SKAP Implementation Guide

pip install selenium openai anthropic beautifulsoup4 pandas numpy playwright
playwright install chromium

import os
from selenium import webdriver
from selenium.webdriver.chrome.options import Options
from openai import OpenAI
import json
import time
from typing import List, Dict, Any, Optional

class SKAPConfig:
    def __init__(self):
        self.openai_client = OpenAI(api_key=os.getenv("OPENAI_API_KEY"))
        self.chrome_options = Options()
        self.chrome_options.add_argument("--headless")
        self.chrome_options.add_argument("--no-sandbox")
        self.chrome_options.add_argument("--disable-dev-shm-usage")
        
    def create_driver(self):
        return webdriver.Chrome(options=self.chrome_options)

from selenium.webdriver.common.by import By
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
from bs4 import BeautifulSoup
import random

class SKAPLearner:
    def __init__(self, config: SKAPConfig):
        self.config = config
        self.driver = config.create_driver()
        self.observations = []
        
    def explore_environment(self, target_url: str, max_interactions: int = 50):
        """Autonomous exploration of target environment"""
        self.driver.get(target_url)
        time.sleep(2)
        
        # Initial page analysis
        dom_structure = self.analyze_dom_structure()
        ui_elements = self.catalog_interactive_elements()
        
        # Systematic interaction
        for interaction in range(max_interactions):
            try:
                # Select unexplored element
                target_element = self.select_exploration_target(ui_elements)
                if not target_element:
                    break
                    
                # Perform interaction
                action_result = self.interact_with_element(target_element)
                
                # Record observation
                observation = {
                    'action': action_result['action'],
                    'element': target_element,
                    'context': self.extract_context(),
                    'outcome': action_result['outcome'],
                    'timestamp': time.time(),
                    'page_url': self.driver.current_url
                }
                self.observations.append(observation)
                
                # Wait for page changes
                time.sleep(1)
                
            except Exception as e:
                print("Exploration error:", e)
                continue
                
        return self.observations

import json
from collections import defaultdict, Counter
from datetime import datetime

class SKAPTranslator:
    def __init__(self, config: SKAPConfig):
        self.config = config
        
    def extract_skills(self, observations: List[Dict]) -> Dict:
        """Extract structured skills from exploration observations"""
        # Analyze interaction patterns
        patterns = self.analyze_interaction_patterns(observations)
        
        # Identify successful workflows
        workflows = self.extract_successful_workflows(observations)
        
        # Define domain expertise
        expertise = self.define_domain_expertise(observations)
        
        # Generate adapter
        return self.generate_skap_adapter(patterns, workflows, expertise)

class SKAPExecutor:
    def __init__(self, adapter_path: str, config: SKAPConfig):
        self.config = config
        self.driver = config.create_driver()
        self.adapter = self.load_skap_adapter(adapter_path)
        self.skills = self.initialize_skills()
        
    def execute_task(self, task_description: str, context: Dict = None) -> Dict:
        """Execute task using SKAP adapter guidance"""
        try:
            # Apply role-specific context
            self.set_execution_context()
            
            # Generate execution plan using LLM with adapter context
            execution_plan = self.plan_with_expertise(task_description, context)
            
            # Execute with skill-guided actions
            result = self.execute_with_skills(execution_plan)
            
            # Validate using domain knowledge
            validation = self.validate_with_domain_knowledge(result)
            
            return {
                'success': True,
                'result': result,
                'validation': validation,
                'execution_time': time.time()
            }
            
        except Exception as e:
            return {
                'success': False,
                'error': str(e),
                'execution_time': time.time()
            }

# Install MiniWoB++
pip install miniwob-plusplus

import gym
import miniwob
from miniwob.action import ActionTypes
import numpy as np

class MiniWoBSKAPEvaluator:
    def __init__(self, skap_executor: SKAPExecutor):
        self.skap_executor = skap_executor
        self.env = None
        
    def evaluate_skap_performance(self, task_name: str, num_episodes: int = 100):
        """Evaluate SKAP performance on MiniWoB++ task"""
        env = self.setup_environment(task_name)
        
        results = {
            'task': task_name,
            'episodes': num_episodes,
            'successes': 0,
            'total_reward': 0.0,
            'episode_results': []
        }