#!/usr/bin/env python3
"""
交互式Gold Standard标注工具
通过问答方式完成标注，无需写代码
"""

import sys
sys.path.insert(0, '/home/xzq/gene-family-mas-v2')

from evaluation.gold_standard_annotator import GoldStandardAnnotator
import json


def print_header(text):
    print("\n" + "="*60)
    print(text)
    print("="*60)


def get_input(prompt, default=None):
    """获取用户输入"""
    if default:
        full_prompt = f"{prompt} [{default}]: "
    else:
        full_prompt = f"{prompt}: "
    
    value = input(full_prompt).strip()
    return value if value else default


def select_from_list(prompt, options):
    """从列表中选择"""
    print(f"\n{prompt}")
    for i, opt in enumerate(options, 1):
        print(f"  {i}. {opt}")
    
    while True:
        choice = input(f"选择 (1-{len(options)}): ").strip()
        try:
            idx = int(choice) - 1
            if 0 <= idx < len(options):
                return options[idx]
        except:
            pass
        print("无效选择，请重试")


def yes_no(prompt, default=True):
    """是/否问题"""
    default_str = "Y/n" if default else "y/N"
    while True:
        answer = input(f"{prompt} [{default_str}]: ").strip().lower()
        if not answer:
            return default
        if answer in ['y', 'yes']:
            return True
        if answer in ['n', 'no']:
            return False
        print("请输入 y 或 n")


def interactive_annotate():
    """交互式标注主流程"""
    
    print_header("GeneFamily-RAG Gold Standard 交互式标注")
    print("\n这个工具会引导你完成论文的人工标注")
    print("标注结果将用于评估自动提取的准确率\n")
    
    # ========== 步骤1：论文信息 ==========
    print_header("步骤1：论文基本信息")
    
    doc_id = get_input("论文ID（如pmid31286919）", "pmid31286919")
    pmid = get_input("PMID", "31286919")
    doi = get_input("DOI", "10.1186/s12870-019-1916-6")
    species = get_input("物种拉丁名", "Fagopyrum tataricum")
    species_cn = get_input("物种中文名", "苦荞")
    family = get_input("基因家族", "SPL")
    year = get_input("发表年份", "2019")
    
    # ========== 步骤2：读取论文文本 ==========
    print_header("步骤2：论文文本")
    
    text_source = select_from_list(
        "选择文本来源",
        ["从PDF自动提取", "手动粘贴文本", "从文件读取"]
    )
    
    text = ""
    if text_source == "从PDF自动提取":
        pdf_path = get_input("PDF文件路径", 
            "/home/xzq/gene-family-mas-v2/paper/test_v2_reproduce/input/苦荞SPL2019BMCplantbios12870-019-1916-6.pdf")
        try:
            import fitz
            doc = fitz.open(pdf_path)
            # 只提取前3页（Abstract + Results开头）
            for page in doc[:3]:
                text += page.get_text()
            doc.close()
            print(f"✓ 已提取 {len(text)} 字符")
        except Exception as e:
            print(f"✗ 提取失败: {e}")
            text = get_input("请手动粘贴论文文本（Abstract + Results开头）")
    
    elif text_source == "手动粘贴文本":
        print("请粘贴论文文本（Abstract + Results开头，按Ctrl+D结束）：")
        lines = []
        try:
            while True:
                line = input()
                lines.append(line)
        except EOFError:
            pass
        text = "\n".join(lines)
    
    else:  # 从文件读取
        file_path = get_input("文本文件路径")
        with open(file_path, 'r', encoding='utf-8') as f:
            text = f.read()
    
    if len(text) < 100:
        print("✗ 文本太短，请重新运行")
        return
    
    print(f"✓ 文本长度: {len(text)} 字符")
    print(f"预览: {text[:200]}...")
    
    # ========== 步骤3：创建标注器 ==========
    annotator = GoldStandardAnnotator(
        doc_id=doc_id,
        text=text,
        title=get_input("论文标题", "Genome-wide identification of SPL gene family")
    )
    
    annotator.set_metadata(
        pmid=pmid,
        doi=doi,
        species=species,
        family=family
    )
    
    # ========== 步骤4：标注实体 ==========
    print_header("步骤3：标注实体")
    print("请从论文中识别关键实体（基因、家族、结构域、组织等）\n")
    
    entity_types = [
        "gene", "protein", "gene_family", "protein_domain", "motif",
        "organism", "tissue", "developmental_stage", "treatment", 
        "phenotype", "assay", "method"
    ]
    
    entity_count = 0
    while yes_no("是否添加新实体?", True):
        entity_count += 1
        print(f"\n--- 实体 #{entity_count} ---")
        
        entity_id = get_input("实体ID（如FtSPL1、SPL、PF03110）")
        if not entity_id:
            break
            
        entity_name = get_input("实体名称", entity_id)
        entity_type = select_from_list("实体类型", entity_types)
        
        entity_species = None
        if entity_type in ['gene', 'protein']:
            entity_species = get_input("所属物种", species)
        
        primary_id = get_input("稳定外部ID（如UniProt、PFAM编号，可选）", "")
        description = get_input("描述（可选）", "")
        
        # 添加到标注器
        annotator.add_entity(
            id=entity_id,
            name=entity_name,
            type=entity_type,
            species=entity_species,
            primary_id=primary_id if primary_id else None,
            description=description if description else None
        )
        
        print(f"✓ 已添加: {entity_id} ({entity_type})")
    
    print(f"\n共标注 {len(annotator.entities)} 个实体")
    
    # ========== 步骤5：标注关系 ==========
    print_header("步骤4：标注关系")
    print("请标注实体之间的生物学关系\n")
    
    relation_types = [
        "member_of", "contains", "expressed_in", "involved_in",
        "activates", "inhibits", "regulates", "orthologous_to",
        "paralogous_to", "classified_into", "belongs_to"
    ]
    
    # 显示已标注的实体供选择
    print("已标注的实体:")
    for e in annotator.entities:
        print(f"  - {e.id} ({e.type})")
    
    relation_count = 0
    while yes_no("是否添加新关系?", relation_count < 3):
        relation_count += 1
        print(f"\n--- 关系 #{relation_count} ---")
        
        source = get_input("源实体ID")
        target = get_input("目标实体ID")
        rel_type = select_from_list("关系类型", relation_types)
        confidence = select_from_list("置信度", ["high", "medium", "low"])
        
        # 证据信息
        print("\n证据信息（原文片段）:")
        snippet = get_input("原文关键句子（50字以内）")
        section = select_from_list("所在章节", 
            ["abstract", "introduction", "results", "discussion", "figure_legend"])
        
        evidence_level = "experiment"
        if confidence in ["high", "medium"]:
            evidence_level = select_from_list("证据等级",
                ["experiment", "omics", "prediction", "curation"])
        
        method = get_input("实验/分析方法（如qRT-PCR、RNA-seq）", "")
        
        # 添加到标注器
        annotator.add_relation(
            source=source,
            target=target,
            type=rel_type,
            confidence=confidence,
            text_snippet=snippet,
            section=section,
            evidence_level=evidence_level,
            method=method if method else None
        )
        
        print(f"✓ 已添加: {source} --[{rel_type}]--> {target}")
    
    print(f"\n共标注 {len(annotator.relations)} 个关系")
    
    # ========== 步骤6：关键发现 ==========
    print_header("步骤5：关键发现")
    print("请总结论文的主要发现（一句话一条）\n")
    
    finding_count = 0
    while yes_no("是否添加关键发现?", finding_count < 3):
        finding_count += 1
        finding = get_input(f"关键发现 #{finding_count}")
        if finding:
            annotator.add_key_finding(finding)
            print(f"✓ 已添加")
    
    # ========== 步骤7：验证和保存 ==========
    print_header("步骤6：验证和保存")
    
    # 显示摘要
    annotator.print_summary()
    
    # 验证
    issues = annotator.validate()
    if issues:
        print("\n⚠️ 发现问题:")
        for issue in issues:
            print(f"  - {issue}")
        if not yes_no("是否仍要保存?"):
            print("已取消保存")
            return
    
    # 保存
    default_output = f"/home/xzq/gene-family-mas-v2/evaluation/gold_standard/{doc_id}_manual.json"
    output_path = get_input("保存路径", default_output)
    
    annotator.save(output_path)
    
    print_header("标注完成！")
    print(f"✓ Gold Standard已保存: {output_path}")
    print(f"\n下一步:")
    print(f"  1. 运行自动提取: python extract_with_llm.py ...")
    print(f"  2. 对比评估: python evaluation/evaluate.py --gold {output_path} --pred <auto_result>")


if __name__ == "__main__":
    try:
        interactive_annotate()
    except KeyboardInterrupt:
        print("\n\n已中断")
    except Exception as e:
        print(f"\n✗ 错误: {e}")
        import traceback
        traceback.print_exc()