File size: 2,932 Bytes
c7a6fe6 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 | from openai import OpenAI
import json, os
source_language = "Bengali"
if source_language == "English":
source_lang_code = "en"
elif source_language == "Spanish":
source_lang_code = "es"
elif source_language == "French":
source_lang_code = "fr"
elif source_language == "Portuguese":
source_lang_code = "pt"
elif source_language == "Bengali":
source_lang_code = "bn"
else:
assert False, "Unsupported language"
print(f"{source_language}")
with open(
"/home/mshahidul/readctrl/prompts/syn_data_generation/syn_data_gen_diff_label_Bangla.txt",
"r",
encoding="utf-8",
) as f:
prompt_template = f.read()
api_file = "/home/mshahidul/api_new.json"
with open(api_file, "r", encoding="utf-8") as f:
api_keys = json.load(f)
openai_api_key = api_keys["openai"]
client = OpenAI(api_key=openai_api_key)
def openai_return(prompt, model="gpt-5"):
"""Send a prompt to GPT and parse JSON."""
response = client.chat.completions.create(
model=model,
messages=[
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": prompt}
]
)
content = response.choices[0].message.content.strip()
cleaned = content.replace("```json", "").replace("```", "").strip()
try:
return json.loads(cleaned)
except json.JSONDecodeError:
print("⚠️ JSON parse failed — storing raw text.")
return cleaned
input_path = "/home/mshahidul/readctrl/data/translated_data/translation_wo_judge/multiclinsum_gs_train_en2bn_gemma(0_200).json"
save_path = f"/home/mshahidul/readctrl/data/synthetic_dataset_diff_labels/syn_data_diff_labels_{source_lang_code}_0_80.json"
res=[]
if os.path.exists(save_path):
with open(save_path, "r", encoding="utf-8") as f:
res = json.load(f)
import tqdm
with open(input_path, "r", encoding="utf-8") as f:
data = json.load(f)
for idx, item in tqdm.tqdm(enumerate(data)):
fulltext_bn = item.get("translated_fulltext")
summary_bn = item.get("translated_summary")
if not fulltext_bn or not summary_bn:
print(f"Skipping idx={idx}, id={item.get('id')} due to missing translated fields.")
continue
prompt = (
prompt_template
.replace("<<<FULL_TEXT>>>", fulltext_bn)
.replace("<<<SOURCE_LANGUAGE>>>", source_language)
.replace("<<<GOLD_SUMMARY>>>", summary_bn)
)
# import ipdb; ipdb.set_trace()
sample = openai_return(prompt, model="gpt-5")
res.append({
"id": item["id"],
"index": idx ,
"fulltext": fulltext_bn,
"diff_label_texts": sample
})
if len(res) % 2 == 0:
with open(save_path, "w", encoding="utf-8") as f:
json.dump(res, f, indent=2, ensure_ascii=False)
print(f"Saved {len(res)} samples so far.")
with open(save_path, "w", encoding="utf-8") as f:
json.dump(res, f, indent=2, ensure_ascii=False)
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