使用 Flask 快速构建 基于langchain 和 chatGPT的 PDF摘要总结
简介
这里不对 langchain 和 chatGPT 进行介绍，仅对实现过程进行整理
环境
Python >=3.8
Flask2.2.3
Jinja23.1.2
langchain0.0.143
openai0.27.4
实现 总结功能
使用 langchain 和 openai 接口实现总结功能
实现逻辑：通过text_splitter 将pdf 分块，送入 langchain 的summarize_chain中进行处理
同样也可以使用 OpenAIEmbeddings 来实现，文档地址：langchain 官方文档
创建文件：summarize.py
from langchain import PromptTemplate
from langchain.callbacks import get_openai_callback
from langchain.chains.summarize import load_summarize_chain
from langchain.text_splitter import RecursiveCharacterTextSplitterdef summarize_docs(docs, doc_url, llm):print(f'You have {len(docs)} document(s) in your {doc_url} data')print(f'There are {len(docs[0].page_content)} characters in your document')text_splitter = RecursiveCharacterTextSplitter(chunk_size=1000, chunk_overlap=0)split_docs = text_splitter.split_documents(docs)print(f'You have {len(split_docs)} split document(s)')prompt_template = """Write a concise summary of the following:{text}CONCISE SUMMARY IN CHINESE:"""PROMPT = PromptTemplate(template=prompt_template, input_variables=["text"])chain = load_summarize_chain(llm, chain_type="map_reduce", verbose=False, return_intermediate_steps=True,map_prompt=PROMPT, combine_prompt=PROMPT)response = ""with get_openai_callback() as cb:response = chain({"input_documents": split_docs}, return_only_outputs=True)print(f"Total Tokens: {cb.total_tokens}")print(f"Prompt Tokens: {cb.prompt_tokens}")print(f"Completion Tokens: {cb.completion_tokens}")print(f"Successful Requests: {cb.successful_requests}")print(f"Total Cost (USD): ${cb.total_cost}")return response
创建接口
使用 Flask 框架创建简单的接口
创建文件server.py
import osfrom flask import Flask, request, make_response, render_template
from langchain import OpenAI
from langchain.document_loaders import PyPDFLoaderfrom summarize import summarize_docsapp = Flask(__name__)@app.route('/summarize', methods=['POST'])
def summarize():index_path = "./upload"if 'file' not in request.files:return "Please send a POST request with a file", 400uploaded_file = request.files["file"]filename = uploaded_file.filenamefilepath = os.path.join(index_path, os.path.basename(filename))uploaded_file.save(filepath)llm = OpenAI(temperature=0, openai_api_key=OPENAI_API_KEY, model_name="text-davinci-003",openai_api_base=OPENAI_API_BASE)loader = PyPDFLoader(filepath)pages = loader.load_and_split()result = summarize_docs(pages, filepath, llm)return make_response(str(result.get("output_text"))), 200if __name__ == '__main__':if not os.path.exists('./upload'):os.makedirs('./upload')os.environ["OPENAI_API_KEY"] = "sk-XXXXXXXXXXXXXXXXXXXXXXXXX"OPENAI_API_KEY = os.environ['OPENAI_API_KEY']OPENAI_API_BASE = 'https://XXXX/v1'app.run(port=19100, host='127.0.0.1')
创建页面
在 server.py 中添加路由地址
@app.route('/')
def index():msg = "welcome to pdf summarize."return render_template("web.html", data=msg)
创建目录 templates, 并创建 html 文件 web.html:
<!DOCTYPE html>
<html><head><meta charset="UTF-8"><title>文件上传</title><style>body {font-family: Arial, sans-serif;margin: 0;padding: 0;background-color: #f5f5f5;}.container {max-width: 600px;margin: 0 auto;padding: 20px;background-color: #fff;border-radius: 10px;box-shadow: 0 0 10px rgba(0, 0, 0, .2);}h1 {margin-top: 0;font-size: 32px;color: #333;text-align: center;}form {display: flex;flex-direction: column;align-items: center;}input[type="file"] {margin-bottom: 20px;font-size: 16px;color: #333;padding: 10px;border: 1px solid #ccc;border-radius: 5px;background-color: #fff;box-shadow: 0 0 5px rgba(0, 0, 0, .1);}button {padding: 10px;background-color: #4CAF50;color: #fff;border: none;border-radius: 5px;cursor: pointer;transition: background-color .2s;}button:hover {background-color: #3e8e41;}.result {margin-top: 20px;padding: 20px;background-color: #f1f1f1;border-radius: 5px;white-space: pre-wrap;}.progress {margin-top: 20px;width: 100%;height: 20px;background-color: #f1f1f1;border-radius: 5px;overflow: hidden;box-shadow: 0 0 5px rgba(0, 0, 0, .1);}.bar {width: 0;height: 100%;background-color: #4CAF50;transition: width .2s;}</style></head><body><div class="container"><h1>文件上传</h1><form id="upload-form" method="POST" action="http://127.0.0.1:5000/summarize" enctype="multipart/form-data"><input type="file" name="file"><button type="submit">生成摘要</button></form><div class="progress"><div class="bar"></div></div><h2>返回结果</h2><div>目前响应时间较长，700k 文件响应时间为22秒，请耐心等待</div><div class="result"><div id="result-text"></div></div><div>页面生成 power by openai chatGPT-3.5</div></div><script>const form = document.querySelector('#upload-form');const progressBar = document.querySelector('.bar');form.addEventListener('submit', async (event) => {event.preventDefault();const formData = new FormData(form);const xhr = new XMLHttpRequest();xhr.upload.addEventListener('progress', (event) => {const percent = (event.loaded / event.total) * 100;progressBar.style.width = percent + '%';});xhr.onreadystatechange = () => {if (xhr.readyState === XMLHttpRequest.DONE && xhr.status === 200) {progressBar.style.width = '0';document.querySelector('#result-text').textContent = xhr.responseText;}};xhr.open(form.method, form.action);xhr.send(formData);});</script></body>
</html>
运行展示
完成后整体项目结构如下：
运行效果如下：
