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Update app.py
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app.py
CHANGED
@@ -80,6 +80,26 @@ def generate_response(user_message, traits):
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return response
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def respond(user_message, history, personality_text):
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"""
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Generate a chatbot response based on user input and personality traits.
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@@ -90,6 +110,10 @@ def respond(user_message, history, personality_text):
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Returns:
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tuple: Updated conversation history.
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"""
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# Analyze personality traits from the provided text
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traits = analyze_personality(personality_text)
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@@ -100,6 +124,19 @@ def respond(user_message, history, personality_text):
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history.append((user_message, final_response))
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return history, history
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def personality_demo():
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"""
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return response
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##def respond(user_message, history, personality_text):
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## """
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## Generate a chatbot response based on user input and personality traits.
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## Args:
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## user_message (str): The user's input message.
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## history (list): A list of message-response tuples to maintain conversation history.
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## personality_text (str): The text defining the chatbot's personality.
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## Returns:
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## tuple: Updated conversation history.
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## """
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## # Analyze personality traits from the provided text
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## traits = analyze_personality(personality_text)
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##
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## # Generate a response using the LLM and personality traits
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## final_response = generate_response(user_message, traits)
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##
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## # Append the new interaction to the conversation history
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## history.append((user_message, final_response))
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##
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## return history, history
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def respond(user_message, history, personality_text):
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"""
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Generate a chatbot response based on user input and personality traits.
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Returns:
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tuple: Updated conversation history.
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"""
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# **Tắt filter hoặc làm sạch nội dung trước khi phân tích**
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user_message = disable_content_filters(user_message) # Hàm tắt filter hoặc xử lý nội dung
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personality_text = disable_content_filters(personality_text)
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# Analyze personality traits from the provided text
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traits = analyze_personality(personality_text)
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history.append((user_message, final_response))
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return history, history
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def disable_content_filters(text):
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"""
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Mock function to simulate content filter disabling.
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For this project, you can extend this logic to preprocess input text.
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"""
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# Remove/replace filtered words (just a simple example)
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# Extend this with a list of words or external API for full functionality
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filtered_words = ["badword1", "badword2", "profanity"]
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for word in filtered_words:
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text = text.replace(word, "[filtered]")
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return text
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def personality_demo():
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"""
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