# flake8: noqa
from langchain.prompts.prompt import PromptTemplate

_DEFAULT_ENTITY_EXTRACTION_TEMPLATE = """Extract all entities from the following text. As a guideline, a proper noun is generally capitalized. You should definitely extract all names and places.

Return the output as a single comma-separated list, or NONE if there is nothing of note to return.

EXAMPLE
i'm trying to improve Langchain's interfaces, the UX, its integrations with various products the user might want ... a lot of stuff.
Output: Langchain
END OF EXAMPLE

EXAMPLE
i'm trying to improve Langchain's interfaces, the UX, its integrations with various products the user might want ... a lot of stuff. I'm working with Sam.
Output: Langchain, Sam
END OF EXAMPLE

Begin!

{input}
Output:"""
ENTITY_EXTRACTION_PROMPT = PromptTemplate(
    input_variables=["input"], template=_DEFAULT_ENTITY_EXTRACTION_TEMPLATE
)

prompt_template = """Use the following knowledge triplets to answer the question at the end. If you don't know the answer, just say that you don't know, don't try to make up an answer.

{context}

Question: {question}
Helpful Answer:"""
PROMPT = PromptTemplate(
    template=prompt_template, input_variables=["context", "question"]
)