fleet-memory/skills/hindsight-docs/references/sdks/integrations/hermes.md

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10	Hermes Agent Persistent Memory with Hindsight | Integration	Add long-term memory to Hermes Agent with Hindsight. Automatically recalls context before every LLM call and retains conversations for future sessions.

Hermes Agent

Persistent long-term memory for Hermes Agent using Hindsight. Automatically recalls relevant context before every LLM call and retains conversations for future sessions — plus explicit retain/recall/reflect tools.

Quick Start

# 1. Install the plugin into Hermes's Python environment
uv pip install hindsight-hermes --python $HOME/.hermes/hermes-agent/venv/bin/python

# 2. Configure (choose one)
# Option A: Config file (recommended)
mkdir -p ~/.hindsight
cat > ~/.hindsight/hermes.json << 'EOF'
{
  "hindsightApiUrl": "http://localhost:9077",
  "bankId": "hermes"
}
EOF

# Option B: Environment variables
export HINDSIGHT_API_URL=http://localhost:9077
export HINDSIGHT_BANK_ID=hermes

# 3. Start Hermes — the plugin activates automatically
hermes

Features

• Auto-recall — on every turn, queries Hindsight for relevant memories and injects them into the system prompt (via pre_llm_call hook)
• Auto-retain — after every response, retains the user/assistant exchange to Hindsight (via post_llm_call hook)
• Explicit tools — hindsight_retain, hindsight_recall, hindsight_reflect for direct model control
• Config file — ~/.hindsight/hermes.json with the same field names as openclaw and claude-code integrations
• Zero config overhead — env vars still work as overrides for CI/automation

:::note The lifecycle hooks (pre_llm_call/post_llm_call) require hermes-agent with PR #2823 or later. On older versions, only the three tools are registered — hooks are silently skipped. :::

Architecture

The plugin registers via Hermes's hermes_agent.plugins entry point system:

Component	Purpose
pre_llm_call hook	Auto-recall — query memories, inject as ephemeral system prompt context
post_llm_call hook	Auto-retain — store user/assistant exchange to Hindsight
hindsight_retain tool	Explicit memory storage (model-initiated)
hindsight_recall tool	Explicit memory search (model-initiated)
hindsight_reflect tool	LLM-synthesized answer from stored memories

Connection Modes

1. External API (recommended for production)

Connect to a running Hindsight server (cloud or self-hosted). No local LLM needed — the server handles fact extraction.

{
  "hindsightApiUrl": "https://your-hindsight-server.com",
  "hindsightApiToken": "your-token",
  "bankId": "hermes"
}

2. Local Daemon

If you're running hindsight-embed locally, point to it:

{
  "hindsightApiUrl": "http://localhost:9077",
  "bankId": "hermes"
}

Follow the Quick Start guide to get the Hindsight API running.

Configuration

All settings are in ~/.hindsight/hermes.json. Every setting can also be overridden via environment variables (env vars take priority).

Connection & Daemon

Setting	Default	Env Var	Description
hindsightApiUrl	—	HINDSIGHT_API_URL	Hindsight API URL
hindsightApiToken	null	HINDSIGHT_API_TOKEN / HINDSIGHT_API_KEY	Auth token for API
apiPort	9077	HINDSIGHT_API_PORT	Port for local Hindsight daemon
daemonIdleTimeout	0	HINDSIGHT_DAEMON_IDLE_TIMEOUT	Seconds before idle daemon shuts down (0 = never)
embedVersion	"latest"	HINDSIGHT_EMBED_VERSION	hindsight-embed version for uvx

LLM Provider (daemon mode only)

Setting	Default	Env Var	Description
llmProvider	auto-detect	HINDSIGHT_LLM_PROVIDER	LLM provider: openai, anthropic, gemini, groq, ollama
llmModel	provider default	HINDSIGHT_LLM_MODEL	Model override

Memory Bank

Setting	Default	Env Var	Description
bankId	—	HINDSIGHT_BANK_ID	Memory bank ID
bankMission	""	HINDSIGHT_BANK_MISSION	Agent identity/purpose for the memory bank
retainMission	null	—	Custom retain mission (what to extract from conversations)
bankIdPrefix	""	—	Prefix for all bank IDs

Auto-Recall

Setting	Default	Env Var	Description
autoRecall	true	HINDSIGHT_AUTO_RECALL	Enable automatic memory recall via pre_llm_call hook
recallBudget	"mid"	HINDSIGHT_RECALL_BUDGET	Recall effort: low, mid, high
recallMaxTokens	4096	HINDSIGHT_RECALL_MAX_TOKENS	Max tokens in recall response
recallMaxQueryChars	800	HINDSIGHT_RECALL_MAX_QUERY_CHARS	Max chars of user message used as query
recallPromptPreamble	see below	—	Header text injected before recalled memories

Default preamble:

Relevant memories from past conversations (prioritize recent when conflicting). Only use memories that are directly useful to continue this conversation; ignore the rest:

Auto-Retain

Setting	Default	Env Var	Description
autoRetain	true	HINDSIGHT_AUTO_RETAIN	Enable automatic retention via post_llm_call hook
retainEveryNTurns	1	—	Retain every Nth turn
retainOverlapTurns	2	—	Extra overlap turns for continuity
retainRoles	["user", "assistant"]	—	Which message roles to retain

Miscellaneous

Setting	Default	Env Var	Description
debug	false	HINDSIGHT_DEBUG	Enable debug logging to stderr

Hermes Gateway (Telegram, Discord, Slack)

When using Hermes in gateway mode (multi-platform messaging), the plugin works across all platforms. Hermes creates a fresh AIAgent per message, and the plugin's pre_llm_call hook ensures relevant memories are recalled for each turn regardless of platform.

Disabling Hermes's Built-in Memory

Hermes has a built-in memory tool that saves to local markdown files. If both are active, the LLM may prefer the built-in one. Disable it:

hermes tools disable memory

Re-enable later with hermes tools enable memory.

Troubleshooting

Plugin not loading: Verify the entry point is registered:

python -c "
import importlib.metadata
eps = importlib.metadata.entry_points(group='hermes_agent.plugins')
print(list(eps))
"

You should see EntryPoint(name='hindsight', value='hindsight_hermes', ...).

Tools don't appear in /tools: Check that hindsightApiUrl (or HINDSIGHT_API_URL) is set. The plugin silently skips registration when unconfigured.

Connection refused: Verify the Hindsight API is running:

curl http://localhost:9077/health

Recall returning no memories: Memories need at least one retain cycle. Try storing a fact first, then asking about it in a new session.