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

- 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

api/app/services/implicit_memory_service.py

@@ -90,13 +90,17 @@ class ImplicitMemoryService:
             # Get user's connected config
             connected_config = get_end_user_connected_config(self.end_user_id, self.db)
             config_id = connected_config.get("memory_config_id")
+            workspace_id = connected_config.get("workspace_id")
             
-            if config_id is None:
+            if config_id is None and workspace_id is None:
                 raise ValueError(f"No memory configuration found for end_user: {self.end_user_id}")
             
-            # Load the memory configuration
+            # Load the memory configuration with workspace fallback
             config_service = MemoryConfigService(self.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
+            )
             
             logger.info(f"Loaded memory config {config_id} for end_user: {self.end_user_id}")
             return memory_config