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import json
import sys
verbose = 1
read_file = '/data/code/gn-ai/gnqa/paper2_eval/data/rag_out_1.json'
values_key = {
"text" : {"name": "contexts", "append": 1},
"associatedQuery": {"name": "question", "append": 0},
"id": {"name": "id", "append": 1},
"title": {"name": "titles", "append": 1},
"document_id": {"name": "document_id", "append": 1},
"extraction_id": {"name": "extraction_id", "append": 1},
"content": {"name": "answer", "append": 0}
}
def get_ragas_out_dict():
return { "titles": [],
"extraction_id": [],
"document_id": [],
"id": [],
"contexts": [],
"answer": "",
"question": ""}
def extract_response(obj, values_key, thedict):
if isinstance(obj, dict):
for key, val in obj.items():
if (key in values_key.keys()):
if (values_key[key]["append"]):
thedict[values_key[key]["name"]].append(val.replace("\n", " ").strip())
else:
thedict[values_key[key]["name"]] = val.replace("\n", " ").strip()
print(("", "Key -> {0}\tValue -> {1}".format(key,val)) [verbose])
else:
if (len(obj.items()) == 1 ):
print(key, " --> ", val)
extract_response(val, values_key, thedict)
elif isinstance(obj, list):
for item in obj:
extract_response(item, values_key, thedict)
# this should be a json file with a list of input files and an output file
with open(read_file, "r") as r_file:
result_file = json.load(r_file)
ragas_output = {
"contexts": [],
"titles": [],
"answer": "",
"question": ""}
extract_response(result_file, values_key, ragas_output)
print(json.dumps(ragas_output, indent=2))
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