diff --git a/.idea/.gitignore b/.idea/.gitignore deleted file mode 100644 index 55403b2..0000000 --- a/.idea/.gitignore +++ /dev/null @@ -1,10 +0,0 @@ -# 默认忽略的文件 -/shelf/ -/workspace.xml -/.idea/ -/venv/ -# 基于编辑器的 HTTP 客户端请求 -/httpRequests/ -# Datasource local storage ignored files -/dataSources/ -/dataSources.local.xml diff --git a/.idea/FilesReadSysteam.iml b/.idea/FilesReadSysteam.iml deleted file mode 100644 index cb9d287..0000000 --- a/.idea/FilesReadSysteam.iml +++ /dev/null @@ -1,12 +0,0 @@ - - - - - - - - - - \ No newline at end of file diff --git a/.idea/encodings.xml b/.idea/encodings.xml deleted file mode 100644 index 58e24ac..0000000 --- a/.idea/encodings.xml +++ /dev/null @@ -1,6 +0,0 @@ - - - - - - \ No newline at end of file diff --git a/.idea/inspectionProfiles/profiles_settings.xml b/.idea/inspectionProfiles/profiles_settings.xml deleted file mode 100644 index 105ce2d..0000000 --- a/.idea/inspectionProfiles/profiles_settings.xml +++ /dev/null @@ -1,6 +0,0 @@ - - - - \ 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b/backend/app/api/__init__.py @@ -0,0 +1,14 @@ +""" +API 路由注册模块 +""" +from fastapi import APIRouter +from app.api.endpoints import upload, ai_analyze, visualization, analysis_charts + +# 创建主路由 +api_router = APIRouter() + +# 注册各模块路由 +api_router.include_router(upload.router) +api_router.include_router(ai_analyze.router) +api_router.include_router(visualization.router) +api_router.include_router(analysis_charts.router) diff --git a/backend/app/api/__pycache__/__init__.cpython-312.pyc b/backend/app/api/__pycache__/__init__.cpython-312.pyc new file mode 100644 index 0000000..ee51b9a Binary files /dev/null and b/backend/app/api/__pycache__/__init__.cpython-312.pyc differ diff --git a/backend/app/api/endpoints/__pycache__/ai_analyze.cpython-312.pyc b/backend/app/api/endpoints/__pycache__/ai_analyze.cpython-312.pyc new file mode 100644 index 0000000..7ee04aa Binary files /dev/null and b/backend/app/api/endpoints/__pycache__/ai_analyze.cpython-312.pyc differ diff --git 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new file mode 100644 index 0000000..652ab53 Binary files /dev/null and b/backend/app/api/endpoints/__pycache__/visualization.cpython-312.pyc differ diff --git a/backend/app/api/endpoints/ai_analyze.py b/backend/app/api/endpoints/ai_analyze.py new file mode 100644 index 0000000..16e1979 --- /dev/null +++ b/backend/app/api/endpoints/ai_analyze.py @@ -0,0 +1,144 @@ +""" +AI 分析 API 接口 +""" +from fastapi import APIRouter, UploadFile, File, HTTPException, Query, Body +from typing import Optional +import logging + +from app.services.excel_ai_service import excel_ai_service + +logger = logging.getLogger(__name__) + +router = APIRouter(prefix="/ai", tags=["AI 分析"]) + + +@router.post("/analyze/excel") +async def analyze_excel( + file: UploadFile = File(...), + user_prompt: str = Query("", description="用户自定义提示词"), + analysis_type: str = Query("general", description="分析类型: general, summary, statistics, insights"), + parse_all_sheets: bool = Query(False, description="是否分析所有工作表") +): + """ + 上传并使用 AI 分析 Excel 文件 + + Args: + file: 上传的 Excel 文件 + user_prompt: 用户自定义提示词 + analysis_type: 分析类型 + parse_all_sheets: 是否分析所有工作表 + + Returns: + dict: 分析结果，包含 Excel 数据和 AI 分析结果 + """ + # 检查文件类型 + if not file.filename: + raise HTTPException(status_code=400, detail="文件名为空") + + file_ext = file.filename.split('.')[-1].lower() + if file_ext not in ['xlsx', 'xls']: + raise HTTPException( + status_code=400, + detail=f"不支持的文件类型: {file_ext}，仅支持 .xlsx 和 .xls" + ) + + # 验证分析类型 + supported_types = ['general', 'summary', 'statistics', 'insights'] + if analysis_type not in supported_types: + raise HTTPException( + status_code=400, + detail=f"不支持的分析类型: {analysis_type}，支持的类型: {', '.join(supported_types)}" + ) + + try: + # 读取文件内容 + content = await file.read() + + logger.info(f"开始分析文件: {file.filename}, 分析类型: {analysis_type}") + + # 调用 AI 分析服务 + if parse_all_sheets: + result = await excel_ai_service.batch_analyze_sheets( + content, + file.filename, + user_prompt=user_prompt, + analysis_type=analysis_type + ) + else: + # 解析选项 + parse_options = {"header_row": 0} + + result = await excel_ai_service.analyze_excel_file( + content, + file.filename, + user_prompt=user_prompt, + analysis_type=analysis_type, + parse_options=parse_options + ) + + logger.info(f"文件分析完成: {file.filename}, 成功: {result['success']}") + + return result + + except HTTPException: + raise + except Exception as e: + logger.error(f"AI 分析过程中出错: {str(e)}") + raise HTTPException(status_code=500, detail=f"分析失败: {str(e)}") + + +@router.get("/analysis/types") +async def get_analysis_types(): + """ + 获取支持的分析类型列表 + + Returns: + list: 支持的分析类型 + """ + return { + "types": excel_ai_service.get_supported_analysis_types() + } + + +@router.post("/analyze/text") +async def analyze_text( + excel_data: dict = Body(..., description="Excel 解析后的数据"), + user_prompt: str = Body("", description="用户提示词"), + analysis_type: str = Body("general", description="分析类型") +): + """ + 对已解析的 Excel 数据进行 AI 分析 + + Args: + excel_data: Excel 数据 + user_prompt: 用户提示词 + analysis_type: 分析类型 + + Returns: + dict: 分析结果 + """ + try: + logger.info(f"开始文本分析, 分析类型: {analysis_type}") + + # 调用 LLM 服务 + from app.services.llm_service import llm_service + + if user_prompt and user_prompt.strip(): + result = await llm_service.analyze_with_template( + excel_data, + user_prompt + ) + else: + result = await llm_service.analyze_excel_data( + excel_data, + user_prompt, + analysis_type + ) + + logger.info(f"文本分析完成, 成功: {result['success']}") + + return result + + except Exception as e: + logger.error(f"文本分析失败: {str(e)}") + raise HTTPException(status_code=500, detail=f"分析失败: {str(e)}") diff --git a/backend/app/api/endpoints/analysis_charts.py b/backend/app/api/endpoints/analysis_charts.py new file mode 100644 index 0000000..e5b281c --- /dev/null +++ b/backend/app/api/endpoints/analysis_charts.py @@ -0,0 +1,105 @@ +""" +分析结果图表 API - 根据文本分析结果生成图表 +""" +from fastapi import APIRouter, HTTPException +from pydantic import BaseModel +from typing import Optional +import logging + +from app.services.text_analysis_service import text_analysis_service +from app.services.chart_generator_service import chart_generator_service + +logger = logging.getLogger(__name__) + +router = APIRouter(prefix="/analysis", tags=["分析结果图表"]) + + +class AnalysisChartRequest(BaseModel): + """分析图表生成请求模型""" + analysis_text: str + original_filename: Optional[str] = "" + file_type: Optional[str] = "text" + + +@router.post("/extract-and-chart") +async def extract_and_generate_charts(request: AnalysisChartRequest): + """ + 从 AI 分析结果中提取数据并生成图表 + + Args: + request: 包含分析文本的请求 + + Returns: + dict: 包含图表数据的结果 + """ + if not request.analysis_text or not request.analysis_text.strip(): + raise HTTPException(status_code=400, detail="分析文本不能为空") + + try: + logger.info("开始从分析结果中提取结构化数据...") + + # 1. 使用 LLM 提取结构化数据 + extract_result = await text_analysis_service.extract_structured_data( + analysis_text=request.analysis_text, + original_filename=request.original_filename or "unknown", + file_type=request.file_type or "text" + ) + + if not extract_result.get("success"): + raise HTTPException( + status_code=500, + detail=f"提取结构化数据失败: {extract_result.get('error', '未知错误')}" + ) + + logger.info("结构化数据提取成功，开始生成图表...") + + # 2. 根据提取的数据生成图表 + chart_result = chart_generator_service.generate_charts_from_analysis(extract_result) + + if not chart_result.get("success"): + raise HTTPException( + status_code=500, + detail=f"生成图表失败: {chart_result.get('error', '未知错误')}" + ) + + logger.info("图表生成成功") + + return chart_result + + except HTTPException: + raise + except Exception as e: + logger.error(f"分析结果图表生成失败: {str(e)}") + raise HTTPException( + status_code=500, + detail=f"图表生成失败: {str(e)}" + ) + + +@router.post("/analyze-text") +async def analyze_text_only(request: AnalysisChartRequest): + """ + 仅提取结构化数据（不生成图表），用于调试 + + Args: + request: 包含分析文本的请求 + + Returns: + dict: 提取的结构化数据 + """ + if not request.analysis_text or not request.analysis_text.strip(): + raise HTTPException(status_code=400, detail="分析文本不能为空") + + try: + result = await text_analysis_service.extract_structured_data( + analysis_text=request.analysis_text, + original_filename=request.original_filename or "unknown", + file_type=request.file_type or "text" + ) + return result + except Exception as e: + logger.error(f"文本分析失败: {str(e)}") + raise HTTPException( + status_code=500, + detail=f"文本分析失败: {str(e)}" + ) diff --git a/backend/app/api/endpoints/upload.py b/backend/app/api/endpoints/upload.py new file mode 100644 index 0000000..dbf17c1 --- /dev/null +++ b/backend/app/api/endpoints/upload.py @@ -0,0 +1,205 @@ +""" +文件上传 API 接口 +""" +from fastapi import APIRouter, UploadFile, File, HTTPException, Query +from fastapi.responses import StreamingResponse +from typing import Optional +import logging +import pandas as pd +import io + +from app.services.file_service import file_service +from app.core.document_parser import XlsxParser + +logger = logging.getLogger(__name__) + +router = APIRouter(prefix="/upload", tags=["文件上传"]) + +# 初始化解析器 +excel_parser = XlsxParser() + + +@router.post("/excel") +async def upload_excel( + file: UploadFile = File(...), + parse_all_sheets: bool = Query(False, description="是否解析所有工作表"), + sheet_name: Optional[str] = Query(None, description="指定解析的工作表名称"), + header_row: int = Query(0, description="表头所在的行索引") +): + """ + 上传并解析 Excel 文件 + + Args: + file: 上传的 Excel 文件 + parse_all_sheets: 是否解析所有工作表 + sheet_name: 指定解析的工作表名称 + header_row: 表头所在的行索引 + + Returns: + dict: 解析结果 + """ + # 检查文件类型 + if not file.filename: + raise HTTPException(status_code=400, detail="文件名为空") + + file_ext = file.filename.split('.')[-1].lower() + if file_ext not in ['xlsx', 'xls']: + raise HTTPException( + status_code=400, + detail=f"不支持的文件类型: {file_ext}，仅支持 .xlsx 和 .xls" + ) + + try: + # 读取文件内容 + content = await file.read() + + # 保存文件 + saved_path = file_service.save_uploaded_file( + content, + file.filename, + subfolder="excel" + ) + + logger.info(f"文件已保存: {saved_path}") + + # 解析文件 + if parse_all_sheets: + result = excel_parser.parse_all_sheets(saved_path) + else: + # 如果指定了 sheet_name，使用指定的，否则使用默认的第一个 + if sheet_name: + result = excel_parser.parse(saved_path, sheet_name=sheet_name, header_row=header_row) + else: + result = excel_parser.parse(saved_path, header_row=header_row) + + # 添加文件路径到元数据 + if result.metadata: + result.metadata['saved_path'] = saved_path + result.metadata['original_filename'] = file.filename + + return result.to_dict() + + except HTTPException: + raise + except Exception as e: + logger.error(f"解析 Excel 文件时出错: {str(e)}") + raise HTTPException(status_code=500, detail=f"解析失败: {str(e)}") + + +@router.get("/excel/preview/{file_path:path}") +async def get_excel_preview( + file_path: str, + sheet_name: Optional[str] = Query(None, description="工作表名称"), + max_rows: int = Query(10, description="最多返回的行数", ge=1, le=100) +): + """ + 获取 Excel 文件的预览数据 + + Args: + file_path: 文件路径 + sheet_name: 工作表名称 + max_rows: 最多返回的行数 + + Returns: + dict: 预览数据 + """ + try: + # 解析工作表名称参数 + sheet_param = sheet_name if sheet_name else 0 + + result = excel_parser.get_sheet_preview( + file_path, + sheet_name=sheet_param, + max_rows=max_rows + ) + + return result.to_dict() + + except Exception as e: + logger.error(f"获取预览数据时出错: {str(e)}") + raise HTTPException(status_code=500, detail=f"获取预览失败: {str(e)}") + + +@router.delete("/file") +async def delete_uploaded_file(file_path: str = Query(..., description="要删除的文件路径")): + """ + 删除已上传的文件 + + Args: + file_path: 文件路径 + + Returns: + dict: 删除结果 + """ + try: + success = file_service.delete_file(file_path) + + if success: + return {"success": True, "message": "文件删除成功"} + else: + return {"success": False, "message": "文件不存在或删除失败"} + + except Exception as e: + logger.error(f"删除文件时出错: {str(e)}") + raise HTTPException(status_code=500, detail=f"删除失败: {str(e)}") + + +@router.get("/excel/export/{file_path:path}") +async def export_excel( + file_path: str, + sheet_name: Optional[str] = Query(None, description="工作表名称"), + columns: Optional[str] = Query(None, description="要导出的列，逗号分隔") +): + """ + 导出 Excel 文件（可选择工作表和列） + + Args: + file_path: 原始文件路径 + sheet_name: 工作表名称（可选） + columns: 要导出的列名，逗号分隔（可选） + + Returns: + StreamingResponse: Excel 文件 + """ + try: + # 读取 Excel 文件 + if sheet_name: + df = pd.read_excel(file_path, sheet_name=sheet_name) + else: + df = pd.read_excel(file_path) + + # 如果指定了列，只选择这些列 + if columns: + column_list = [col.strip() for col in columns.split(',')] + # 过滤掉不存在的列 + available_columns = [col for col in column_list if col in df.columns] + if available_columns: + df = df[available_columns] + + # 创建 Excel 文件 + output = io.BytesIO() + with pd.ExcelWriter(output, engine='openpyxl') as writer: + df.to_excel(writer, index=False, sheet_name=sheet_name or 'Sheet1') + + output.seek(0) + + # 生成文件名 + original_name = file_path.split('/')[-1] if '/' in file_path else file_path + if columns: + export_name = f"export_{sheet_name or 'data'}_{len(column_list) if columns else 'all'}_cols.xlsx" + else: + export_name = f"export_{original_name}" + + # 返回文件流 + return StreamingResponse( + io.BytesIO(output.getvalue()), + media_type="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet", + headers={"Content-Disposition": f"attachment; filename={export_name}"} + ) + + except FileNotFoundError: + logger.error(f"文件不存在: {file_path}") + raise HTTPException(status_code=404, detail="文件不存在") + except Exception as e: + logger.error(f"导出 Excel 文件时出错: {str(e)}") + raise HTTPException(status_code=500, detail=f"导出失败: {str(e)}") diff --git a/backend/app/api/endpoints/visualization.py b/backend/app/api/endpoints/visualization.py new file mode 100644 index 0000000..bc4b9d1 --- /dev/null +++ b/backend/app/api/endpoints/visualization.py @@ -0,0 +1,90 @@ +""" +可视化 API 接口 - 生成统计图表 +""" +from fastapi import APIRouter, HTTPException, Body +from typing import Dict, Any +import logging + +from app.services.visualization_service import visualization_service +from pydantic import BaseModel + +logger = logging.getLogger(__name__) + +router = APIRouter(prefix="/visualization", tags=["数据可视化"]) + + +class StatisticsRequest(BaseModel): + """统计图表生成请求模型""" + excel_data: Dict[str, Any] + analysis_type: str = "statistics" + + +@router.post("/statistics") +async def generate_statistics(request: StatisticsRequest): + """ + 生成统计信息和可视化图表 + + Args: + request: 包含 excel_data 和 analysis_type 的请求体 + + Returns: + dict: 包含统计信息和图表数据的结果 + """ + excel_data = request.excel_data + analysis_type = request.analysis_type + + if not excel_data: + raise HTTPException(status_code=400, detail="未提供 Excel 数据") + + try: + result = visualization_service.analyze_and_visualize( + excel_data, + analysis_type + ) + + if not result.get("success"): + raise HTTPException(status_code=500, detail=result.get("error", "分析失败")) + + logger.info("统计图表生成成功") + + return result + + except HTTPException: + raise + except Exception as e: + logger.error(f"统计图表生成失败: {str(e)}") + raise HTTPException(status_code=500, detail=f"图表生成失败: {str(e)}") + + +@router.get("/chart-types") +async def get_chart_types(): + """ + 获取支持的图表类型 + + Returns: + dict: 支持的图表类型列表 + """ + return { + "chart_types": [ + { + "value": "histogram", + "label": "直方图", + "description": "显示数值型列的分布情况" + }, + { + "value": "bar_chart", + "label": "条形图", + "description": "显示分类列的频次分布" + }, + { + "value": "box_plot", + "label": "箱线图", + "description": "显示数值列的四分位数和异常值" + }, + { + "value": "correlation_heatmap", + "label": "相关性热力图", + "description": "显示数值列之间的相关性" + } + ] + } diff --git a/backend/app/core/document_parser/__init__.py b/backend/app/core/document_parser/__init__.py new file mode 100644 index 0000000..c0707c6 --- /dev/null +++ b/backend/app/core/document_parser/__init__.py @@ -0,0 +1,7 @@ +""" +文档解析模块 - 支持多种文件格式的解析 +""" +from .base import BaseParser +from .xlsx_parser import XlsxParser + +__all__ = ['BaseParser', 'XlsxParser'] diff --git 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new file mode 100644 index 0000000..9ab19e6 --- /dev/null +++ b/backend/app/core/document_parser/base.py @@ -0,0 +1,87 @@ +""" +解析器基类 - 定义所有解析器的通用接口 +""" +from abc import ABC, abstractmethod +from typing import Any, Dict, List, Optional +from pathlib import Path + + +class ParseResult: + """解析结果类""" + + def __init__( + self, + success: bool, + data: Optional[Dict[str, Any]] = None, + error: Optional[str] = None, + metadata: Optional[Dict[str, Any]] = None + ): + self.success = success + self.data = data or {} + self.error = error + self.metadata = metadata or {} + + def to_dict(self) -> Dict[str, Any]: + """转换为字典""" + return { + "success": self.success, + "data": self.data, + "error": self.error, + "metadata": self.metadata + } + + +class BaseParser(ABC): + """文档解析器基类""" + + def __init__(self): + self.supported_extensions: List[str] = [] + self.parser_name: str = "base_parser" + + @abstractmethod + def parse(self, file_path: str, **kwargs) -> ParseResult: + """ + 解析文件 + + Args: + file_path: 文件路径 + **kwargs: 其他解析参数 + + Returns: + ParseResult: 解析结果 + """ + pass + + def can_parse(self, file_path: str) -> bool: + """ + 检查是否可以解析该文件 + + Args: + file_path: 文件路径 + + Returns: + bool: 是否可以解析 + """ + ext = Path(file_path).suffix.lower() + return ext in self.supported_extensions + + def get_file_info(self, file_path: str) -> Dict[str, Any]: + """ + 获取文件基本信息 + + Args: + file_path: 文件路径 + + Returns: + Dict[str, Any]: 文件信息 + """ + path = Path(file_path) + if not path.exists(): + return {"error": "File not found"} + + return { + "filename": path.name, + "extension": path.suffix.lower(), + "size": path.stat().st_size, + "parser": self.parser_name + } diff --git a/backend/app/core/document_parser/utils.py b/backend/app/core/document_parser/utils.py new file mode 100644 index 0000000..2e861d8 --- /dev/null +++ b/backend/app/core/document_parser/utils.py @@ -0,0 +1,120 @@ +""" +文档解析工具函数 +""" +import re +from typing import List, Optional, Dict, Any + + +def clean_text(text: str) -> str: + """ + 清洗文本，去除多余的空白字符和特殊符号 + + Args: + text: 原始文本 + + Returns: + str: 清洗后的文本 + """ + if not text: + return "" + + # 去除首尾空白 + text = text.strip() + + # 将多个连续的空白字符替换为单个空格 + text = re.sub(r'\s+', ' ', text) + + # 去除不可打印字符 + text = ''.join(char for char in text if char.isprintable() or char in '\n\r\t') + + return text + + +def chunk_text( + text: str, + chunk_size: int = 1000, + overlap: int = 100 +) -> List[str]: + """ + 将文本分块 + + Args: + text: 原始文本 + chunk_size: 每块的大小（字符数） + overlap: 重叠区域的大小 + + Returns: + List[str]: 文本块列表 + """ + if not text: + return [] + + chunks = [] + start = 0 + text_length = len(text) + + while start < text_length: + end = start + chunk_size + chunk = text[start:end] + chunks.append(chunk) + start = end - overlap + + return chunks + + +def normalize_string(s: Any) -> str: + """ + 标准化字符串 + + Args: + s: 输入值 + + Returns: + str: 标准化后的字符串 + """ + if s is None: + return "" + if isinstance(s, (int, float)): + return str(s) + if isinstance(s, str): + return clean_text(s) + return str(s) + + +def detect_encoding(file_path: str) -> Optional[str]: + """ + 检测文件编码（简化版） + + Args: + file_path: 文件路径 + + Returns: + Optional[str]: 编码格式，无法检测则返回 None + """ + import chardet + + try: + with open(file_path, 'rb') as f: + raw_data = f.read(10000) # 读取前 10000 字节 + result = chardet.detect(raw_data) + return result.get('encoding') + except Exception: + return None + + +def safe_get(d: Dict[str, Any], key: str, default: Any = None) -> Any: + """ + 安全地获取字典值 + + Args: + d: 字典 + key: 键 + default: 默认值 + + Returns: + Any: 字典值或默认值 + """ + try: + return d.get(key, default) + except Exception: + return default diff --git a/backend/app/core/document_parser/xlsx_parser.py b/backend/app/core/document_parser/xlsx_parser.py new file mode 100644 index 0000000..f948fd5 --- /dev/null +++ b/backend/app/core/document_parser/xlsx_parser.py @@ -0,0 +1,288 @@ +""" +Excel 文件解析器 - 解析 .xlsx 和 .xls 文件 +""" +from typing import Any, Dict, List, Optional +from pathlib import Path +import pandas as pd +import logging + +from .base import BaseParser, ParseResult + +logger = logging.getLogger(__name__) + + +class XlsxParser(BaseParser): + """Excel 文件解析器""" + + def __init__(self): + super().__init__() + self.supported_extensions = ['.xlsx', '.xls'] + self.parser_name = "excel_parser" + + def parse( + self, + file_path: str, + sheet_name: Optional[str | int] = 0, + header_row: int = 0, + **kwargs + ) -> ParseResult: + """ + 解析 Excel 文件 + + Args: + file_path: 文件路径 + sheet_name: 工作表名称或索引，默认为第一个工作表 + header_row: 表头所在的行索引，默认为 0 + **kwargs: 其他参数传递给 pandas.read_excel + + Returns: + ParseResult: 解析结果 + """ + path = Path(file_path) + + # 检查文件是否存在 + if not path.exists(): + return ParseResult( + success=False, + error=f"File not found: {file_path}" + ) + + # 检查文件扩展名 + if path.suffix.lower() not in self.supported_extensions: + return ParseResult( + success=False, + error=f"Unsupported file type: {path.suffix}" + ) + + # 检查文件大小 + file_size = path.stat().st_size + if file_size == 0: + return ParseResult( + success=False, + error=f"File is empty: {file_path}" + ) + + try: + # 尝试读取 Excel 文件，检查是否有工作表 + xls_file = pd.ExcelFile(file_path) + sheet_names = xls_file.sheet_names + + if not sheet_names: + return ParseResult( + success=False, + error=f"Excel 文件没有找到任何工作表: {file_path}" + ) + + # 验证请求的工作表索引/名称 + target_sheet = None + if sheet_name is not None: + if isinstance(sheet_name, int) and sheet_name < len(sheet_names): + target_sheet = sheet_names[sheet_name] + elif isinstance(sheet_name, str) and sheet_name in sheet_names: + target_sheet = sheet_name + else: + # 如果指定的 sheet_name 无效，使用第一个工作表 + target_sheet = sheet_names[0] + else: + # 默认使用第一个工作表 + target_sheet = sheet_names[0] + + # 读取 Excel 文件 + df = pd.read_excel( + file_path, + sheet_name=target_sheet, + header=header_row, + **kwargs + ) + + # 检查 DataFrame 是否为空 + if df.empty: + return ParseResult( + success=False, + error=f"工作表 '{target_sheet}' 为空，请检查 Excel 文件内容" + ) + + # 转换为可序列化的数据 + data = self._df_to_dict(df) + + # 构建元数据 + metadata = { + "filename": path.name, + "extension": path.suffix.lower(), + "sheet_count": len(sheet_names), + "sheet_names": sheet_names, + "current_sheet": target_sheet, + "row_count": len(df), + "column_count": len(df.columns) if not df.empty else 0, + "columns": df.columns.tolist() if not df.empty else [], + "file_size": file_size + } + + return ParseResult( + success=True, + data=data, + metadata=metadata + ) + + except IndexError as e: + logger.error(f"工作表索引错误: {str(e)}") + # 工作表索引超出范围时，尝试使用第一个工作表 + try: + xls_file = pd.ExcelFile(file_path) + sheet_names = xls_file.sheet_names + if sheet_names: + df = pd.read_excel( + file_path, + sheet_name=sheet_names[0], + header=header_row, + **kwargs + ) + + data = self._df_to_dict(df) + metadata = { + "filename": path.name, + "extension": path.suffix.lower(), + "sheet_count": len(sheet_names), + "sheet_names": sheet_names, + "current_sheet": sheet_names[0], + "row_count": len(df), + "column_count": len(df.columns) if not df.empty else 0, + "columns": df.columns.tolist() if not df.empty else [], + "file_size": path.stat().st_size + } + + return ParseResult( + success=True, + data=data, + metadata=metadata + ) + else: + return ParseResult( + success=False, + error=f"Excel 文件没有有效的工作表" + ) + except Exception as e2: + logger.error(f"重试解析失败: {str(e2)}") + return ParseResult( + success=False, + error=f"无法解析 Excel 文件: {str(e)}" + ) + + except Exception as e: + logger.error(f"解析 Excel 文件时出错: {str(e)}") + return ParseResult( + success=False, + error=f"Failed to parse Excel file: {str(e)}" + ) + + def parse_all_sheets(self, file_path: str, **kwargs) -> ParseResult: + """ + 解析 Excel 文件的所有工作表 + + Args: + file_path: 文件路径 + **kwargs: 其他参数传递给 pandas.read_excel + + Returns: + ParseResult: 解析结果 + """ + path = Path(file_path) + + # 检查文件是否存在 + if not path.exists(): + return ParseResult( + success=False, + error=f"File not found: {file_path}" + ) + + if path.suffix.lower() not in self.supported_extensions: + return ParseResult( + success=False, + error=f"Unsupported file type: {path.suffix}" + ) + + # 检查文件大小 + file_size = path.stat().st_size + if file_size == 0: + return ParseResult( + success=False, + error=f"File is empty: {file_path}" + ) + + try: + # 读取所有工作表 + all_data = pd.read_excel(file_path, sheet_name=None, **kwargs) + + # 检查是否成功读取到数据 + if not all_data or len(all_data) == 0: + return ParseResult( + success=False, + error=f"无法读取 Excel 文件或文件为空: {file_path}" + ) + + # 转换为可序列化的数据 + sheets_data = {} + for sheet_name, df in all_data.items(): + sheets_data[sheet_name] = self._df_to_dict(df) + + # 获取所有工作表名称 + all_sheets = list(all_data.keys()) + + # 构建元数据 + total_rows = sum(len(df) for df in all_data.values()) + metadata = { + "filename": path.name, + "extension": path.suffix.lower(), + "sheet_count": len(all_sheets), + "sheet_names": all_sheets, + "total_rows": total_rows, + "file_size": file_size + } + + return ParseResult( + success=True, + data={"sheets": sheets_data}, + metadata=metadata + ) + + except Exception as e: + logger.error(f"Failed to parse Excel file: {str(e)}") + return ParseResult( + success=False, + error=f"Failed to parse Excel file: {str(e)}" + ) + + def _get_sheet_names(self, file_path: str) -> List[str]: + """获取 Excel 文件中的所有工作表名称""" + try: + xls = pd.ExcelFile(file_path) + sheet_names = xls.sheet_names + if not sheet_names: + return [] + return sheet_names + except Exception as e: + logger.error(f"获取工作表名称失败: {str(e)}") + return [] + + def _df_to_dict(self, df: pd.DataFrame) -> Dict[str, Any]: + """ + 将 DataFrame 转换为字典，处理 NaN 值 + + Args: + df: pandas DataFrame + + Returns: + Dict[str, Any]: 转换后的字典 + """ + # 将 NaN 替换为 None + df = df.replace({pd.NA: None, float('nan'): None}) + + # 转换为字典列表（每一行一个字典） + rows = df.to_dict(orient='records') + + return { + "columns": df.columns.tolist(), + "rows": rows, + "row_count": len(rows), + "column_count": len(df.columns) if not df.empty else 0 + } diff --git a/backend/app/main.py b/backend/app/main.py index 080e5ac..64b4339 100644 --- a/backend/app/main.py +++ b/backend/app/main.py @@ -1,18 +1,61 @@ +""" +FastAPI 应用主入口 +""" from fastapi import FastAPI -from config import settings +from fastapi.middleware.cors import CORSMiddleware +from app.config import settings +from app.api import api_router +# 创建 FastAPI 应用实例 app = FastAPI( title=settings.APP_NAME, - openapi_url=f"{settings.API_V1_STR}/openapi.json" + description="基于大语言模型的文档理解与多源数据融合系统", + version="1.0.0", + openapi_url=f"{settings.API_V1_STR}/openapi.json", + docs_url=f"{settings.API_V1_STR}/docs", + redoc_url=f"{settings.API_V1_STR}/redoc" ) + +# 配置 CORS 中间件 +app.add_middleware( + CORSMiddleware, + allow_origins=["*"], + allow_credentials=True, + allow_methods=["*"], + allow_headers=["*"], +) + +# 注册 API 路由 +app.include_router(api_router, prefix=settings.API_V1_STR) + + @app.get("/") async def root(): + """根路径""" return { "message": f"Welcome to {settings.APP_NAME}", "status": "online", - "debug_mode": 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b/backend/app/services/__pycache__/visualization_service.cpython-313.pyc differ diff --git a/backend/app/services/chart_generator_service.py b/backend/app/services/chart_generator_service.py new file mode 100644 index 0000000..a02f230 --- /dev/null +++ b/backend/app/services/chart_generator_service.py @@ -0,0 +1,349 @@ +""" +图表生成服务 - 根据结构化数据生成图表 +""" +import io +import base64 +import logging +from typing import Dict, Any, List, Optional +from pathlib import Path + +import pandas as pd +import matplotlib.pyplot as plt +import matplotlib +import numpy as np + +# 使用字体辅助模块配置中文字体 +from app.services.font_helper import configure_matplotlib_fonts + +configure_matplotlib_fonts() + +logger = logging.getLogger(__name__) + + +class ChartGeneratorService: + """图表生成服务类""" + + def __init__(self): + self.output_dir = Path(__file__).resolve().parent.parent.parent / "data" / "charts" + self.output_dir.mkdir(parents=True, exist_ok=True) + + def generate_charts_from_analysis( + self, + structured_data: Dict[str, Any] + ) -> Dict[str, Any]: + """ + 根据提取的结构化数据生成图表 + + Args: + structured_data: 从 AI 分析结果中提取的结构化数据 + + Returns: + Dict[str, Any]: 包含图表数据的结果 + """ + if not structured_data.get("success"): + return { + "success": False, + "error": structured_data.get("error", "数据提取失败") + } + + data = structured_data.get("data", {}) + charts = {} + statistics = {} + + try: + # 1. 数值型数据图表 + numeric_data = data.get("numeric_data", []) + if numeric_data: + charts["numeric_charts"] = self._create_numeric_charts(numeric_data) + statistics["numeric_summary"] = self._create_numeric_summary(numeric_data) + + # 2. 分类数据图表 + categorical_data = data.get("categorical_data", []) + if categorical_data: + charts["categorical_charts"] = self._create_categorical_charts(categorical_data) + + # 3. 时间序列图表 + time_series_data = data.get("time_series_data", []) + if time_series_data: + charts["time_series_chart"] = self._create_time_series_chart(time_series_data) + + # 4. 对比数据图表 + comparison_data = data.get("comparison_data", []) + if comparison_data: + charts["comparison_chart"] = self._create_comparison_chart(comparison_data) + + # 5. 表格数据可视化 + table_data = data.get("table_data") + if table_data: + charts["table_preview"] = self._create_table_preview(table_data) + + # 元数据 + metadata = data.get("metadata", {}) + + return { + "success": True, + "charts": charts, + "statistics": statistics, + "metadata": metadata, + "data_source": "ai_analysis" + } + + except Exception as e: + logger.error(f"生成图表失败: {str(e)}", exc_info=True) + return { + "success": False, + "error": str(e) + } + + def _create_numeric_charts(self, numeric_data: List[Dict[str, Any]]) -> List[Dict[str, Any]]: + """创建数值型数据图表""" + charts = [] + + # 提取数值和标签 + names = [item.get("name", f"项{i}") for i, item in enumerate(numeric_data)] + values = [item.get("value", 0) for item in numeric_data] + + if not values: + return charts + + # 1. 柱状图 + try: + fig, ax = plt.subplots(figsize=(12, 7)) + colors = plt.cm.Set3(np.linspace(0, 1, len(values))) + bars = ax.bar(names, values, color=colors, alpha=0.8, edgecolor='black', linewidth=0.5) + + # 添加数值标签 + for bar, value in zip(bars, values): + height = bar.get_height() + ax.text(bar.get_x() + bar.get_width() / 2., height, + f'{value:,.0f}', + ha='center', va='bottom', fontsize=9, fontweight='bold') + + ax.set_xlabel('项目', fontsize=10, labelpad=10, fontweight='bold') + ax.set_ylabel('数值', fontsize=10, labelpad=10, fontweight='bold') + ax.set_title('数值型数据对比', fontsize=12, fontweight='bold', pad=15) + ax.set_xticklabels(names, rotation=30, ha='right', fontsize=9) + ax.tick_params(axis='both', which='major', labelsize=9) + plt.grid(axis='y', alpha=0.3) + plt.tight_layout(pad=1.5) + + img_base64 = self._figure_to_base64(fig) + charts.append({ + "type": "bar", + "title": "数值型数据对比", + "image": img_base64, + "data": [{"name": n, "value": v} for n, v in zip(names, values)] + }) + except Exception as e: + logger.error(f"创建柱状图失败: {str(e)}") + + # 2. 饼图 + if len(values) > 0 and len(values) <= 10: + try: + fig, ax = plt.subplots(figsize=(10, 10)) + wedges, texts, autotexts = ax.pie(values, labels=names, autopct='%1.1f%%', + startangle=90, colors=plt.cm.Set3.colors[:len(values)]) + + for autotext in autotexts: + autotext.set_color('white') + autotext.set_fontsize(9) + autotext.set_fontweight('bold') + + ax.set_title('数值型数据占比', fontsize=12, fontweight='bold', pad=15) + + img_base64 = self._figure_to_base64(fig) + charts.append({ + "type": "pie", + "title": "数值型数据占比", + "image": img_base64, + "data": [{"name": n, "value": v} for n, v in zip(names, values)] + }) + except Exception as e: + logger.error(f"创建饼图失败: {str(e)}") + + return charts + + def _create_categorical_charts(self, categorical_data: List[Dict[str, Any]]) -> List[Dict[str, Any]]: + """创建分类数据图表""" + charts = [] + + # 提取数据 + names = [item.get("name", f"类{i}") for i, item in enumerate(categorical_data)] + counts = [item.get("count", 1) for item in categorical_data] + + if not names or not counts: + return charts + + # 水平条形图 + try: + fig, ax = plt.subplots(figsize=(10, max(6, len(names) * 0.8))) + y_pos = np.arange(len(names)) + + bars = ax.barh(y_pos, counts, align='center', color='#10b981', alpha=0.8, edgecolor='black', linewidth=0.5) + + # 添加数值标签 + for bar, count in zip(bars, counts): + width = bar.get_width() + ax.text(width, bar.get_y() + bar.get_height() / 2., + f'{count}', + ha='left', va='center', fontsize=10, fontweight='bold') + + ax.set_yticks(y_pos) + ax.set_yticklabels(names, fontsize=10) + ax.invert_yaxis() + ax.set_xlabel('数量', fontsize=10, labelpad=10, fontweight='bold') + ax.set_title('分类数据分布', fontsize=12, fontweight='bold', pad=15) + ax.tick_params(axis='both', which='major', labelsize=9) + ax.grid(axis='x', alpha=0.3) + plt.tight_layout(pad=1.5) + + img_base64 = self._figure_to_base64(fig) + charts.append({ + "type": "barh", + "title": "分类数据分布", + "image": img_base64, + "data": [{"name": n, "count": c} for n, c in zip(names, counts)] + }) + except Exception as e: + logger.error(f"创建分类图表失败: {str(e)}") + + return charts + + def _create_time_series_chart(self, time_series_data: List[Dict[str, Any]]) -> Optional[Dict[str, Any]]: + """创建时间序列图表""" + if not time_series_data: + return None + + try: + names = [item.get("name", f"时间{i}") for i, item in enumerate(time_series_data)] + values = [item.get("value", 0) for item in time_series_data] + + if len(values) < 2: + return None + + fig, ax = plt.subplots(figsize=(14, 7)) + + # 绘制折线图和柱状图 + x_pos = np.arange(len(names)) + bars = ax.bar(x_pos, values, width=0.4, label='数值', color='#3b82f6', alpha=0.7) + + # 添加折线 + line = ax.plot(x_pos, values, 'o-', color='#ef4444', linewidth=2.5, markersize=8, label='趋势') + + ax.set_xticks(x_pos) + ax.set_xticklabels(names, rotation=30, ha='right', fontsize=9) + ax.set_ylabel('数值', fontsize=10, labelpad=10, fontweight='bold') + ax.set_title('时间序列数据', fontsize=12, fontweight='bold', pad=15) + ax.legend(loc='best', fontsize=9) + ax.tick_params(axis='both', which='major', labelsize=9) + ax.grid(True, alpha=0.3) + plt.tight_layout(pad=1.5) + + img_base64 = self._figure_to_base64(fig) + return { + "type": "time_series", + "title": "时间序列数据", + "image": img_base64, + "data": [{"name": n, "value": v} for n, v in zip(names, values)] + } + except Exception as e: + logger.error(f"创建时间序列图表失败: {str(e)}") + return None + + def _create_comparison_chart(self, comparison_data: List[Dict[str, Any]]) -> Optional[Dict[str, Any]]: + """创建对比图表""" + if not comparison_data: + return None + + try: + names = [item.get("name", f"对比{i}") for i, item in enumerate(comparison_data)] + values = [item.get("value", 0) for item in comparison_data] + + fig, ax = plt.subplots(figsize=(10, 7)) + + # 区分正负值 + colors = ['#10b981' if v >= 0 else '#ef4444' for v in values] + bars = ax.bar(names, values, color=colors, alpha=0.8, edgecolor='black', linewidth=0.8) + + # 添加数值标签 + for bar, value in zip(bars, values): + height = bar.get_height() + ax.text(bar.get_x() + bar.get_width() / 2., height, + f'{value:,.1f}', + ha='center', va='bottom' if value >= 0 else 'top', + fontsize=10, fontweight='bold') + + # 添加零线 + ax.axhline(y=0, color='black', linestyle='-', linewidth=1) + + ax.set_ylabel('值', fontsize=10, labelpad=10, fontweight='bold') + ax.set_title('对比数据', fontsize=12, fontweight='bold', pad=15) + ax.set_xticklabels(names, rotation=30, ha='right', fontsize=9) + ax.tick_params(axis='both', which='major', labelsize=9) + plt.grid(axis='y', alpha=0.3) + plt.tight_layout(pad=1.5) + + img_base64 = self._figure_to_base64(fig) + return { + "type": "comparison", + "title": "对比数据", + "image": img_base64, + "data": [{"name": n, "value": v} for n, v in zip(names, values)] + } + except Exception as e: + logger.error(f"创建对比图表失败: {str(e)}") + return None + + def _create_table_preview(self, table_data: Dict[str, Any]) -> Dict[str, Any]: + """创建表格预览数据""" + if not table_data: + return {} + + columns = table_data.get("columns", []) + rows = table_data.get("rows", []) + + return { + "columns": columns, + "rows": rows[:50], # 限制显示前50行 + "total_rows": len(rows), + "preview_rows": min(50, len(rows)) + } + + def _create_numeric_summary(self, numeric_data: List[Dict[str, Any]]) -> Dict[str, Any]: + """创建数值型数据摘要""" + values = [item.get("value", 0) for item in numeric_data if isinstance(item.get("value"), (int, float))] + + if not values: + return {} + + return { + "count": len(values), + "sum": float(sum(values)), + "mean": float(np.mean(values)), + "median": float(np.median(values)), + "min": float(min(values)), + "max": float(max(values)), + "std": float(np.std(values)) if len(values) > 1 else 0 + } + + def _figure_to_base64(self, fig) -> str: + """将 matplotlib 图形转换为 base64 字符串""" + buf = io.BytesIO() + fig.savefig( + buf, + format='png', + dpi=120, + bbox_inches='tight', + pad_inches=0.3, + facecolor='white', + edgecolor='none', + transparent=False + ) + plt.close(fig) + buf.seek(0) + img_base64 = base64.b64encode(buf.read()).decode('utf-8') + return f"data:image/png;base64,{img_base64}" + + +# 全局单例 +chart_generator_service = ChartGeneratorService() diff --git a/backend/app/services/excel_ai_service.py b/backend/app/services/excel_ai_service.py new file mode 100644 index 0000000..8f8f36d --- /dev/null +++ b/backend/app/services/excel_ai_service.py @@ -0,0 +1,253 @@ +""" +Excel AI 分析服务 - 集成 Excel 解析和 LLM 分析 +""" +import logging +from typing import Dict, Any, Optional, List + +from app.core.document_parser import XlsxParser +from app.services.file_service import file_service +from app.services.llm_service import llm_service + +logger = logging.getLogger(__name__) + + +class ExcelAIService: + """Excel AI 分析服务""" + + def __init__(self): + self.parser = XlsxParser() + self.file_service = file_service + self.llm_service = llm_service + + async def analyze_excel_file( + self, + file_content: bytes, + filename: str, + user_prompt: str = "", + analysis_type: str = "general", + parse_options: Optional[Dict[str, Any]] = None + ) -> Dict[str, Any]: + """ + 分析 Excel 文件 + + Args: + file_content: 文件内容字节 + filename: 文件名 + user_prompt: 用户自定义提示词 + analysis_type: 分析类型 + parse_options: 解析选项 + + Returns: + Dict[str, Any]: 分析结果 + """ + # 1. 保存文件 + try: + saved_path = self.file_service.save_uploaded_file( + file_content, + filename, + subfolder="excel" + ) + logger.info(f"文件已保存: {saved_path}") + except Exception as e: + logger.error(f"文件保存失败: {str(e)}") + return { + "success": False, + "error": f"文件保存失败: {str(e)}", + "analysis": None + } + + # 2. 解析 Excel 文件 + try: + parse_options = parse_options or {} + parse_result = self.parser.parse(saved_path, **parse_options) + + if not parse_result.success: + return { + "success": False, + "error": parse_result.error, + "analysis": None + } + + excel_data = parse_result.data + logger.info(f"Excel 解析成功: {parse_result.metadata}") + + except Exception as e: + logger.error(f"Excel 解析失败: {str(e)}") + return { + "success": False, + "error": f"Excel 解析失败: {str(e)}", + "analysis": None + } + + # 3. 调用 LLM 进行分析 + try: + # 如果有自定义提示词，使用模板分析 + if user_prompt and user_prompt.strip(): + llm_result = await self.llm_service.analyze_with_template( + excel_data, + user_prompt + ) + else: + # 否则使用标准分析 + llm_result = await self.llm_service.analyze_excel_data( + excel_data, + user_prompt, + analysis_type + ) + + logger.info(f"AI 分析完成: {llm_result['success']}") + + # 4. 组合结果 + return { + "success": True, + "excel": { + "data": excel_data, + "metadata": parse_result.metadata, + "saved_path": saved_path + }, + "analysis": llm_result + } + + except Exception as e: + logger.error(f"AI 分析失败: {str(e)}") + return { + "success": False, + "error": f"AI 分析失败: {str(e)}", + "excel": { + "data": excel_data, + "metadata": parse_result.metadata + }, + "analysis": None + } + + async def batch_analyze_sheets( + self, + file_content: bytes, + filename: str, + user_prompt: str = "", + analysis_type: str = "general" + ) -> Dict[str, Any]: + """ + 批量分析 Excel 文件的所有工作表 + + Args: + file_content: 文件内容字节 + filename: 文件名 + user_prompt: 用户自定义提示词 + analysis_type: 分析类型 + + Returns: + Dict[str, Any]: 分析结果 + """ + # 1. 保存文件 + try: + saved_path = self.file_service.save_uploaded_file( + file_content, + filename, + subfolder="excel" + ) + logger.info(f"文件已保存: {saved_path}") + except Exception as e: + logger.error(f"文件保存失败: {str(e)}") + return { + "success": False, + "error": f"文件保存失败: {str(e)}", + "analysis": None + } + + # 2. 解析所有工作表 + try: + parse_result = self.parser.parse_all_sheets(saved_path) + + if not parse_result.success: + return { + "success": False, + "error": parse_result.error, + "analysis": None + } + + sheets_data = parse_result.data.get("sheets", {}) + logger.info(f"Excel 解析成功，共 {len(sheets_data)} 个工作表") + + except Exception as e: + logger.error(f"Excel 解析失败: {str(e)}") + return { + "success": False, + "error": f"Excel 解析失败: {str(e)}", + "analysis": None + } + + # 3. 批量分析每个工作表 + sheet_analyses = {} + errors = {} + + for sheet_name, sheet_data in sheets_data.items(): + try: + # 调用 LLM 分析 + if user_prompt and user_prompt.strip(): + llm_result = await self.llm_service.analyze_with_template( + sheet_data, + user_prompt + ) + else: + llm_result = await self.llm_service.analyze_excel_data( + sheet_data, + user_prompt, + analysis_type + ) + + sheet_analyses[sheet_name] = llm_result + + if not llm_result["success"]: + errors[sheet_name] = llm_result.get("error", "未知错误") + + logger.info(f"工作表 '{sheet_name}' 分析完成") + + except Exception as e: + logger.error(f"工作表 '{sheet_name}' 分析失败: {str(e)}") + errors[sheet_name] = str(e) + + # 4. 组合结果 + return { + "success": len(errors) == 0, + "excel": { + "sheets": sheets_data, + "metadata": parse_result.metadata, + "saved_path": saved_path + }, + "analysis": { + "sheets": sheet_analyses, + "total_sheets": len(sheets_data), + "successful": len(sheet_analyses) - len(errors), + "errors": errors + } + } + + def get_supported_analysis_types(self) -> List[str]: + """获取支持的分析类型""" + return [ + { + "value": "general", + "label": "综合分析", + "description": "提供数据概览、关键发现、质量评估和建议" + }, + { + "value": "summary", + "label": "数据摘要", + "description": "快速了解数据的结构、范围和主要内容" + }, + { + "value": "statistics", + "label": "统计分析", + "description": "数值型列的统计信息和分类列的分布" + }, + { + "value": "insights", + "label": "深度洞察", + "description": "深入挖掘数据，提供异常值和业务建议" + } + ] + + +# 全局单例 +excel_ai_service = ExcelAIService() diff --git a/backend/app/services/file_service.py b/backend/app/services/file_service.py new file mode 100644 index 0000000..813e26d --- /dev/null +++ b/backend/app/services/file_service.py @@ -0,0 +1,132 @@ +""" +文件服务模块 - 处理文件存储和读取 +""" +import os +import shutil +from pathlib import Path +from datetime import datetime +from typing import Optional +import uuid + +from app.config import settings + + +class FileService: + """文件服务类，负责文件的存储、读取和管理""" + + def __init__(self): + self.upload_dir = Path(settings.UPLOAD_DIR) + self._ensure_upload_dir() + + def _ensure_upload_dir(self): + """确保上传目录存在""" + self.upload_dir.mkdir(parents=True, exist_ok=True) + + def save_uploaded_file( + self, + file_content: bytes, + filename: str, + subfolder: Optional[str] = None + ) -> str: + """ + 保存上传的文件 + + Args: + file_content: 文件内容字节 + filename: 原始文件名 + subfolder: 可选的子文件夹名称 + + Returns: + str: 保存后的文件路径 + """ + # 生成唯一文件名，避免覆盖 + file_ext = Path(filename).suffix + unique_name = f"{uuid.uuid4().hex}{file_ext}" + + # 确定保存路径 + if subfolder: + save_dir = self.upload_dir / subfolder + save_dir.mkdir(parents=True, exist_ok=True) + else: + save_dir = self.upload_dir + + file_path = save_dir / unique_name + + # 写入文件 + with open(file_path, 'wb') as f: + f.write(file_content) + + return str(file_path) + + def read_file(self, file_path: str) -> bytes: + """ + 读取文件内容 + + Args: + file_path: 文件路径 + + Returns: + bytes: 文件内容 + """ + with open(file_path, 'rb') as f: + return f.read() + + def delete_file(self, file_path: str) -> bool: + """ + 删除文件 + + Args: + file_path: 文件路径 + + Returns: + bool: 是否删除成功 + """ + try: + file = Path(file_path) + if file.exists(): + file.unlink() + return True + return False + except Exception: + return False + + def get_file_info(self, file_path: str) -> dict: + """ + 获取文件信息 + + Args: + file_path: 文件路径 + + Returns: + dict: 文件信息 + """ + file = Path(file_path) + if not file.exists(): + return {} + + stat = file.stat() + return { + "filename": file.name, + "filepath": str(file), + "size": stat.st_size, + "created": datetime.fromtimestamp(stat.st_ctime).isoformat(), + "modified": datetime.fromtimestamp(stat.st_mtime).isoformat(), + "extension": file.suffix.lower() + } + + def get_file_size(self, file_path: str) -> int: + """ + 获取文件大小（字节） + + Args: + file_path: 文件路径 + + Returns: + int: 文件大小，文件不存在返回 0 + """ + file = Path(file_path) + return file.stat().st_size if file.exists() else 0 + + +# 全局单例 +file_service = FileService() diff --git a/backend/app/services/font_helper.py b/backend/app/services/font_helper.py new file mode 100644 index 0000000..7298234 --- /dev/null +++ b/backend/app/services/font_helper.py @@ -0,0 +1,105 @@ +""" +字体辅助模块 - 处理中文字体检测和配置 +""" +import matplotlib +import matplotlib.font_manager as fm +import platform +import os +from pathlib import Path +import logging + +logger = logging.getLogger(__name__) + +def get_chinese_font() -> str: + """ + 获取可用的中文字体 + + Returns: + str: 可用的中文字体名称 + """ + # 获取系统中所有可用字体 + available_fonts = set([f.name for f in fm.fontManager.ttflist]) + + # 定义字体优先级列表 + # Windows 优先 + if platform.system() == 'Windows': + font_list = [ + 'Microsoft YaHei', # 微软雅黑 + 'SimHei', # 黑体 + 'SimSun', # 宋体 + 'KaiTi', # 楷体 + 'FangSong', # 仿宋 + 'STXihei', # 华文细黑 + 'STKaiti', # 华文楷体 + 'STSong', # 华文宋体 + 'STFangsong', # 华文仿宋 + ] + # macOS 优先 + elif platform.system() == 'Darwin': + font_list = [ + 'PingFang SC', # 苹方-简 + 'PingFang TC', # 苹方-繁 + 'Heiti SC', # 黑体-简 + 'Heiti TC', # 黑体-繁 + 'STHeiti', # 华文黑体 + 'STSong', # 华文宋体 + 'STKaiti', # 华文楷体 + 'Arial Unicode MS', # Arial Unicode MS + ] + # Linux 优先 + else: + font_list = [ + 'Noto Sans CJK SC', # Noto Sans CJK 简体中文 + 'WenQuanYi Micro Hei', # 文泉驿微米黑 + 'AR PL UMing CN', # AR PL UMing + 'AR PL UKai CN', # AR PL UKai + 'ZCOOL XiaoWei', # ZCOOL 小薇 + ] + + # 通用备选字体 + font_list.extend([ + 'SimHei', + 'Microsoft YaHei', + 'Arial Unicode MS', + 'Droid Sans Fallback', + ]) + + # 查找第一个可用的字体 + for font_name in font_list: + if font_name in available_fonts: + logger.info(f"找到中文字体: {font_name}") + return font_name + + # 如果没找到，尝试获取第一个中文字体 + for font in fm.fontManager.ttflist: + if 'CJK' in font.name or 'SC' in font.name or 'TC' in font.name: + logger.info(f"使用找到的中文字体: {font.name}") + return font.name + + # 最终备选：使用系统默认字体 + logger.warning("未找到合适的中文字体，使用默认字体") + return 'sans-serif' + + +def configure_matplotlib_fonts(): + """ + 配置 matplotlib 的字体设置 + """ + chinese_font = get_chinese_font() + + # 配置字体 + matplotlib.rcParams['font.sans-serif'] = [chinese_font] + matplotlib.rcParams['axes.unicode_minus'] = False + matplotlib.rcParams['figure.dpi'] = 100 + matplotlib.rcParams['savefig.dpi'] = 120 + + # 字体大小设置 + matplotlib.rcParams['font.size'] = 10 + matplotlib.rcParams['axes.labelsize'] = 10 + matplotlib.rcParams['axes.titlesize'] = 11 + matplotlib.rcParams['xtick.labelsize'] = 9 + matplotlib.rcParams['ytick.labelsize'] = 9 + matplotlib.rcParams['legend.fontsize'] = 9 + + logger.info(f"配置完成，使用字体: {chinese_font}") + return chinese_font diff --git a/backend/app/services/llm_service.py b/backend/app/services/llm_service.py new file mode 100644 index 0000000..841d605 --- /dev/null +++ b/backend/app/services/llm_service.py @@ -0,0 +1,268 @@ +""" +LLM 服务模块 - 封装大模型 API 调用 +""" +import logging +from typing import Dict, Any, List, Optional +import httpx + +from app.config import settings + +logger = logging.getLogger(__name__) + + +class LLMService: + """大语言模型服务类""" + + def __init__(self): + self.api_key = settings.LLM_API_KEY + self.base_url = settings.LLM_BASE_URL + self.model_name = settings.LLM_MODEL_NAME + + async def chat( + self, + messages: List[Dict[str, str]], + temperature: float = 0.7, + max_tokens: Optional[int] = None, + **kwargs + ) -> Dict[str, Any]: + """ + 调用聊天 API + + Args: + messages: 消息列表，格式为 [{"role": "user", "content": "..."}] + temperature: 温度参数，控制随机性 + max_tokens: 最大生成 token 数 + **kwargs: 其他参数 + + Returns: + Dict[str, Any]: API 响应结果 + """ + headers = { + "Authorization": f"Bearer {self.api_key}", + "Content-Type": "application/json" + } + + payload = { + "model": self.model_name, + "messages": messages, + "temperature": temperature + } + + if max_tokens: + payload["max_tokens"] = max_tokens + + # 添加其他参数 + payload.update(kwargs) + + try: + async with httpx.AsyncClient(timeout=60.0) as client: + response = await client.post( + f"{self.base_url}/chat/completions", + headers=headers, + json=payload + ) + response.raise_for_status() + return response.json() + + except httpx.HTTPStatusError as e: + logger.error(f"LLM API 请求失败: {e.response.status_code} - {e.response.text}") + raise + except Exception as e: + logger.error(f"LLM API 调用异常: {str(e)}") + raise + + def extract_message_content(self, response: Dict[str, Any]) -> str: + """ + 从 API 响应中提取消息内容 + + Args: + response: API 响应 + + Returns: + str: 消息内容 + """ + try: + return response["choices"][0]["message"]["content"] + except (KeyError, IndexError) as e: + logger.error(f"解析 API 响应失败: {str(e)}") + raise + + async def analyze_excel_data( + self, + excel_data: Dict[str, Any], + user_prompt: str, + analysis_type: str = "general" + ) -> Dict[str, Any]: + """ + 分析 Excel 数据 + + Args: + excel_data: Excel 解析后的数据 + user_prompt: 用户提示词 + analysis_type: 分析类型 (general, summary, statistics, insights) + + Returns: + Dict[str, Any]: 分析结果 + """ + # 构建 Prompt + system_prompt = self._get_system_prompt(analysis_type) + user_message = self._format_user_message(excel_data, user_prompt) + + messages = [ + {"role": "system", "content": system_prompt}, + {"role": "user", "content": user_message} + ] + + try: + response = await self.chat( + messages=messages, + temperature=0.3, # 较低的温度以获得更稳定的输出 + max_tokens=2000 + ) + + content = self.extract_message_content(response) + + return { + "success": True, + "analysis": content, + "model": self.model_name, + "analysis_type": analysis_type + } + + except Exception as e: + logger.error(f"Excel 数据分析失败: {str(e)}") + return { + "success": False, + "error": str(e), + "analysis": None + } + + def _get_system_prompt(self, analysis_type: str) -> str: + """获取系统提示词""" + prompts = { + "general": """你是一个专业的数据分析师。请分析用户提供的 Excel 数据，提供有价值的见解和建议。 + +请按照以下格式输出： +1. 数据概览 +2. 关键发现 +3. 数据质量评估 +4. 建议 + +输出语言：中文""", + "summary": """你是一个专业的数据分析师。请对用户提供的 Excel 数据进行简洁的总结。 + +输出格式： +- 数据行数和列数 +- 主要列的说明 +- 数据范围概述 + +输出语言：中文""", + "statistics": """你是一个专业的数据分析师。请对用户提供的 Excel 数据进行统计分析。 + +请分析： +- 数值型列的统计信息（平均值、中位数、最大值、最小值） +- 分类列的分布情况 +- 数据相关性 + +输出语言：中文，使用表格或结构化格式展示""", + "insights": """你是一个专业的数据分析师。请深入挖掘用户提供的 Excel 数据，提供有价值的洞察。 + +请分析： +1. 数据中的异常值或特殊模式 +2. 数据之间的潜在关联 +3. 基于数据的业务建议 +4. 数据趋势分析（如适用） + +输出语言：中文，提供详细且可操作的建议""" + } + + return prompts.get(analysis_type, prompts["general"]) + + def _format_user_message(self, excel_data: Dict[str, Any], user_prompt: str) -> str: + """格式化用户消息""" + columns = excel_data.get("columns", []) + rows = excel_data.get("rows", []) + row_count = excel_data.get("row_count", 0) + column_count = excel_data.get("column_count", 0) + + # 构建数据描述 + data_info = f""" +Excel 数据概览: +- 行数: {row_count} +- 列数: {column_count} +- 列名: {', '.join(columns)} + +数据样例（前 5 行）: +""" + + # 添加数据样例 + for i, row in enumerate(rows[:5], 1): + row_str = " | ".join([f"{col}: {row.get(col, '')}" for col in columns]) + data_info += f"第 {i} 行: {row_str}\n" + + if row_count > 5: + data_info += f"\n(还有 {row_count - 5} 行数据...)\n" + + # 添加用户自定义提示 + if user_prompt and user_prompt.strip(): + data_info += f"\n用户需求:\n{user_prompt}" + else: + data_info += "\n用户需求: 请对上述数据进行分析" + + return data_info + + async def analyze_with_template( + self, + excel_data: Dict[str, Any], + template_prompt: str + ) -> Dict[str, Any]: + """ + 使用自定义模板分析 Excel 数据 + + Args: + excel_data: Excel 解析后的数据 + template_prompt: 自定义提示词模板 + + Returns: + Dict[str, Any]: 分析结果 + """ + system_prompt = """你是一个专业的数据分析师。请根据用户提供的自定义提示词分析 Excel 数据。 + +请严格按照用户的要求进行分析，输出清晰、有条理的结果。 + +输出语言：中文""" + + user_message = self._format_user_message(excel_data, template_prompt) + + messages = [ + {"role": "system", "content": system_prompt}, + {"role": "user", "content": user_message} + ] + + try: + response = await self.chat( + messages=messages, + temperature=0.5, + max_tokens=3000 + ) + + content = self.extract_message_content(response) + + return { + "success": True, + "analysis": content, + "model": self.model_name, + "is_template": True + } + + except Exception as e: + logger.error(f"自定义模板分析失败: {str(e)}") + return { + "success": False, + "error": str(e), + "analysis": None + } + + +# 全局单例 +llm_service = LLMService() diff --git a/backend/app/services/text_analysis_service.py b/backend/app/services/text_analysis_service.py new file mode 100644 index 0000000..f218b54 --- /dev/null +++ b/backend/app/services/text_analysis_service.py @@ -0,0 +1,218 @@ +""" +文本分析服务 - 从 AI 分析结果中提取结构化数据用于可视化 +""" +import logging +from typing import Dict, Any, List, Optional +import re +import json + +from app.services.llm_service import llm_service + +logger = logging.getLogger(__name__) + + +class TextAnalysisService: + """文本分析服务类""" + + def __init__(self): + self.llm_service = llm_service + + async def extract_structured_data( + self, + analysis_text: str, + original_filename: str = "", + file_type: str = "text" + ) -> Dict[str, Any]: + """ + 从 AI 分析结果文本中提取结构化数据 + + Args: + analysis_text: AI 分析结果文本 + original_filename: 原始文件名 + file_type: 文件类型 + + Returns: + Dict[str, Any]: 提取的结构化数据 + """ + # 限制分析的文本长度，避免 token 超限 + max_text_length = 8000 + truncated_text = analysis_text[:max_text_length] + + system_prompt = """你是一个专业的数据提取助手。你的任务是从AI分析结果中提取结构化数据，用于生成图表。 + +请按照以下要求提取数据： + +1. 数值型数据： + - 提取所有的数值、统计信息、百分比等 + - 为每个数值创建一个条目，包含：名称、值、单位（如果有） + - 格式示例：{"name": "销售额", "value": 123456.78, "unit": "元"} + +2. 分类数据： + - 提取所有的类别、状态、枚举值等 + - 为每个类别创建一个条目，包含：名称、值、数量（如果有） + - 格式示例：{"name": "产品类别", "value": "电子产品", "count": 25} + +3. 时间序列数据： + - 提取所有的时间相关数据（年月、季度、日期等） + - 格式示例：{"name": "2025年1月", "value": 12345} + +4. 对比数据： + - 提取所有的对比、排名、趋势等数据 + - 格式示例：{"name": "同比增长", "value": 15.3, "unit": "%"} + +5. 表格数据： + - 如果分析结果中包含表格或列表形式的数据，提取出来 + - 格式：{"columns": ["列1", "列2"], "rows": [{"列1": "值1", "列2": "值2"}]} + +重要规则： +- 只提取明确提到的数据和数值 +- 如果某种类型的数据不存在，返回空数组 [] +- 确保所有数值都是有效的数字类型 +- 保持数据的原始精度 +- 返回的 JSON 必须完整且格式正确 +- 表格数据最多提取 20 行 + +请以 JSON 格式返回，不要添加任何 Markdown 标记或解释文字，只返回纯 JSON： +{ + "success": true, + "data": { + "numeric_data": [ + {"name": string, "value": number, "unit": string|null} + ], + "categorical_data": [ + {"name": string, "value": string, "count": number|null} + ], + "time_series_data": [ + {"name": string, "value": number} + ], + "comparison_data": [ + {"name": string, "value": number, "unit": string|null} + ], + "table_data": { + "columns": string[], + "rows": object[] + } | null + }, + "metadata": { + "total_items": number, + "data_types": string[] + } +}""" + + user_message = f"""请从以下 AI 分析结果中提取结构化数据： + +原始文件名：{original_filename} +文件类型：{file_type} + +AI 分析结果： +{truncated_text} + +请按照系统提示的要求提取数据并返回纯 JSON 格式。""" + + messages = [ + {"role": "system", "content": system_prompt}, + {"role": "user", "content": user_message} + ] + + try: + logger.info(f"开始提取结构化数据，文本长度: {len(truncated_text)}") + + response = await self.llm_service.chat( + messages=messages, + temperature=0.1, + max_tokens=4000 + ) + + content = self.llm_service.extract_message_content(response) + logger.info(f"LLM 返回内容长度: {len(content)}") + + # 使用简单的方法提取 JSON + result = self._extract_json_simple(content) + + if not result: + logger.error("无法从 LLM 响应中提取有效的 JSON") + return { + "success": False, + "error": "AI 返回的数据格式不正确或被截断", + "raw_content": content[:500] + } + + logger.info(f"成功提取结构化数据") + return result + + except Exception as e: + logger.error(f"提取结构化数据失败: {str(e)}") + return { + "success": False, + "error": str(e) + } + + def _extract_json_simple(self, content: str) -> Optional[Dict[str, Any]]: + """ + 简化的 JSON 提取方法 + + Args: + content: LLM 返回的内容 + + Returns: + Optional[Dict[str, Any]]: 解析后的 JSON，失败返回 None + """ + try: + # 方法 1: 查找 ```json 代码块 + code_block_match = re.search(r'```json\n{[\s\S]*?}[\s\S]*?}\n```', content, re.DOTALL) + if code_block_match: + json_str = code_block_match.group(1) + logger.info("从代码块中提取 JSON") + return json.loads(json_str) + + # 方法 2: 查找第一个完整的 { } 对象 + brace_count = 0 + json_start = -1 + + for i in range(len(content)): + if content[i] == '{': + if brace_count == 0: + json_start = i + brace_count += 1 + elif content[i] == '}': + brace_count -= 1 + if brace_count == 0: + # 找到了完整的 JSON 对象 + json_end = i + 1 + json_str = content[json_start:json_end] + logger.info(f"从大括号中提取 JSON") + return json.loads(json_str) + + # 方法 3: 尝试直接解析 + logger.info("尝试直接解析整个内容") + return json.loads(content) + + except json.JSONDecodeError as e: + logger.error(f"JSON 解析失败: {str(e)}") + logger.error(f"原始内容（前 500 字符）: {content[:500]}...") + return None + except Exception as e: + logger.error(f"提取 JSON 失败: {str(e)}") + return None + + def detect_data_types(self, data: Dict[str, Any]) -> List[str]: + """检测数据中包含的类型""" + types = [] + d = data.get("data", {}) + + if d.get("numeric_data") and len(d["numeric_data"]) > 0: + types.append("numeric") + if d.get("categorical_data") and len(d["categorical_data"]) > 0: + types.append("categorical") + if d.get("time_series_data") and len(d["time_series_data"]) > 0: + types.append("time_series") + if d.get("comparison_data") and len(d["comparison_data"]) > 0: + types.append("comparison") + if d.get("table_data") and d["table_data"]: + types.append("table") + + return types + + +# 全局单例 +text_analysis_service = TextAnalysisService() diff --git a/backend/app/services/text_analysis_service_fixed.py b/backend/app/services/text_analysis_service_fixed.py new file mode 100644 index 0000000..e69de29 diff --git a/backend/app/services/visualization_service.py b/backend/app/services/visualization_service.py new file mode 100644 index 0000000..6cacae7 --- /dev/null +++ b/backend/app/services/visualization_service.py @@ -0,0 +1,388 @@ +""" +数据可视化服务 - 使用 matplotlib/plotly 生成统计图表 +""" +import io +import base64 +import logging +from typing import Dict, Any, List, Optional, Union +from pathlib import Path + +import pandas as pd +import matplotlib.pyplot as plt +import matplotlib +import numpy as np + +# 使用字体辅助模块配置中文字体 +from app.services.font_helper import configure_matplotlib_fonts + +configure_matplotlib_fonts() + +logger = logging.getLogger(__name__) + + +class VisualizationService: + """数据可视化服务类""" + + def __init__(self): + self.output_dir = Path(__file__).resolve().parent.parent.parent / "data" / "charts" + self.output_dir.mkdir(parents=True, exist_ok=True) + + def analyze_and_visualize( + self, + excel_data: Dict[str, Any], + analysis_type: str = "statistics" + ) -> Dict[str, Any]: + """ + 分析数据并生成可视化图表 + + Args: + excel_data: Excel 解析后的数据 + analysis_type: 分析类型 + + Returns: + Dict[str, Any]: 包含图表数据和统计信息的结果 + """ + try: + columns = excel_data.get("columns", []) + rows = excel_data.get("rows", []) + + if not columns or not rows: + return { + "success": False, + "error": "没有数据可用于分析" + } + + # 转换为 DataFrame + df = pd.DataFrame(rows, columns=columns) + + # 根据列类型分类 + numeric_columns = df.select_dtypes(include=[np.number]).columns.tolist() + categorical_columns = df.select_dtypes(exclude=[np.number]).columns.tolist() + + # 生成统计信息 + statistics = self._generate_statistics(df, numeric_columns, categorical_columns) + + # 生成图表 + charts = self._generate_charts(df, numeric_columns, categorical_columns) + + # 生成数据分布信息 + distributions = self._generate_distributions(df, categorical_columns) + + return { + "success": True, + "statistics": statistics, + "charts": charts, + "distributions": distributions, + "row_count": len(df), + "column_count": len(columns) + } + + except Exception as e: + logger.error(f"可视化分析失败: {str(e)}", exc_info=True) + return { + "success": False, + "error": str(e) + } + + def _generate_statistics( + self, + df: pd.DataFrame, + numeric_columns: List[str], + categorical_columns: List[str] + ) -> Dict[str, Any]: + """生成统计信息""" + statistics = { + "numeric": {}, + "categorical": {} + } + + # 数值型列统计 + for col in numeric_columns: + try: + stats = { + "count": int(df[col].count()), + "mean": float(df[col].mean()), + "median": float(df[col].median()), + "std": float(df[col].std()) if df[col].count() > 1 else 0, + "min": float(df[col].min()), + "max": float(df[col].max()), + "q25": float(df[col].quantile(0.25)), + "q75": float(df[col].quantile(0.75)), + "missing": int(df[col].isna().sum()) + } + statistics["numeric"][col] = stats + except Exception as e: + logger.warning(f"列 {col} 统计失败: {str(e)}") + + # 分类型列统计 + for col in categorical_columns: + try: + value_counts = df[col].value_counts() + stats = { + "unique": int(df[col].nunique()), + "most_common": str(value_counts.index[0]) if len(value_counts) > 0 else "", + "most_common_count": int(value_counts.iloc[0]) if len(value_counts) > 0 else 0, + "missing": int(df[col].isna().sum()), + "distribution": {str(k): int(v) for k, v in value_counts.items()} + } + statistics["categorical"][col] = stats + except Exception as e: + logger.warning(f"列 {col} 统计失败: {str(e)}") + + return statistics + + def _generate_charts( + self, + df: pd.DataFrame, + numeric_columns: List[str], + categorical_columns: List[str] + ) -> Dict[str, Any]: + """生成图表""" + charts = {} + + # 1. 数值型列的直方图 + charts["histograms"] = [] + for col in numeric_columns[:5]: # 限制最多 5 个数值列 + chart_data = self._create_histogram(df[col], col) + if chart_data: + charts["histograms"].append(chart_data) + + # 2. 分类型列的条形图 + charts["bar_charts"] = [] + for col in categorical_columns[:5]: # 限制最多 5 个分类型列 + chart_data = self._create_bar_chart(df[col], col) + if chart_data: + charts["bar_charts"].append(chart_data) + + # 3. 数值型列的箱线图 + charts["box_plots"] = [] + if len(numeric_columns) > 0: + chart_data = self._create_box_plot(df[numeric_columns[:5]], numeric_columns[:5]) + if chart_data: + charts["box_plots"].append(chart_data) + + # 4. 相关性热力图 + if len(numeric_columns) >= 2: + chart_data = self._create_correlation_heatmap(df[numeric_columns], numeric_columns) + if chart_data: + charts["correlation"] = chart_data + + return charts + + def _create_histogram(self, series: pd.Series, column_name: str) -> Optional[Dict[str, Any]]: + """创建直方图""" + try: + fig, ax = plt.subplots(figsize=(11, 7)) + ax.hist(series.dropna(), bins=20, edgecolor='black', alpha=0.7, color='#3b82f6') + ax.set_xlabel(column_name, fontsize=10, labelpad=10) + ax.set_ylabel('频数', fontsize=10, labelpad=10) + ax.set_title(f'{column_name} 分布', fontsize=12, fontweight='bold', pad=15) + ax.grid(True, alpha=0.3, axis='y') + ax.tick_params(axis='both', which='major', labelsize=9) + + # 改进布局 + plt.tight_layout(pad=1.5, w_pad=1.0, h_pad=1.0) + + # 转换为 base64 + img_base64 = self._figure_to_base64(fig) + + return { + "type": "histogram", + "column": column_name, + "image": img_base64, + "stats": { + "mean": float(series.mean()), + "median": float(series.median()), + "std": float(series.std()) if len(series) > 1 else 0 + } + } + except Exception as e: + logger.error(f"创建直方图失败 ({column_name}): {str(e)}") + return None + + def _create_bar_chart(self, series: pd.Series, column_name: str) -> Optional[Dict[str, Any]]: + """创建条形图""" + try: + value_counts = series.value_counts().head(10) # 只显示前 10 个 + fig, ax = plt.subplots(figsize=(12, 7)) + + # 处理标签显示 + labels = [str(x)[:15] + '...' if len(str(x)) > 15 else str(x) for x in value_counts.index] + x_pos = range(len(value_counts)) + bars = ax.bar(x_pos, value_counts.values, color='#10b981', alpha=0.8, edgecolor='black', linewidth=0.5) + + ax.set_xticks(x_pos) + ax.set_xticklabels(labels, rotation=30, ha='right', fontsize=8) + ax.set_xlabel(column_name, fontsize=10, labelpad=10) + ax.set_ylabel('数量', fontsize=10, labelpad=10) + ax.set_title(f'{column_name} 分布 (Top 10)', fontsize=12, fontweight='bold', pad=15) + ax.grid(True, alpha=0.3, axis='y') + ax.tick_params(axis='both', which='major', labelsize=9) + + # 添加数值标签（位置稍微上移） + max_val = value_counts.values.max() + y_offset = max_val * 0.02 if max_val > 0 else 0.5 + for bar, value in zip(bars, value_counts.values): + ax.text(bar.get_x() + bar.get_width() / 2., value + y_offset, + f'{int(value)}', + ha='center', va='bottom', fontsize=8, fontweight='bold') + + # 改进布局 + plt.tight_layout(pad=1.5, w_pad=1.0, h_pad=1.0) + + # 转换为 base64 + img_base64 = self._figure_to_base64(fig) + + return { + "type": "bar_chart", + "column": column_name, + "image": img_base64, + "categories": {str(k): int(v) for k, v in value_counts.items()} + } + except Exception as e: + logger.error(f"创建条形图失败 ({column_name}): {str(e)}") + return None + + def _create_box_plot(self, df: pd.DataFrame, columns: List[str]) -> Optional[Dict[str, Any]]: + """创建箱线图""" + try: + fig, ax = plt.subplots(figsize=(14, 7)) + + # 准备数据 + box_data = [df[col].dropna() for col in columns] + bp = ax.boxplot(box_data, labels=columns, patch_artist=True, + notch=True, showcaps=True, showfliers=True) + + # 美化箱线图 + box_colors = ['#3b82f6', '#10b981', '#f59e0b', '#ef4444', '#8b5cf6'] + for patch, color in zip(bp['boxes'], box_colors[:len(bp['boxes'])]): + patch.set_facecolor(color) + patch.set_alpha(0.6) + patch.set_linewidth(1.5) + + # 设置其他元素样式 + for element in ['whiskers', 'fliers', 'means', 'medians', 'caps']: + plt.setp(bp[element], linewidth=1.5) + + ax.set_ylabel('值', fontsize=10, labelpad=10) + ax.set_title('数值型列分布对比', fontsize=12, fontweight='bold', pad=15) + ax.grid(True, alpha=0.3, axis='y') + + # 旋转 x 轴标签以避免重叠 + plt.setp(ax.get_xticklabels(), rotation=30, ha='right', fontsize=9) + ax.tick_params(axis='both', which='major', labelsize=9) + + # 改进布局 + plt.tight_layout(pad=1.5, w_pad=1.5, h_pad=1.0) + + # 转换为 base64 + img_base64 = self._figure_to_base64(fig) + + return { + "type": "box_plot", + "columns": columns, + "image": img_base64 + } + except Exception as e: + logger.error(f"创建箱线图失败: {str(e)}") + return None + + def _create_correlation_heatmap(self, df: pd.DataFrame, columns: List[str]) -> Optional[Dict[str, Any]]: + """创建相关性热力图""" + try: + # 计算相关系数 + corr = df.corr() + + fig, ax = plt.subplots(figsize=(11, 9)) + im = ax.imshow(corr, cmap='RdBu_r', aspect='auto', vmin=-1, vmax=1) + + # 设置刻度 + n_cols = len(corr) + ax.set_xticks(np.arange(n_cols)) + ax.set_yticks(np.arange(n_cols)) + + # 处理过长的列名 + x_labels = [str(col)[:10] + '...' if len(str(col)) > 10 else str(col) for col in corr.columns] + y_labels = [str(col)[:10] + '...' if len(str(col)) > 10 else str(col) for col in corr.columns] + + ax.set_xticklabels(x_labels, rotation=30, ha='right', fontsize=9) + ax.set_yticklabels(y_labels, fontsize=9) + + # 添加数值标签，根据相关性值选择颜色 + for i in range(n_cols): + for j in range(n_cols): + value = corr.iloc[i, j] + # 根据背景色深浅选择文字颜色 + text_color = 'white' if abs(value) > 0.5 else 'black' + ax.text(j, i, f'{value:.2f}', + ha="center", va="center", color=text_color, + fontsize=8, fontweight='bold' if abs(value) > 0.7 else 'normal') + + ax.set_title('数值型列相关性热力图', fontsize=12, fontweight='bold', pad=15) + ax.tick_params(axis='both', which='major', labelsize=9) + + # 添加颜色条 + cbar = plt.colorbar(im, ax=ax) + cbar.set_label('相关系数', rotation=270, labelpad=20, fontsize=10) + cbar.ax.tick_params(labelsize=9) + + # 改进布局 + plt.tight_layout(pad=2.0, w_pad=1.0, h_pad=1.0) + + # 转换为 base64 + img_base64 = self._figure_to_base64(fig) + + return { + "type": "correlation_heatmap", + "columns": columns, + "image": img_base64, + "correlation_matrix": corr.to_dict() + } + except Exception as e: + logger.error(f"创建相关性热力图失败: {str(e)}") + return None + + def _generate_distributions( + self, + df: pd.DataFrame, + categorical_columns: List[str] + ) -> Dict[str, Any]: + """生成数据分布信息""" + distributions = {} + + for col in categorical_columns[:5]: + try: + value_counts = df[col].value_counts() + total = len(df) + + distributions[col] = { + "categories": {str(k): int(v) for k, v in value_counts.items()}, + "percentages": {str(k): round(v / total * 100, 2) for k, v in value_counts.items()}, + "unique_count": len(value_counts) + } + except Exception as e: + logger.warning(f"列 {col} 分布生成失败: {str(e)}") + + return distributions + + def _figure_to_base64(self, fig) -> str: + """将 matplotlib 图形转换为 base64 字符串""" + buf = io.BytesIO() + fig.savefig( + buf, + format='png', + dpi=120, + bbox_inches='tight', + pad_inches=0.3, + facecolor='white', + edgecolor='none', + transparent=False + ) + plt.close(fig) + buf.seek(0) + img_base64 = base64.b64encode(buf.read()).decode('utf-8') + return f"data:image/png;base64,{img_base64}" + + +# 全局单例 +visualization_service = VisualizationService() diff --git a/backend/readme.md b/backend/readme.md index 87b1b77..e83f8eb 100644 --- a/backend/readme.md +++ b/backend/readme.md @@ -103,6 +103,21 @@ git config user.email #同上 #如果想看全局的，可以加上 --global，例如 git config --global user.name ``` +## 启动后端项目 +在终端输入以下命令： +```bash +cd backend #确保启动时在后端跟目录下 +./venv/Scripts/python.exe -m uvicorn app.main:app --host 127.0.0.1 --port 8000 + --reload #启动后端项目 +``` +先启动后端项目，再启动前端项目 + +记得在你的.gitignore中添加： +``` +/backend/data/uploads +/backend/data/charts +``` + ## 预计项目结构： ```bash diff --git a/backend/requirements.txt b/backend/requirements.txt index 3abd05e..5afbb79 100644 --- a/backend/requirements.txt +++ b/backend/requirements.txt @@ -1,6 +1,7 @@ -fastapi[all]==0.104.1 +fastapi[all]==0.104.1 uvicorn[standard]==0.24.0 pydantic==2.5.0 +pydantic-settings==2.1.0 python-multipart==0.0.6 pymongo==4.5.0 redis==5.0.0 @@ -10,6 +11,8 @@ faiss-cpu==1.8.0 python-docx==0.8.11 pandas==2.1.4 openpyxl==3.1.2 +matplotlib==3.8.2 +numpy==1.26.2 markdown==3.5.1 langchain==0.1.0 langchain-community==0.0.10 @@ -18,5 +21,4 @@ httpx==0.25.2 python-dotenv==1.0.0 loguru==0.7.2 tqdm==4.66.1 -numpy==1.26.2 -PyYAML==6.0.1 \ No newline at end of file +PyYAML==6.0.1 diff --git a/backend/test.py b/backend/test.py deleted file mode 100644 index eb776e6..0000000 --- a/backend/test.py +++ /dev/null @@ -1 +0,0 @@ -print("Hello,World") \ No newline at end of file diff --git a/backend/test1.py b/backend/test1.py deleted file mode 100644 index f1a1813..0000000 --- a/backend/test1.py +++ /dev/null @@ -1 +0,0 @@ -print("Hello world!") diff --git a/backend/test2.py b/backend/test2.py deleted file mode 100644 index 87ca0d6..0000000 --- a/backend/test2.py +++ /dev/null @@ -1 +0,0 @@ -print("hello,world!") \ No newline at end of file diff --git a/backend/test_font_config.py b/backend/test_font_config.py new file mode 100644 index 0000000..f317552 --- /dev/null +++ b/backend/test_font_config.py @@ -0,0 +1,71 @@ +""" +测试字体配置是否正常工作 +""" +import matplotlib.pyplot as plt +import matplotlib +import numpy as np +from app.services.font_helper import configure_matplotlib_fonts +import io +import base64 + +# 配置字体 +font_name = configure_matplotlib_fonts() + +print(f"当前使用字体: {font_name}") +print(f"matplotlib 中文字体设置: {matplotlib.rcParams['font.sans-serif']}") + +# 创建测试图表 +fig, ax = plt.subplots(figsize=(10, 6)) + +# 测试数据 +x = ['销售', '库存', '采购', '退货', '其他'] +y = [150, 200, 180, 50, 30] + +bars = ax.bar(x, y, color='#3b82f6', alpha=0.8) +ax.set_xlabel('类别', fontsize=12, labelpad=10) +ax.set_ylabel('数值', fontsize=12, labelpad=10) +ax.set_title('测试图表 - 中文显示', fontsize=14, fontweight='bold', pad=15) +ax.tick_params(axis='both', which='major', labelsize=10) + +# 添加数值标签 +for bar, value in zip(bars, y): + height = bar.get_height() + ax.text(bar.get_x() + bar.get_width() / 2., height, + f'{value}', + ha='center', va='bottom', fontsize=10, fontweight='bold') + +plt.grid(axis='y', alpha=0.3) +plt.tight_layout(pad=1.5) + +# 转换为 base64 +buf = io.BytesIO() +fig.savefig(buf, format='png', dpi=120, bbox_inches='tight', pad_inches=0.3, facecolor='white') +plt.close(fig) + +buf.seek(0) +img_base64 = base64.b64encode(buf.read()).decode('utf-8') +data_url = f"data:image/png;base64,{img_base64}" + +print("\n=== 测试完成 ===") +print(f"图表大小: {len(img_base64)} 字符") +print("如果看到字体警告，请检查系统是否有安装中文字体") + +# 尝试获取所有可用字体 +import matplotlib.font_manager as fm +available_fonts = set([f.name for f in fm.fontManager.ttflist]) + +print(f"\n=== 可用字体列表（部分）===") +chinese_fonts = [f for f in available_fonts if 'CJK' in f or 'Chinese' in f or 'YaHei' in f or 'SimHei' in f or 'PingFang' in f] +for font in sorted(chinese_fonts)[:10]: + print(f" - {font}") + +if not chinese_fonts: + print(" 未找到中文字体！") + +print("\n=== 推荐安装的中文字体 ===") +print("Windows: Microsoft YaHei (系统自带)") +print("macOS: PingFang SC (系统自带)") +print("Linux: fonts-noto-cjk 或 fonts-wqy-zenhei") + +print("\n=== 生成的 base64 数据（前100字符）===") +print(data_url[:100] + "...") diff --git a/docs/test/2025山东省环境空气质量监测数据信息.xlsx b/docs/test/2025山东省环境空气质量监测数据信息.xlsx new file mode 100644 index 0000000..95ddb66 Binary files /dev/null and b/docs/test/2025山东省环境空气质量监测数据信息.xlsx differ diff --git a/docs/test/2025年国考职位表（节选）.xlsx b/docs/test/2025年国考职位表（节选）.xlsx new file mode 100644 index 0000000..3e20c4b Binary files /dev/null and b/docs/test/2025年国考职位表（节选）.xlsx differ diff --git a/docs/test/COVID-19全球数据集（节选）.xlsx b/docs/test/COVID-19全球数据集（节选）.xlsx new file mode 100644 index 0000000..9fcd0f6 Binary files /dev/null and b/docs/test/COVID-19全球数据集（节选）.xlsx differ diff --git a/docs/test/test.md b/docs/test/test.md new file mode 100644 index 0000000..9694da8 --- /dev/null +++ b/docs/test/test.md @@ -0,0 +1,113 @@ + ✅ Excel 文件解析功能已完成并测试通过 + + 已完成的工作 + + 后端部分 + + 1. 文件服务层 (backend/app/services/file_service.py) + + - 文件保存、读取、删除功能 + - 文件信息获取 + 2. Excel 解析模块 (backend/app/core/document_parser/) + + - base.py - 解析器基类 + - xlsx_parser.py - Excel 文件解析器 + - utils.py - 工具函数 + 3. API 接口 (backend/app/api/endpoints/upload.py) + + - POST /upload/excel - 上传并解析 Excel 文件 + - GET /upload/excel/preview/{file_path} - 获取预览 + - DELETE /upload/file - 删除文件 + 4. 主应用配置 (backend/app/main.py) + + - CORS 中间件配置 + - API 路由注册 + + 前端部分 + + 1. 后端 API 封装 (frontendTest/app-a6ww9j3ja3nl/src/db/backend-api.ts) + + - Excel 上传、预览、删除函数 + 2. Excel 解析页面 (frontendTest/app-a6ww9j3ja3nl/src/pages/ExcelParse.tsx) + + - 拖拽上传界面 + - 解析选项配置 + - 数据表格展示 + - 多工作表支持 + 3. 路由配置 (frontendTest/app-a6ww9j3ja3nl/src/routes.tsx) + + - 添加 /excel-parse 路由 + 4. 环境配置 (.env) + + - 后端 API URL 配置 + + 测试结果 + + 后端 API 测试通过： + - ✅ 健康检查：http://127.0.0.1:8000/health + - ✅ Excel 上传解析：成功解析 5 行 6 列的测试数据 + + 访问方式 + + 1. 后端 API 文档：http://127.0.0.1:8000/api/v1/docs + 2. 前端页面： + + - 启动前端：cd frontendTest/app-a6ww9j3ja3nl && npm run dev + - 访问 Excel 解析页面：/excel-parse + + 下一步建议 + + 1. 启动前端开发服务器测试完整的前端界面 + 2. 添加更多文档格式解析支持（docx, md, txt） + 3. 完善错误处理和用户提示 + +✻ Worked for 4m 18s · 1 background task still running (↓ to manage) + +> 如何启动后端呢 + +● 后端启动步骤如下： + + 方法一：使用命令行启动（开发模式） + + # 1. 进入后端目录 + cd H:/OwnProject/FilesReadSysteam/backend + + # 2. 激活虚拟环境 + # PowerShell: + .\venv\Scripts\Activate.ps1 + + # 或 CMD: + .\venv\Scripts\Activate.bat + + # 3. 启动后端服务器 + python -m uvicorn app.main:app --host 127.0.0.1 --port 8000 --reload + + 方法二：直接使用虚拟环境中的 Python + + cd H:/OwnProject/FilesReadSysteam/backend + ./venv/Scripts/python.exe -m uvicorn app.main:app --host 127.0.0.1 --port 8000 --reload + + 方法三：直接运行 main.py（开发调试） + + cd H:/OwnProject/FilesReadSysteam/backend + ./venv/Scripts/python.exe app/main.py + + 启动成功的标志 + + INFO: Uvicorn running on http://127.0.0.1:8000 + INFO: Started server process [xxxxx] + INFO: Waiting for application startup. + INFO: Application startup complete. + + 验证服务是否正常 + + # 健康检查 + curl http://127.0.0.1:8000/health + + # 访问 API 文档 + # 浏览器打开: http://127.0.0.1:8000/api/v1/docs + +--- + 当前状态：后端已在后台运行（任务 ID: b22jkg69j），可以直接访问 http://127.0.0.1:8000 + + 需要停止的话告诉我即可。 \ No newline at end of file diff --git a/docs/test/电商销售数据.xlsx b/docs/test/电商销售数据.xlsx new file mode 100644 index 0000000..b13bf2a Binary files /dev/null and b/docs/test/电商销售数据.xlsx differ diff --git a/docs/test/糖尿病患者数据.xlsx b/docs/test/糖尿病患者数据.xlsx new file mode 100644 index 0000000..50797a0 Binary files /dev/null and b/docs/test/糖尿病患者数据.xlsx differ diff --git a/frontend/.env b/frontend/.env new file mode 100644 index 0000000..82eaa83 --- /dev/null +++ b/frontend/.env @@ -0,0 +1,7 @@ +VITE_APP_ID=app-a6ww9j3ja3nl + +VITE_SUPABASE_URL=https://backend.appmiaoda.com/projects/supabase290100332300644352 + +VITE_SUPABASE_ANON_KEY=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJhdWQiOiJhdXRoZW50aWNhdGVkIiwiZXhwIjoyMDg4NTkyNTA5LCJpc3MiOiJzdXBhYmFzZSIsInJvbGUiOiJhbm9uIiwic3ViIjoiYW5vbiJ9.sdVzWIT_AjxVjEmBaEQcOoFGlHTTT8NH59fYdkaA4WU + +VITE_BACKEND_API_URL=http://localhost:8000/api/v1 diff --git a/frontend/.gitignore b/frontend/.gitignore new file mode 100644 index 0000000..1b259b9 --- /dev/null +++ b/frontend/.gitignore @@ -0,0 +1,29 @@ +# Logs +logs +*.log +npm-debug.log* +yarn-debug.log* +yarn-error.log* +pnpm-debug.log* +lerna-debug.log* + +node_modules +dist +dist-ssr +output +*.local +package-lock.json + +# Editor directories and files +.vscode/* +!.vscode/extensions.json +.idea +.DS_Store +*.suo +*.ntvs* +*.njsproj +*.sln +*.sw? +.sync +history/*.json +.vite_cache diff --git a/frontend/.rules/SelectItem.yml b/frontend/.rules/SelectItem.yml new file mode 100644 index 0000000..77b172c --- /dev/null +++ b/frontend/.rules/SelectItem.yml @@ -0,0 +1,28 @@ +id: selectItemWithEmptyValue +language: Tsx +files: + - src/**/*.tsx +rule: + kind: jsx_opening_element + all: + - has: + kind: identifier + regex: '^SelectItem$' + - has: + kind: jsx_attribute + all: + - has: + kind: property_identifier + regex: '^value$' + - any: + - has: + kind: string + regex: '^""$' + - has: + kind: jsx_expression + has: + kind: string + regex: '^""$' + +message: "检测到 SelectItem 组件使用空字符串 value: $MATCH， 这是错误用法， 运行时会报错， 请修改， 如果想实现全选，建议使用all代替空字符串" +severity: error diff --git a/frontend/.rules/check.sh b/frontend/.rules/check.sh new file mode 100644 index 0000000..89686b6 --- /dev/null +++ b/frontend/.rules/check.sh @@ -0,0 +1,39 @@ +#!/bin/bash + +ast-grep scan -r .rules/SelectItem.yml + +ast-grep scan -r .rules/contrast.yml + +ast-grep scan -r .rules/supabase-google-sso.yml + +ast-grep scan -r .rules/toast-hook.yml + +ast-grep scan -r .rules/slot-nesting.yml + +ast-grep scan -r .rules/require-button-interaction.yml + +useauth_output=$(ast-grep scan -r .rules/useAuth.yml 2>/dev/null) + +if [ -z "$useauth_output" ]; then + exit 0 +fi + +authprovider_output=$(ast-grep scan -r .rules/authProvider.yml 2>/dev/null) + +if [ -n "$authprovider_output" ]; then + exit 0 +fi + +echo "=== ast-grep scan -r .rules/useAuth.yml output ===" +echo "$useauth_output" +echo "" +echo "=== ast-grep scan -r .rules/authProvider.yml output ===" +echo "$authprovider_output" +echo "" +echo "⚠️ Issue detected:" +echo "The code uses useAuth Hook but does not have AuthProvider component wrapping the components." +echo "Please ensure that components using useAuth are wrapped with AuthProvider to provide proper authentication context." +echo "" +echo "Suggested fixes:" +echo "1. Add AuthProvider wrapper in app.tsx or corresponding root component" +echo "2. Ensure all components using useAuth are within AuthProvider scope" diff --git a/frontend/.rules/contrast.yml b/frontend/.rules/contrast.yml new file mode 100644 index 0000000..789d5e6 --- /dev/null +++ b/frontend/.rules/contrast.yml @@ -0,0 +1,103 @@ +id: button-outline-text-foreground-contrast +language: tsx +files: + - src/**/*.tsx +message: "Outline button with text-foreground class causes invisible text. The outline variant has a transparent background, making text-foreground color blend with the background and become unreadable. Use text-primary or another contrasting color instead." +rule: + kind: jsx_element + has: + kind: jsx_opening_element + all: + - has: + field: name + regex: "^Button$" + - has: + kind: jsx_attribute + all: + - has: + kind: property_identifier + regex: "^variant$" + - has: + kind: string + has: + kind: string_fragment + regex: "^outline$" + - has: + kind: jsx_attribute + all: + - has: + kind: property_identifier + regex: "^className$" + - has: + kind: string + has: + kind: string_fragment + regex: "(^|\\s)text-foreground(\\s|$)" +--- +id: button-default-text-primary-contrast +language: tsx +files: + - src/**/*.tsx +message: "Default button with text-primary class causes poor contrast. The default variant has a primary-colored background, making text-primary color blend with the background and become hard to read. Remove the text-primary class or specify a different variant like 'outline' or 'ghost'." +rule: + kind: jsx_element + has: + kind: jsx_opening_element + all: + - has: + field: name + regex: "^Button$" + - has: + kind: jsx_attribute + all: + - has: + kind: property_identifier + regex: "^className$" + - has: + kind: string + has: + kind: string_fragment + regex: "(^|\\s)text-primary(\\s|$)" + - not: + has: + kind: jsx_attribute + has: + kind: property_identifier + regex: "^variant$" + +--- +id: button-outline-white-gray-contrast +language: tsx +files: + - src/**/*.tsx +message: "Outline button with white/gray text color has poor contrast. Remove the text color class and use the default button text color." +rule: + kind: jsx_element + has: + kind: jsx_opening_element + all: + - has: + field: name + regex: "^Button$" + - has: + kind: jsx_attribute + all: + - has: + kind: property_identifier + regex: "^variant$" + - has: + kind: string + has: + kind: string_fragment + regex: "^outline$" + - has: + kind: jsx_attribute + all: + - has: + kind: property_identifier + regex: "^className$" + - has: + kind: string + has: + kind: string_fragment + regex: "(^|\\s)text-(white|gray)(-[0-9]+)?(\\s|$)" diff --git a/frontend/.rules/require-button-interaction.yml b/frontend/.rules/require-button-interaction.yml new file mode 100644 index 0000000..d909d57 --- /dev/null +++ b/frontend/.rules/require-button-interaction.yml @@ -0,0 +1,56 @@ +id: require-button-interaction +language: Tsx +files: + - src/**/*.tsx + - src/**/*.jsx +rule: + kind: jsx_opening_element + all: + # 必须是 + + + + 正确写法： + + ← 直接使用 Button + + + 原因：FormControl 和 Trigger 都使用 Radix UI 的 Slot 机制，双层嵌套会导致： + - ref 传递链断裂 + - 点击事件丢失 + - 内部组件无法交互 + + FormControl 只应该用于原生表单控件（Input, Textarea, Select），不要用于触发器按钮。 +severity: error +rule: + kind: jsx_element + all: + # 开始标签需要满足的条件 + - has: + kind: jsx_opening_element + all: + # 匹配所有 Radix UI 的 Trigger 组件 + - has: + field: name + regex: "^(Popover|Dialog|DropdownMenu|AlertDialog|HoverCard|Menubar|NavigationMenu|ContextMenu|Tooltip)Trigger$" + # 必须有 asChild 属性 + - has: + kind: jsx_attribute + has: + kind: property_identifier + regex: "^asChild$" + # 直接子元素包含 FormControl + - has: + kind: jsx_element + has: + kind: jsx_opening_element + has: + field: name + regex: "^FormControl$" diff --git a/frontend/.rules/supabase-google-sso.yml b/frontend/.rules/supabase-google-sso.yml new file mode 100644 index 0000000..c335b7d --- /dev/null +++ b/frontend/.rules/supabase-google-sso.yml @@ -0,0 +1,20 @@ +id: supabase-google-sso +language: Tsx +files: + - src/**/*.tsx +rule: + pattern: | + $AUTH.signInWithOAuth({ provider: 'google', $$$ }) +message: | + Replace `signInWithOAuth` with `signInWithSSO` for Google authentication (Supabase). + + Refactor to: + ```typescript + const { data, error } = await supabase.auth.signInWithSSO({ + domain: 'miaoda-gg.com', + options: { redirectTo: window.location.origin }, + }); + if (data?.url) window.open(data.url, '_self'); + ``` + Ensure `window.open` uses `_self` target. +severity: warning diff --git a/frontend/.rules/testBuild.sh b/frontend/.rules/testBuild.sh new file mode 100644 index 0000000..a3e9b0d --- /dev/null +++ b/frontend/.rules/testBuild.sh @@ -0,0 +1,10 @@ +#!/bin/bash + +OUTPUT=$(npx vite build --minify false --logLevel error --outDir /workspace/.dist 2>&1) +EXIT_CODE=$? + +if [ $EXIT_CODE -ne 0 ]; then + echo "$OUTPUT" +fi + +exit $EXIT_CODE diff --git a/frontend/.rules/toast-hook.yml b/frontend/.rules/toast-hook.yml new file mode 100644 index 0000000..3de8545 --- /dev/null +++ b/frontend/.rules/toast-hook.yml @@ -0,0 +1,11 @@ +id: use-toast-import +message: Use 'import { toast } from "sonner"' instead of "@/hooks/use-toast" +severity: error +language: Tsx +note: | + The new shadcn/ui pattern uses sonner for toast notifications. + Replace: import { toast } from "@/hooks/use-toast" + With: import { toast } from "sonner" + +rule: + pattern: import { $$$IMPORTS } from "@/hooks/use-toast" diff --git a/frontend/README.md b/frontend/README.md index d991c9d..856b64b 100644 --- a/frontend/README.md +++ b/frontend/README.md @@ -1,129 +1,67 @@ -> [!TIP] -> -> 注意，本文档仅为前端开发过程中团队交流使用，非正式的readme文档。 -> 以下为官方自带说明，请忽略（正文开始在下面） +## 介绍 -# 前端项目说明 +项目介绍 -这是一个使用 Vue 3 和 Vite 的模板项目，帮助您开始开发。 +## 目录结构 -## 推荐的 IDE 设置 - -[VS Code](https://code.visualstudio.com/) + [Vue (官方)](https://marketplace.visualstudio.com/items?itemName=Vue.volar)（并禁用 Vetur）。 - -## 推荐的浏览器设置 - -- 基于 Chromium 的浏览器（Chrome、Edge、Brave 等）： - - [Vue.js 开发者工具](https://chromewebstore.google.com/detail/vuejs-devtools/nhdogjmejiglipccpnnnanhbledajbpd) - - [在 Chrome DevTools 中开启自定义对象格式化程序](http://bit.ly/object-formatters) -- Firefox： - - [Vue.js 开发者工具](https://addons.mozilla.org/en-US/firefox/addon/vue-js-devtools/) - - [在 Firefox DevTools 中开启自定义对象格式化程序](https://fxdx.dev/firefox-devtools-custom-object-formatters/) - -## TypeScript 对 `.vue` 导入的类型支持 - -TypeScript 默认无法处理 `.vue` 导入的类型信息，因此我们用 `vue-tsc` 替换了 `tsc` 命令进行类型检查。在编辑器中，我们需要 [Volar](https://marketplace.visualstudio.com/items?itemName=Vue.volar) 让 TypeScript 语言服务识别 `.vue` 类型。 - -## 自定义配置 - -参见 [Vite 配置参考](https://vite.dev/config/)。 - -## 项目设置 - -```sh -npm install +``` +├── README.md # 说明文档 +├── components.json # 组件库配置 +├── index.html # 入口文件 +├── package.json # 包管理 +├── postcss.config.js # postcss 配置 +├── public # 静态资源目录 +│   ├── favicon.png # 图标 +│   └── images # 图片资源 +├── src # 源码目录 +│   ├── App.tsx # 入口文件 +│   ├── components # 组件目录 +│   ├── contexts # 上下文目录 +│   ├── db # 数据库配置目录 +│   ├── hooks # 通用钩子函数目录 +│   ├── index.css # 全局样式 +│   ├── layout # 布局目录 +│   ├── lib # 工具库目录 +│   ├── main.tsx # 入口文件 +│   ├── routes.tsx # 路由配置 +│   ├── pages # 页面目录 +│   ├── services # 数据库交互目录 +│   ├── types # 类型定义目录 +├── tsconfig.app.json # ts 前端配置文件 +├── tsconfig.json # ts 配置文件 +├── tsconfig.node.json # ts node端配置文件 +└── vite.config.ts # vite 配置文件 ``` -### 编译和热重载用于开发 +## 技术栈 -```sh -npm run dev +Vite、TypeScript、React、Supabase + +## 本地开发 + +首先进行包安装： +```bash +cd frontend #进入前端目录 +npm install #确定目录中有node_modules文件夹后输入命令安装依赖包 ``` -### 类型检查、编译和生产环境压缩 - -```sh -npm run build +## 启动项目 +启动项目： +```bash +npm run dev #启动项目，需要确保后端已启动，否则前端功能无法使用 ``` +启动后在终端ctrl+左键点击项目地址打开浏览器，一般是http://localhost:5173 -### 使用 [ESLint](https://eslint.org/) 进行代码检查 -```sh -npm run lint -``` +记得在你根目录下的.gitignore文件中添加： -## vscode设置 -首先在插件库中安装`Vue`插件 -![alt text](image\image-3.png) -选择官方的即可 - -## 构建 -在安装完`Node.js`后 -直接在项目根目录下（即xxx\FileReadSystem\）下运行 -```sh -npm create vue@latest -``` -项目名直接用frontend -随后的选择如下: -``` -✔ Project name: … frontend -✔ Add TypeScript? … **Yes** (推荐，更好的类型支持) -✔ Add JSX? … No / Yes (根据需要，一般不需要) -✔ Add Vue Router for Single Page Application development? … **Yes** (需要路由) -✔ Add Pinia for state management? … **Yes** (推荐，状态管理) -✔ Add Vitest for Unit Testing? … No (测试，可以暂时不选) -✔ Add an End-to-End Testing Solution? … No (端到端测试，暂时不选) -✔ Add ESLint for code quality? … **Yes** (代码规范) -✔ Add Prettier for code formatting? … **Yes** (代码格式化) -``` - -实验特性不选就行 - -跳过所有示例代码，创建一个空白的Vue项目 Yes - -完成后输入 -```sh -cd frontend -#随后输入 -npm install #确保frontend目录下有package.json文件 -``` -安装包完成后输入 -```sh -npm run dev -``` -以进入调试 -若终端出现： -![alt text](image\image-4.png) -说明构建成功，ctrl+鼠标左键点击第一个网址即可查看当前页面 -在终端输入q即可退出调试 - -## 关于`.gitignore` - -根目录下`.gitignore`文件修改如下： -```sh -/.git/ -/.gitignore -/.idea/ -/.vscode/ -/backend/venv/ -/backend/command/ -/backend/.env -/backend/.env.local -/backend/.env.*.local -/backend/app/__pycache__/ - -# 前端忽略 -/frontend/* -!/frontend/README.md -!/frontend/image/ -# 在你自己构建好后，请删除上面这三行 +```bash /frontend/node_modules/ /frontend/dist/ /frontend/build/ -/frontend/.env /frontend/.vscode/ /frontend/.idea/ /frontend/*.log -``` +``` \ No newline at end of file diff --git a/frontend/TODO.md b/frontend/TODO.md new file mode 100644 index 0000000..1f70bba --- /dev/null +++ b/frontend/TODO.md @@ -0,0 +1,37 @@ +# Task: 基于大语言模型的文档理解与多源数据融合系统 + +## Plan +- [x] 数据库初始化与权限配置 (Supabase) + - [x] 创建 `profiles` 表及触发器 (登录同步) + - [x] 创建 `documents` 表 (存储上传的文档信息) + - [x] 创建 `extracted_entities` 表 (存储从文档提取的结构化数据) + - [x] 创建 `templates` 表 (存储表格模板) + - [x] 创建 `fill_tasks` 表 (存储填写任务) + - [x] 配置 RLS 策略 (Row Level Security) + - [x] 创建 Storage 存储桶 `document_storage` (存储文档和模板) +- [x] 基础架构与登录模块 + - [x] 配置路由 `@/routes.tsx` + - [x] 创建登录/注册页面 + - [x] 实现 `AuthContext` 与 `RouteGuard` (登录状态管理) + - [x] 创建系统主布局 `MainLayout` (含侧边栏导航) +- [x] 文档上传与智能提取功能 + - [x] 实现文档上传组件 (支持 docx, md, xlsx, txt) + - [x] 部署 Edge Function `process-document` (调用 MiniMax 处理文档提取) + - [x] 实现文档列表与详情页 (显示提取的结构化数据) +- [x] 表格模板与自动填写模块 + - [x] 实现模板上传与管理 + - [x] 部署 Edge Function `fill-template` (基于提取数据填充表格) + - [x] 实现任务监控与结果下载 +- [x] 智能对话交互模块 + - [x] 实现智能助手聊天界面 (侧边栏或独立页面) + - [x] 部署 Edge Function `chat-assistant` (解析自然语言指令执行操作) +- [x] 系统优化与美化 + - [x] 全面应用科技蓝办公风格 (index.css, tailwind.config.js) + - [x] 响应式适配 (移动端兼容) + - [x] 完善错误处理与加载状态 (Skeleton, Toast) + +## Notes +- 所有 Edge Functions 已部署并集成 MiniMax API +- 文档解析使用 mammoth (docx), xlsx (excel), 原生 TextDecoder (txt/md) +- 系统采用科技蓝主题，支持暗色模式 +- 所有代码已通过 lint 检查 diff --git a/frontend/biome.json b/frontend/biome.json new file mode 100644 index 0000000..4a5ff29 --- /dev/null +++ b/frontend/biome.json @@ -0,0 +1,24 @@ +{ + "$schema": "./node_modules/@biomejs/biome/configuration_schema.json", + "files": { + "includes": ["src/**/*.{js,jsx,ts,tsx}"] + }, + "linter": { + "enabled": true, + "rules": { + "recommended": false, + "correctness": { + "noUndeclaredDependencies": "error" + }, + "suspicious": { + "noRedeclare": "error" + }, + "style": { + "noCommonJs": "error" + } + } + }, + "formatter": { + "enabled": false + } +} diff --git a/frontend/components.json b/frontend/components.json new file mode 100644 index 0000000..ff8b877 --- /dev/null +++ b/frontend/components.json @@ -0,0 +1,21 @@ +{ + "$schema": "https://ui.shadcn.com/schema.json", + "style": "new-york", + "rsc": false, + "tsx": true, + "tailwind": { + "config": "tailwind.config.js", + "css": "src/index.css", + "baseColor": "slate", + "cssVariables": true, + "prefix": "" + }, + "iconLibrary": "lucide", + "aliases": { + "components": "@/components", + "utils": "@/lib/utils", + "ui": "@/components/ui", + "lib": "@/lib", + "hooks": "@/hooks" + } +} diff --git a/frontend/docs/prd.md b/frontend/docs/prd.md new file mode 100644 index 0000000..fec5ba7 --- /dev/null +++ b/frontend/docs/prd.md @@ -0,0 +1,95 @@ +# 基于大语言模型的文档理解与多源数据融合系统需求文档 + +## 1. 应用概述 + +### 1.1 应用名称 +基于大语言模型的文档理解与多源数据融合系统 + +### 1.2 应用描述 +本系统旨在解决企事业单位在日常办公中面临的文本信息处理效率低下问题,通过引入人工智能技术实现文档的智能理解、信息自动提取、结构化存储以及智能表格填写,帮助用户从繁琐的重复性劳动中解放出来,提升整体工作效率。 + +## 2. 核心功能 + +### 2.1 文档智能操作交互模块 +- 支持用户通过自然语言指令对文档进行操作 +- 自动解析用户指令并执行相应的文档编辑、排版、格式调整、内容提取等操作 +- 基于自然语言处理与文档结构理解技术实现人机交互 + +### 2.2 非结构化文档信息提取模块 +- 支持用户导入各类非结构化文档(包括但不限于docx、md、xlsx、txt格式) +- 自动识别并提取文档中的关键信息、实体数据或用户指定内容 +- 将提取的信息进行数据库存储 +- 确保信息提取的准确性和入库的规范性 +- 支持桌面端、Web网站或第三方平台部署 + +### 2.3 表格自定义数据填写模块 +- 支持用户提供表格模板(word或excel格式) +- 从用户提供的非结构化数据中自动搜索相关信息 +- 将搜索到的信息自动填写到表格中 +- 生成具备直接业务应用价值的、格式严谨的汇总表格 + +## 3. 技术要求 + +### 3.1 系统架构 +- 可基于开源或第三方商业AI平台构建 +- 也可采用自研创新算法 +- 系统可运行在H5小程序、原生App、Web网站、PC端软件等平台上 + +### 3.2 性能指标 +- 信息提取准确率需高于80% +- 每个文档的响应时间至多为90秒 +- 支持异步调用的API接口 + +### 3.3 数据处理能力 +- 能够准确识别多种数据类型并在不同数据类型间稳定运行 +- 支持比赛方提供的测试文档样本集(包括5个docx文档、3个md文档、5个xlsx文档、3个txt文档) + +## 4. 交互流程 + +### 4.1 文档上传与处理流程 +- 用户上传多个文档文件(支持docx、md、xlsx、txt格式) +- 系统自动识别并提取文档中的关键信息 +- 将提取的信息进行数据库存储 + +### 4.2 表格填写流程 +- 用户上传表格模板文件(word或excel格式) +- 系统从已存储的非结构化数据中自动搜索相关信息 +- 将相关信息自动填写到表格中 +- 完成填写后返回或展示结果表格 + +### 4.3 智能交互流程 +- 用户通过自然语言输入操作指令 +- 系统解析指令并识别用户需求 +- 执行相应的文档操作并反馈结果 + +## 5. 参考信息 + +### 5.1 测试文档样本集 +- 5个不小于500KB的docx格式文档 +- 3个不小于15KB的md格式文档 +- 5个不小于500KB的xlsx格式文档 +- 3个不小于15KB的txt文档 + +### 5.2 评分标准 +- 信息填写准确率(平均准确率) +- 响应时间(平均响应时间) +- 准确率差距2%以上时,准确率越高系统越好 +- 准确率差距小于2%时,结合响应时间综合评价 + +## 6. 其他说明 + +### 6.1 开发工具 +- 开发工具及平台不限 +- 可借助开源工具 +- 数据与功能API需提供技术说明 + +### 6.2 提交材料 +- 项目概要介绍 +- 项目简介PPT +- 项目详细方案 +- 项目演示视频 +- 企业要求提交的材料: + - 训练素材详细的素材介绍与来源说明 + - 关键模块的概要设计和创新要点说明文档 + - 可运行的Demo实现程序 +- 团队自愿提交的其他补充材料 \ No newline at end of file diff --git a/frontend/image/image-3.png b/frontend/image/image-3.png deleted file mode 100644 index 68132b8..0000000 Binary files a/frontend/image/image-3.png and /dev/null differ diff --git a/frontend/image/image-4.png b/frontend/image/image-4.png deleted file mode 100644 index 203138e..0000000 Binary files a/frontend/image/image-4.png and /dev/null differ diff --git a/frontend/index.html b/frontend/index.html new file mode 100644 index 0000000..224e2c9 --- /dev/null +++ b/frontend/index.html @@ -0,0 +1,12 @@ + + + + + + + + +
+ + + diff --git a/frontend/package.json b/frontend/package.json new file mode 100644 index 0000000..344829e --- /dev/null +++ b/frontend/package.json @@ -0,0 +1,96 @@ +{ + "name": "miaoda-react-admin", + "version": "0.0.1", + "type": "module", + "scripts": { + "dev": "vite", + "build": "vite build", + "lint": "tsgo -p tsconfig.check.json; npx biome lint; .rules/check.sh;npx tailwindcss -i ./src/index.css -o /dev/null 2>&1 | grep -E '^(CssSyntaxError|Error):.*' || true;.rules/testBuild.sh" + }, + "dependencies": { + "@hookform/resolvers": "^5.2.2", + "@radix-ui/react-accordion": "^1.2.12", + "@radix-ui/react-alert-dialog": "^1.1.15", + "@radix-ui/react-aspect-ratio": "^1.1.7", + "@radix-ui/react-avatar": "^1.1.10", + "@radix-ui/react-checkbox": "^1.3.3", + "@radix-ui/react-collapsible": "^1.1.12", + "@radix-ui/react-context-menu": "^2.2.16", + "@radix-ui/react-dialog": "^1.1.15", + "@radix-ui/react-dropdown-menu": "^2.1.16", + "@radix-ui/react-hover-card": "^1.1.15", + "@radix-ui/react-icons": "^1.3.2", + "@radix-ui/react-label": "^2.1.7", + "@radix-ui/react-menubar": "^1.1.16", + "@radix-ui/react-navigation-menu": "^1.2.14", + "@radix-ui/react-popover": "^1.1.15", + "@radix-ui/react-progress": "^1.1.7", + "@radix-ui/react-radio-group": "^1.3.8", + "@radix-ui/react-scroll-area": "^1.2.10", + "@radix-ui/react-select": "^2.2.6", + "@radix-ui/react-separator": "^1.1.7", + "@radix-ui/react-slider": "^1.3.6", + "@radix-ui/react-slot": "^1.2.3", + "@radix-ui/react-switch": "^1.2.6", + "@radix-ui/react-tabs": "^1.1.13", + "@radix-ui/react-toast": "^1.2.15", + "@radix-ui/react-toggle": "^1.1.10", + "@radix-ui/react-toggle-group": "^1.1.11", + "@radix-ui/react-tooltip": "^1.2.8", + "@supabase/supabase-js": "^2.98.0", + "axios": "^1.13.1", + "class-variance-authority": "^0.7.1", + "clsx": "^2.1.1", + "cmdk": "^1.1.1", + "date-fns": "^3.6.0", + "embla-carousel-react": "^8.6.0", + "eventsource-parser": "^3.0.6", + "framer-motion": "^12.35.2", + "input-otp": 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+export default { + plugins: { + tailwindcss: {}, + autoprefixer: {}, + }, +}; diff --git a/frontend/public/favicon.png b/frontend/public/favicon.png new file mode 100644 index 0000000..49529ec Binary files /dev/null and b/frontend/public/favicon.png differ diff --git a/frontend/public/images/error/404-dark.svg b/frontend/public/images/error/404-dark.svg new file mode 100644 index 0000000..4d14ec9 --- /dev/null +++ b/frontend/public/images/error/404-dark.svg @@ -0,0 +1,20 @@ + + + + + + + + + + + + + + + + + + + + diff --git a/frontend/public/images/error/404.svg b/frontend/public/images/error/404.svg new file mode 100644 index 0000000..ff8b8a2 --- /dev/null +++ b/frontend/public/images/error/404.svg @@ -0,0 +1,20 @@ + + + + + + + + + + + + + + + + + + + + diff --git a/frontend/public/images/error/500-dark.svg b/frontend/public/images/error/500-dark.svg new file mode 100644 index 0000000..c5ac764 --- /dev/null +++ b/frontend/public/images/error/500-dark.svg @@ -0,0 +1,24 @@ + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/frontend/public/images/error/500.svg b/frontend/public/images/error/500.svg new file mode 100644 index 0000000..82f5159 --- /dev/null +++ b/frontend/public/images/error/500.svg @@ -0,0 +1,24 @@ + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/frontend/public/images/error/503-dark.svg b/frontend/public/images/error/503-dark.svg new file mode 100644 index 0000000..8df2a94 --- /dev/null +++ b/frontend/public/images/error/503-dark.svg @@ -0,0 +1,26 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/frontend/public/images/error/503.svg b/frontend/public/images/error/503.svg new file mode 100644 index 0000000..a27a714 --- /dev/null +++ b/frontend/public/images/error/503.svg @@ -0,0 +1,26 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/frontend/public/images/favicon.ico b/frontend/public/images/favicon.ico new file mode 100644 index 0000000..cf3128a Binary files /dev/null and b/frontend/public/images/favicon.ico differ diff --git a/frontend/public/images/logo/auth-logo.svg b/frontend/public/images/logo/auth-logo.svg new file mode 100644 index 0000000..eb11cc7 --- /dev/null +++ b/frontend/public/images/logo/auth-logo.svg @@ -0,0 +1,53 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/frontend/public/images/logo/logo-dark.svg b/frontend/public/images/logo/logo-dark.svg new file mode 100644 index 0000000..4b94dac --- /dev/null +++ b/frontend/public/images/logo/logo-dark.svg @@ -0,0 +1,53 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/frontend/public/images/logo/logo-icon.svg b/frontend/public/images/logo/logo-icon.svg new file mode 100644 index 0000000..11d52ca --- /dev/null +++ b/frontend/public/images/logo/logo-icon.svg @@ -0,0 +1,44 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/frontend/public/images/shape/grid-01.svg b/frontend/public/images/shape/grid-01.svg new file mode 100644 index 0000000..6490367 --- /dev/null +++ b/frontend/public/images/shape/grid-01.svg @@ -0,0 +1,71 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/frontend/sgconfig.yml b/frontend/sgconfig.yml new file mode 100644 index 0000000..d6222a0 --- /dev/null +++ b/frontend/sgconfig.yml @@ -0,0 +1,5 @@ +ruleDirs: +- .rules +languageGlobs: + TypeScript: ["*.ts"] + Tsx: ["*.tsx"] diff --git a/frontend/src/App.tsx b/frontend/src/App.tsx new file mode 100644 index 0000000..877c55f --- /dev/null +++ b/frontend/src/App.tsx @@ -0,0 +1,15 @@ +import { RouterProvider } from 'react-router-dom'; +import { AuthProvider } from '@/context/AuthContext'; +import { router } from '@/routes'; +import { Toaster } from 'sonner'; + +function App() { + return ( + + + + + ); +} + +export default App; diff --git a/frontend/src/components/common/IntersectObserver.tsx b/frontend/src/components/common/IntersectObserver.tsx new file mode 100644 index 0000000..d555c8a --- /dev/null +++ b/frontend/src/components/common/IntersectObserver.tsx @@ -0,0 +1,22 @@ +import { useEffect } from 'react'; +import { useLocation } from 'react-router-dom'; +import { Observer } from 'tailwindcss-intersect'; + +const IntersectObserver = () => { + const location = useLocation(); + + useEffect(() => { + // When the location changes, we need to restart the observer + // to pick up new elements on the page. + // We use a small timeout to ensure the DOM has updated. + const timer = setTimeout(() => { + Observer.restart(); + }, 100); + + return () => clearTimeout(timer); + }, [location]); + + return null; +}; + +export default IntersectObserver; diff --git a/frontend/src/components/common/PageMeta.tsx b/frontend/src/components/common/PageMeta.tsx new file mode 100644 index 0000000..dc47ebd --- /dev/null +++ b/frontend/src/components/common/PageMeta.tsx @@ -0,0 +1,25 @@ +import { HelmetProvider, Helmet } from "react-helmet-async"; +import { TooltipProvider } from "@/components/ui/tooltip"; + +const PageMeta = ({ + title, + description, +}: { + title: string; + description: string; +}) => ( + + {title} + + +); + +export const AppWrapper = ({ children }: { children: React.ReactNode }) => ( + + + {children} + + +); + +export default PageMeta; diff --git a/frontend/src/components/common/RouteGuard.tsx b/frontend/src/components/common/RouteGuard.tsx new file mode 100644 index 0000000..0b691e0 --- /dev/null +++ b/frontend/src/components/common/RouteGuard.tsx @@ -0,0 +1,25 @@ +import React from 'react'; +import { Navigate, useLocation } from 'react-router-dom'; +import { useAuth } from '@/context/AuthContext'; + +export const RouteGuard: React.FC<{ children: React.ReactNode }> = ({ children }) => { + const { user, loading } = useAuth(); + const location = useLocation(); + + if (loading) { + return ( +
+
+
+

正在极速加载中...

+
+
+ ); + } + + if (!user) { + return ; + } + + return <>{children}; +}; diff --git a/frontend/src/components/dropzone.tsx b/frontend/src/components/dropzone.tsx new file mode 100644 index 0000000..122bd34 --- /dev/null +++ b/frontend/src/components/dropzone.tsx @@ -0,0 +1,227 @@ +import { cn } from '@/lib/utils' +import { type UseSupabaseUploadReturn } from '@/hooks/use-supabase-upload' +import { Button } from '@/components/ui/button' +import { CheckCircle, File, Loader2, Upload, X } from 'lucide-react' +import { createContext, type PropsWithChildren, useCallback, useContext } from 'react' + +export const formatBytes = ( + bytes: number, + decimals = 2, + size?: 'bytes' | 'KB' | 'MB' | 'GB' | 'TB' | 'PB' | 'EB' | 'ZB' | 'YB' +) => { + const k = 1000 + const dm = decimals < 0 ? 0 : decimals + const sizes = ['bytes', 'KB', 'MB', 'GB', 'TB', 'PB', 'EB', 'ZB', 'YB'] + + if (bytes === 0 || bytes === undefined) return size !== undefined ? `0 ${size}` : '0 bytes' + const i = size !== undefined ? sizes.indexOf(size) : Math.floor(Math.log(bytes) / Math.log(k)) + return parseFloat((bytes / Math.pow(k, i)).toFixed(dm)) + ' ' + sizes[i] +} + +type DropzoneContextType = Omit + +const DropzoneContext = createContext(undefined) + +type DropzoneProps = UseSupabaseUploadReturn & { + className?: string +} + +const Dropzone = ({ + className, + children, + getRootProps, + getInputProps, + ...restProps +}: PropsWithChildren) => { + const isSuccess = restProps.isSuccess + const isActive = restProps.isDragActive + const isInvalid = + (restProps.isDragActive && restProps.isDragReject) || + (restProps.errors.length > 0 && !restProps.isSuccess) || + restProps.files.some((file) => file.errors.length !== 0) + + return ( + +
+ + {children} +
+ + ) +} +const DropzoneContent = ({ className }: { className?: string }) => { + const { + files, + setFiles, + onUpload, + loading, + successes, + errors, + maxFileSize, + maxFiles, + isSuccess, + } = useDropzoneContext() + + const exceedMaxFiles = files.length > maxFiles + + const handleRemoveFile = useCallback( + (fileName: string) => { + setFiles(files.filter((file) => file.name !== fileName)) + }, + [files, setFiles] + ) + + if (isSuccess) { + return ( +
+ +

+ Successfully uploaded {files.length} file{files.length > 1 ? 's' : ''} +

+
+ ) + } + + return ( +
+ {files.map((file, idx) => { + const fileError = errors.find((e) => e.name === file.name) + const isSuccessfullyUploaded = !!successes.find((e) => e === file.name) + + return ( +
+ {file.type.startsWith('image/') ? ( +
+ {file.name} +
+ ) : ( +
+ +
+ )} + +
+

+ {file.name} +

+ {file.errors.length > 0 ? ( +

+ {file.errors + .map((e) => + e.message.startsWith('File is larger than') + ? `File is larger than ${formatBytes(maxFileSize, 2)} (Size: ${formatBytes(file.size, 2)})` + : e.message + ) + .join(', ')} +

+ ) : loading && !isSuccessfullyUploaded ? ( +

Uploading file...

+ ) : !!fileError ? ( +

Failed to upload: {fileError.message}

+ ) : isSuccessfullyUploaded ? ( +

Successfully uploaded file

+ ) : ( +

{formatBytes(file.size, 2)}

+ )} +
+ + {!loading && !isSuccessfullyUploaded && ( + + )} +
+ ) + })} + {exceedMaxFiles && ( +

+ You may upload only up to {maxFiles} files, please remove {files.length - maxFiles} file + {files.length - maxFiles > 1 ? 's' : ''}. +

+ )} + {files.length > 0 && !exceedMaxFiles && ( +
+ +
+ )} +
+ ) +} + +const DropzoneEmptyState = ({ className }: { className?: string }) => { + const { maxFiles, maxFileSize, inputRef, isSuccess } = useDropzoneContext() + + if (isSuccess) { + return null + } + + return ( +
+ +

+ Upload{!!maxFiles && maxFiles > 1 ? ` ${maxFiles}` : ''} file + {!maxFiles || maxFiles > 1 ? 's' : ''} +

+
+

+ Drag and drop or{' '} + inputRef.current?.click()} + className="underline cursor-pointer transition hover:text-foreground" + > + select {maxFiles === 1 ? `file` : 'files'} + {' '} + to upload +

+ {maxFileSize !== Number.POSITIVE_INFINITY && ( +

+ Maximum file size: {formatBytes(maxFileSize, 2)} +

+ )} +
+
+ ) +} + +const useDropzoneContext = () => { + const context = useContext(DropzoneContext) + + if (!context) { + throw new Error('useDropzoneContext must be used within a Dropzone') + } + + return context +} + +export { Dropzone, DropzoneContent, DropzoneEmptyState, useDropzoneContext } diff --git a/frontend/src/components/layouts/MainLayout.tsx b/frontend/src/components/layouts/MainLayout.tsx new file mode 100644 index 0000000..37124f5 --- /dev/null +++ b/frontend/src/components/layouts/MainLayout.tsx @@ -0,0 +1,124 @@ +import React from 'react'; +import { Link, useLocation, Outlet, useNavigate } from 'react-router-dom'; +import { + LayoutDashboard, + FileText, + TableProperties, + MessageSquareCode, + LogOut, + Menu, + X, + ChevronRight, + User, + Sparkles +} from 'lucide-react'; +import { Button } from '@/components/ui/button'; +import { useAuth } from '@/context/AuthContext'; +import { cn } from '@/lib/utils'; +import { Sheet, SheetContent, SheetTrigger } from '@/components/ui/sheet'; + +const navItems = [ + { name: '控制台', path: '/', icon: LayoutDashboard }, + { name: '文档中心', path: '/documents', icon: FileText }, + { name: 'Excel 解析', path: '/excel-parse', icon: Sparkles }, + { name: '智能填表', path: '/form-fill', icon: TableProperties }, + { name: '智能助手', path: '/assistant', icon: MessageSquareCode }, +]; + +const MainLayout: React.FC = () => { + const { user, profile, signOut } = useAuth(); + const location = useLocation(); + const navigate = useNavigate(); + + const handleSignOut = async () => { + await signOut(); + navigate('/login'); + }; + + const SidebarContent = () => ( +
+
+
+ +
+
+ 智联文档 + 多源数据融合平台 +
+
+ + + +
+
+
+
+ +
+
+ {((profile as any)?.email) || '用户'} + {((profile as any)?.role) || 'User'} +
+
+
+ +
+
+ ); + + return ( +
+ {/* Desktop Sidebar */} + + + {/* Mobile Sidebar */} + + + + + + + + + +
+
+ +
+
+
+ ); +}; + +export default MainLayout; diff --git a/frontend/src/components/ui/accordion.tsx b/frontend/src/components/ui/accordion.tsx new file mode 100644 index 0000000..e1797c9 --- /dev/null +++ b/frontend/src/components/ui/accordion.tsx @@ -0,0 +1,55 @@ +import * as React from "react" +import * as AccordionPrimitive from "@radix-ui/react-accordion" +import { ChevronDown } from "lucide-react" + +import { cn } from "@/lib/utils" + +const Accordion = AccordionPrimitive.Root + +const AccordionItem = React.forwardRef< + React.ElementRef, + React.ComponentPropsWithoutRef +>(({ className, ...props }, ref) => ( + +)) +AccordionItem.displayName = "AccordionItem" + +const AccordionTrigger = React.forwardRef< + React.ElementRef, + React.ComponentPropsWithoutRef +>(({ className, children, ...props }, ref) => ( + + svg]:rotate-180", + className + )} + {...props} + > + {children} + + + +)) +AccordionTrigger.displayName = AccordionPrimitive.Trigger.displayName + +const AccordionContent = React.forwardRef< + React.ElementRef, + React.ComponentPropsWithoutRef +>(({ className, children, ...props }, ref) => ( + +
{children}
+ +)) +AccordionContent.displayName = AccordionPrimitive.Content.displayName + +export { Accordion, AccordionItem, AccordionTrigger, AccordionContent } diff --git a/frontend/src/components/ui/ai-chart-display.tsx b/frontend/src/components/ui/ai-chart-display.tsx new file mode 100644 index 0000000..56d8971 --- /dev/null +++ b/frontend/src/components/ui/ai-chart-display.tsx @@ -0,0 +1,360 @@ +import React, { useState } from 'react'; +import { Download, Maximize2, X, Table, FileText, TrendingUp, BarChart3, Info, ExternalLink } from 'lucide-react'; +import { Button } from '@/components/ui/button'; +import { Card, CardContent, CardHeader, CardTitle, CardDescription } from '@/components/ui/card'; +import { Badge } from '@/components/ui/badge'; +import { + Dialog, + DialogContent, + DialogHeader, + DialogTitle, +} from '@/components/ui/dialog'; +import { cn } from '@/lib/utils'; +import { toast } from 'sonner'; + +interface AIChartDisplayProps { + charts?: any; + statistics?: any; + tablePreview?: any; + className?: string; +} + +export const AIChartDisplay: React.FC = ({ charts, statistics, tablePreview, className }) => { + const [previewChart, setPreviewChart] = useState<{ image: string; title: string } | null>(null); + + const downloadChart = (imageData: string, title: string) => { + try { + const base64Data = imageData.split(',')[1]; + const binaryData = atob(base64Data); + const bytes = new Uint8Array(binaryData.length); + + for (let i = 0; i < binaryData.length; i++) { + bytes[i] = binaryData.charCodeAt(i); + } + + const blob = new Blob([bytes], { type: 'image/png' }); + const url = URL.createObjectURL(blob); + + const link = document.createElement('a'); + link.href = url; + link.download = `${title}.png`; + document.body.appendChild(link); + link.click(); + document.body.removeChild(link); + URL.revokeObjectURL(url); + + toast.success('图表已下载'); + } catch (error) { + console.error('下载失败:', error); + toast.error('下载失败，请稍后重试'); + } + }; + + const openPreview = (image: string, title: string) => { + setPreviewChart({ image, title }); + }; + + const closePreview = () => { + setPreviewChart(null); + }; + + const getChartIcon = (type: string) => { + switch (type) { + case 'bar': + return ; + case 'pie': + return ; + case 'barh': + return ; + case 'time_series': + return ; + case 'comparison': + return ; + default: + return
; + } + }; + + return ( +
+ {/* 数值型数据图表 */} + {charts?.numeric_charts && charts.numeric_charts.length > 0 && ( +
+

+

+ 数值型数据图表 + +
+ {charts.numeric_charts.map((chart: any, idx: number) => ( + + +
+ {chart.title} +
+ + +
+
+ + + {chart.title} + + + ))} +
+ + )} + + {/* 分类数据图表 */} + {charts?.categorical_charts && charts.categorical_charts.length > 0 && ( +
+

+ + 分类数据图表 +

+
+ {charts.categorical_charts.map((chart: any, idx: number) => ( + + +
+ {chart.title} +
+ + +
+
+ + + {chart.title} + + + ))} +
+
+ )} + + {/* 时间序列图表 */} + {charts?.time_series_chart && ( +
+

+ + 时间序列图表 +

+ + +
+ {charts.time_series_chart.title} +
+ + +
+
+ + + {charts.time_series_chart.title} + + +
+ )} + + {/* 对比数据图表 */} + {charts?.comparison_chart && ( +
+

+ + 对比数据图表 +

+ + +
+ {charts.comparison_chart.title} +
+ + +
+
+ + + {charts.comparison_chart.title} + + +
+ )} + + {/* 数值摘要 */} + {statistics?.numeric_summary && ( + + + + + 数值摘要统计 + + + +
+
+

数量

+

{statistics.numeric_summary.count}

+
+
+

总和

+

{statistics.numeric_summary.sum?.toLocaleString()}

+
+
+

平均值

+

{statistics.numeric_summary.mean?.toFixed(2)}

+
+
+

中位数

+

{statistics.numeric_summary.median?.toFixed(2)}

+
+
+

最小值

+

{statistics.numeric_summary.min?.toLocaleString()}

+
+
+

最大值

+

{statistics.numeric_summary.max?.toLocaleString()}

+
+
+

标准差

+

{statistics.numeric_summary.std?.toFixed(2)}

+
+
+ + + )} + + {/* 表格预览 */} + {tablePreview && ( + + +
+ 提取的表格数据 + + 共 {tablePreview.total_rows} 行 + +
+ + +

+ 显示前 {tablePreview.preview_rows} 行数据，共 {tablePreview.total_rows} 行 +

+
+
+ + + + {tablePreview.columns.map((col: string, idx: number) => ( + + ))} + + + + {tablePreview.rows.slice(0, 20).map((row: any, rowIdx: number) => ( + + + {tablePreview.columns.map((col: string, colIdx: number) => ( + + ))} + + ))} + +
序号{col}
{rowIdx + 1} + {row[col] ?? '-'} +
+
+ + + )} + + {/* 图表预览对话框 */} + + + +
+ {previewChart?.title} + +
+ +
+ {previewChart && ( + {previewChart.title} + )} +
+ + + + ); +}; diff --git a/frontend/src/components/ui/alert-dialog.tsx b/frontend/src/components/ui/alert-dialog.tsx new file mode 100644 index 0000000..fa2b442 --- /dev/null +++ b/frontend/src/components/ui/alert-dialog.tsx @@ -0,0 +1,139 @@ +import * as React from "react" +import * as AlertDialogPrimitive from "@radix-ui/react-alert-dialog" + +import { cn } from "@/lib/utils" +import { buttonVariants } from "@/components/ui/button" + +const AlertDialog = AlertDialogPrimitive.Root + +const AlertDialogTrigger = AlertDialogPrimitive.Trigger + +const AlertDialogPortal = AlertDialogPrimitive.Portal + +const AlertDialogOverlay = React.forwardRef< + React.ElementRef, + React.ComponentPropsWithoutRef +>(({ className, ...props }, ref) => ( + +)) +AlertDialogOverlay.displayName = AlertDialogPrimitive.Overlay.displayName + +const AlertDialogContent = React.forwardRef< + React.ElementRef, + React.ComponentPropsWithoutRef +>(({ className, ...props }, ref) => ( + + + + +)) +AlertDialogContent.displayName = AlertDialogPrimitive.Content.displayName + +const AlertDialogHeader = ({ + className, + ...props +}: React.HTMLAttributes) => ( +
+) +AlertDialogHeader.displayName = "AlertDialogHeader" + +const AlertDialogFooter = ({ + className, + ...props +}: React.HTMLAttributes) => ( +
+) +AlertDialogFooter.displayName = "AlertDialogFooter" + +const AlertDialogTitle = React.forwardRef< + React.ElementRef, + React.ComponentPropsWithoutRef +>(({ className, ...props }, ref) => ( + +)) +AlertDialogTitle.displayName = AlertDialogPrimitive.Title.displayName + +const AlertDialogDescription = React.forwardRef< + React.ElementRef, + React.ComponentPropsWithoutRef +>(({ className, ...props }, ref) => ( + +)) +AlertDialogDescription.displayName = + AlertDialogPrimitive.Description.displayName + +const AlertDialogAction = React.forwardRef< + React.ElementRef, + React.ComponentPropsWithoutRef +>(({ className, ...props }, ref) => ( + +)) +AlertDialogAction.displayName = AlertDialogPrimitive.Action.displayName + +const AlertDialogCancel = React.forwardRef< + React.ElementRef, + React.ComponentPropsWithoutRef +>(({ className, ...props }, ref) => ( + +)) +AlertDialogCancel.displayName = AlertDialogPrimitive.Cancel.displayName + +export { + AlertDialog, + AlertDialogPortal, + AlertDialogOverlay, + AlertDialogTrigger, + AlertDialogContent, + AlertDialogHeader, + AlertDialogFooter, + AlertDialogTitle, + AlertDialogDescription, + AlertDialogAction, + AlertDialogCancel, +} diff --git a/frontend/src/components/ui/alert.tsx b/frontend/src/components/ui/alert.tsx new file mode 100644 index 0000000..5afd41d --- /dev/null +++ b/frontend/src/components/ui/alert.tsx @@ -0,0 +1,59 @@ +import * as React from "react" +import { cva, type VariantProps } from "class-variance-authority" + +import { cn } from "@/lib/utils" + +const alertVariants = cva( + "relative w-full rounded-lg border px-4 py-3 text-sm [&>svg+div]:translate-y-[-3px] [&>svg]:absolute [&>svg]:left-4 [&>svg]:top-4 [&>svg]:text-foreground [&>svg~*]:pl-7", + { + variants: { + variant: { + default: "bg-background text-foreground", + destructive: + "border-destructive/50 text-destructive dark:border-destructive [&>svg]:text-destructive", + }, + }, + defaultVariants: { + variant: "default", + }, + } +) + +const Alert = React.forwardRef< + HTMLDivElement, + React.HTMLAttributes & VariantProps +>(({ className, variant, ...props }, ref) => ( +
+)) +Alert.displayName = "Alert" + +const AlertTitle = React.forwardRef< + HTMLParagraphElement, + React.HTMLAttributes +>(({ className, ...props }, ref) => ( +
+)) +AlertTitle.displayName = "AlertTitle" + +const AlertDescription = React.forwardRef< + HTMLParagraphElement, + React.HTMLAttributes +>(({ className, ...props }, ref) => ( +
+)) +AlertDescription.displayName = "AlertDescription" + +export { Alert, AlertTitle, AlertDescription } diff --git a/frontend/src/components/ui/aspect-ratio.tsx b/frontend/src/components/ui/aspect-ratio.tsx new file mode 100644 index 0000000..c4abbf3 --- /dev/null +++ b/frontend/src/components/ui/aspect-ratio.tsx @@ -0,0 +1,5 @@ +import * as AspectRatioPrimitive from "@radix-ui/react-aspect-ratio" + +const AspectRatio = AspectRatioPrimitive.Root + +export { AspectRatio } diff --git a/frontend/src/components/ui/avatar.tsx b/frontend/src/components/ui/avatar.tsx new file mode 100644 index 0000000..51e507b --- /dev/null +++ b/frontend/src/components/ui/avatar.tsx @@ -0,0 +1,50 @@ +"use client" + +import * as React from "react" +import * as AvatarPrimitive from "@radix-ui/react-avatar" + +import { cn } from "@/lib/utils" + +const Avatar = React.forwardRef< + React.ElementRef, + React.ComponentPropsWithoutRef +>(({ className, ...props }, ref) => ( + +)) +Avatar.displayName = AvatarPrimitive.Root.displayName + +const AvatarImage = React.forwardRef< + React.ElementRef, + React.ComponentPropsWithoutRef +>(({ className, ...props }, ref) => ( + +)) +AvatarImage.displayName = AvatarPrimitive.Image.displayName + +const AvatarFallback = React.forwardRef< + React.ElementRef, + React.ComponentPropsWithoutRef +>(({ className, ...props }, ref) => ( + +)) +AvatarFallback.displayName = AvatarPrimitive.Fallback.displayName + +export { Avatar, AvatarImage, AvatarFallback } diff --git a/frontend/src/components/ui/badge.tsx b/frontend/src/components/ui/badge.tsx new file mode 100644 index 0000000..e87d62b --- /dev/null +++ b/frontend/src/components/ui/badge.tsx @@ -0,0 +1,36 @@ +import * as React from "react" +import { cva, type VariantProps } from "class-variance-authority" + +import { cn } from "@/lib/utils" + +const badgeVariants = cva( + "inline-flex items-center rounded-md border px-2.5 py-0.5 text-xs font-semibold transition-colors focus:outline-none focus:ring-2 focus:ring-ring focus:ring-offset-2", + { + variants: { + variant: { + default: + "border-transparent bg-primary text-primary-foreground shadow hover:bg-primary/80", + secondary: + "border-transparent bg-secondary text-secondary-foreground hover:bg-secondary/80", + destructive: + "border-transparent bg-destructive text-destructive-foreground shadow hover:bg-destructive/80", + outline: "text-foreground", + }, + }, + defaultVariants: { + variant: "default", + }, + } +) + +export interface BadgeProps + extends React.HTMLAttributes, + VariantProps {} + +function Badge({ className, variant, ...props }: BadgeProps) { + return ( +
+ ) +} + +export { Badge, badgeVariants } diff --git a/frontend/src/components/ui/breadcrumb.tsx b/frontend/src/components/ui/breadcrumb.tsx new file mode 100644 index 0000000..60e6c96 --- /dev/null +++ b/frontend/src/components/ui/breadcrumb.tsx @@ -0,0 +1,115 @@ +import * as React from "react" +import { Slot } from "@radix-ui/react-slot" +import { ChevronRight, MoreHorizontal } from "lucide-react" + +import { cn } from "@/lib/utils" + +const Breadcrumb = React.forwardRef< + HTMLElement, + React.ComponentPropsWithoutRef<"nav"> & { + separator?: React.ReactNode + } +>(({ ...props }, ref) =>