Chains allow you to combine multiple LLM operations.
Build complex workflows with LangChain chains.
Chain Types
SimpleChain: Single input/output
SequentialChain: Multiple steps in sequence
RouterChain: Conditional routing
Sequential Chain Example
from langchain.chains import SequentialChain
chain1 = LLMChain(llm=llm, prompt=prompt1)
chain2 = LLMChain(llm=llm, prompt=prompt2)
overall_chain = SequentialChain(chains=[chain1, chain2])
Best Practices
✅ Keep chains focused
✅ Handle errors gracefully
✅ Monitor token usage
Conclusion
Chains enable complex LLM workflows!