mirror of
https://github.com/hwchase17/langchain
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41 lines
1.0 KiB
Python
41 lines
1.0 KiB
Python
from langchain.llms import OpenAI
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from langchain.output_parsers import GuardrailsOutputParser
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from langchain.prompts import PromptTemplate
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# Define rail string
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rail_str = """
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<rail version="0.1">
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<output>
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<string
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description="Profanity-free translation"
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format="is-profanity-free"
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name="translated_statement"
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on-fail-is-profanity-free="fix">
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</string>
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</output>
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<prompt>
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Translate the given statement into English:
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${statement_to_be_translated}
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${gr.complete_json_suffix}
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</prompt>
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</rail>
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"""
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# Create the GuardrailsOutputParser object from the rail string
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output_parser = GuardrailsOutputParser.from_rail_string(rail_str)
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# Define the prompt, model and chain
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prompt = PromptTemplate(
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template=output_parser.guard.prompt.escape(),
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input_variables=output_parser.guard.prompt.variable_names,
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)
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chain = prompt | OpenAI() | output_parser
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# This is needed because GuardrailsOutputParser does not have an inferrable type
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chain = chain.with_types(output_type=dict)
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