from datetime import datetime

from config import Config
from evaluator import ClaudeEvaluator, evaluate_answer
from models import Answer, InterviewReport, Question, QuestionResult
from reporter import ReportGenerator
from speech import (
    DryRunRecognizer,
    DryRunSynthesizer,
    SpeechRecognizer,
    SpeechSynthesizer,
)


class Interviewer:
    def __init__(self, config: Config, questions: list[Question]):
        self.config = config
        self.questions = questions

        if config.dry_run:
            self.recognizer = DryRunRecognizer()
            self.synthesizer = DryRunSynthesizer()
        else:
            self.recognizer = SpeechRecognizer(
                model_name=config.whisper_model,
                sample_rate=config.sample_rate,
                silence_timeout=config.silence_timeout,
                max_duration=config.max_answer_duration,
            )
            self.synthesizer = SpeechSynthesizer()

        self.claude = ClaudeEvaluator(
            api_key=config.anthropic_api_key,
            model=config.claude_model,
        )
        self.reporter = ReportGenerator(output_dir=config.output_dir)

    def run(self) -> InterviewReport:
        candidate_name = self._greet()
        results: list[QuestionResult] = []

        for i, question in enumerate(self.questions, start=1):
            print(f"\n--- 質問 {i}/{len(self.questions)} [{question.category}] ---")

            answer = self._ask_question(question)

            if not answer.transcribed_text.strip():
                print("  回答なし。スキップします。")
                answer = Answer(transcribed_text="（回答なし）", audio_duration_sec=0.0)

            print(f"  📝 書き起こし: {answer.transcribed_text}")
            print("  評価中...")

            result = evaluate_answer(question, answer, self.claude)
            results.append(result)

            print(f"  スコア: {result.total_score:.1f}/{question.max_score}点")
            print(f"  💬 {result.ai_feedback}")

            # 追加質問の判定
            if question.follow_up and result.total_score < question.max_score * 0.4:
                follow_up_result = self._ask_follow_up(question, result)
                if follow_up_result:
                    results.append(follow_up_result)

            if i < len(self.questions):
                self.synthesizer.speak("ありがとうございます。次の質問に進みます。")

        self._close()

        total_score = sum(r.total_score for r in results)
        max_possible = sum(r.question.max_score for r in results)
        percentage = total_score / max_possible if max_possible > 0 else 0
        is_passed = percentage >= self.config.pass_threshold

        report = InterviewReport(
            candidate_name=candidate_name,
            interview_date=datetime.now(),
            results=results,
            total_score=total_score,
            max_possible_score=max_possible,
            pass_threshold=self.config.pass_threshold,
            is_passed=is_passed,
        )

        filepath = self.reporter.generate(report)
        self.reporter.print_summary(report)
        print(f"\n📄 レポート保存先: {filepath}")

        return report

    def _greet(self) -> str:
        self.synthesizer.speak(
            "こんにちは。これからAI面接を開始します。"
            "各質問に対して、音声でお答えください。"
            "準備ができましたら、お名前をお聞かせください。"
        )

        print("\n候補者のお名前:")
        if self.config.dry_run:
            name = input("> ").strip()
        else:
            name, _ = self.recognizer.listen()
            name = name.strip()

        if not name:
            name = "名前未入力"

        print(f"候補者: {name}")
        self.synthesizer.speak(f"{name}さん、よろしくお願いいたします。それでは面接を始めましょう。")
        return name

    def _ask_question(self, question: Question) -> Answer:
        self.synthesizer.speak(question.question_text)

        text, duration = self.recognizer.listen()

        # 空の場合は1回リトライ
        if not text.strip():
            self.synthesizer.speak("聞き取れませんでした。もう一度お答えください。")
            text, duration = self.recognizer.listen()

        return Answer(transcribed_text=text, audio_duration_sec=duration)

    def _ask_follow_up(
        self, question: Question, original_result: QuestionResult
    ) -> QuestionResult | None:
        print(f"  📌 追加質問: {question.follow_up}")
        self.synthesizer.speak(question.follow_up)

        text, duration = self.recognizer.listen()
        if not text.strip():
            return None

        print(f"  📝 追加回答: {text}")
        print("  追加回答を評価中...")

        # 追加質問の評価（元の質問の半分の配点）
        follow_up_question = Question(
            id=question.id,
            category=question.category,
            question_text=question.follow_up,
            expected_keywords=question.expected_keywords,
            keyword_weight=question.keyword_weight,
            ai_weight=question.ai_weight,
            improv_weight=question.improv_weight,
            max_score=question.max_score // 2,
            scoring_criteria=question.scoring_criteria + "（追加質問への回答）",
            follow_up="",
        )

        answer = Answer(transcribed_text=text, audio_duration_sec=duration)
        result = evaluate_answer(follow_up_question, answer, self.claude)
        print(f"  追加スコア: {result.total_score:.1f}/{follow_up_question.max_score}点")
        return result

    def _close(self) -> None:
        self.synthesizer.speak(
            "以上で面接は終了です。"
            "本日はお時間をいただきありがとうございました。"
            "結果は後日お知らせいたします。お疲れ様でした。"
        )
        print("\n面接終了。レポートを生成中...")