Update app.py
Browse files
app.py
CHANGED
@@ -257,9 +257,11 @@ def process_pdf(uploaded_files, llm_model, n_criteria = num_criteria):
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'Title': title,
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'Author': author_result
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}
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-
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new_row.update({f'score_cr_{i}': score for i, score in enumerate(score_list, 1)})
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new_row.update({f'reasoning_cr_{i}':
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# Check if the CSV file exists
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if os.path.exists(csv_file_path):
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@@ -267,11 +269,12 @@ def process_pdf(uploaded_files, llm_model, n_criteria = num_criteria):
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df = pd.read_csv(csv_file_path)
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else:
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# Or create a new DataFrame if the file does not exist
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# Append the new data
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df = df.append(new_row, ignore_index=True)
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# Save the updated DataFrame back to CSV
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df.to_csv(csv_file_path, index=False)
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'Title': title,
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'Author': author_result
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}
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new_row.update({f'score_cr_{i}': score for i, score in enumerate(score_list, 1)})
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new_row.update({f'reasoning_cr_{i}': reasoning for i, reasoning in enumerate(reasoning, 1)})
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# Convert new_row dictionary to a DataFrame for easy appending
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new_row_df = pd.DataFrame([new_row])
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# Check if the CSV file exists
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if os.path.exists(csv_file_path):
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df = pd.read_csv(csv_file_path)
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else:
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# Or create a new DataFrame if the file does not exist
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columns = ['Id', 'Title', 'Author'] + [f'score_cr_{i}' for i in range(1, 10)] + [f'reasoning_cr_{i}' for i in range(1, 10)]
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df = pd.DataFrame(columns=columns)
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# Append the new data using pd.concat
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df = pd.concat([df, new_row_df], ignore_index=True)
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# Save the updated DataFrame back to CSV
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df.to_csv(csv_file_path, index=False)
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