* [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
* refactor(celery): optimize task routing and worker configuration
- Simplify Celery queue configuration with single default 'io_tasks' queue
- Implement task routing strategy separating IO-bound and CPU-bound tasks
- Add Flower monitoring support with task event tracking enabled
- Add summary node search optimization to only retrieve summary nodes
- Clean up unused imports and reorganize import statements for consistency
- Update docker-compose configuration to support multi-queue worker setup
* chore(celery): simplify flower configuration and add gevent dependency
* chore(dependencies): add gevent dependency to requirements
- Add gevent==24.11.1 to api/requirements.txt
- Gevent is required for async worker support in Celery
- Complements existing flower and celery configuration
* refactor(celery): simplify async event loop handling and reorganize task queues
- Replace complex nest_asyncio and manual event loop management with asyncio.run() in read_message_task, write_message_task, regenerate_memory_cache, and workspace_reflection_task
- Rename task queues from io_tasks/cpu_tasks to memory_tasks/document_tasks for better semantic clarity
- Update task routing configuration to reflect new queue names for memory agent tasks and document processing tasks
- Remove redundant exception handling comments and simplify error handling logic
- Update README with improved community support section including GitHub Issues, Pull Requests, Discussions, and WeChat community links
- Simplifies event loop management by leveraging asyncio.run() which handles loop creation and cleanup automatically, reducing code complexity and potential race conditions
Add functions related to knowledge base graph:
1. Entity type generation,
2. Knowledge base graph acquisition,
3. Hard deletion of knowledge base graph,
4. Knowledge base graph reconstruction (asynchronous)
