from __future__ import annotations

from typing import Any, Dict

from .stages import PipelineStages


class GenerationOrchestrator:
    def __init__(self, generator: Any):
        self.stages = PipelineStages(generator)

    async def generate(self, user_prompt: str) -> Dict:
        understanding = self.stages.stage1_task_understanding(user_prompt)
        context = self.stages.stage2_context_binding(user_prompt, understanding)
        
        if understanding.scene_mode == "simple":
            draft = self.stages.stage3_macro_planning(user_prompt, understanding, context)
            return self.stages.stage6_validate_and_postprocess(user_prompt, understanding, context, draft, draft.llm_raw_json)
        
        # Round 1: 宏观规划
        draft = self.stages.stage3_macro_planning(user_prompt, understanding, context)
        
        # Middleware: 动态依赖解析
        resolved_data = self.stages.stage4_middleware_resolution(draft)
        
        # Round 2: 微观填参
        final_tree = self.stages.stage5_micro_filling(draft, resolved_data, understanding)
        
        # 验证与后处理
        return self.stages.stage6_validate_and_postprocess(user_prompt, understanding, context, draft, final_tree)