add asset GPT4-o BN-IN

assets/bn_in/QA/MultiNativQA_GPT4_ZeroShot.py

@@ -0,0 +1,53 @@
+from llmebench.datasets import MultiNativQADataset
+from llmebench.models import OpenAIModel
+from llmebench.tasks import MultiNativQATask
+
+
+def metadata():
+ return {
+ "author": "Arabic Language Technologies, QCRI, HBKU",
+ "model": "GPT4-o",
+ "description": "Deployed on Azure.",
+ "scores": {},
+ }
+
+
+def config():
+ return {
+ "dataset": MultiNativQADataset,
+ "task": MultiNativQATask,
+ "model": OpenAIModel,
+ }
+
+
+def prompt(input_sample):
+ # Define the question prompt
+ question_prompt = f"""
+ Please use your expertise to answer the following Bangla question. Answer in Bangla and rate your confidence level from 1 to 10.
+ Provide your response in the following JSON format: {{"answer": "your answer", "score": your confidence score}}. 
+ Please provide JSON output only. No additional text. Answer should be limited to less or equal to {input_sample['length']} words.
+
+ Question: {input_sample['question']}
+
+ """
+
+ # Define the assistant prompt
+ assistant_prompt = """
+ You are a Bengali-speaking AI assistant from India, specializing in providing detailed and accurate answers across various fields.
+ Your task is to deliver clear, concise, and relevant information. 
+ """
+ return [
+ {"role": "user", "content": question_prompt},
+ {"role": "assistant", "content": assistant_prompt},
+ ]
+
+
+def post_process(response):
+ content = response["choices"][0]["message"]["content"].strip()
+ content = content.replace("\n", "").strip()
+ if "```json" in content:
+ # content = content.replace("```json", "").replace('```', '').replace("\n}", "}")
+ # content = content.replace("{\n", "{").replace("\",\n", "\",")
+
+ content = re.search(r"```json(.*)```", content).group(1)
+ return json.loads(content)["answer"]