Complete the code to define a structured output parser in LangChain.
from langchain.output_parsers import [1] parser = [1]()
The StructuredOutputParser is used to define clear, structured outputs in LangChain.
Complete the code to specify the output schema for structured output.
from langchain.output_parsers import [1] schema = [1](name="answer", description="The final answer") parser = StructuredOutputParser.from_schemas([schema])
ResponseSchema defines the structure of the output expected from the model.
Fix the error in the code to correctly parse the structured output.
response = '{"answer": "42"}' parsed = parser.[1](response)
The parse method is used to convert the raw response string into structured data.
Fill both blanks to create a prompt template that uses structured output parsing.
from langchain.prompts import PromptTemplate prompt = PromptTemplate( template="Answer the question: {question}", input_variables=[[1]], output_parser=[2] )
The input variable is "question" and the output parser is the parser instance.
Fill all three blanks to extract the structured output and access the answer value.
result = parser.parse([1]) answer = result.[2] print(f"The answer is: [3]")
We parse the response, access the answer attribute, and print it.