split_result接口增加文件摘要抽取功能

chunk_text.py

@@ -15,6 +15,7 @@ except ImportError:
 from pathlib import PurePath, PurePosixPath, Path as PathLib
 from fastapi import FastAPI, File, Path, UploadFile, HTTPException, Form, Request, Header, Body
 from fileparse_util import process_document
+from generate_summary import generate_summaries
 from io import BytesIO
 from urllib.parse import unquote, urlparse
 import asyncio
@@ -44,6 +45,42 @@ except ImportError:
     SHIP_MODEL_NAME = ""
 logger = logging.getLogger(__name__)
 
+SUMMARY_GENERATION_TIMEOUT_SECONDS = 60
+
+
+def get_text_level_summary_fallback(content_list) -> str:
+    summary_parts = []
+    for record in content_list:
+        if not isinstance(record, dict):
+            continue
+
+        text_level = record.get("text_level")
+        if text_level is None or text_level == "":
+            continue
+
+        text = record.get("text")
+        if text:
+            summary_parts.append(str(text).strip())
+
+    return "\n".join(summary_parts)
+
+
+async def generate_summary_from_md(md_content: Optional[str],content_list) -> str:
+    if not md_content or not str(md_content).strip():
+        return get_text_level_summary_fallback(content_list)
+    try:
+        summaries = await asyncio.wait_for(
+            generate_summaries([str(md_content)]),
+            timeout=SUMMARY_GENERATION_TIMEOUT_SECONDS,
+        )
+        summary = summaries[0] if summaries else ""
+        if summary:
+            return summary
+        logger.warning("生成文档摘要为空，使用 content_list text_level 兜底摘要")
+    except Exception as exc:
+        logger.error(f"生成文档摘要失败，使用 content_list text_level 兜底摘要: {exc}", exc_info=True)
+    return get_text_level_summary_fallback(content_list)
+
 
 ocr_engine = RapidOCR()
 OCR_SEMAPHORE = asyncio.Semaphore(max(1, OCR_CONCURRENCY))
@@ -355,7 +392,6 @@ def record_to_chunk_text(ins: Dict[str, Any]) -> str:
         return join_nonempty_parts(
             ocr_text,
             ins.get("text"),
-            ins.get("img_path"),
         )
 
     if record_type == "code":
@@ -1086,6 +1122,8 @@ async def data_replace(data, prefix):
     使用 pathlib 安全处理路径。
     """
     for ins in data:
+        if isinstance(ins, dict) and ins.get("type") == "equation":
+            continue
         if isinstance(ins, dict) and "img_path" in ins:
             img_path = ins["img_path"]
             local_image_paths = []
@@ -1255,103 +1293,6 @@ def find_ship_info_by_hull(json_file_path, data):
     except json.JSONDecodeError:
         print("错误：JSON 文件格式不正确")
         return None
-# def merge_short_slices(slices, min_length=30,filename="122-06A0014-B01003_雷达-使用说明书.pdf"):
-    """ 
-    合并过短的切片：
-    - 如果某切片 content 长度 <= min_length，则将其合并到下一个切片的开头
-    - 若处于末尾无下一个切片，则反向合并到上一个切片末尾
-    - content 用换行拼接，positions 顺序拼接
-    
-    Args:
-        slices: [{"content": str, "positions": [...]}]
-        min_length: 短切片的字符长度阈值（含）
-        filename: 用于实体提取的文件名
-    
-    Returns:
-        合并后的 slices 列表
-    """
-    if not slices:
-        return slices
-
-    result = []
-    pending_contents = []  # 缓存等待合并到"下一个"的短切片 content
-    pending_positions = []  # 缓存对应的 positions
-
-    for ins in slices:
-        content = ins.get("content", "") or ""
-        positions = ins.get("positions", []) or []
-
-        if len(content) <= min_length:
-            # 暂存，等到下一个正常长度的切片再合并
-            pending_contents.append(content)
-            pending_positions.extend(positions)
-        else:
-            # 正常切片：把暂存的短切片合并到它的开头
-            if pending_contents:
-                merged_prefix = "\n".join(pending_contents)
-                content = merged_prefix + ("\n" if merged_prefix else "") + content
-                positions = pending_positions + positions
-                pending_contents = []
-                pending_positions = []
-            
-            result.append({
-                "content": content,
-                "positions": positions
-            })
-
-    # 收尾：如果末尾还有未合并的短切片（后面没有正常切片可合并）
-    # 则反向合并到上一个切片末尾
-    if pending_contents:
-        merged_suffix = "\n".join(pending_contents)
-        if result:
-            last = result[-1]
-            last["content"] = (last["content"] or "") + ("\n" if last["content"] else "") + merged_suffix
-            last["positions"] = (last["positions"] or []) + pending_positions
-        else:
-            # 极端情况：所有切片都很短，整体作为一个切片返回
-            result.append({
-                "content": merged_suffix,
-                "positions": pending_positions
-            })
-
-    try:
-        final_result = get_entity(filename)
-        xinghao = find_ship_info_by_hull(SHIP_MODEL_NAME, final_result)
-        if xinghao is None:  # 确保 xinghao 为 None 时不会报错
-            xinghao = {"model_name": "", "ship_name": ""}
-            print("未找到匹配的舰船信息")
-
-        # 安全处理 xinghao 为 None 的情况
-        model_name = ""
-        if xinghao and 'model_name' in xinghao:
-            model_name = xinghao['model_name']
-            
-        other_data = format_entity_text(final_result)
-        logger.info(f"文件名实体提取成功: {other_data}")
-    except Exception as e:
-        logger.warning(f"文件名实体提取失败: {e}")
-        other_data = ""
-        model_name = ""  # 确保异常时 model_name 有定义
-
-    # 将提取的信息（如舰艇名、型号）注入到每个切片的开头
-    for ins in result:
-        content = ins['content']
-        # 如果没有提取到有效数据，则跳过注入
-            
-        newline_idx = content.find('\n')
-        info = other_data
-        if model_name:
-            info += f'，型号为{model_name}'
-        suffix = f'({info})'
-        
-        # 将信息插入到第一行末尾
-        if newline_idx == -1:
-            ins['content'] = content + suffix
-        else:
-            ins['content'] = content[:newline_idx] + suffix + content[newline_idx:]
-
-    return result
-
 
 def merge_short_slices(slices, min_length=30, filename="122-06A0014-B01003_雷达-使用说明书.pdf"):
     """ 
@@ -1490,14 +1431,16 @@ async def process_pdf_file(pdf_path: Path, image_prefix: str,filename:str) -> Op
     """异步调用 PDF 分析服务并处理响应"""
     doc_result = await process_document(filename)
     if doc_result is not None:
-        content_list, images = doc_result
+        content_list, images, md_content = doc_result
         if content_list and images:
             replaced_content_textlevel = reset_textlevel(content_list)
             replaced_content_list = await data_replace(replaced_content_textlevel, image_prefix)
             slices = get_chunk_bbox(replaced_content_list)
             slices_check = chunk_check(slices, 8000)
             slices_check = merge_short_slices(slices_check, min_length=30,filename=filename) 
-            return {"slices": slices_check, "images": images}
+            summary = await generate_summary_from_md(md_content,content_list)
+            summary = f"文件名:{filename}\n" + summary
+            return {"slices": slices_check, "images": images, "summary": summary}
 
     api_url = get_api_url()
     try:
@@ -1516,19 +1459,20 @@ async def process_pdf_file(pdf_path: Path, image_prefix: str,filename:str) -> Op
         data = result.get("data", {})
         content_list = data.get("content_list", [])
         images = data.get("images", {})
+        md_content = data.get("full_content", "")
         replaced_content_textlevel = reset_textlevel(content_list)
         replaced_content_list = await data_replace(replaced_content_textlevel, image_prefix)
         slices = get_chunk_bbox(replaced_content_list)
         slices_check = chunk_check(slices, 8000)
         slices_check = merge_short_slices(slices_check, min_length=30,filename=filename) 
-        print(11111111111111111111111111111111111111)
-        print(len(images))
-        return {"slices": slices_check, "images": images}
+        summary = await generate_summary_from_md(md_content,content_list)
+        summary = f"文件名:{filename}\n" + summary
+        return {"slices": slices_check, "images": images, "summary": summary}
 
     except json.JSONDecodeError:
         logger.error("❌ 响应不是有效的 JSON 格式")
         logger.debug(response.text)
-        return {"slices": [], "images": {}}
+        return {"slices": [], "images": {}, "summary": ""}
     except Exception as e:
         logger.error(f"处理 PDF 文件时出错: {e}", exc_info=True)
         return None
@@ -1540,13 +1484,15 @@ async def process_other_file(pdf_path: Path, image_prefix: str, filename: str) -
     # 优先尝试走本地/缓存处理（保持与你原逻辑一致）
     doc_result = await process_document(filename)
     if doc_result is not None:
-        content_list, images = doc_result
+        content_list, images, md_content = doc_result
         if content_list and images:
             replaced_content_textlevel = reset_textlevel(content_list)
             replaced_content_list = await data_replace(replaced_content_textlevel, image_prefix)
             slices = get_chunk_bbox(replaced_content_list)
             slices_check = chunk_check(slices, 8000)
-            return {"slices": slices_check, "images": images}
+            summary = await generate_summary_from_md(md_content,content_list)
+            summary = f"文件名:{filename}\n" + summary
+            return {"slices": slices_check, "images": images, "summary": summary}
 
     api_url = get_api_url()
     analyze_other_url = api_url.replace("/analyze-pdf", "/analyze-otherfile")
@@ -1571,19 +1517,21 @@ async def process_other_file(pdf_path: Path, image_prefix: str, filename: str) -
         data = result.get("data", {})
         content_list = data.get("content_list", [])
         images = data.get("images", {})
-        
+        md_content = data.get("full_content", "")
         # 后续的数据替换与切片处理逻辑
         replaced_content_textlevel = reset_textlevel(content_list)
         replaced_content_list = await data_replace(replaced_content_textlevel, image_prefix)
         slices = get_chunk_bbox(replaced_content_list)
         slices_check = chunk_check(slices, 8000)
 
-        return {"slices": slices_check, "images": images}
+        summary = await generate_summary_from_md(md_content,content_list)
+        summary = f"文件名:{filename}\n" + summary
+        return {"slices": slices_check, "images": images, "summary": summary}
 
     except json.JSONDecodeError:
         error_text = response.text if 'response' in locals() else "请求未到达服务器"
         logger.error(f"❌ 响应不是有效的 JSON 格式: {error_text}")
-        return {"slices": [], "images": {}}
+        return {"slices": [], "images": {}, "summary": ""}
     except Exception as e:
         logger.error(f"处理 Office 文件时出错: {e}", exc_info=True)
         return None

fileparse_util.py

@@ -44,6 +44,34 @@ async def find_and_read_content_list(
         return None, None
 
 
+async def find_and_read_md_file(
+    directory: str,
+    original_filename: str,
+    encoding: str = 'utf-8'
+) -> Tuple[Optional[str], Optional[str]]:
+    """Find and read the Markdown file matching the uploaded document basename."""
+    file_name, _ = os.path.splitext(original_filename)
+    target_filename = f"{file_name}.md"
+    logger.info(f"正在查找 Markdown 文件: {target_filename}")
+
+    def _walk_for_file():
+        for root, _, files in os.walk(directory):
+            if target_filename in files:
+                return os.path.join(root, target_filename)
+        return None
+
+    file_path = await asyncio.to_thread(_walk_for_file)
+    if file_path is None:
+        return None, None
+
+    try:
+        async with aiofiles.open(file_path, 'r', encoding=encoding, errors='ignore') as f:
+            return await f.read(), file_path
+    except Exception as e:
+        logger.error(f"读取 Markdown 文件 {file_path} 时发生错误: {e}")
+        return None, None
+
+
 def extract_all_jpg_filenames(doc_data: list) -> set:
     """从文档数据中提取所有 .jpg 图片的纯文件名。纯 CPU 操作,不需要 async。"""
     result_set = set()
@@ -105,7 +133,7 @@ async def process_document(
     input_file_name: str,
     local_image_dir: Optional[str] = None,
     concurrency: int = 32,
-) -> Optional[Tuple[list, Dict[str, str]]]:
+) -> Optional[Tuple[list, Dict[str, str], Optional[str]]]:
     """
     异步处理文档:查找 content_list.json,提取图片引用,并发编码为 base64。
 
@@ -116,7 +144,7 @@ async def process_document(
         concurrency: 图片编码的并发数上限,默认 32
 
     Returns:
-        成功: (content_list, images_dict)
+        成功: (content_list, images_dict, md_content)
         失败: None
     """
     search_dir = SEARCH_DIR
@@ -128,6 +156,13 @@ async def process_document(
     logger.info(f"✅ 找到文件: {content_path}")
     logger.info(f"内容类型: {type(content).__name__}, 长度: {len(str(content))}")
 
+    md_content, md_path = await find_and_read_md_file(search_dir, input_file_name)
+    if md_content is None:
+        logger.info("未找到对应的 Markdown 文件。")
+    else:
+        logger.info(f"找到 Markdown 文件: {md_path}")
+        logger.info(f"Markdown 内容长度: {len(md_content)}")
+
     if local_image_dir is None:
         local_image_dir = os.path.join(os.path.dirname(content_path), "images")
     logger.info(f"图片目录: {local_image_dir}")
@@ -140,20 +175,19 @@ async def process_document(
     )
     logger.info(f"成功编码 {len(images_dict)} 张图片")
 
-    return content, images_dict
+    return content, images_dict, md_content
 
 
 async def main():
     result = await process_document(
         input_file_name="163-06A0014-B01001_发动机-维修手册.pdf",
-        search_dir="/app/mineru_output",
         concurrency=32,
     )
 
     if result is None:
         return 1
 
-    content, images_dict = result
+    content, images_dict, md_content = result
     print(f"\n=== 处理完成 ===")
     print(f"文档段落数: {len(content)}")
     print(f"图片数量: {len(images_dict)}")

generate_summary.py

@@ -0,0 +1,142 @@
+"""
+文件概述生成工具
+把 wiki_engine 的文档概述能力独立出来
+输入：markdown 格式的文件内容
+输出：文件概述（SUMMARY 行 + markdown 正文）
+支持并发
+"""
+import asyncio
+from typing import List, Optional
+from config import LLM_CONFIG
+from openai import AsyncOpenAI
+
+
+# ==================== 配置 ====================
+_MAX_CONCURRENCY = 8  # 最大并发数
+
+_client: Optional[AsyncOpenAI] = None
+_semaphore: Optional[asyncio.Semaphore] = None
+
+
+def _get_client() -> AsyncOpenAI:
+    """获取或创建 AsyncOpenAI 单例客户端"""
+    global _client
+    if _client is None:
+        _client = AsyncOpenAI(api_key=LLM_CONFIG['api_key'], base_url=LLM_CONFIG['base_url'])
+    return _client
+
+
+def _get_semaphore() -> asyncio.Semaphore:
+    """获取或创建并发信号量"""
+    global _semaphore
+    if _semaphore is None:
+        _semaphore = asyncio.Semaphore(_MAX_CONCURRENCY)
+    return _semaphore
+
+
+# ==================== Prompt（与 wiki_builder.py 的 WIKI_SUMMARY_PROMPT 一致，仅去掉 extracted_slugs 相关部分） ====================
+SUMMARY_PROMPT = """You are a wiki editor. Given the following document content, create a structured wiki summary page in Markdown format.
+
+<document>
+<content>
+{content}
+</content>
+</document>
+
+<instructions>
+1. The FIRST line of your output MUST be: SUMMARY: {{one sentence, 15-40 words, describing what this document is about for wiki index listing}}
+2. Create a concise but useful document-level summary.
+3. Include the document's main subject, scope, important procedures, standards, systems, equipment, tables, fields.
+4. Do NOT invent facts. Stay grounded in the document content.
+5. Write in Chinese.
+6. If the content is empty or has no substantive information, output exactly: "SUMMARY: No textual content was extractable from this document." followed by a brief note.
+</instructions>
+
+Output the SUMMARY line first, then the Markdown content. Do not include any other preamble."""
+
+
+async def generate_summary(content: str) -> str:
+    """
+    从 markdown 内容生成文件概述
+
+    Args:
+        content: markdown 格式的文件内容
+
+    Returns:
+        文件概述（SUMMARY 行 + markdown 正文）
+    """
+    if not content or not content.strip():
+        return ""
+
+    prompt = SUMMARY_PROMPT.format(content=content)
+    client = _get_client()
+
+    async with _get_semaphore():
+        try:
+            response = await client.chat.completions.create(
+                model=LLM_CONFIG['model'],
+                messages=[
+                    {"role": "system", "content": "You are a grounded wiki editor. Do not invent facts."},
+                    {"role": "user", "content": prompt},
+                ],
+                temperature=0.1,
+                max_tokens=LLM_CONFIG['max_tokens'],
+                stream=False,
+                extra_body={"chat_template_kwargs": {"enable_thinking": False}},
+            )
+            return (response.choices[0].message.content or "").strip()
+        except Exception as exc:
+            print(f"[generate_summary] 概述生成失败: {exc}")
+            return ""
+
+
+async def generate_summaries(contents: List[str]) -> List[str]:
+    """
+    并发生成多个文件的概述
+
+    Args:
+        contents: markdown 格式的文件内容列表
+
+    Returns:
+        文件概述列表，顺序与输入一致
+    """
+    return await asyncio.gather(*(generate_summary(c) for c in contents))
+
+
+if __name__ == "__main__":
+#     import sys
+    from pathlib import Path
+
+#     if len(sys.argv) > 1:
+#         with open(sys.argv[1], "r", encoding="utf-8") as f:
+#             test_content = f.read()
+#     else:
+#         test_content = """
+# # 船舶动力系统维护规程
+
+# ## 概述
+# 本文档详细介绍了船舶动力系统的日常维护和故障处理流程。
+
+# ## 发动机日常检查
+# - 润滑油位检查：每日检查发动机润滑油位，保持在标尺正常范围
+# - 冷却液位检查：确保冷却系统液位正常，无泄漏
+# - 皮带张紧度：检查传动皮带张紧度，过松或过紧均需调整
+
+# ## 冷却系统维护
+# 定期清洗热交换器，检查水泵密封性，更换老化管路。
+
+# ## 故障诊断流程
+# 1. 现象观察：记录故障现象和发生条件
+# 2. 数据采集：收集运行参数和报警信息
+# 3. 原因分析：对照标准参数分析故障原因
+# 4. 处理方案：制定维修方案并执行
+
+# ## 安全注意事项
+# 所有维护操作必须在停机状态下进行，操作人员需佩戴防护装备。
+# """
+    md_path = Path(r"E:\ZKYNLP\Hjunproject\project0506\kgrag\船舶主机燃油泵自动控制系统故障树分析.md")
+    with open(md_path, "r", encoding="utf-8") as f:
+        test_content = f.read()
+
+    result = asyncio.run(generate_summary(test_content))
+    print(result)