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feat(memory): add workspace_id fallback support for memory config resolution

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- Add workspace_id fallback parameter to memory config loading across all services
- Update hot_memory_tags.py to pass workspace_id when resolving memory configuration
- Enhance emotion_analytics_service.py to support workspace_id as fallback for config resolution
- Improve implicit_memory_service.py with workspace_id fallback in config loading
- Update memory_agent_service.py to handle workspace_id resolution and add refactoring TODO
- Enhance preference_analysis.jinja2 prompt with critical guidance on supporting_evidence extraction
- Add validation to check both config_id and workspace_id before raising configuration errors
- Improve error handling and logging for memory configuration resolution across services
- This enables more flexible memory configuration resolution when config_id is unavailable
This commit is contained in:
Ke Sun
2026-02-06 14:48:58 +08:00
parent 7a78f15a90
commit 5c10f11681
8 changed files with 195 additions and 134 deletions
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8
api/app/services/user_memory_service.py
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@@ -62,10 +62,14 @@ def _get_llm_client_for_user(user_id: str):
from app.services.memory_agent_service import get_end_user_connected_config
connected_config = get_end_user_connected_config(user_id, db)
config_id = connected_config.get("memory_config_id")
workspace_id = connected_config.get("workspace_id")
if config_id:
if config_id or workspace_id:
config_service = MemoryConfigService(db)
memory_config = config_service.load_memory_config(config_id)
memory_config = config_service.load_memory_config(
config_id=config_id,
workspace_id=workspace_id
)
factory = MemoryClientFactory(db)
return factory.get_llm_client(memory_config.llm_model_id)
else: