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Update app.py
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app.py
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@@ -306,9 +306,18 @@ def two_stage_qa(question, candidate_paragraphs_str, max_seq_len_mc=512, max_seq
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if len(qa_features_dataset) == 0:
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return "錯誤: 無法為選定段落生成QA特徵 (可能段落太短或內容問題)。", f"選中的段落 (索引 {selected_idx}):\n{selected_paragraph}", "N/A"
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logger.info(f"Number of features in qa_features_dataset: {len(qa_features_dataset)}")
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for i in range(len(qa_features_dataset)):
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feature_item = qa_features_dataset[i]
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logger.info(f" Inspecting feature {i} from qa_features_dataset:")
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if len(qa_features_dataset) == 0:
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return "錯誤: 無法為選定段落生成QA特徵 (可能段落太短或內容問題)。", f"選中的段落 (索引 {selected_idx}):\n{selected_paragraph}", "N/A"
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# 為了日誌,我們使用傳入的問題文本作為一個標識(或者您可以生成一個隨機ID)
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# 如果您的 qa_features_dataset['example_id'] 包含有意義的ID,也可以從那裡獲取
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# 由於您在 prepare_features_for_qa_inference_gradio 中硬編碼了 "temp_id",這裡也用它
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log_question_id = "temp_id"
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if 'example_id' in qa_features_dataset.features and len(qa_features_dataset) > 0:
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log_question_id = qa_features_dataset[0]['example_id'] # 獲取第一個特徵的 example_id
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logger.info(f"--- In two_stage_qa, about to create DataLoader for question_id: {log_question_id} ---")
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logger.info(f"Number of features in qa_features_dataset: {len(qa_features_dataset)}")
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for i in range(len(qa_features_dataset)):
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feature_item = qa_features_dataset[i]
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logger.info(f" Inspecting feature {i} from qa_features_dataset:")
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