# /// script
# requires-python = ">=3.12"
# dependencies = [
#     "numpy",
#     "einops",
#     "pandas",
#     "matplotlib",
#     "protobuf",
#     "torch",
#     "sentencepiece",
#     "torchvision",
#     "transformers",
#     "timm",
#     "diffusers",
#     "sentence-transformers",
#     "accelerate",
#     "peft",
#     "slack-sdk",
# ]
# ///

try:
    from sentence_transformers import CrossEncoder
    
    model = CrossEncoder("zeroentropy/zerank-2")
    
    query = "Which planet is known as the Red Planet?"
    passages = [
    	"Venus is often called Earth's twin because of its similar size and proximity.",
    	"Mars, known for its reddish appearance, is often referred to as the Red Planet.",
    	"Jupiter, the largest planet in our solar system, has a prominent red spot.",
    	"Saturn, famous for its rings, is sometimes mistaken for the Red Planet."
    ]
    
    scores = model.predict([(query, passage) for passage in passages])
    print(scores)
    with open('zeroentropy_zerank-2_0.txt', 'w', encoding='utf-8') as f:
        f.write('Everything was good in zeroentropy_zerank-2_0.txt')
except Exception as e:
    import os
    from slack_sdk import WebClient
    client = WebClient(token=os.environ['SLACK_TOKEN'])
    client.chat_postMessage(
        channel='#hub-model-metadata-snippets-sprint',
        text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/zeroentropy_zerank-2_0.txt|zeroentropy_zerank-2_0.txt>',
    )

    with open('zeroentropy_zerank-2_0.txt', 'a', encoding='utf-8') as f:
        import traceback
        f.write('''```CODE: 
from sentence_transformers import CrossEncoder

model = CrossEncoder("zeroentropy/zerank-2")

query = "Which planet is known as the Red Planet?"
passages = [
	"Venus is often called Earth's twin because of its similar size and proximity.",
	"Mars, known for its reddish appearance, is often referred to as the Red Planet.",
	"Jupiter, the largest planet in our solar system, has a prominent red spot.",
	"Saturn, famous for its rings, is sometimes mistaken for the Red Planet."
]

scores = model.predict([(query, passage) for passage in passages])
print(scores)
```

ERROR: 
''')
        traceback.print_exc(file=f)
    
finally:
    from huggingface_hub import upload_file
    upload_file(
        path_or_fileobj='zeroentropy_zerank-2_0.txt',
        repo_id='model-metadata/code_execution_files',
        path_in_repo='zeroentropy_zerank-2_0.txt',
        repo_type='dataset',
    )