from __future__ import annotations

from typing import Any

from engine.config import AppConfig
from engine.script_gen import generate_scenes, refine_scene

from .base import BaseLLM


class OpenAIAdapter(BaseLLM):
    def __init__(self, cfg: AppConfig):
        self.cfg = cfg

    def generate_script(self, prompt: str, context: dict[str, Any] | None = None):
        # Existing script_gen already enforces JSON schema and length constraints.
        return generate_scenes(prompt, self.cfg)

    def refine_scene(self, scene: Any, context: dict[str, Any] | None = None):
        if context is None:
            context = {}
        # Context carries needed values to call refine_scene in script_gen.
        scenes = context.get("scenes")
        prompt2 = context.get("prompt")
        target_index = context.get("target_index")
        if scenes is None or prompt2 is None or target_index is None:
            raise ValueError("OpenAIAdapter.refine_scene missing context: scenes/prompt/target_index")
        return refine_scene(prompt=prompt2, scenes=scenes, target_index=int(target_index), cfg=self.cfg)