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Configure and troubleshoot Honcho memory for Hermes.

AI & Automation 221,168 stars 42199 forks Updated today MIT

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# Honcho Memory for Hermes Honcho provides AI-native cross-session user modeling. It learns who the user is across conversations and gives every Hermes profile its own peer identity while sharing a unified view of the user. ## When to Use - Setting up Honcho (cloud or self-hosted) - Troubleshooting memory not working / peers not syncing - Creating multi-profile setups where each agent has its own Honcho peer - Tuning observation, recall, dialectic depth, or write frequency settings - Understanding what the 5 Honcho tools do and when to use them - Configuring context budgets and session summary injection ## Setup ### Cloud (app.honcho.dev) ```bash hermes memory setup honcho # select "cloud", paste API key from https://app.honcho.dev ``` ### Self-hosted ```bash hermes memory setup honcho # select "local", enter base URL (e.g. http://localhost:8000) ``` See: https://docs.honcho.dev/v3/guides/integrations/hermes#running-honcho-locally-with-hermes ### Verify ```bash hermes honcho status # shows resolved config, connection test, peer info ``` ## Architecture ### Base Context Injection When Honcho injects context into the system prompt (in `hybrid` or `context` recall modes), it assembles the base context block in this order: 1. **Session summary** -- a short digest of the current session so far (placed first so the model has immediate conversational continuity) 2. **User representation** -- Honcho's accumulated model of the user (preferences, facts, patterns) 3. *...

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Author
NousResearch
Repository
NousResearch/hermes-agent
Created
1 years ago
Last Updated
today
Language
Python
License
MIT

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