ai-agent-book 精选快照（<2MB 代码与文档，来自 github.com/bojieli/ai-agent-book）

chapter3/user-memory/quickstart.py

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+#!/usr/bin/env python3
+"""
+Quick start script for User Memory System with Separated Architecture
+Demonstrates conversation-based memory processing
+"""
+
+import os
+import sys
+import time
+from dotenv import load_dotenv
+from conversational_agent import ConversationalAgent, ConversationConfig
+from background_memory_processor import BackgroundMemoryProcessor, MemoryProcessorConfig
+from config import Config, MemoryMode
+from memory_manager import create_memory_manager
+from memory_operation_formatter import display_memory_operations
+
+# Load environment variables
+load_dotenv()
+
+
+def quickstart():
+    """Run a quick demonstration of the memory system with separated architecture"""
+    print("\n" + "="*60)
+    print("🚀 USER MEMORY SYSTEM - QUICK START")
+    print("   (Conversation-Based Memory Processing)")
+    print("="*60)
+    
+    # Check configuration
+    if not Config.MOONSHOT_API_KEY:
+        print("\n❌ ERROR: MOONSHOT_API_KEY not found!")
+        print("\nPlease set up your .env file with:")
+        print("  MOONSHOT_API_KEY=your_api_key_here")
+        print("\nYou can get an API key from: https://platform.moonshot.cn/")
+        sys.exit(1)
+    
+    # Create directories
+    Config.create_directories()
+    
+    # Setup demo user
+    user_id = "quickstart_user"
+    memory_mode = MemoryMode.NOTES
+    
+    print(f"\n📌 Setting up separated architecture:")
+    print(f"   • User: {user_id}")
+    print(f"   • Memory Mode: {memory_mode.value}")
+    print(f"   • Processing: After each conversation round")
+    
+    # Initialize conversational agent
+    print("\n🤖 Initializing conversational agent...")
+    agent = ConversationalAgent(
+        user_id=user_id,
+        memory_mode=memory_mode,
+        config=ConversationConfig(
+            enable_memory_context=True,
+            enable_conversation_history=True
+        ),
+        verbose=False
+    )
+    
+    # Initialize background memory processor
+    print("🧠 Initializing memory processor...")
+    processor = BackgroundMemoryProcessor(
+        user_id=user_id,
+        memory_mode=memory_mode,
+        config=MemoryProcessorConfig(
+            conversation_interval=1,  # Process after each conversation
+            min_conversation_turns=1,
+            output_operations=True
+        ),
+        verbose=False
+    )
+    
+    print("✅ System initialized\n")
+    
+    # Session 1: Introduction
+    print("="*60)
+    print("SESSION 1: INTRODUCTION & LEARNING")
+    print("="*60)
+    
+    intro_messages = [
+        "Hi! I'm Alex, a software developer who loves Python and machine learning.",
+        "I'm currently working on a recommendation system project using PyTorch.",
+        "I prefer dark themes in my IDE and always use type hints in my Python code."
+    ]
+    
+    for i, msg in enumerate(intro_messages, 1):
+        print(f"\n[Conversation Round {i}]")
+        print(f"👤 User: {msg}")
+        
+        # Have conversation
+        response = agent.chat(msg)
+        print(f"🤖 Assistant: {response[:150]}..." if len(response) > 150 else f"🤖 Assistant: {response}")
+        
+        # Trigger memory processing after each conversation
+        processor.increment_conversation_count()
+        
+        print(f"\n📝 Processing memory after conversation {i}...")
+        results = processor.process_recent_conversations()
+        
+        # Display memory operations
+        operations = results.get('operations', [])
+        if operations:
+            print("\nMemory Operations:")
+            for j, op in enumerate(operations, 1):
+                icon = {'add': '➕', 'update': '📝', 'delete': '🗑️'}.get(op['action'], '❓')
+                print(f"  {j}. {icon} {op['action'].upper()}: {op.get('content', '')[:80]}...")
+        else:
+            print("  ℹ️ No memory updates needed")
+        
+        summary = results.get('summary', {})
+        if any(summary.values()):
+            print(f"  Summary: {summary.get('added', 0)} added, {summary.get('updated', 0)} updated")
+    
+    # Show current memory state
+    print("\n" + "="*40)
+    print("💾 MEMORY STATE AFTER SESSION 1")
+    print("="*40)
+    memory_manager = create_memory_manager(user_id, memory_mode)
+    print(memory_manager.get_context_string())
+    
+    # Session 2: Testing memory recall and updates
+    print("\n" + "="*60)
+    print("SESSION 2: MEMORY RECALL & UPDATES")
+    print("="*60)
+    
+    # Start new conversation session
+    agent.reset_session()
+    print("🔄 Started new conversation session\n")
+    
+    recall_messages = [
+        "What do you remember about my work and preferences?",
+        "Actually, I recently switched from PyTorch to JAX for better performance.",
+        "Can you recommend tools for my recommendation system based on what you know about me?"
+    ]
+    
+    for i, msg in enumerate(recall_messages, 1):
+        print(f"\n[Conversation Round {i}]")
+        print(f"👤 User: {msg}")
+        
+        # Have conversation
+        response = agent.chat(msg)
+        
+        # Show full response for memory recall questions
+        if "remember" in msg.lower() or "recommend" in msg.lower():
+            print(f"🤖 Assistant: {response}")
+        else:
+            print(f"🤖 Assistant: {response[:150]}..." if len(response) > 150 else f"🤖 Assistant: {response}")
+        
+        # Trigger memory processing
+        processor.increment_conversation_count()
+        
+        print(f"\n📝 Processing memory after conversation {i}...")
+        results = processor.process_recent_conversations()
+        
+        # Display memory operations
+        operations = results.get('operations', [])
+        if operations:
+            print("\nMemory Operations:")
+            for j, op in enumerate(operations, 1):
+                icon = {'add': '➕', 'update': '📝', 'delete': '🗑️'}.get(op['action'], '❓')
+                content = op.get('content', op.get('memory_id', 'N/A'))
+                print(f"  {j}. {icon} {op['action'].upper()}: {content[:80]}...")
+                if op.get('reason'):
+                    print(f"     Reason: {op['reason'][:80]}...")
+        else:
+            print("  ℹ️ No memory updates needed")
+        
+        summary = results.get('summary', {})
+        if any(summary.values()):
+            print(f"  Summary: {summary.get('added', 0)} added, {summary.get('updated', 0)} updated")
+    
+    # Final memory state
+    print("\n" + "="*40)
+    print("💾 FINAL MEMORY STATE")
+    print("="*40)
+    memory_manager = create_memory_manager(user_id, memory_mode)
+    final_memory = memory_manager.get_context_string()
+    print(final_memory if final_memory else "No memories stored")
+    
+    # Summary
+    print("\n" + "="*60)
+    print("✨ QUICK START COMPLETED!")
+    print("="*60)
+    print("\n🎯 Key Features Demonstrated:")
+    print("  • Separated conversation and memory processing")
+    print("  • Memory operations after each conversation round")
+    print("  • Clear list of add/update/delete operations")
+    print("  • Memory persistence across sessions")
+    
+    print("\n📚 Next Steps:")
+    print("  1. Interactive mode: python main.py --mode interactive --user your_name")
+    print("  2. Adjust processing: --conversation-interval 2 (process every 2 conversations)")
+    print("  3. Manual processing: --background-processing False")
+    print("  4. Try JSON cards: --memory-mode json_cards")
+    print("  5. Run full demo: python main.py --mode demo")
+
+
+if __name__ == "__main__":
+    quickstart()