"""Reviewer Agent — bilingual quality check with strongest reasoning model."""

from __future__ import annotations

import json
from typing import Any

from .base import BaseAgent
from app.config import settings


class ReviewerAgent(BaseAgent):
    name = "reviewer"
    description = "双语报告质量审查 — 使用最强推理模型"

    system_prompt = """\
You are a senior consulting partner reviewing a report before client delivery.
The report has both Chinese and English versions (or will be translated).

Review dimensions:
1. **Accuracy** — Are data points, percentages, and claims supported by the research?
   Cross-check global claims against English research, Chinese claims against Chinese research.
2. **Logical consistency** — Does the narrative flow? Are there contradictions between chapters?
3. **Depth of analysis** — Is it consultancy-grade or just surface-level? Would a C-suite exec find it valuable?
4. **Bilingual quality** — If translated version exists, check for translation artifacts,
   mistranslated terminology, or cultural mismatches.
5. **Data gaps honesty** — Are uncertainties acknowledged or are claims fabricated?
6. **Completeness** — Are any critical aspects of the requirement left unaddressed?

Scoring guide:
- 90+: Publication-ready
- 80-89: Minor issues, can pass with notes
- 70-79: Needs revision (verdict: revise)
- <70: Significant problems (verdict: reject)

Output (JSON):
{
  "overall_score": 85,
  "verdict": "pass|revise|reject",
  "issues": [
    {
      "severity": "high|medium|low",
      "chapter": "affected chapter",
      "dimension": "accuracy|consistency|depth|bilingual|gaps|completeness",
      "description": "issue description",
      "suggestion": "specific fix suggestion"
    }
  ],
  "strengths": ["what the report does well"],
  "summary": "Overall assessment (2-3 sentences)"
}"""

    def __init__(self):
        super().__init__(model=settings.model_for_domain("reasoning"))

    async def run(self, context: dict[str, Any]) -> dict[str, Any]:
        draft = context["draft"]
        draft_translated = context.get("draft_translated", {})
        research = context["research"]

        sections = [
            "## Research Plan (what was asked)",
            json.dumps(research, ensure_ascii=False, indent=2),
            "",
            "## Primary Draft",
            json.dumps(draft, ensure_ascii=False, indent=2),
        ]

        if draft_translated:
            sections.extend([
                "",
                "## Translated Version",
                json.dumps(draft_translated, ensure_ascii=False, indent=2),
            ])

        prompt = "\n".join(sections) + "\n\nReview the report. Output JSON."

        result = await self.call_llm_json(prompt, max_tokens=4096)
        return {"review": result}