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from langchain.output_parsers.structured import StructuredOutputParser, ResponseSchema
from langchain_core.prompts import PromptTemplate
from langchain_core.runnables import RunnablePassthrough, RunnableLambda, RunnableBranch
from climateqa.engine.prompts import reformulation_prompt_template
from climateqa.engine.utils import pass_values, flatten_dict
response_schemas = [
ResponseSchema(name="language", description="The detected language of the input message"),
ResponseSchema(name="question", description="The reformulated question always in English")
]
output_parser = StructuredOutputParser.from_response_schemas(response_schemas)
format_instructions = output_parser.get_format_instructions()
def fallback_default_values(x):
if x["question"] is None:
x["question"] = x["query"]
x["language"] = "english"
return x
def make_reformulation_chain(llm):
prompt = PromptTemplate(
template=reformulation_prompt_template,
input_variables=["query"],
partial_variables={"format_instructions": format_instructions}
)
chain = (prompt | llm.bind(stop=["```"]) | output_parser)
reformulation_chain = (
{"reformulation":chain,**pass_values(["query"])}
| RunnablePassthrough()
| flatten_dict
| fallback_default_values
)
return reformulation_chain
|