前情提要

检索增强生成（RAG）技术，作为 AI 领域的尖端技术，能够提供可靠且最新的外部知识，极大地便利了各种任务。在 AI 内容生成的浪潮中，RAG 通过其强大的检索能力为生成式 AI 提供了额外的知识，助力其产出高质量内容。尽管大型语言模型（LLMs）在语言处理上展现了突破性的能力，但仍受限于内部知识的幻觉和过时。因此，检索增强的 LLMs 应运而生，它们利用外部权威知识库，而非仅依赖内部知识，以提升生成质量。

遇到问题

针对pptx的文档解析技术存在已久，但是ppt格式文件无法进行解析，且我没有搜索到在Linux系统服务器中ppt转pptx的资料，window系统中倒是可以转换

解决方案

安装系统依赖

apt-get install unoconv
apt-get install libreoffice

安装软件包依赖

pip install unoconv
pip install pyuno
pip install weaviate-client
pip install unstructured[all-docs] == 0.13.3
pip install python-dotenv

代码demo

import glob
import os
import subprocess
import weaviate
import weaviate.classes as wvc
from dotenv import load_dotenv
from unstructured.chunking.title import chunk_by_title
from unstructured.documents.elements import CompositeElement, Table
from unstructured.partition.pptx import partition_pptx
from weaviate.config import AdditionalConfigload_dotenv()
os.environ['UNO_PATH'] = '/usr/lib/libreoffice'
os.environ['PATH'] += ':/usr/lib/libreoffice/program'file_path = "/your/ppt_path/case_1.ppt"def extract_text(file_name: str):elements = partition_pptx(filename=file_name,multipage_sections=True,infer_table_structure=True,include_page_breaks=False,)chunks = chunk_by_title(elements=elements,multipage_sections=True,combine_text_under_n_chars=0,new_after_n_chars=None,max_characters=4096,)text_list = []for chunk in chunks:if isinstance(chunk, CompositeElement):text = chunk.texttext_list.append(text)elif isinstance(chunk, Table):if text_list:text_list[-1] = text_list[-1] + "\n" + chunk.metadata.text_as_htmlelse:text_list.append(chunk.hunk.metadata.text_as_html)result_dict = {"无标题":[]}for text in text_list:split_text = text.split("\n\n", 1)if len(split_text) == 2:title, text = split_textif title not in result_dict:result_dict[title] = []result_dict[title].append(text)else:result_dict["无标题"].append(text)return result_dictdef split_chunks(text_list: list, source: str):chunks = []for text in text_list:for key, value in text.items():chunks.append({"question": key, "answer": value, "source": source})return chunksdef convert_ppt_to_pptx(ppt_file_path):# Define the command to run LibreOffice in headless modecommand = ['libreoffice','--headless','--convert-to', 'pptx','--outdir', os.path.dirname(ppt_file_path),ppt_file_path]# Run the commandresult = subprocess.run(command, capture_output=True, text=True)if result.returncode != 0:raise RuntimeError(f"Failed to convert '{ppt_file_path}' to PPTX.\nError: {result.stderr}")return ppt_file_path.replace('.ppt', '.pptx')pptx_file_path = convert_ppt_to_pptx(file_path)
print("convert ppt to pptx done")
contents = extract_text(pptx_file_path)
for k,v in contents.items():print(k,v)print("__"*30)