jayebaku commited on
Commit
4da2d54
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verified ·
1 Parent(s): a99954f

Update _app.py

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Files changed (1) hide show
  1. _app.py +11 -4
_app.py CHANGED
@@ -134,12 +134,17 @@ def add_query(to_add, history):
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  # return q_a_df, answers_df, summary
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- def qa_summarise(selected_queries, qa_llm_model, text_field, data_df):
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  qa_input_df = data_df[data_df["model_label"] != "none"].reset_index()
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  texts = qa_input_df[text_field].to_list()
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- summary = generate_answer(qa_llm_model, texts, selected_queries[0], selected_queries, mode="multi_summarize")
 
 
 
 
 
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  doc_df = pd.DataFrame()
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  doc_df["number"] = [i+1 for i in range(len(texts))]
@@ -228,7 +233,7 @@ with gr.Blocks() as demo:
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  outputs=[incorrect, correct, accuracy, data_eval, download_csv])
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  qa_tab = gr.Tab("Question Answering")
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-
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  with qa_tab:
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  # XXX Add some button disabling here, if the classification process is not completed first XXX
@@ -251,6 +256,8 @@ with gr.Blocks() as demo:
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  with gr.Column():
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  batch_size = gr.Slider(50, 500, value=150, step=1, label="Batch size", info="Choose between 50 and 500", interactive=True)
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  topk = gr.Slider(1, 10, value=5, step=1, label="Number of results to retrieve", info="Choose between 1 and 10", interactive=True)
 
 
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  selected_queries = gr.CheckboxGroup(label="Select at least one query using the checkboxes", interactive=True)
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  queries_state = gr.State()
@@ -269,7 +276,7 @@ with gr.Blocks() as demo:
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  # inputs=[selected_queries, qa_llm_model, aggregator, batch_size, topk, text_field, data],
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  # outputs=[qa_df, answers_df, hsummary])
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  qa_button.click(qa_summarise,
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- inputs=[selected_queries, qa_llm_model, text_field, data],
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  outputs=[hsummary, qa_df])
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  # return q_a_df, answers_df, summary
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+ def qa_summarise(selected_queries, qa_llm_model, text_field, response_lang, data_df):
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  qa_input_df = data_df[data_df["model_label"] != "none"].reset_index()
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  texts = qa_input_df[text_field].to_list()
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+ summary = generate_answer(qa_llm_model,
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+ texts,
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+ selected_queries[0],
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+ selected_queries,
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+ response_lang,
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+ mode="multi_summarize")
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  doc_df = pd.DataFrame()
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  doc_df["number"] = [i+1 for i in range(len(texts))]
 
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  outputs=[incorrect, correct, accuracy, data_eval, download_csv])
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  qa_tab = gr.Tab("Question Answering")
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+
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  with qa_tab:
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  # XXX Add some button disabling here, if the classification process is not completed first XXX
 
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  with gr.Column():
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  batch_size = gr.Slider(50, 500, value=150, step=1, label="Batch size", info="Choose between 50 and 500", interactive=True)
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  topk = gr.Slider(1, 10, value=5, step=1, label="Number of results to retrieve", info="Choose between 1 and 10", interactive=True)
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+
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+ response_lang = gr.Dropdown(["english", "german", "catalan", "spanish"], label="Response language", value="english", interactive=True)
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  selected_queries = gr.CheckboxGroup(label="Select at least one query using the checkboxes", interactive=True)
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  queries_state = gr.State()
 
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  # inputs=[selected_queries, qa_llm_model, aggregator, batch_size, topk, text_field, data],
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  # outputs=[qa_df, answers_df, hsummary])
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  qa_button.click(qa_summarise,
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+ inputs=[selected_queries, qa_llm_model, text_field, response_lang, data],
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  outputs=[hsummary, qa_df])
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