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)
[fix]Fix the bug that affects user memory.
* fix/othername-name: (11 commits squashed)
- [fix]Fix the issue with the display of the user's memory list
- [fix]Ensure the six dimensions of emotional expression
- [fix]Fix the issue with the display of the user's memory list
- [fix]Ensure the six dimensions of emotional expression
- Merge branch 'fix/othername-name' of codeup.aliyun.com:redbearai/python/redbear-mem-open into fix/othername-name
- [fix]Restore the display of memory types
- [fix]Fix the issue with the display of the user's memory list
- [fix]Ensure the six dimensions of emotional expression
- [fix]Restore the display of memory types
- Merge branch 'fix/othername-name' of codeup.aliyun.com:redbearai/python/redbear-mem-open into fix/othername-name
- [updated]Update the title of the "analytics/node_statistics" log
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/47
- Reorganize imports and remove unused dependencies across memory agent controllers
- Extract config validation logic into dedicated validators module
- Create new memory_config_model and memory_config_schema for configuration management
- Implement memory_config_service for centralized config handling
- Add embedder_utils module for embedding model utilities
- Refactor memory agent service to use new config validation framework
- Clean up configuration files (remove config.json, testdata.json, dbrun.json)
- Remove deprecated hybrid_chatbot.py and config overrides
- Update logging configuration and error handling across memory modules
- Consolidate LLM and embedding model validation into validators
- Improve code organization and reduce duplication in memory storage services
- Enhance type classification and verification tools with better error handling
- Replace the system prompt of the prompt optimization model with a built-in prompt.
- Remove system prompt entries from the database.
- Remove the API endpoint for managing system prompt configuration.
- Added API endpoints for prompt optimization:
* POST /prompt/sessions: Create a new prompt optimization session
* GET /prompt/sessions/{session_id}: Retrieve session message history
* POST /prompt/sessions/{session_id}/messages: Send message and get optimized prompt
* PUT /prompt/model: Create or update system prompt model configuration
- Added database models for prompt optimization:
* prompt_opt_session: Stores session metadata
* prompt_opt_session_history: Stores session message history
* prompt_opt_message: Stores user and assistant messages
* prompt_opt_model_config: Stores system prompt model configurations
- Updated service layer to handle message creation, prompt optimization, and variable parsing
- Added corresponding Pydantic schemas for request and response validation
