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Update app.py
Browse files
app.py
CHANGED
@@ -33,7 +33,15 @@ def prediction_analyse(prediction_content):
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# 遍历 predictions,计算每个 question_type_id 的正确预测数和总预测数
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for prediction in predictions:
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-
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question_id = prediction["question_id"]
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gt_item = ground_truth[question_id]
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question_type_id = gt_item["question_type_id"]
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@@ -77,10 +85,16 @@ def add_new_eval(
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LLM_name = LLM_name_textbox
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else:
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LLM_name = LLM_type
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# add new data
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new_data = [
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model_type,
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LLM_name,
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each_task_accuracy[1],
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each_task_accuracy[2],
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@@ -148,7 +162,6 @@ with block:
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)
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def on_checkbox_group_change(selected_columns):
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print("TEst")
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# pdb.set_trace()
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selected_columns = [item for item in TASK_INFO if item in selected_columns]
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present_columns = MODEL_INFO + selected_columns
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@@ -156,8 +169,6 @@ with block:
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updated_headers = present_columns
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update_datatype = [DATA_TITILE_TYPE[COLUMN_NAMES.index(x)] for x in updated_headers]
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# data_component.update(value=updated_data, headers=updated_headers, datatype=update_datatype)
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filter_component = gr.components.Dataframe(
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value=updated_data,
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headers=updated_headers,
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@@ -202,7 +213,7 @@ with block:
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],
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label="Model type",
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multiselect=False,
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value="
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interactive=True,
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)
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model_link = gr.Textbox(
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# 遍历 predictions,计算每个 question_type_id 的正确预测数和总预测数
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for prediction in predictions:
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# pdb.set_trace()
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prediction = prediction.strip()
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if not prediction:
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continue
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try:
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prediction = json.loads(prediction)
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except json.JSONDecodeError:
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print(f"Warning: Skipping invalid JSON data in line: {prediction}")
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continue
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question_id = prediction["question_id"]
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gt_item = ground_truth[question_id]
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question_type_id = gt_item["question_type_id"]
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LLM_name = LLM_name_textbox
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else:
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LLM_name = LLM_type
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pdb.set_trace()
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if model_link == '':
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model_name = model_name_textbox # no url
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else:
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model_name = '[' + model_name_textbox + '](' + model_link + ')'
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# add new data
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new_data = [
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model_type,
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model_name,
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LLM_name,
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each_task_accuracy[1],
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each_task_accuracy[2],
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)
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def on_checkbox_group_change(selected_columns):
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# pdb.set_trace()
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selected_columns = [item for item in TASK_INFO if item in selected_columns]
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present_columns = MODEL_INFO + selected_columns
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updated_headers = present_columns
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update_datatype = [DATA_TITILE_TYPE[COLUMN_NAMES.index(x)] for x in updated_headers]
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filter_component = gr.components.Dataframe(
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value=updated_data,
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headers=updated_headers,
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],
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label="Model type",
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multiselect=False,
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value=ModelType.FT.to_str(" : "),
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interactive=True,
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)
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model_link = gr.Textbox(
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