📄 中文摘要
许多开发者认为部署大型语言模型（LLM）就是产品的最终目标，然而这只是一个开始。LLM能够生成文本，支持多种应用场景，但要实现其真正的价值，需要将其与其他工具和服务进行整合。通过使用LangChain，可以将LLM与金融市场数据工具、FastAPI API等结合，构建出强大的企业级金融研究助手。这种模块化的C4架构能够有效地协调不同的LLM代理，提升应用的灵活性和功能性。
使用 LangChain AI 协调构建 LLM 应用
出处: Building LLM Apps Using LangChain AI Orchestration
发布: 2026年3月7日
📄 English Summary
Building LLM Apps Using LangChain AI Orchestration
Many developers perceive deploying a large language model (LLM) as the end goal of their product, but this is merely the beginning. While LLMs can generate text and support various applications, their true value is realized when integrated with other tools and services. By utilizing LangChain, LLMs can be combined with financial market data tools, FastAPI APIs, and more to create powerful enterprise-grade financial research assistants. This modular C4 architecture effectively orchestrates different LLM agents, enhancing the flexibility and functionality of applications.