- Replace hardcoded os.path.expanduser('~/.hermes') with
get_hermes_home() from hermes_constants for profile isolation
- Fix README echo command quoting error
1.8 KiB
1.8 KiB
Supermemory Memory Provider
Semantic long-term memory with profile recall, semantic search, explicit memory tools, and session-end conversation ingest.
Requirements
pip install supermemory- Supermemory API key from supermemory.ai
Setup
hermes memory setup # select "supermemory"
Or manually:
hermes config set memory.provider supermemory
echo 'SUPERMEMORY_API_KEY=your-key-here' >> ~/.hermes/.env
Config
Config file: $HERMES_HOME/supermemory.json
| Key | Default | Description |
|---|---|---|
container_tag |
hermes |
Container tag used for search and writes |
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 |
entity_context |
built-in default | Extraction guidance passed to Supermemory |
api_timeout |
5.0 |
Timeout for SDK and ingest requests |
Tools
| Tool | Description |
|---|---|
supermemory_store |
Store an explicit memory |
supermemory_search |
Search memories by semantic similarity |
supermemory_forget |
Forget a memory by ID or best-match query |
supermemory_profile |
Retrieve persistent profile and recent context |
Behavior
When enabled, Hermes can:
- prefetch relevant memory context before each turn
- store cleaned conversation turns after each completed response
- ingest the full session on session end for richer graph updates
- expose explicit tools for search, store, forget, and profile access