* [fix]The log retains genuine alerts and errors, while filtering out unnecessary noise.
* [fix]Scenario English and Chinese, emotion specifications
* [fix]Change the "no data" scenario from 0.0 to None
1. when adding a model API key to the model list, a tenant_id uniqueness check needs to be added;
2.the Model Square has cancelled custom models;
3. optimization of the interface logic for customizing model configurations in the model list
* [add]Integration of the core engineering and memory extraction
* [add]The import and export function of the main body engineering files
* [add]Improve the import interface
* [add]Introducing generic types helps with entity extraction
* [add]Modify the references of the main repository to the sub-repositories
* [add]The extraction trial run introduces the ontology type.
* [add]Integration of the core engineering and memory extraction
* [add]The import and export function of the main body engineering files
* [add]Improve the import interface
* [add]Introducing generic types helps with entity extraction
* [add]Modify the references of the main repository to the sub-repositories
* [add]The extraction trial run introduces the ontology type.
* [add]Complete the second phase of the main project content
* [add]The dependencies and configurations of the main body project
* [add]Modify the code based on the AI review
1. Three party web website data access - Web site synchronization
Building a knowledge base by crawling web page data in batches through web crawlers
Web site synchronization utilizes crawler technology, which can automatically capture all websites under the same domain name through a single entry website. Currently, it supports up to 200 subpages. For compliance and security reasons, only static site crawling is supported, mainly used for quickly building knowledge bases on various document sites.
2. Feishu Knowledge Base
By configuring Feishu document permissions, a knowledge base can be built using Feishu documents, and the documents will not undergo secondary storage
3. Language Bird Knowledge Base
You can configure the permissions of the language bird document to build a knowledge base using the language bird document, and the document will not undergo secondary storage
1. Add the "Skills" module;
2. The loading of the model square has been modified to be controlled through environment variables;
3. Dynamic scheduling of the skill binding tool;
4. Agent Integration Skills
* [changes]Add 'id' as the secondary sorting key, and 'scene_id' now returns a UUID object
* [fix]Fix the "end_user" return to be sorted by update time.
* [fix]Set the default values of the memory configuration model based on the spatial model.
* [fix]Remove the entity extraction check combination model, read the configuration list, and add the return of scene_id
* [fix]Fix the "end_user" return to be sorted by update time.
* [fix]
* [fix]Fix the issue of inconsistent language in explicit and episodic memory.
* [fix]Fix the issue of inconsistent language in explicit and episodic memory.
* [add]Add scene_id
* [fix]Based on the AI review to fix the code
- Add force parameter to delete_config endpoint for controlled deletion of in-use configs
- Implement MemoryConfigService.delete_config with protection against deleting default configs
- Add validation to prevent deletion of configs with connected end-users unless force=True
- Reorganize controller imports to remove duplicates and improve maintainability
- Clean up unused database connection management code from memory_storage_controller
- Add detailed docstring to delete_config endpoint explaining protection mechanisms
- Update error handling with specific BizCode.RESOURCE_IN_USE for configs in active use
- Add comprehensive logging for deletion attempts, warnings, and affected users
- Refactor ConfigParamsDelete schema usage to use MemoryConfigService directly
- Improve API response structure with affected_users count and force_required flag
* [changes]refactor locomo_test
* [fix]Fix the circular import of ModelParameters
* [changes]The benchmark test can run stably.
* [fix]Complete end-to-end LoCoMo repair
* [fix]Complete the end-to-end longmemeval and memsciqa fixes
* [changes]Complete the benchmark test description document to ensure that the configuration parameters take effect.
* [changes]refactor locomo_test
* [fix]Fix the circular import of ModelParameters
* [changes]The benchmark test can run stably.
* [fix]Complete end-to-end LoCoMo repair
* [fix]Complete the end-to-end longmemeval and memsciqa fixes
* [changes]Complete the benchmark test description document to ensure that the configuration parameters take effect.
* [changes]Benchmark test adaptation for end_user_id
* [changes]refactor locomo_test
* [fix]Fix the circular import of ModelParameters
* [changes]The benchmark test can run stably.
* [fix]Complete end-to-end LoCoMo repair
* [fix]Complete the end-to-end longmemeval and memsciqa fixes
* [changes]Complete the benchmark test description document to ensure that the configuration parameters take effect.
* [fix]Complete the end-to-end longmemeval and memsciqa fixes
* [changes]Complete the benchmark test description document to ensure that the configuration parameters take effect.
* [changes]Benchmark test adaptation for end_user_id
