Update app.py
Browse files
app.py
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@@ -236,13 +236,13 @@ def factextraction (message):
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# 1 seem best for testing
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####
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#download and setup the model and tokenizer
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tokenizer = BlenderbotTokenizer.from_pretrained(
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def func (message):
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inputs = tokenizer(message, return_tensors="pt")
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result =
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print(result)
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return tokenizer.decode(result[0])
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@@ -416,17 +416,18 @@ sentiment_analysis_result_inputfield = gr.Textbox(label="Sentiment ")
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topic_sale_inform_result_inputfield = gr.Textbox(label="Thema ")
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chat_bot = gr.Interface(fn=callChains ,
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outputs=[final_answer_inputfield,sentiment_analysis_result_inputfield,topic_sale_inform_result_inputfield],
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# create a public link, set `share=True` in `launch()
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####################
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# 1 seem best for testing
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####
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#download and setup the model and tokenizer
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model_name_chat = 'facebook/blenderbot-400M-distill'
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tokenizer = BlenderbotTokenizer.from_pretrained(model_name_chat)
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model_chat = BlenderbotForConditionalGeneration.from_pretrained(model_name_chat)
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def func (message):
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inputs = tokenizer(message, return_tensors="pt")
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result = model_chat.generate(**inputs)
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print(result)
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return tokenizer.decode(result[0])
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topic_sale_inform_result_inputfield = gr.Textbox(label="Thema ")
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chat_bot = gr.Interface(fn=callChains ,
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inputs=[
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current_message_inputfield,
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gr.Slider(minimum=1.0,maximum=200.0,value=50.0,step=1,interactive=True,label="max_length"),
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gr.Slider(minimum=1.0,maximum=20.0,value=1.0,step=1,interactive=True,label="length_penalty"),
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gr.Slider(minimum=0.0,maximum=5.0,value=3.0,step=1,interactive=True,label="no_repeat_ngram_size"),
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gr.Slider(minimum=1.0,maximum=20.0,value=1.0,step=1,interactive=True,label="num_beams"),
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gr.Dropdown(["Deutsch", "Englisch"],value="Deutsch"),
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],
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outputs=[final_answer_inputfield,sentiment_analysis_result_inputfield,topic_sale_inform_result_inputfield],
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title="Conversation Bot with extra")
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# create a public link, set `share=True` in `launch()
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chat_bot.launch()
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####################
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