LangChain Framework
LangChain is a Python/JS framework for composing LLM applications. It abstracts prompt templates, memory, chains, and tool integration. Developers use it to build chatbots, question-answering systems, and autonomous agents. Mastery takes 4-6 weeks. Senior practitioners command 25-30% premiums because they can architect multi-stage LLM workflows. This is the most-used LLM framework in industry (2026).
什麼是 LangChain Framework
LangChain is a Python and JavaScript framework for building applications with large language models. It provides abstractions for common patterns: prompts (templates + input variables), chains (sequences of LLM calls), memory (conversation history), agents (LLMs that decide which tools to use), and tool integration (web search, calculators, databases). Without LangChain, you'd manually manage prompts, parse LLM outputs, handle errors, and orchestrate workflows. LangChain standardizes these patterns. Most LLM applications built in 2024-2026 use LangChain or its competitors (LlamaIndex, Haystack).
💰 各地區薪資
| 地區 | 初級 | 中級 | 高級 |
|---|---|---|---|
| USA | $80,000 | $135,000 | $200,000 |
| UK | £50,000 | £82,000 | £125,000 |
| EU | €55,000 | €90,000 | €135,000 |
| CANADA | CA$85,000 | CA$145,000 | CA$215,000 |
🎓 認證
🎯 使用 LangChain Framework 的職業
❓ 常見問題
When should I use LangChain vs CrewAI?
How do I add memory to a chain?
What's the difference between a chain and a tool?
How do I handle token limits in long conversations?
Can I use LangChain with open-source models?
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