- Consolidate memory search services by removing separate content_search.py and perceptual_search.py
- Update model client handling in base_pipeline.py to use ModelApiKeyService for LLM client initialization
- Add new prompt files and modify existing services to support consolidated search architecture
- Refactor memory read pipeline and related services to use updated model client approach
- Consolidate memory search services by removing separate content_search.py and perceptual_search.py
- Update model client handling in base_pipeline.py to use ModelApiKeyService for LLM client initialization
- Add new prompt files and modify existing services to support consolidated search architecture
- Refactor memory read pipeline and related services to use updated model client approach
- Replace storage_services/search with new read_services/memory_search structure
- Implement content_search and perceptual_search strategies
- Add query_preprocessor for search optimization
- Create memory_service as unified interface
- Update celery_app and graph_search for new architecture
- Add enums for memory operations
- Implement base_pipeline and memory_read pipeline patterns
* 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
* [fix]Fix the return of the "content" attribute
* [changes]Improve the code based on AI review
* Apply suggestion from @sourcery-ai[bot]
Co-authored-by: sourcery-ai[bot] <58596630+sourcery-ai[bot]@users.noreply.github.com>
* [fix]Fix the return of the "content" attribute
* [changes]Improve the code based on AI review
* Apply suggestion from @sourcery-ai[bot]
Co-authored-by: sourcery-ai[bot] <58596630+sourcery-ai[bot]@users.noreply.github.com>
* [changes]Improve the code based on AI review
---------
Co-authored-by: sourcery-ai[bot] <58596630+sourcery-ai[bot]@users.noreply.github.com>
[feature]actr-记忆遗忘需求开发
* feature/actr-forget: (12 commits squashed)
- [feature]
1.Extended fields of the date_config table;
2.New activation value calculation has been added, and the ACTR parameter has been introduced in Neo4j.
- [feature]1.Create a forgetting strategy executor;2.Create the forgetting scheduler
- [feature]Introduce activation values for retrieval, and develop a two-stage retrieval reordering process
- [feature]
1.Extended fields of the date_config table;
2.New activation value calculation has been added, and the ACTR parameter has been introduced in Neo4j.
- [feature]1.Create a forgetting strategy executor;2.Create the forgetting scheduler
- [feature]Introduce activation values for retrieval, and develop a two-stage retrieval reordering process
- Merge branch 'feature/actr-forget' of codeup.aliyun.com:redbearai/python/redbear-mem-open into feature/actr-forget
- [fix]Eliminate the interference caused by redundant code
- [feature]
1.Extended fields of the date_config table;
2.New activation value calculation has been added, and the ACTR parameter has been introduced in Neo4j.
- [feature]1.Create a forgetting strategy executor;2.Create the forgetting scheduler
- [feature]Introduce activation values for retrieval, and develop a two-stage retrieval reordering process
- Merge branch 'feature/actr-forget' of codeup.aliyun.com:redbearai/python/redbear-mem-open into feature/actr-forget
Signed-off-by: 乐力齐 <accounts_690c7b0af9007d7e338af636@mail.teambition.com>
Reviewed-by: aliyun6762716068 <accounts_68cb7c6b61f5dcc4200d6251@mail.teambition.com>
Merged-by: aliyun6762716068 <accounts_68cb7c6b61f5dcc4200d6251@mail.teambition.com>
CR-link: https://codeup.aliyun.com/redbearai/python/redbear-mem-open/change/85
