chains.summarize import load_summarize_chain from langchain.text_splitter import RecursiveCharacterTextSplitter llm = OpenAI(temperature=0, openai_api_key=openai_api_key) 代码语言:javascript 代码运行次数:0 运行 AI代码解释 with open('wonderland.txt', 'r') as file: text = file.read() # 文章...
LangChain 通过他们的load_summarize_chain开箱即用地支持不同的总结方法。 较长文本的摘要 注意:此方法也适用于短文本 摘要涉及创建多个较长文档的较小摘要。这对于将长文档提炼成核心信息很有用。 开始使用汇总链的推荐方法是: from langchain.llms import OpenAI from langchain.chains.summarize import load_summ...
Lang Chain 提供了开箱即用的工具解决长文本的问题:load_summarize_chain # Summaries Of Longer Text from langchain.llms import OpenAI from langchain.chains.summarize import load_summarize_chain from langchain.text_splitter import RecursiveCharacterTextSplitter llm = OpenAI(temperature=0, openai_api_key=...
# 设置 lang chain# 使用 map_reduce的chain_type,这样可以将多个文档合并成一个chain = load_summarize_chain(llm=llm, chain_type='map_reduce') # verbose=True 展示运行日志 # Use it. This will run through the 36 documents, summarize the chunks, then get a summary of the summary.# 典型的map...
load:首先我们需要加载数据。 这是通过 DocumentLoaders 完成的。 Split:文本分割器将大文档分成更小的块。 这对于索引数据和将其传递到模型都很有用,因为大块更难搜索并且不适合模型的有限上下文窗口。 store:我们需要某个地方来存储和索引我们的分割,以便以后可以搜索它们。 这通常是使用 VectorStore 和 Embeddings ...
chains.summarize.chain.load_summarize_chain(llm) Load summarizing chain. Deprecated classes chains.api.base.APIChain Deprecated since version 0.2.13: This class is deprecated and will be removed in langchain 1.0. See API reference for replacement: https://api.python.langchain.com/en/latest/chains...
langgraph: Orchestration framework for combining LangChain components into production-ready applications with persistence, streaming, and other key features. SeeLangGraph documentation. Guides Tutorials If you're looking to build something specific or are more of a hands-on learner, check out ...
summarize_chain, prompt_generation_chain, web_search_agent, ] ) Step 5: Apply the LangChain transformer to perform the workload at scale We can now use the defined pipeline to process a DataFrame containing links of different documents, e.g., arXiv...
key, use_ssl=use_ssl)document = file_loader.load()Python Langchain 示例 - S3 文件加载程序Langchain S3 目录加载程序：from langchain_community.document_loaders.s3_directory import S3DirectoryLoader# Initialize and load documentsdirectory_loader = S3DirectoryLoader( bucket='web-documentation', ...
You can use LangChain to build chatbots or personal assistants, to summarize, analyze, or generate Q&A over documents or structured data, to write or understand code, to interact with APIs, and to create other applications that take advantage of generative AI. There are currently two versions...