The get_related_doc function in the hana_ml.text.tm module returns the top-ranked related documents for a query document or multiple documents based on Term Frequency - Inverse Document Frequency (TF-IDF) result or reference data, with various parameters to customize the output such as language, index name, thread ratio, and more.
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Here is the executable code template for the `get_related_doc` function:

```python
from hana_ml.text.tm import get_related_doc

# pred_data DataFrame
pred_data = ...

# ref_data DataFrame or tuple of DataFrame
ref_data = ...

# Optional parameters
top = ...
threshold = ...
lang = ...
index_name = ...
thread_ratio = ...
created_index = ...
key = ...

# Call the function
result = get_related_doc(
    pred_data=pred_data,
    ref_data=ref_data,
    top=top,
    threshold=threshold,
    lang=lang,
    index_name=index_name,
    thread_ratio=thread_ratio,
    created_index=created_index,
    key=key
)

# Collect the result
result_df = result.collect()
```

Please replace the `...` with your actual data and parameter values.