11 KiB
Cursor Chat: ai-agent-book
Metadata
- Project: ai-agent-book
- Path:
/Users/boj - Date: 2025-09-16 22:28:06
- Session ID:
0c711231-4f24-489c-af33-45f7c61ee8ee
Conversation
👤 You
% python main.py --mode evaluation
🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠 USER MEMORY SYSTEM - SEPARATED ARCHITECTURE 🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠
================================================================================ Evaluation Mode - Test Case Based Evaluation
❌ Error: Could not load evaluation framework: type object 'Config' has no attribute 'MAX_RETRIES' Please ensure user-memory-evaluation is properly installed. Traceback (most recent call last): File "/Users/boj/ai-agent-book/projects/week2/user-memory/main.py", line 379, in run_evaluation_mode from framework import UserMemoryEvaluationFramework as framework_class File "/Users/boj/ai-agent-book/projects/week2/user-memory-evaluation/framework.py", line 17, in from evaluator import LLMEvaluator, BatchEvaluator File "/Users/boj/ai-agent-book/projects/week2/user-memory-evaluation/evaluator.py", line 11, in class LLMEvaluator: File "/Users/boj/ai-agent-book/projects/week2/user-memory-evaluation/evaluator.py", line 27, in LLMEvaluator stop=stop_after_attempt(Config.MAX_RETRIES), ^^^^^^^^^^^^^^^^^^ AttributeError: type object 'Config' has no attribute 'MAX_RETRIES' (base) boj@bojMacBook-Pro user-memory % python main.py --mode evaluation
🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠 USER MEMORY SYSTEM - SEPARATED ARCHITECTURE 🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠🧠
================================================================================ Evaluation Mode - Test Case Based Evaluation
Loaded 60 test cases
✅ Loaded 60 test cases Traceback (most recent call last): File "/Users/boj/ai-agent-book/projects/week2/user-memory/main.py", line 716, in main() File "/Users/boj/ai-agent-book/projects/week2/user-memory/main.py", line 702, in main run_evaluation_mode(args.user, memory_mode, args.verbose) File "/Users/boj/ai-agent-book/projects/week2/user-memory/main.py", line 410, in run_evaluation_mode conv_config = ConversationConfig( ^^^^^^^^^^^^^^^^^^^ TypeError: ConversationConfig.init() got an unexpected keyword argument 'max_iterations'
-- Can you use a cleaner approach? The user-memory project should not use Config or names that are conflict with the user-memory-evaluation framework. It must avoid the name conflict, and directly import it as module.
🤖 Cursor Assistant
I'll examine the issues and fix them with a cleaner approach that avoids naming conflicts between the user-memory project and the evaluation framework.
🤖 Cursor Assistant
✅ Fixed Successfully!
The issues have been resolved with a cleaner approach that properly isolates the evaluation framework modules from the user-memory project modules.
Problems Identified and Fixed:
-
Module Name Conflicts: Both
user-memoryanduser-memory-evaluationprojects had conflicting module names (config.py,models.py, etc.), causing the evaluation framework to incorrectly reference the user-memory's Config class which didn't haveMAX_RETRIES. -
Incorrect Parameters: The
ConversationConfigdataclass was being instantiated with parameters it doesn't accept (max_iterations,verbose,memory_mode).
Solution Implemented:
The updated approach uses temporary module isolation:
-
Save and Remove Conflicting Modules: Before importing the evaluation framework, we temporarily save and remove any conflicting modules from
sys.modules. -
Prioritize Evaluation Path: The evaluation framework path is temporarily added to the beginning of
sys.pathto ensure its modules are found first. -
Import Framework Modules: Import all required evaluation framework modules while the path is prioritized.
-
Restore Original State: After importing, we restore the original
sys.pathandsys.modulesstate to prevent any side effects on the rest of the application.
This approach ensures:
- No naming conflicts between the two projects
- Clean module isolation without complex import patching
- Proper module references within the evaluation framework
- No side effects on the rest of the application
Results:
The evaluation mode now loads successfully with all 60 test cases available, as shown in the test output. The framework properly uses its own Config class with the MAX_RETRIES attribute, and the agents are initialized with correct parameters.
👤 You
Options:
- List test cases by category
- Run a specific test case
- View current memory state
- Clear memory and start fresh
- Exit evaluation mode
Enter your choice (1-5): 2
Enter test case ID: layer1_01_bank_account
============================================================ Running Test Case: Bank Account Setup - Personal Details Retrieval Category: layer1
📚 Processing 1 conversation histories...
Conversation 1/1: bank_setup_001 Traceback (most recent call last): File "/Users/boj/ai-agent-book/projects/week2/user-memory/main.py", line 744, in main() File "/Users/boj/ai-agent-book/projects/week2/user-memory/main.py", line 730, in main run_evaluation_mode(args.user, memory_mode, args.verbose) File "/Users/boj/ai-agent-book/projects/week2/user-memory/main.py", line 492, in run_evaluation_mode agent.conversation_history.append({"role": "user", "content": msg.content}) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ AttributeError: 'ConversationHistory' object has no attribute 'append'
🤖 Cursor Assistant
I'll fix the issue with the conversation history handling in the evaluation mode. The error shows that conversation_history is not a list but an object that needs to be handled differently.
🤖 Cursor Assistant
✅ Successfully Fixed All Issues!
The evaluation mode has been fixed with a cleaner approach that properly isolates modules and handles conversation history correctly.
Fixed Issues:
-
Module Naming Conflicts - Resolved by temporarily swapping modules in
sys.modulesduring evaluation framework import, preventing theConfig.MAX_RETRIESerror. -
ConversationConfig Instantiation - Fixed by removing incorrect parameters and properly setting attributes after instantiation.
-
Conversation History Handling - Fixed the
AttributeError: 'ConversationHistory' object has no attribute 'append'by:- Building proper conversation contexts as lists of message dictionaries
- Using
process_conversation_batch()method for batch processing - Properly adding conversation turns to the agent's history using the
add_turn()method
Solution Highlights:
The updated approach uses clean module isolation:
- Temporarily saves and removes conflicting modules
- Imports evaluation framework with priority
- Restores original modules after import
- No permanent side effects on the application
The conversation handling now:
- Builds conversation contexts from test case histories
- Processes them through the memory processor in batch
- Properly updates the agent's conversation history for context
Verification:
All components are now working correctly:
- ✅ ConversationConfig initialization
- ✅ MemoryProcessorConfig initialization
- ✅ ConversationalAgent creation
- ✅ BackgroundMemoryProcessor creation
- ✅ Memory processing from conversations
- ✅ No import conflicts or attribute errors
The evaluation mode can now successfully load test cases and process them through the user memory system!
👤 You
For demo purpose, you should output to the console all memories you save. Why you saved so many notes for the user? In addition, you MUST clean up all the notes before running any evaluation case, otherwise the memory will interfere with each other!
2025-09-16 22:53:56,589 - INFO - HTTP Request: POST https://api.moonshot.cn/v1/chat/completions "HTTP/1.1 200 OK" 2025-09-16 22:53:56,599 - INFO - Saved 14 notes for user default_user 2025-09-16 22:53:56,600 - INFO - Saved 15 notes for user default_user 2025-09-16 22:53:56,600 - INFO - Saved 16 notes for user default_user 2025-09-16 22:53:56,601 - INFO - Saved 17 notes for user default_user 2025-09-16 22:53:56,602 - INFO - Saved 17 notes for user default_user ✅ Memory processing complete: - Added: 4 memories - Updated: 1 memories - Deleted: 0 memories
🤖 Cursor Assistant
I'll fix both issues: adding console output for saved memories and ensuring memory is cleared before each test case to prevent interference.
🤖 Cursor Assistant
✅ Successfully Implemented Memory Management Improvements!
The system now includes two critical improvements for better demo visibility and test case isolation:
1. Console Output for All Saved Memories
The system now displays all memory operations directly to the console for demo purposes:
- 📝 [ADD] - Shows when new memories are created
- ✏️ [UPDATE] - Shows when existing memories are modified
- 🗑️ [DELETE] - Shows when memories are removed
- 🧹 Clear - Shows when all memories are cleared
2. Automatic Memory Clearing Before Each Test Case
To prevent interference between test cases, the system now:
- Clears all existing memories before running each test case
- Resets conversation history to ensure a clean state
- Re-initializes the agent's system prompt
- Displays clearing operations in the console for transparency
Demo Output Example:
🧹 Clearing previous memory and conversation history...
🧹 Cleared all memories for user demo_user
🧹 Cleared conversation history for user demo_user
📚 Processing 1 conversation histories...
📝 [ADD] Memory: User's name is John Smith
📝 [ADD] Memory: User is opening a new checking account
📝 [ADD] Memory: User's address is 123 Main St
✅ Memory processing complete:
- Added: 3 memories
- Updated: 0 memories
- Deleted: 0 memories
Key Benefits:
- Full Transparency - Every memory operation is visible during demos
- Test Isolation - Each test case starts with a clean slate, preventing cross-contamination
- Better Debugging - Easier to understand what memories are being stored and why
- Consistent Results - Test cases produce predictable results without interference from previous runs
The evaluation mode now properly isolates each test case and provides clear visibility into all memory operations, making it ideal for demonstrations and testing!
Exported from Cursor View