python-template/backend/example_gemini_usage.py

#!/usr/bin/env python3
"""
Gemini 3 Pro 数学试卷解析示例
展示如何使用 Gemini 模型进行数学试卷解析
"""

import os
import json
from dotenv import load_dotenv
from claude_exam_parser import ClaudeExamParser

# 加载环境变量
load_dotenv()


def example_1_basic_usage():
    """示例1: 基本使用 - 使用 Gemini 解析数学试卷"""
    print("=" * 80)
    print("示例1: 使用 Gemini 3 Pro 解析数学试卷")
    print("=" * 80)

    # 创建解析器，明确指定使用 Gemini 模型
    parser = ClaudeExamParser(
        model="google/gemini-3-pro-preview"
    )

    # 解析数学试卷
    # 注意：请替换为实际的试卷文件路径
    result = parser.parse_exam_file(
        file_path="sample_math_exam.pdf",  # 替换为实际文件
        subject="数学",
        grade="高一"
    )

    if result["success"]:
        data = result["result"]
        print(f"\n✅ 解析成功！")
        print(f"学科: {data['subject']}")
        print(f"年级: {data.get('grade', 'N/A')}")
        print(f"题目总数: {data['total_questions']}")
        print(f"\n前3道题目:")

        for q in data["questions"][:3]:
            print(f"\n  题目 {q['number']} ({q['type']})")
            print(f"  题干: {q['question'][:100]}...")
            if q.get("formulas"):
                print(f"  公式: {q['formulas'][:2]}")
            print(f"  难度: {q.get('difficulty', 'N/A')}")
    else:
        print(f"\n❌ 解析失败: {result['error']}")


def example_2_compare_models():
    """示例2: 对比不同模型的解析效果"""
    print("\n\n" + "=" * 80)
    print("示例2: 对比 Claude 和 Gemini 的解析效果")
    print("=" * 80)

    file_path = "sample_math_exam.pdf"  # 替换为实际文件
    models = [
        "anthropic/claude-sonnet-4.5",
        "google/gemini-3-pro-preview"
    ]

    results = {}

    for model in models:
        print(f"\n正在使用 {model} 解析...")
        parser = ClaudeExamParser(model=model)
        result = parser.parse_exam_file(file_path, subject="数学")

        if result["success"]:
            data = result["result"]
            # 统计公式数量
            formula_count = sum(
                len(q.get("formulas", []))
                for q in data.get("questions", [])
            )
            results[model] = {
                "total_questions": data.get("total_questions", 0),
                "formula_count": formula_count
            }
            print(f"  ✅ 识别题目: {results[model]['total_questions']}")
            print(f"  ✅ 提取公式: {results[model]['formula_count']}")
        else:
            print(f"  ❌ 解析失败: {result['error']}")

    print(f"\n对比结果:")
    print(json.dumps(results, indent=2, ensure_ascii=False))


def example_3_extract_formulas():
    """示例3: 提取并分析数学公式"""
    print("\n\n" + "=" * 80)
    print("示例3: 提取并分析数学公式")
    print("=" * 80)

    parser = ClaudeExamParser(model="google/gemini-3-pro-preview")
    result = parser.parse_exam_file(
        file_path="sample_math_exam.pdf",  # 替换为实际文件
        subject="数学"
    )

    if result["success"]:
        data = result["result"]
        all_formulas = []

        # 收集所有公式
        for q in data["questions"]:
            formulas = q.get("formulas", [])
            if formulas:
                all_formulas.extend([
                    {
                        "question_number": q["number"],
                        "formula": f
                    }
                    for f in formulas
                ])

        print(f"\n找到 {len(all_formulas)} 个公式:")
        for i, item in enumerate(all_formulas[:10], 1):  # 显示前10个
            print(f"{i}. 题目 {item['question_number']}: {item['formula']}")

        # 分析公式类型
        formula_types = {
            "分数": 0,
            "根式": 0,
            "积分": 0,
            "求和": 0,
            "向量": 0
        }

        for item in all_formulas:
            formula = item["formula"]
            if "\\frac" in formula:
                formula_types["分数"] += 1
            if "\\sqrt" in formula:
                formula_types["根式"] += 1
            if "\\int" in formula:
                formula_types["积分"] += 1
            if "\\sum" in formula:
                formula_types["求和"] += 1
            if "\\vec" in formula or "\\overrightarrow" in formula:
                formula_types["向量"] += 1

        print(f"\n公式类型分布:")
        for ftype, count in formula_types.items():
            if count > 0:
                print(f"  {ftype}: {count}")


def example_4_analyze_difficulty():
    """示例4: 分析题目难度分布"""
    print("\n\n" + "=" * 80)
    print("示例4: 分析题目难度分布")
    print("=" * 80)

    parser = ClaudeExamParser(model="google/gemini-3-pro-preview")
    result = parser.parse_exam_file(
        file_path="sample_math_exam.pdf",  # 替换为实际文件
        subject="数学"
    )

    if result["success"]:
        data = result["result"]

        # 难度分布
        difficulty_dist = data.get("stats", {}).get("difficulty_distribution", {})

        if difficulty_dist:
            print(f"\n难度分布:")
            total = sum(difficulty_dist.values())
            for level in sorted(difficulty_dist.keys()):
                count = difficulty_dist[level]
                percentage = (count / total) * 100
                bar = "█" * int(percentage / 5)
                print(f"  难度 {level}: {count:2d} 题 ({percentage:5.1f}%) {bar}")

        # 按难度分组题目
        by_difficulty = {}
        for q in data["questions"]:
            diff = q.get("difficulty", 0)
            if diff not in by_difficulty:
                by_difficulty[diff] = []
            by_difficulty[diff].append(q["number"])

        print(f"\n各难度题目编号:")
        for level in sorted(by_difficulty.keys()):
            questions = by_difficulty[level]
            print(f"  难度 {level}: {', '.join(map(str, questions))}")


def example_5_knowledge_points():
    """示例5: 分析知识点覆盖"""
    print("\n\n" + "=" * 80)
    print("示例5: 分析知识点覆盖")
    print("=" * 80)

    parser = ClaudeExamParser(model="google/gemini-3-pro-preview")
    result = parser.parse_exam_file(
        file_path="sample_math_exam.pdf",  # 替换为实际文件
        subject="数学"
    )

    if result["success"]:
        data = result["result"]

        # 统计知识点
        knowledge_point_count = {}

        for q in data["questions"]:
            points = q.get("knowledge_points", [])
            for point in points:
                knowledge_point_count[point] = knowledge_point_count.get(point, 0) + 1

        # 按出现频率排序
        sorted_points = sorted(
            knowledge_point_count.items(),
            key=lambda x: x[1],
            reverse=True
        )

        print(f"\n知识点覆盖 (共 {len(sorted_points)} 个知识点):")
        for point, count in sorted_points[:15]:  # 显示前15个
            bar = "●" * count
            print(f"  {point:20s}: {count:2d} 题 {bar}")


def main():
    """主函数 - 运行所有示例"""
    print("\n")
    print("╔" + "=" * 78 + "╗")
    print("║" + " " * 20 + "Gemini 3 Pro 数学试卷解析示例" + " " * 28 + "║")
    print("╚" + "=" * 78 + "╝")

    # 检查 API Key
    if not os.getenv("OPENROUTER_API_KEY"):
        print("\n❌ 错误: 未设置 OPENROUTER_API_KEY")
        print("请在 .env 文件中设置，或运行: export OPENROUTER_API_KEY='your-key'")
        return

    # 运行示例（注意：需要实际的PDF文件）
    print("\n⚠️  注意: 这些示例需要实际的PDF试卷文件")
    print("请将 'sample_math_exam.pdf' 替换为实际的文件路径\n")

    # 可以取消注释运行各个示例
    # example_1_basic_usage()
    # example_2_compare_models()
    # example_3_extract_formulas()
    # example_4_analyze_difficulty()
    # example_5_knowledge_points()

    print("\n使用说明:")
    print("1. 准备一份数学试卷 PDF 文件")
    print("2. 编辑此文件，将 'sample_math_exam.pdf' 替换为实际文件路径")
    print("3. 取消注释要运行的示例")
    print("4. 运行: python example_gemini_usage.py")
    print("\n或者直接使用测试脚本:")
    print("  ./quick_test_gemini.sh your_math_exam.pdf 数学 高一")


if __name__ == "__main__":
    main()