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Create app.py
Browse filesCopied from preplexity.ai so not sure if is good
app.py
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import gradio as gr
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from transformers import Conversation, pipeline
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# Example group recommendation database
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GROUP_DB = [
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{"group": "Red Velvet", "style": "pop"},
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{"group": "TWICE", "style": "pop"},
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{"group": "BLACKPINK", "style": "pop"},
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{"group": "BTS", "style": "pop"},
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# Add more groups with styles!
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]
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# Conversational model from Hugging Face
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chatbot = pipeline(model="facebook/blenderbot-400M-distill", task="conversational")
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def custom_kpop_response(user_input, history):
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user_input_lower = user_input.lower()
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# Detect greeting and genre hint from the user
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if any(greet in user_input_lower for greet in ["hi", "hello", "hey"]):
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greeting = "Hi there! Welcome to K-pop world! "
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else:
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greeting = ""
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# Custom pop music recommendation logic
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if ("taylor swift" in user_input_lower or
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("pop" in user_input_lower and "kpop" in user_input_lower)):
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recommendation = ("If you like Taylor Swift's pop style, "
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"you might enjoy K-pop groups like Red Velvet, TWICE, or BLACKPINK! "
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"They’re known for catchy melodies and energetic choreography.")
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return greeting + recommendation
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# Fallback: let chatbot handle other cases
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conversation = Conversation(user_input)
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result = chatbot(conversation)
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# Just return chatbot's generated text
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return greeting + conversation.generated_responses[-1]
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iface = gr.ChatInterface(
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custom_kpop_response,
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title="K-Pop Genie Chatbot",
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description="Say hi! Ask for K-pop groups or songs similar to your Western favorites."
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)
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iface.launch()
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