Key	Default	Description
`venvPython`	`F:\Hermes\HERMES_HOME\hermes-agent\venv\Scripts\python.exe`	Python with `hindsight_embed` installed
`configJson`	`F:\Hermes\HERMES_HOME\hindsight\config.json`	JSON with `llm_api_key` / `llm_base_url` / `llm_model` (source of the DeepSeek key; never hardcoded)
`llmBaseUrl` / `llmModel` / `llmProvider`	DeepSeek defaults	Embedding endpoint; `deepseek`/`openai_compatible`/`openrouter` map to `openai`
`profile`	`deepseek`	Hindsight profile name (own daemon port + PG instance + bank)
`bank`	= `profile`	Bank id used by retain/recall/reflect
`autoRecall`	`false`	Inject relevant memories before each agent step
`recallTypes`	`["observation","experience","world"]`	Fact types searched
`recallLimit`	`4`	Max memories per recall
`recallMinUserChars`	`20`	Min user-message length before auto-recall triggers
`recallBudgetTokens`	`1200`	Token budget for auto-recall injection

The model calls the tools directly. Example retention policy (mirrors a self-evolution protocol):

Retain after complex tasks (5+ tool calls), after resolving a pitfall, when the user expresses a durable preference, or after key design decisions.
Recall at the start of complex tasks, when the user references past work, or when a situation smells like a repeat.

dsh-hindsight-memory

同名套件的其他儲存庫