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import json
import sys
read_file = '/data/code/gn-ai/gnqa/paper2_eval/data/rag_out_1.json'
def iterate_json(obj, thedict):
if isinstance(obj, dict):
for key, val in obj.items():
if (key == "text"):
thedict["contexts"].append(val.replace("\n", " ").strip())
print("Key -> {0}\tValue -> {1}".format(key,val))
elif (key == "metadata"):
thedict["answer"] = val#.replace("\n", " ").strip()
print("Key -> {0}\tValue -> {1}".format(key,val))
elif (key == "id"):
print("Key -> {0}\tValue -> {1}".format(key,val))
elif (key == "associatedQuery"):
thedict["question"] = val.replace("\n", " ").strip()
print("Key -> {0}\tValue -> {1}".format(key,val))
elif (key == "title"):
print("Key -> {0}\tValue -> {1}".format(key,val))
elif (key == "document_id"):
print("Key -> {0}\tValue -> {1}".format(key,val))
else:
if (len(obj.items()) == 1 ):
print(key, " --> ", val)
iterate_json(val, thedict)
elif isinstance(obj, list):
for item in obj:
iterate_json(item, 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": ""}
vector_search_results = result_file["vector_search_results"]
iterate_json(vector_search_results, ragas_output)
print(json.dumps(ragas_output, indent=2))
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