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添加系统架构图

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dj
2026-04-16 23:08:21 +08:00
parent 38b0c7e62e
commit 975ebf536b
8 changed files with 339 additions and 57 deletions
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83
backend/app/api/endpoints/ai_analyze.py
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@@ -1,7 +1,7 @@
"""
AI 分析 API 接口
"""
from fastapi import APIRouter, UploadFile, File, HTTPException, Query, Body
from fastapi import APIRouter, UploadFile, File, HTTPException, Query, Body, Form
from fastapi.responses import StreamingResponse
from typing import Optional
import logging
@@ -21,7 +21,8 @@ router = APIRouter(prefix="/ai", tags=["AI 分析"])
@router.post("/analyze/excel")
async def analyze_excel(
file: UploadFile = File(...),
file: Optional[UploadFile] = File(None),
doc_id: Optional[str] = Form(None, description="文档ID（从数据库读取）"),
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")
@@ -30,7 +31,8 @@ async def analyze_excel(
上传并使用 AI 分析 Excel 文件
Args:
file: 上传的 Excel 文件
file: 上传的 Excel 文件（与 doc_id 二选一）
doc_id: 文档ID（从数据库读取）
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
@@ -38,7 +40,57 @@ async def analyze_excel(
Returns:
dict: 分析结果，包含 Excel 数据和 AI 分析结果
"""
# 检查文件类型
filename = None
# 从数据库读取模式
if doc_id:
try:
from app.core.database.mongodb import mongodb
doc = await mongodb.get_document(doc_id)
if not doc:
raise HTTPException(status_code=404, detail=f"文档不存在: {doc_id}")
filename = doc.get("metadata", {}).get("original_filename", "unknown.xlsx")
file_ext = filename.split('.')[-1].lower()
if file_ext not in ['xlsx', 'xls']:
raise HTTPException(status_code=400, detail=f"文档类型不是 Excel: {file_ext}")
file_path = doc.get("metadata", {}).get("file_path")
if not file_path:
raise HTTPException(status_code=400, detail="文档没有存储文件路径，请重新上传")
# 使用文件路径进行 AI 分析
if parse_all_sheets:
result = await excel_ai_service.batch_analyze_sheets_from_path(
file_path=file_path,
filename=filename,
user_prompt=user_prompt,
analysis_type=analysis_type
)
else:
result = await excel_ai_service.analyze_excel_file_from_path(
file_path=file_path,
filename=filename,
user_prompt=user_prompt,
analysis_type=analysis_type
)
if result.get("success"):
return result
else:
return result
except HTTPException:
raise
except Exception as e:
logger.error(f"从数据库读取 Excel 文档失败: {str(e)}")
raise HTTPException(status_code=500, detail=f"读取文档失败: {str(e)}")
# 文件上传模式
if not file:
raise HTTPException(status_code=400, detail="请提供文件或文档ID")
if not file.filename:
raise HTTPException(status_code=400, detail="文件名为空")
@@ -61,7 +113,11 @@ async def analyze_excel(
# 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}")
# 验证文件内容不为空
if not content:
raise HTTPException(status_code=400, detail="文件内容为空，请确保文件已正确上传")
logger.info(f"开始分析文件: {file.filename}, 分析类型: {analysis_type}, 文件大小: {len(content)} bytes")
# 调用 AI 分析服务
if parse_all_sheets:
@@ -155,7 +211,7 @@ async def analyze_text(
@router.post("/analyze/md")
async def analyze_markdown(
file: Optional[UploadFile] = File(None),
doc_id: Optional[str] = Query(None, description="文档ID（从数据库读取）"),
doc_id: Optional[str] = Form(None, description="文档ID（从数据库读取）"),
analysis_type: str = Query("summary", description="分析类型: summary, outline, key_points, questions, tags, qa, statistics, section, charts"),
user_prompt: str = Query("", description="用户自定义提示词"),
section_number: Optional[str] = Query(None, description="指定章节编号，如 '一' 或 '（一）'")
@@ -198,7 +254,7 @@ async def analyze_markdown(
if file_ext not in ['md', 'markdown']:
raise HTTPException(status_code=400, detail=f"文档类型不是 Markdown: {file_ext}")
content = doc.get("content", "")
content = doc.get("content") or ""
if not content:
raise HTTPException(status_code=400, detail="文档内容为空")
@@ -392,7 +448,7 @@ async def get_markdown_outline(
@router.post("/analyze/txt")
async def analyze_txt(
file: Optional[UploadFile] = File(None),
doc_id: Optional[str] = Query(None, description="文档ID（从数据库读取）"),
doc_id: Optional[str] = Form(None, description="文档ID（从数据库读取）"),
analysis_type: str = Query("structured", description="分析类型: structured, charts")
):
"""
@@ -427,7 +483,7 @@ async def analyze_txt(
raise HTTPException(status_code=400, detail=f"文档类型不是 TXT: {file_ext}")
# 使用数据库中的 content
text_content = doc.get("content", "")
text_content = doc.get("content") or ""
if not text_content:
raise HTTPException(status_code=400, detail="文档内容为空")
@@ -498,8 +554,8 @@ async def analyze_txt(
@router.post("/analyze/word")
async def analyze_word(
file: Optional[UploadFile] = File(None),
doc_id: Optional[str] = Query(None, description="文档ID（从数据库读取）"),
user_hint: str = Query("", description="用户提示词，如'请提取表格数据'"),
doc_id: Optional[str] = Form(None, description="文档ID（从数据库读取）"),
user_hint: str = Form("", description="用户提示词，如'请提取表格数据'"),
analysis_type: str = Query("structured", description="分析类型: structured, charts")
):
"""
@@ -536,8 +592,9 @@ async def analyze_word(
raise HTTPException(status_code=400, detail=f"文档类型不是 Word: {file_ext}")
# 使用数据库中的 content 进行分析
content = doc.get("content", "")
tables = doc.get("structured_data", {}).get("tables", [])
content = doc.get("content", "") or ""
structured_data = doc.get("structured_data") or {}
tables = structured_data.get("tables", [])
# 调用 AI 分析服务，传入数据库内容
if analysis_type == "charts":