from tech_wizard.tech_kb import TechKnowledgeBase
from tech_wizard.openai_module import OpenAIClient
import os
import json

class TechWizardTools:
    def __init__(self, openai_api_key=None):
        self.kb = TechKnowledgeBase()
        self.llm = OpenAIClient(api_key=openai_api_key or os.getenv("OPENAI_API_KEY"))

    def architect_system(self, requirements: str) -> str:
        """Design a technical system architecture."""
        kb_context = self.kb.get_info("architecture")
        prompt = f"""
        Requirements: {requirements}
        Architecture Patterns Knowledge: {json.dumps(kb_context, indent=2)}
        
        Please design a technical architecture. Include:
        1. Recommended Pattern (e.g., Microservices vs Monolith).
        2. Technology Stack (Frontend, Backend, DB, Cache).
        3. A Mermaid.js diagram representing the system.
        4. Scalability and Security considerations.
        """
        return self.llm.chat(prompt)

    def design_api(self, features: str) -> str:
        """Design a secure and versioned API surface."""
        kb_context = self.kb.get_info("api")
        prompt = f"""
        Feature Requirements: {features}
        API Best Practices: {json.dumps(kb_context, indent=2)}
        
        Design a REST or GraphQL API surface. Include:
        1. Endpoint paths and methods.
        2. Request/Response schemas (JSON).
        3. Authentication/Authorization strategy.
        4. Error handling logic.
        """
        return self.llm.chat(prompt)

    def setup_webhooks(self, source_platform: str) -> str:
        """Generate secure webhook handler logic."""
        kb_context = self.kb.get_info("webhooks")
        prompt = f"""
        Source Platform (e.g., Stripe, GitHub, Shopify): {source_platform}
        Webhook Knowledge: {json.dumps(kb_context, indent=2)}
        
        Generate a secure webhook handler (Python/FastAPI or Node.js). 
        Must include signature verification, idempotency, and asynchronous processing.
        """
        return self.llm.chat(prompt)

    def configure_routing(self, domain: str, app_details: str) -> str:
        """Design DNS and routing configuration."""
        kb_context = self.kb.get_info("domains")
        prompt = f"""
        Domain: {domain}
        App/Infrastructure Details: {app_details}
        Routing Knowledge: {json.dumps(kb_context, indent=2)}
        
        Provide a DNS configuration plan (A, CNAME, TXT records) and SSL/TLS strategy.
        """
        return self.llm.chat(prompt)