application.py

import os

'''
shared environment variables
'''

aws_access_key_id = os.getenv('AMRA_AWS_ACCESS_KEY_ID')
aws_secret_access_key = os.getenv('AMRA_AWS_SECRET_ACCESS_KEY')
openai_api_key = os.getenv('AMRA_OPENAI_API_KEY')

default_region = "Spine"

device_options={
    "secondary extraction":False,
    "secondary extraction count":0
}

default_s3_bucket = "amra-studies"

'''
ui equivalent environment variables
'''
ec_options={
    "Equivalent Comparator":False,
    "Equivalent Comparator require SD":False,
    "Equivalent Comparator count":0
}

anatomic_domains=[
    # "Dental/CMF",
    "Extremity",
    "Spine"
]

'''
dynamodb tables structure
'''

# logic_keywords = {
#         "groups":["group"],
#         "preoperatives":["preoperative","preop","pre-op"]
#     }

source_format = "<column 1 field>\n<value 1>\n<value 2>...<value n>\n<column 2 field>\n<value 1>\n<value 2>...<value n>\n...<column n field>\n<value 1>\n<value 2>...<value n>\n"

anatomic_list = ["Spinal","Extremities"]

tables_inst=[
    f"extract tables from the system text. the tables are mostly in the following format: {source_format}",
    f"reformat the returned tables into a markdown table syntax.",
    f"if applicable, remove the standard deviation after the mean and round all the numbers to one decimal places.",
    f"include all table titles."
]

reformat_inst = f"reformat the returned tables into a markdown table syntax if applicable."

article_prompts = {
    "Authors": '''extract all of the authors of the article from the above text.\n
    Return the results on the same line separated by commas as Authors: Author A, Author B...
    ''',
    "Acceptance Year": '''extract the acceptance year of the article from the above text.\n
    Return the results on a single line as Accepted Year: <year>.
    ''',

    "Acceptance Month":'''extract the acceptance month of the article from the above text.\n
    Return the results on a single line as Accepted Month: <month>.
    '''
}

'''
application default data
'''
app_data = {
    "current article":{},
    "articles":{},
    "prompts":{},
    "terms":[],
    "summary":{},
    "current":{
        "term":""
    }
}