Description

Currently, Hermes Agent's memory and state are global across all conversations/channels. When deployed to multiple chats (e.g., personal 1v1 + work group), there's no isolation between conversations — content from one chat could potentially leak to another.

This feature request is for proper per-conversation context isolation.

Use Case

• User has personal 1v1 chat (Telegram) and work group chat
• Personal conversations should stay personal
• Work group discussions should stay in work context
• No cross-contamination of memories, preferences, or context

Proposed Solution

1. Namespace-based memory keys — prefix memory entries by conversation ID (e.g., work:user_preference, personal:memo)
2. Conversation context tracking — know which "mode" the agent is operating in per session
3. Isolation boundaries — explicit rules about what can/cannot be shared between contexts
4. Optional: skill scoping — load different skills per conversation type

Benefits

• Privacy-preserving across chat platforms
• Clean separation for work vs. personal use cases
• No risk of leaking personal info to work groups (or vice versa)
• Better multi-chatbot deployments

Alternatives Considered

• Using separate bot instances per conversation (wasteful, expensive)
• Manual memory prefixing (error-prone, requires user discipline)

Additional Context

See discussion in https://github.com/NousResearch/hermes-agent/discussions (if any)

Tags: feature-request, memory, isolation, multi-chat