https://ui.hindsight.vectorize.io). Local: LLM API key (OpenAI, Groq, OpenRouter, etc.) |
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| **Data storage** | Hindsight Cloud or local embedded PostgreSQL |
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| **Cost** | Hindsight pricing (cloud) or free (local) |
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**Tools:** `hindsight_retain` (store with entity extraction), `hindsight_recall` (multi-strategy search), `hindsight_reflect` (cross-memory synthesis)
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**Setup:**
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```bash
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hermes memory setup # select "hindsight"
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# Or manually:
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hermes config set memory.provider hindsight
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echo "HINDSIGHT_API_KEY=your-key" >> ~/.hermes/.env
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```
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The setup wizard installs dependencies automatically and only installs what's needed for the selected mode (`hindsight-client` for cloud, `hindsight-all` for local). Requires `hindsight-client >= 0.4.22` (auto-upgraded on session start if outdated).
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**Local mode UI:** `hindsight-embed -p hermes ui start`
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**Config:** `$HERMES_HOME/hindsight/config.json`
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| Key | Default | Description |
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|-----|---------|-------------|
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| `mode` | `cloud` | `cloud` or `local` |
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| `bank_id` | `hermes` | Memory bank identifier |
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| `recall_budget` | `mid` | Recall thoroughness: `low` / `mid` / `high` |
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| `memory_mode` | `hybrid` | `hybrid` (context + tools), `context` (auto-inject only), `tools` (tools only) |
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| `auto_retain` | `true` | Automatically retain conversation turns |
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| `auto_recall` | `true` | Automatically recall memories before each turn |
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| `retain_async` | `true` | Process retain asynchronously on the server |
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| `tags` | — | Tags applied when storing memories |
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| `recall_tags` | — | Tags to filter on recall |
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See [plugin README](https://github.com/NousResearch/hermes-agent/blob/main/plugins/memory/hindsight/README.md) for the full configuration reference.
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---
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### Holographic
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Local SQLite fact store with FTS5 full-text search, trust scoring, and HRR (Holographic Reduced Representations) for compositional algebraic queries.
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| **Best for** | Local-only memory with advanced retrieval, no external dependencies |
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| **Requires** | Nothing (SQLite is always available). NumPy optional for HRR algebra. |
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| **Data storage** | Local SQLite |
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| **Cost** | Free |
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**Tools:** `fact_store` (9 actions: add, search, probe, related, reason, contradict, update, remove, list), `fact_feedback` (helpful/unhelpful rating that trains trust scores)
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**Setup:**
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```bash
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hermes memory setup # select "holographic"
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# Or manually:
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hermes config set memory.provider holographic
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```
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**Config:** `config.yaml` under `plugins.hermes-memory-store`
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| Key | Default | Description |
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|-----|---------|-------------|
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| `db_path` | `$HERMES_HOME/memory_store.db` | SQLite database path |
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| `auto_extract` | `false` | Auto-extract facts at session end |
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| `default_trust` | `0.5` | Default trust score (0.0–1.0) |
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**Unique capabilities:**
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- `probe` — entity-specific algebraic recall (all facts about a person/thing)
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- `reason` — compositional AND queries across multiple entities
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- `contradict` — automated detection of conflicting facts
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- Trust scoring with asymmetric feedback (+0.05 helpful / -0.10 unhelpful)
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---
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### RetainDB
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Cloud memory API with hybrid search (Vector + BM25 + Reranking), 7 memory types, and delta compression.
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|---|---|
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| **Best for** | Teams already using RetainDB's infrastructure |
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| **Requires** | RetainDB account + API key |
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| **Data storage** | RetainDB Cloud |
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| **Cost** | $20/month |
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**Tools:** `retaindb_profile` (user profile), `retaindb_search` (semantic search), `retaindb_context` (task-relevant context), `retaindb_remember` (store with type + importance), `retaindb_forget` (delete memories)
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**Setup:**
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```bash
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hermes memory setup # select "retaindb"
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# Or manually:
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hermes config set memory.provider retaindb
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echo "RETAINDB_API_KEY=your-key" >> ~/.hermes/.env
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```
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---
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### ByteRover
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Persistent memory via the `brv` CLI — hierarchical knowledge tree with tiered retrieval (fuzzy text → LLM-driven search). Local-first with optional cloud sync.
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|---|---|
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| **Best for** | Developers who want portable, local-first memory with a CLI |
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| **Requires** | ByteRover CLI (`npm install -g byterover-cli` or [install script](https://byterover.dev)) |
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| **Data storage** | Local (default) or ByteRover Cloud (optional sync) |
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||
| **Cost** | Free (local) or ByteRover pricing (cloud) |
|
||
|
||
**Tools:** `brv_query` (search knowledge tree), `brv_curate` (store facts/decisions/patterns), `brv_status` (CLI version + tree stats)
|
||
|
||
**Setup:**
|
||
```bash
|
||
# Install the CLI first
|
||
curl -fsSL https://byterover.dev/install.sh | sh
|
||
|
||
# Then configure Hermes
|
||
hermes memory setup # select "byterover"
|
||
# Or manually:
|
||
hermes config set memory.provider byterover
|
||
```
|
||
|
||
**Key features:**
|
||
- Automatic pre-compression extraction (saves insights before context compression discards them)
|
||
- Knowledge tree stored at `$HERMES_HOME/byterover/` (profile-scoped)
|
||
- SOC2 Type II certified cloud sync (optional)
|
||
|
||
---
|
||
|
||
### Supermemory
|
||
|
||
Semantic long-term memory with profile recall, semantic search, explicit memory tools, and session-end conversation ingest via the Supermemory graph API.
|
||
|
||
| | |
|
||
|---|---|
|
||
| **Best for** | Semantic recall with user profiling and session-level graph building |
|
||
| **Requires** | `pip install supermemory` + [API key](https://supermemory.ai) |
|
||
| **Data storage** | Supermemory Cloud |
|
||
| **Cost** | Supermemory pricing |
|
||
|
||
**Tools:** `supermemory_store` (save explicit memories), `supermemory_search` (semantic similarity search), `supermemory_forget` (forget by ID or best-match query), `supermemory_profile` (persistent profile + recent context)
|
||
|
||
**Setup:**
|
||
```bash
|
||
hermes memory setup # select "supermemory"
|
||
# Or manually:
|
||
hermes config set memory.provider supermemory
|
||
echo 'SUPERMEMORY_API_KEY=***' >> ~/.hermes/.env
|
||
```
|
||
|
||
**Config:** `$HERMES_HOME/supermemory.json`
|
||
|
||
| Key | Default | Description |
|
||
|-----|---------|-------------|
|
||
| `container_tag` | `hermes` | Container tag used for search and writes. Supports `{identity}` template for profile-scoped tags. |
|
||
| `auto_recall` | `true` | Inject relevant memory context before turns |
|
||
| `auto_capture` | `true` | Store cleaned user-assistant turns after each response |
|
||
| `max_recall_results` | `10` | Max recalled items to format into context |
|
||
| `profile_frequency` | `50` | Include profile facts on first turn and every N turns |
|
||
| `capture_mode` | `all` | Skip tiny or trivial turns by default |
|
||
| `search_mode` | `hybrid` | Search mode: `hybrid`, `memories`, or `documents` |
|
||
| `api_timeout` | `5.0` | Timeout for SDK and ingest requests |
|
||
|
||
**Environment variables:** `SUPERMEMORY_API_KEY` (required), `SUPERMEMORY_CONTAINER_TAG` (overrides config).
|
||
|
||
**Key features:**
|
||
- Automatic context fencing — strips recalled memories from captured turns to prevent recursive memory pollution
|
||
- Session-end conversation ingest for richer graph-level knowledge building
|
||
- Profile facts injected on first turn and at configurable intervals
|
||
- Trivial message filtering (skips "ok", "thanks", etc.)
|
||
- **Profile-scoped containers** — use `{identity}` in `container_tag` (e.g. `hermes-{identity}` → `hermes-coder`) to isolate memories per Hermes profile
|
||
- **Multi-container mode** — enable `enable_custom_container_tags` with a `custom_containers` list to let the agent read/write across named containers. Automatic operations (sync, prefetch) stay on the primary container.
|
||
|
||
<details>
|
||
<summary>Multi-container example</summary>
|
||
|
||
```json
|
||
{
|
||
"container_tag": "hermes",
|
||
"enable_custom_container_tags": true,
|
||
"custom_containers": ["project-alpha", "shared-knowledge"],
|
||
"custom_container_instructions": "Use project-alpha for coding context."
|
||
}
|
||
```
|
||
|
||
</details>
|
||
|
||
**Support:** [Discord](https://supermemory.link/discord) · [support@supermemory.com](mailto:support@supermemory.com)
|
||
|
||
---
|
||
|
||
## Provider Comparison
|
||
|
||
| Provider | Storage | Cost | Tools | Dependencies | Unique Feature |
|
||
|----------|---------|------|-------|-------------|----------------|
|
||
| **Honcho** | Cloud | Paid | 5 | `honcho-ai` | Dialectic user modeling + session-scoped context |
|
||
| **OpenViking** | Self-hosted | Free | 5 | `openviking` + server | Filesystem hierarchy + tiered loading |
|
||
| **Mem0** | Cloud | Paid | 3 | `mem0ai` | Server-side LLM extraction |
|
||
| **Hindsight** | Cloud/Local | Free/Paid | 3 | `hindsight-client` | Knowledge graph + reflect synthesis |
|
||
| **Holographic** | Local | Free | 2 | None | HRR algebra + trust scoring |
|
||
| **RetainDB** | Cloud | $20/mo | 5 | `requests` | Delta compression |
|
||
| **ByteRover** | Local/Cloud | Free/Paid | 3 | `brv` CLI | Pre-compression extraction |
|
||
| **Supermemory** | Cloud | Paid | 4 | `supermemory` | Context fencing + session graph ingest + multi-container |
|
||
|
||
## Profile Isolation
|
||
|
||
Each provider's data is isolated per [profile](/docs/user-guide/profiles):
|
||
|
||
- **Local storage providers** (Holographic, ByteRover) use `$HERMES_HOME/` paths which differ per profile
|
||
- **Config file providers** (Honcho, Mem0, Hindsight, Supermemory) store config in `$HERMES_HOME/` so each profile has its own credentials
|
||
- **Cloud providers** (RetainDB) auto-derive profile-scoped project names
|
||
- **Env var providers** (OpenViking) are configured via each profile's `.env` file
|
||
|
||
## Building a Memory Provider
|
||
|
||
See the [Developer Guide: Memory Provider Plugins](/docs/developer-guide/memory-provider-plugin) for how to create your own.
|