This is part 3 of a blog series. In this blog, we’ll show you how to build an LLM question and answering service. In future parts, we will optimize the code and measure performance: cost, latency and throughput.
这是博客系列的第 3 部分。在本博客中,我们将向您展示如何构建LLM问答服务。在以后的部分中,我们将优化代码并测量性能:成本、延迟和吞吐量。
目录
Step 1: The Prompt Template 第 1 步:提示模板
Step 2: Setting up the embeddings and the LLM第 2 步:设置嵌入和 LLM
Step 3: Respond to questions 第 3 步:回答问题
This blog post builds on Part 1 of our LangChain series, where we built a semantic search service in about 100 lines. Still, search is so … 2022. What if we wanted to build a question