File size: 2,012 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 | from openai import OpenAI
import json, os
source_language = "English"
target_language = "Hindi"
print(f"Translating from {source_language} to {target_language}")
with open("/home/mshahidul/readctrl/prompts/translation_prompt.txt", "r") as f:
prompt_template = f.read()
api_file = "/home/mshahidul/api_new.json"
with open(api_file, "r") 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
save_path=f"/home/mshahidul/readctrl/data/translated_data/translation_{source_language[:2].lower()}2{target_language[:2].lower()}_v1.json"
res=[]
if os.path.exists(save_path):
with open(save_path, "r") as f:
res = json.load(f)
import tqdm
with open("/home/mshahidul/readctrl/data/testing_data_gs/multiclinsum_gs_train_en.json", "r") as f:
data = json.load(f)
for item in tqdm.tqdm(data[:15]):
prompt=prompt_template.replace("<MEDICAL_TEXT>", item["fulltext"]).replace("<SOURCE_LANGUAGE>", source_language).replace("<TARGET_LANGUAGE>", target_language)
# import ipdb; ipdb.set_trace()
sample = openai_return(prompt, model="gpt-5")
res.append(sample)
if len(res) % 2 == 0:
with open(save_path, "w") as f:
json.dump(res, f, indent=2, ensure_ascii=False)
print(f"Saved {len(res)} samples so far.")
with open(save_path, "w") as f:
json.dump(res, f, indent=2, ensure_ascii=False)
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