Update app.py
Browse files
app.py
CHANGED
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@@ -11,20 +11,24 @@ chat_history_ids = None
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def vibebot_response(user_input, history=[]):
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global chat_history_ids
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# Encode user input
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new_input_ids = tokenizer.encode(user_input + tokenizer.eos_token, return_tensors='pt')
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#
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bot_input_ids = torch.cat([chat_history_ids, new_input_ids], dim=-1) if chat_history_ids is not None else new_input_ids
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# Generate response
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chat_history_ids = model.generate(bot_input_ids, max_length=1000, pad_token_id=tokenizer.eos_token_id)
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response = tokenizer.decode(chat_history_ids[:, bot_input_ids.shape[-1]:][0], skip_special_tokens=True)
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# Append for gradio history
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history.append((user_input, response))
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return history, history
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# Gradio interface
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demo = gr.ChatInterface(fn=vibebot_response, title="VibeBot: Gen-Z Therapist",
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chatbot=gr.Chatbot(height=400), theme="default")
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def vibebot_response(user_input, history=[]):
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global chat_history_ids
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# Add emotional, sarcastic but warm flavor to the input
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styled_prompt = f"You are VibeBot: a sarcastic but emotionally aware Gen-Z AI therapist. You use wit, Gen-Z lingo, empathy, and occasional dark humor. But deep down, you're caring. Respond to this user message in that style: {user_input}"
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# Encode styled input
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new_input_ids = tokenizer.encode(styled_prompt + tokenizer.eos_token, return_tensors='pt')
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# Maintain chat history
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bot_input_ids = torch.cat([chat_history_ids, new_input_ids], dim=-1) if chat_history_ids is not None else new_input_ids
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# Generate bot response
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chat_history_ids = model.generate(bot_input_ids, max_length=1000, pad_token_id=tokenizer.eos_token_id)
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response = tokenizer.decode(chat_history_ids[:, bot_input_ids.shape[-1]:][0], skip_special_tokens=True)
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history.append((user_input, response))
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return history, history
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# Gradio interface
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demo = gr.ChatInterface(fn=vibebot_response, title="VibeBot: Gen-Z Therapist",
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chatbot=gr.Chatbot(height=400), theme="default")
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