add mistral asset BN-BD (#347)

assets/bn/QA/MultiNativQA_Mistral_7b_ZeroShot.py

@@ -0,0 +1,61 @@
+import json
+
+from llmebench.datasets import MultiNativQADataset
+from llmebench.models import AzureModel
+from llmebench.tasks import MultiNativQATask
+
+
+def metadata():
+ return {
+ "author": "Arabic Language Technologies, QCRI, HBKU",
+ "model": "Mistral 7b",
+ "description": "Deployed on Azure.",
+ "scores": {},
+ }
+
+
+def config():
+ return {
+ "dataset": MultiNativQADataset,
+ "task": MultiNativQATask,
+ "model": AzureModel,
+ "general_args": {"test_split": "bangla_bd"},
+ }
+
+
+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 an Bangla AI assistant specialized in providing detailed and accurate answers across various fields. 
+ Your task is to deliver clear, concise, and relevant information. 
+ """
+
+ return [
+ # {
+ # "role": "assistant",
+ # "content": assistant_prompt,
+ # },
+ {
+ "role": "user",
+ "content": question_prompt,
+ },
+ ]
+
+
+def post_process(response):
+ data = response["output"]
+ if "\n\n" in data:
+ data = data.split("\n\n")[0]
+ response = json.loads(data)
+ answer = response["answer"]
+ return answer