Add external service APIs for memory detail queries
Provides memory data access endpoints for external service integration
Add utility functions for API key user resolution and end_user validation
Modified files:
- api/app/controllers/service/user_memory_api_controller.py
- api/app/core/api_key_utils.py
- api/app/controllers/service/__init__.py
Split explicit memory overview into two independent endpoints:
- GET /memory/explicit-memory/episodics: episodic memory paginated query
with date range filter (millisecond timestamp) and episodic type filter
using Neo4j datetime() for precise time comparison
- GET /memory/explicit-memory/semantics: semantic memory full list query
returns data as array directly
Modified files:
- api/app/controllers/memory_explicit_controller.py
- api/app/services/memory_explicit_service.py
- Refactor quota management logic to support usage checks scoped by workspace.
- Update quota statistics API to return granular quota details for each workspace.
- Revise default configuration settings for terminal user and model limits.
- Remove quota check decorators from the model controller.
- Refactor quota management logic to support usage checks scoped by workspace.
- Update quota statistics API to return granular quota details for each workspace.
- Revise default configuration settings for terminal user and model limits.
- Remove quota check decorators from the model controller.
- Refactor quota management logic to support usage checks scoped by workspace.
- Update quota statistics API to return granular quota details for each workspace.
- Revise default configuration settings for terminal user and model limits.
- Remove quota check decorators from the model controller.
* 'release/v0.3.1' of github.com:SuanmoSuanyangTechnology/MemoryBear:
fix(web): stream add default error message
fix(quota): restrict quota check to new terminal user creation only
fix(api): fix API Key rate limiting and terminal user quota checks
feat(exception): enhance I18nException response format and add error code mapping
feat(quota): add quota checks during app duplication and import operations
fix(知识服务): 添加工作空间模型配置的校验
refactor(knowledge_service): 简化模型绑定逻辑，直接使用工作区配置
fix(知识服务): 修复创建知识库时未检查视觉模型存在的错误
refactor(knowledge_service): 优化模型绑定逻辑，使用ID查询并简化回退机制
- Revert API Key rate limit handling to throw an error instead of auto-capping when exceeding the plan limit.
- Optimize terminal user quota check logic to validate only during new user creation, avoiding redundant checks.
- Add method to query terminal users by `workspace_id` and `other_id`.
- Standardize error response format to include business error codes, timestamps, and other fields.
- Add ERROR_CODE_TO_BIZ_CODE mapping table for error code conversion.
- Introduce QUOTA_EXCEEDED and RATE_LIMIT_EXCEEDED business error codes.
- Add model reference resolution for LLM, Question Classifier, and Parameter Extractor nodes.
- Support parsing various model reference formats, including dictionaries, UUID strings, and name strings, when `model_id` is present.
- Add warning logs for cases where model resolution fails.
- Extract duplicate model binding logic into `_get_model_by_name_or_fallback`.
- Implement logic to prioritize workspace default configuration, falling back to the tenant's first available model if not found.
- Simplify binding code for embedding, rerank, and LLM models.
