Create extract_table.py
Browse files- utils/extract_table.py +51 -0
utils/extract_table.py
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import io
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import pandas as pd
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def extract_table_from_response(gpt_response):
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# Split the response into lines
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lines = gpt_response.strip().split("\n")
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# Find where the table starts and ends (based on the presence of pipes `|` and at least 3 columns)
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table_lines = [line for line in lines if '|' in line and len(line.split('|')) > 3]
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# If no table is found, return None or an empty string
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if not table_lines:
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return None
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# Find the first and last index of the table lines
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first_table_index = lines.index(table_lines[0])
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last_table_index = lines.index(table_lines[-1])
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# Extract only the table part
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table_text = lines[first_table_index:last_table_index + 1]
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return table_text
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def gpt_response_to_dataframe(gpt_response):
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# Extract the table text from the GPT response
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table_lines = extract_table_from_response(gpt_response)
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# If no table found, return an empty DataFrame
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if table_lines is None or len(table_lines) == 0:
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return pd.DataFrame()
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# Find the header and row separator (assume it's a line with dashes like |---|)
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try:
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# The separator line (contains dashes separating headers and rows)
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sep_line_index = next(i for i, line in enumerate(table_lines) if set(line.strip()) == {'|', '-'})
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except StopIteration:
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# If no separator line is found, return an empty DataFrame
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return pd.DataFrame()
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# Extract headers (the line before the separator) and rows (lines after the separator)
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headers = [h.strip() for h in table_lines[sep_line_index - 1].split('|')[1:-1]]
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# Extract rows (each line after the separator)
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rows = [
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[cell.strip() for cell in row.split('|')[1:-1]]
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for row in table_lines[sep_line_index + 1:]
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]
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# Create DataFrame
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df = pd.DataFrame(rows, columns=headers)
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return df
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