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

chapter9/browser-use-rpa/quickstart.py

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+"""
+Quick start script for the Learning Agent.
+
+This script provides a simple example of how to use the learning agent
+for common tasks.
+"""
+
+import asyncio
+from dotenv import load_dotenv
+from browser_use import ChatOpenAI, ChatGoogle
+from learning_agent import LearningAgent
+from llm_factory import make_llm
+
+# Load environment variables
+load_dotenv()
+
+
+async def example_search():
+    """Example: Search on Google."""
+    print("\n🔍 Example 1: Google Search")
+    print("-" * 40)
+    
+    agent = LearningAgent(
+        task="Go to Google and search for 'browser automation with AI'",
+        llm=make_llm(),
+        knowledge_base_path="./my_knowledge",
+        headless=False  # Show browser
+    )
+    
+    result = await agent.run(max_steps=10)
+    print(f"✅ Completed in {result['execution_time']:.2f}s")
+    print(f"   LLM calls: {result.get('llm_calls', 0)}")
+    print(f"   Workflow reused: {result.get('replay_used', False)}")
+
+
+async def example_weather():
+    """Example: Check weather."""
+    print("\n☀️ Example 2: Weather Check")
+    print("-" * 40)
+    
+    agent = LearningAgent(
+        task="Check the weather forecast for Tokyo",
+        llm=ChatGoogle(model="gemini-3.5-flash"),  # You can use different LLMs
+        knowledge_base_path="./my_knowledge",
+        headless=False
+    )
+    
+    result = await agent.run(max_steps=15)
+    print(f"✅ Completed in {result['execution_time']:.2f}s")
+    
+    # Run again with different city - should be faster!
+    print("\n   Running again for New York...")
+    agent2 = LearningAgent(
+        task="Check the weather forecast for New York",
+        llm=ChatGoogle(model="gemini-3.5-flash"),
+        knowledge_base_path="./my_knowledge",
+        headless=False
+    )
+    
+    result2 = await agent2.run(max_steps=15)
+    print(f"✅ Completed in {result2['execution_time']:.2f}s")
+    
+    if result2.get('replay_used'):
+        speedup = result['execution_time'] / result2['execution_time']
+        print(f"   🚀 {speedup:.1f}x faster with learned workflow!")
+
+
+async def example_custom_task():
+    """Example: Custom task from user input."""
+    print("\n💡 Example 3: Custom Task")
+    print("-" * 40)
+    
+    task = input("Enter your task: ")
+    
+    if not task:
+        task = "Go to Wikipedia and search for 'artificial intelligence'"
+    
+    print(f"\nTask: {task}")
+    
+    agent = LearningAgent(
+        task=task,
+        llm=make_llm(),
+        knowledge_base_path="./my_knowledge",
+        headless=False
+    )
+    
+    result = await agent.run(max_steps=20)
+    
+    print(f"\n✅ Task completed!")
+    print(f"   Success: {result['success']}")
+    print(f"   Time: {result['execution_time']:.2f}s")
+    print(f"   Workflow reused: {result.get('replay_used', False)}")
+    
+    if not result.get('replay_used'):
+        print("\n💡 Tip: Try the same task again - it will be much faster!")
+
+
+def show_knowledge_stats():
+    """Show knowledge base statistics."""
+    from learning_agent import KnowledgeBase
+    
+    print("\n📊 Knowledge Base Statistics")
+    print("-" * 40)
+    
+    kb = KnowledgeBase("./my_knowledge")
+    stats = kb.get_statistics()
+    
+    if stats['total_workflows'] == 0:
+        print("No workflows learned yet. Run some tasks first!")
+    else:
+        for key, value in stats.items():
+            formatted_key = key.replace('_', ' ').title()
+            print(f"   {formatted_key}: {value}")
+        
+        print("\n   Learned workflows:")
+        for workflow in kb.workflows.values():
+            print(f"      • {workflow.intent}")
+            if workflow.success_count > 0:
+                print(f"        (used {workflow.success_count} times)")
+
+
+async def main():
+    """Main menu."""
+    print("=" * 60)
+    print("LEARNING AGENT - QUICK START")
+    print("=" * 60)
+    
+    while True:
+        print("\nOptions:")
+        print("1. Google Search Example")
+        print("2. Weather Check Example")
+        print("3. Custom Task")
+        print("4. Show Knowledge Base Stats")
+        print("5. Exit")
+        
+        choice = input("\nSelect option (1-5): ")
+        
+        if choice == "1":
+            await example_search()
+        elif choice == "2":
+            await example_weather()
+        elif choice == "3":
+            await example_custom_task()
+        elif choice == "4":
+            show_knowledge_stats()
+        elif choice == "5":
+            print("\nGoodbye! 👋")
+            break
+        else:
+            print("Invalid option, please try again.")
+
+
+if __name__ == "__main__":
+    try:
+        asyncio.run(main())
+    except KeyboardInterrupt:
+        print("\n\nInterrupted by user. Goodbye! 👋")