fleet-memory/hindsight-docs/docs-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. Get an API key at ui.hindsight.vectorize.io/connect. The API endpoint is https://api.hindsight.vectorize.io.

2. Run the setup wizard:

hermes memory setup    # select "hindsight"

The wizard will prompt for your API key and API URL, and configure everything automatically.

Or configure manually:

hermes config set memory.provider hindsight
# Add your key and the API endpoint
echo "HINDSIGHT_API_KEY=your-key" >> ~/.hermes/.env
echo "HINDSIGHT_API_URL=https://api.hindsight.vectorize.io" >> ~/.hermes/.env

3. Confirm memory is active:

hermes memory status

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
• Memory modes — choose between automatic injection, tools-only, or hybrid
• Zero config overhead — env vars 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. Cloud (recommended for production)

Connect to Hindsight Cloud at https://api.hindsight.vectorize.io. Get an API key at ui.hindsight.vectorize.io/connect.

{
  "mode": "cloud",
  "api_url": "https://api.hindsight.vectorize.io",
  "api_key": "hsk_your_token",
  "bank_id": "hermes"
}

2. Local (embedded)

Runs an embedded Hindsight server with built-in PostgreSQL. Requires an LLM API key for memory extraction and synthesis. The daemon starts automatically in the background on first use.

{
  "mode": "local",
  "llm_provider": "groq",
  "llm_api_key": "your-groq-key"
}

:::note The embedded server starts on the first message when Hermes says "starting agent". On a fresh system this can take over a minute while the embedded PostgreSQL initializes. Subsequent startups are fast. :::

Daemon startup logs: ~/.hermes/logs/hindsight-embed.log
Daemon runtime logs: ~/.hindsight/profiles/<profile>.log

Configuration

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

Connection & Daemon

Setting	Default	Env Var	Description
mode	cloud	HINDSIGHT_MODE	cloud or local
api_url	https://api.hindsight.vectorize.io	HINDSIGHT_API_URL	Hindsight API URL
api_key	null	HINDSIGHT_API_KEY	Auth token for Hindsight Cloud
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 (local mode only)

Setting	Default	Env Var	Description
llm_provider	openai	HINDSIGHT_LLM_PROVIDER	LLM provider: openai, anthropic, gemini, groq, minimax, ollama, lmstudio
llm_api_key	—	HINDSIGHT_LLM_API_KEY	API key for the chosen LLM provider
llm_model	provider default	HINDSIGHT_LLM_MODEL	Model override (auto-defaults per provider)

Default models per provider: openai → gpt-4o-mini, anthropic → claude-haiku-4-5, gemini → gemini-2.5-flash, groq → openai/gpt-oss-120b, minimax → MiniMax-M2.7, ollama → gemma3:12b.

Memory Bank

Setting	Default	Env Var	Description
bank_id	hermes	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)

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

Integration Mode

Setting	Default	Env Var	Description
memory_mode	hybrid	—	How memories are integrated into the agent (see below)
prefetch_method	recall	—	Method used for automatic context injection (see below)

memory_mode:

• hybrid — automatic context injection before each turn, plus tools available to the LLM
• context — automatic injection only; no tools exposed to the model
• tools — tools only (hindsight_retain, hindsight_recall, hindsight_reflect); no automatic injection

prefetch_method:

• recall — injects raw memory facts into the system prompt (fast)
• reflect — injects an LLM-synthesized summary of relevant memories (slower, more coherent)

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 api_url (or HINDSIGHT_API_URL) is set, or that HINDSIGHT_API_KEY is set for cloud mode. The plugin silently skips tool registration when unconfigured.

Connection refused: Verify the Hindsight API is running:

curl http://localhost:9077/health

Local daemon not starting: Check the daemon log for errors:

cat ~/.hermes/logs/hindsight-embed.log

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