import os
from pydantic import BaseModel
from common.utils import get_env
from integrations.llm.schemas.report import (
    ReportInput, ReportOutput,
    CriticalIssuesInput, CriticalIssuesOutput,
    YouTubeDiagnosisInput, YouTubeDiagnosisOutput,
    BrandConsistencyInput, BrandConsistencyOutput,
    TransformationInput, TransformationProposal,
    RoadmapInput, RoadmapOutput,
)
from integrations.llm.schemas.plan import PlanInput, PlanOutput
from integrations.llm.schemas.market import (
    MarketCompetitorsInput, MarketCompetitorsOutput,
    MarketKeywordsInput, MarketKeywordsOutput,
    MarketTrendInput, MarketTrendOutput,
    MarketTargetAudienceInput, MarketTargetAudienceOutput,
)

_PROMPT_DIR = os.path.join(os.path.dirname(__file__), "temp-prompt")


class Prompt:
    file_name: str
    prompt_model: str
    input_class: type[BaseModel]
    output_class: type[BaseModel]

    def __init__(self, file_name: str, prompt_model: str, input_class: type[BaseModel], output_class: type[BaseModel]):
        self.file_name = file_name
        self.prompt_model = prompt_model
        self.input_class = input_class
        self.output_class = output_class
        self.template, self.model = self._load_prompt()

    def _load_prompt(self) -> tuple[str, str]:
        with open(os.path.join(_PROMPT_DIR, self.file_name), encoding="utf-8") as f:
            template = f.read()
        return template, get_env(self.prompt_model)

    def _reload_prompt(self):
        self.template, self.model = self._load_prompt()

    def build(self, input_data: dict) -> str:
        verified = self.input_class(**input_data)
        return self.template.format(**verified.model_dump())


report_prompt = Prompt(
    file_name="report_prompt.txt",
    prompt_model="REPORT_MODEL",
    input_class=ReportInput,
    output_class=ReportOutput,
)

plan_prompt = Prompt(
    file_name="plan_prompt.txt",
    prompt_model="PLAN_MODEL",
    input_class=PlanInput,
    output_class=PlanOutput,
)

market_competitors_prompt = Prompt(
    file_name="market_competitors_prompt.txt",
    prompt_model="MARKET_MODEL",
    input_class=MarketCompetitorsInput,
    output_class=MarketCompetitorsOutput,
)

market_keywords_prompt = Prompt(
    file_name="market_keywords_prompt.txt",
    prompt_model="MARKET_MODEL",
    input_class=MarketKeywordsInput,
    output_class=MarketKeywordsOutput,
)

market_trend_prompt = Prompt(
    file_name="market_trend_prompt.txt",
    prompt_model="MARKET_MODEL",
    input_class=MarketTrendInput,
    output_class=MarketTrendOutput,
)

market_target_audience_prompt = Prompt(
    file_name="market_target_audience_prompt.txt",
    prompt_model="MARKET_MODEL",
    input_class=MarketTargetAudienceInput,
    output_class=MarketTargetAudienceOutput,
)

youtube_diagnosis_prompt = Prompt(
    file_name="youtube_diagnosis_prompt.txt",
    prompt_model="REPORT_MODEL",
    input_class=YouTubeDiagnosisInput,
    output_class=YouTubeDiagnosisOutput,
)

brand_consistency_prompt = Prompt(
    file_name="brand_consistency_prompt.txt",
    prompt_model="REPORT_MODEL",
    input_class=BrandConsistencyInput,
    output_class=BrandConsistencyOutput,
)

critical_issues_prompt = Prompt(
    file_name="critical_issues_prompt.txt",
    prompt_model="REPORT_MODEL",
    input_class=CriticalIssuesInput,
    output_class=CriticalIssuesOutput,
)

transformation_prompt = Prompt(
    file_name="transformation_prompt.txt",
    prompt_model="REPORT_MODEL",
    input_class=TransformationInput,
    output_class=TransformationProposal,
)

roadmap_prompt = Prompt(
    file_name="roadmap_prompt.txt",
    prompt_model="REPORT_MODEL",
    input_class=RoadmapInput,
    output_class=RoadmapOutput,
)