<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:sy="http://purl.org/rss/1.0/modules/syndication/" xmlns:media="http://search.yahoo.com/mrss/"><channel><title>Langchain on Shaowen Chen's Website</title><link>https://www.chenshaowen.com/en/tags/langchain/</link><description>Recent content in Langchain on Shaowen Chen's Website</description><generator>Hugo -- gohugo.io</generator><language>en</language><copyright>&amp;copy;2016 - {year}, All Rights Reserved.</copyright><lastBuildDate>Wed, 16 Aug 2023 00:00:00 +0000</lastBuildDate><sy:updatePeriod>weekly</sy:updatePeriod><atom:link href="https://www.chenshaowen.com/en/tags/langchain/atom.xml" rel="self" type="application/rss+xml"/><item><title>Calling Functions Through Dialogue with OpenAI and Langchain</title><link>https://www.chenshaowen.com/en/blog/call-functions-through-dialogue-using-openai-and-langchain.html</link><pubDate>Wed, 16 Aug 2023 00:00:00 +0000</pubDate><atom:modified>Wed, 16 Aug 2023 00:00:00 +0000</atom:modified><guid>https://www.chenshaowen.com/en/blog/call-functions-through-dialogue-using-openai-and-langchain.html</guid><description>1. LLMs and Langchain Many people may never get the chance to train, or even fine-tune, a large model, but using large models is the wave of the future. So how should we embrace this change? The answer is Langchain. A large model provides a broad, general-purpose foundation. So far</description><dc:creator>微信公众号</dc:creator><category>OpenAI</category><category>Langchain</category><category>AI</category><category>LLM</category><category>R&amp;D</category><category>Learning</category><category>Function Calling</category><category>Application Development</category><category>Best Practices</category></item></channel></rss>