openclaw - 💡(How to fix) Fix Feature Request: Cross-channel session context sharing for the same agent [1 participants]

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openclaw/openclaw#59355Fetched 2026-04-08 02:25:34
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Root Cause

User is working on a project (discussed in webchat). Later, they ask about the project status via WeChat - the agent cannot recall the previous discussion because it's a different session.

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Feature Request: Cross-channel session context sharing for the same agent

Problem

When the same agent (e.g., agent:main) is accessed from multiple channels (webchat, WeChat, Telegram, etc.), each channel maintains its own independent session. This means:

  • Webchat session: agent:main:main - has full conversation history
  • WeChat session: g-agent-main-main - starts fresh when session resets

If a user discusses something in webchat, then asks via WeChat, the agent has no memory of the previous conversation.

Use Case

User is working on a project (discussed in webchat). Later, they ask about the project status via WeChat - the agent cannot recall the previous discussion because it's a different session.

Proposed Solution

Option 1: Allow binding sessions to a unified context pool

  • Same agent across channels shares a common memory/context layer
  • When session resets on any channel, restore context from shared memory

Option 2: Automatic context sync on session reset

  • When a channel session resets, automatically restore context from shared memory file
  • Provide a mechanism to define what context should be preserved (e.g., a shared-memory.md file)

Option 3: Built-in shared memory API

  • Expose an API/endpoint that allows agents to read/write a shared context
  • Could be file-based (~/.openclaw/agents/{agentId}/shared-memory.md) or database-backed

Priority

Medium-High - This is critical for multi-channel deployments where users expect consistent context across platforms.

extent analysis

TL;DR

Implementing a shared memory mechanism, such as a unified context pool or automatic context sync, can enable cross-channel session context sharing for the same agent.

Guidance

  • Evaluate the proposed solutions (Option 1, Option 2, Option 3) to determine the best approach for implementing shared memory across channels.
  • Consider the trade-offs between using a file-based versus database-backed shared memory solution.
  • Assess the requirements for defining what context should be preserved across channels, such as using a shared-memory.md file.
  • Investigate the feasibility of exposing an API/endpoint for agents to read/write shared context.

Example

No explicit code example is provided, as the issue focuses on proposing high-level solutions rather than implementing specific code changes.

Notes

The choice of solution will depend on the specific requirements and constraints of the project, including performance, scalability, and security considerations.

Recommendation

Apply a workaround, such as implementing a unified context pool (Option 1), as it seems to be a viable solution for enabling cross-channel session context sharing. This approach allows for a common memory/context layer to be shared across channels, enabling the agent to recall previous conversations.

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