from llmops.config import prompt_path
from llmops.base import (
    Step,
    AbstractOperation,
    Judgement4GPT,
    ExecutionResult
)
from llmops.utils.llm_client import LlmClient, LlmConfig
from llmops.business.business_expert import BusinessExpert
from typing import Dict, Any


class TargetMatcher:
    """Check if the last step matches the target operation"""

    def __init__(self, business_expert: BusinessExpert, model: str):
        self.system_prompt_template = prompt_path / "is_target_ready.md"
        # self.business_expert = business_expert
        self.llm_client = LlmClient(self.system_prompt_template, llm_config=LlmConfig(model=model))
        self.trajectory = []

    def matches(self, last_step: Step, response: ExecutionResult, target: AbstractOperation) -> Judgement4GPT:
        user_prompt = {
            "last_request": {
                "operation_id": last_step.operation_id,
                "request": last_step.request.model_dump(),
            },
            "last_response": response.model_dump(),
            "expect": last_step.expect,
            "target_operation": target.model_dump(),
        }
        result = self.llm_client.generate(user_prompt, Judgement4GPT)
        self.trajectory.append(
            {
                "input": {
                    "last_step": last_step.model_dump(),
                    "target_operation": target.model_dump(),
                },
                "output": result.model_dump(),
            }
        )
        return result

    def get_trajectory(self) -> Dict[str, Any]:
        """Get the trajectory of target matching process"""
        return self.trajectory