# /// script
# requires-python = ">=3.12"
# dependencies = [
#     "torch",
#     "torchvision",
#     "transformers",
#     "diffusers",
#     "sentence-transformers",
#     "accelerate",
#     "peft",
#     "slack-sdk",
# ]
# ///

try:
    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("BAAI/bge-m3")
    
    sentences = [
        "That is a happy person",
        "That is a happy dog",
        "That is a very happy person",
        "Today is a sunny day"
    ]
    embeddings = model.encode(sentences)
    
    similarities = model.similarity(embeddings, embeddings)
    print(similarities.shape)
    # [4, 4]
    with open('BAAI_bge-m3_0.txt', 'w', encoding='utf-8') as f:
        f.write('Everything was good in BAAI_bge-m3_0.txt')
except Exception as e:
    import os
    from slack_sdk import WebClient
    client = WebClient(token=os.environ['SLACK_TOKEN'])
    client.chat_postMessage(
        channel='#exp-slack-alerts',
        text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/BAAI_bge-m3_0.txt|BAAI_bge-m3_0.txt>',
    )

    with open('BAAI_bge-m3_0.txt', 'a', encoding='utf-8') as f:
        import traceback
        f.write('''```CODE: 
from sentence_transformers import SentenceTransformer

model = SentenceTransformer("BAAI/bge-m3")

sentences = [
    "That is a happy person",
    "That is a happy dog",
    "That is a very happy person",
    "Today is a sunny day"
]
embeddings = model.encode(sentences)

similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [4, 4]
```

ERROR: 
''')
        traceback.print_exc(file=f)
    
finally:
    from huggingface_hub import upload_file
    upload_file(
        path_or_fileobj='BAAI_bge-m3_0.txt',
        repo_id='model-metadata/code_execution_files',
        path_in_repo='BAAI_bge-m3_0.txt',
        repo_type='dataset',
    )