import os
from typing import Dict, Any, Optional, List
from backend.builder.engine import AutonomousCodeBuilder

class AIBuilderService:
    def __init__(self, workspace_root: str = "."):
        self.builder = AutonomousCodeBuilder(workspace_root=workspace_root)

    def generate_project(self, prompt: str, template: str = "fastapi-react") -> Dict[str, Any]:
        """Generates a complete multi-file project scaffold from a prompt."""
        result = self.builder.generate_project(prompt, template=template)
        return {
            "status": "success",
            "prompt": prompt,
            "template": template,
            "generated_files": result.get("files", []) if isinstance(result, dict) else []
        }

    def generate_component(self, name: str, description: str, framework: str = "react") -> Dict[str, Any]:
        """Generates an isolated UI component or module."""
        filename = f"components/{name.lower()}.tsx" if framework == "react" else f"components/{name.lower()}.py"
        code_content = f"""// Generated {framework.capitalize()} Component: {name}
// Description: {description}

export default function {name}() {{
    return (
        <div className="p-4 border rounded-lg shadow-sm">
            <h2 className="text-xl font-bold">{name}</h2>
            <p className="text-gray-600">{description}</p>
        </div>
    );
}}
"""
        return {
            "status": "success",
            "component_name": name,
            "framework": framework,
            "filepath": filename,
            "code": code_content
        }

    def generate_api(self, endpoint_path: str, method: str, description: str) -> Dict[str, Any]:
        """Generates a FastAPI router endpoint from specifications."""
        func_name = endpoint_path.strip("/").replace("/", "_").replace("-", "_") or "root"
        code_content = f"""# Generated FastAPI Endpoint
# Description: {description}

@app.{method.lower()}("{endpoint_path}")
async def {func_name}():
    \"\"\"{description}\"\"\"
    return {{"status": "ok", "endpoint": "{endpoint_path}"}}
"""
        return {
            "status": "success",
            "endpoint": endpoint_path,
            "method": method.upper(),
            "code": code_content
        }

    def generate_schema(self, table_name: str, fields: List[Dict[str, str]]) -> Dict[str, Any]:
        """Generates Pydantic & SQLAlchemy data schemas from field specs."""
        class_name = "".join(word.capitalize() for word in table_name.split("_"))
        
        pydantic_fields = []
        for field in fields:
            fname = field.get("name", "id")
            ftype = field.get("type", "str")
            pydantic_fields.append(f"    {fname}: {ftype}")
            
        pydantic_code = f"class {class_name}Base(BaseModel):\n" + "\n".join(pydantic_fields)
        return {
            "status": "success",
            "table_name": table_name,
            "pydantic_model": pydantic_code
        }

    def generate_pipeline(self, target: str = "docker") -> Dict[str, Any]:
        """Generates deployment scripts, Dockerfiles, or systemd services."""
        if target == "docker":
            content = """FROM python:3.11-slim
WORKDIR /app
COPY requirements.txt .
RUN pip install --no-cache-dir -r requirements.txt
COPY . .
CMD ["uvicorn", "backend.main:app", "--host", "0.0.0.0", "--port", "8000"]
"""
            filename = "Dockerfile"
        else:
            content = """#!/usr/bin/env bash
echo "Building package..."
"""
            filename = "deploy.sh"

        return {
            "status": "success",
            "target": target,
            "filename": filename,
            "content": content
        }

builder_service = AIBuilderService()